ALBERT

Description: Singular vector based targeted observations of chemical constituents: description and first application of the EURAD-IM-SVA Geoscientific Model Development Discussions, 8, 6267-6307, 2015 Author(s): N. Goris and H. Elbern Measurements of the large dimensional chemical state of the atmosphere provide only sparse snapshots of the state of the system due to their typically insufficient temporal and spatial density. In order to optimize the measurement configurations despite those limitations, the present work describes the identification of sensitive states of the chemical system as optimal target areas for adaptive observations. For this purpose, the technique of singular vector analysis (SVA), which has been proved effective for targeted observations in numerical weather predication, is implemented into the chemical transport model EURAD-IM (EURopean Air pollution and Dispersion – Inverse Model) yielding the EURAD-IM-SVA. Besides initial values, emissions are investigated as critical simulation controlling targeting variables. For both variants, singular vectors are applied to determine the optimal placement for observations and moreover to quantify which chemical compounds have to be observed with preference. Based on measurements of the airship based ZEPTER-2 campaign, the EURAD-IM-SVA has been evaluated by conducting a comprehensive set of model runs involving different initial states and simulation lengths. Since the considered cases are restricted in terms of considered chemical compounds and selected areas, they allow for a retracing of the results and a confirmation of their correctness. Our analysis shows that the optimal placement for observations of chemical species is not entirely determined by mere transport and mixing processes. Rather, a combination of initial chemical concentrations, chemical conversions, and meteorological processes determine the influence of chemical compounds and regions. We furthermore demonstrate that the optimal placement of observations of emission strengths is highly dependent on the location of emission sources and that the benefit of including emissions as target variables outperforms the value of initial value optimisation with growing simulation length. The obtained results confirm the benefit of considering both initial values and emission strengths as target variables and of applying the EURAD-IM-SVA for measurement decision guidance with respect to chemical compounds.

Description: A global scale mechanistic model of the photosynthetic capacity Geoscientific Model Development Discussions, 8, 6217-6266, 2015 Author(s): A. A. Ali, C. Xu, A. Rogers, R. A. Fisher, S. D. Wullschleger, N. G. McDowell, E. C. Massoud, J. A. Vrugt, J. D. Muss, J. B. Fisher, P. B. Reich, and C. J. Wilson Although plant photosynthetic capacity as determined by the maximum carboxylation rate (i.e., V c, max25 ) and the maximum electron transport rate (i.e., J max25 ) at a reference temperature (generally 25 °C) is known to vary substantially in space and time in response to environmental conditions, it is typically parameterized in Earth system models (ESMs) with tabulated values associated to plant functional types. In this study, we developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA V1.0) to predict the photosynthetic capacity at the global scale under different environmental conditions, based on the optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The LUNA model was able to reasonably well capture the observed patterns of photosynthetic capacity in view that it explained approximately 55 % of the variation in observed V c, max25 and 65 % of the variation in observed J max25 across the globe. Our model simulations under current and future climate conditions indicated that V c, max25 could be most affected in high-latitude regions under a warming climate and that ESMs using a fixed V c, max25 or J max25 by plant functional types were likely to substantially overestimate future global photosynthesis.

Description: Evaluation of an operational ocean model configuration at 1/12° spatial resolution for the Indonesian seas – Part 2: Biogeochemistry Geoscientific Model Development Discussions, 8, 6669-6706, 2015 Author(s): E. Gutknecht, G. Reffray, M. Gehlen, I. Triyulianti, D. Berlianty, and P. Gaspar In the framework of the INDESO (Infrastructure evelopment of Space Oceanography) project, an operational ocean forecasting system was developed to monitor the state of the Indonesian seas in terms of circulation, biogeochemistry and fisheries. This forecasting system combines a suite of numerical models connecting physical and biogeochemical variables to population dynamics of large marine predators (tunas). The physical/biogeochemical coupled component (INDO12BIO configuration) covers a large region extending from the western Pacific Ocean to the Eastern Indian Ocean at 1/12° resolution. The OPA/NEMO physical ocean model and the PISCES biogeochemical model are coupled in "on-line" mode without degradation in space and time. The operational global ocean forecasting system (1/4°) operated by Mercator Ocean provides the physical forcing while climatological open boundary conditions are prescribed for the biogeochemistry. This paper describes the skill assessment of the INDO12BIO configuration. Model skill is assessed by evaluating a reference hindcast simulation covering the last 8 years (2007–2014). Model results are compared to satellite, climatological and in situ observations. Diagnostics are performed on chlorophyll a , primary production, mesozooplankton, nutrients and oxygen. Model results reproduce the main characteristics of biogeochemical tracer distributions in space and time. The seasonal cycle of chlorophyll a is in phase with satellite observations. The northern and southern parts of the archipelago present a distinct seasonal cycle, with higher chlorophyll biomass in the southern (northern) part during SE (NW) monsoon. Nutrient and oxygen concentrations are correctly reproduced in terms of horizontal and vertical distributions. The biogeochemical content of water masses entering in the archipelago as well as the water mass transformation across the archipelago conserves realistic vertical distribution in Banda Sea and at the exit of the archipelago.

Description: Decadal evaluation of regional climate, air quality, and their interactions using WRF/Chem Version 3.6.1 Geoscientific Model Development Discussions, 8, 6707-6756, 2015 Author(s): K. Yahya, K. Wang, P. Campbell, T. Glotfelty, J. He, and Y. Zhang The Weather Research and Forecasting model with Chemistry (WRF/Chem) v3.6.1 with the Carbon Bond 2005 (CB05) gas-phase mechanism is evaluated for its first decadal application during 2001–2010 using the Representative Concentration Pathway (RCP 8.5) emissions to assess its capability and appropriateness for long-term climatological simulations. The initial and boundary conditions are downscaled from the modified Community Earth System Model/Community Atmosphere Model (CESM/CAM5) v1.2.2. The meteorological initial and boundary conditions are bias-corrected using the National Center for Environmental Protection's Final (FNL) Operational Global Analysis data. Climatological evaluations are carried out for meteorological, chemical, and aerosol-cloud-radiation variables against data from surface networks and satellite retrievals. The model performs very well for the 2 m temperature (T2) for the 10 year period with only a small cold bias of −0.3 °C. Biases in other meteorological variables including relative humidity at 2 m, wind speed at 10 m, and precipitation tend to be site- and season-specific; however, with the exception of T2, consistent annual biases exist for most of the years from 2001 to 2010. Ozone mixing ratios are slightly overpredicted at both urban and rural locations but underpredicted at rural locations. PM 2.5 concentrations are slightly overpredicted at rural sites, but slightly underpredicted at urban/suburban sites. In general, the model performs relatively well for chemical and meteorological variables, and not as well for aerosol-cloud-radiation variables. Cloud-aerosol variables including aerosol optical depth, cloud water path, cloud optical thickness, and cloud droplet number concentration are generally underpredicted on average across the continental US. Overpredictions of several cloud variables over eastern US result in underpredictions of radiation variables and overpredictions of shortwave and longwave cloud forcing which are important climate variables. While the current performance is deemed to be acceptable, improvements to the bias-correction method for CESM downscaling and the model parameterizations of cloud dynamics and thermodynamics, as well as aerosol-cloud interactions can potentially improve model performance for long-term climate simulations.

Description: The GEWEX LandFlux project: evaluation of model evaporation using tower-based and globally-gridded forcing data Geoscientific Model Development Discussions, 8, 6809-6866, 2015 Author(s): M. F. McCabe, A. Ershadi, C. Jimenez, D. G. Miralles, D. Michel, and E. F. Wood Determining the spatial distribution and temporal development of evaporation at regional and global scales is required to improve our understanding of the coupled water and energy cycles and to better monitor any changes in observed trends and variability of linked hydrological processes. With recent international efforts guiding the development of long-term and globally distributed flux estimates, continued product assessments are required to inform upon the selection of suitable model structures and also to establish the appropriateness of these multi-model simulations for global application. In support of the objectives of the GEWEX LandFlux project, four commonly used evaporation models are evaluated against data from tower-based eddy-covariance observations, distributed across a range of biomes and climate zones. The selected schemes include the Surface Energy Balance System (SEBS) approach, the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, the Penman-Monteith based Mu model (PM-Mu) and the Global Land Evaporation: the Amsterdam Methodology (GLEAM). Here we seek to examine the fidelity of global evaporation simulations by examining the multi-model response to varying sources of forcing data. To do this, we perform parallel and collocated model simulations using tower-based data together with a global-scale grid-based forcing product. Through quantifying the multi-model response to high-quality tower data, a better understanding of the subsequent model response to coarse-scale globally gridded data that underlies the LandFlux product can be obtained, while also providing a relative evaluation and assessment of model performance. Using surface flux observations from forty-five globally distributed eddy-covariance stations as independent metrics of performance, the tower-based analysis indicated that PT-JPL provided the highest overally statistical performance (0.72; 61 W m −2 ; 0.65), followed closely by GLEAM (0.68; 64 W m −2 ; 0.62), with values in parenthesis representing the R 2 , RMSD and Nash-Sutcliffe Efficiency (NSE) and respectively. PM-Mu (0.51; 78 W m −2 ; 0.45) tended to underestimate fluxes, while SEBS (0.72; 101 W m −2 ; 0.24) overestimated values relative to observations. A focused analysis across specific biome types and climate zones showed considerable variability in the performance of all models, with no single model consistently able to outperform any other. Results also indicated that the global gridded data tended to reduce the performance for all of the studied models when compared to the tower data, likely a response to scale mismatch and issues related to forcing quality. Rather than relying on any single model simulation, the spatial and temporal variability at both the tower- and grid-scale highlighted the potential benefits of developing an ensemble or blended evaporation product for global scale LandFlux applications. Challenges related to the robust assessment of the LandFlux product are also discussed.

Description: GO2OGS: a versatile workflow to integrate complex geological information with fault data into numerical simulation models Geoscientific Model Development Discussions, 8, 6309-6348, 2015 Author(s): T. Fischer, M. Walther, S. Sattler, D. Naumov, and O. Kolditz We offer a versatile workflow to convert geological models built with the software Paradigm™ GOCAD © into the open-source VTU format for the usage in numerical simulation models. Tackling relevant scientific questions or engineering tasks often involves multidisciplinary approaches. Conversion workflows are needed as a way of communication between the diverse tools of the various disciplines. Our approach offers an open-source, platform independent, robust, and comprehensible method that is potentially useful for a multitude of similar environmental studies. With two application examples in the Thuringian Syncline, we show how a heterogeneous geological GOCAD model including multiple layers and faults can be used for numerical groundwater flow modelling. The presented workflow offers the chance to incorporate increasingly detailed data, utilizing growing availability of computational power to simulate numerical models.

Description: WRF4G: WRF experiment management made simple Geoscientific Model Development Discussions, 8, 6551-6582, 2015 Author(s): V. Fernández-Quiruelas, J. Fernández, A. S. Cofiño, C. Blanco, M. García-Díez, M. Magariño, L. Fita, and J. M. Gutiérrez This work presents a framework, WRF4G, to manage the experiment workflow of the Weather Research and Forecasting (WRF) modelling system. WRF4G provides a flexible design, execution and monitoring for a general class of scientific experiments. It has been designed with the aim of facilitating the management and reproducibility of complex experiments. Furthermore, the concepts behind the design of this framework can be straightforwardly extended to other models. We describe the user interface and the new concepts required to design parameter-sweep, hindcast and climate simulation experiments. A number of examples are provided, based on the design used for existing (published) WRF experiments. This software is open-source and publicly available http://www.meteo.unican.es/software/wrf4g ).

Description: Implementation of the Community Earth System Model (CESM1, version 1.2.1) as a new basemodel into version 2.50 of the MESSy framework Geoscientific Model Development Discussions, 8, 6523-6550, 2015 Author(s): A. J. G. Baumgaertner, P. Jöckel, A. Kerkweg, R. Sander, and H. Tost The Community Earth System Model (CESM1), maintained by the United States National Centre for Atmospheric Research (NCAR) is connected with the Modular Earth Submodel System (MESSy). For the MESSy user community, this offers many new possibilities. The option to use the CESM1(CAM) atmospheric dynamical cores, especially the spectral element (SE) core, as an alternative to the ECHAM5 spectral transform dynamical core will provide scientific and computational advances for atmospheric chemistry and climate modelling with MESSy. The SE dynamical core does not require polar filters since the grid is quasi-uniform. By advecting the surface pressure rather then the logarithm of surface pressure the SE core locally conserves energy and mass. Furthermore, it has the possibility to scale to up to 10 5 compute cores, which is useful for current and future computing architectures. The well-established finite volume core from CESM1(CAM) is also made available. This offers the possibility to compare three different atmospheric dynamical cores within MESSy. Additionally, the CESM1 land, river, sea ice, glaciers and ocean component models can be used in CESM1/MESSy simulations, allowing to use MESSy as a comprehensive Earth System Model. For CESM1/MESSy setups, the MESSy process and diagnostic submodels for atmospheric physics and chemistry are used together with one of the CESM1(CAM) dynamical cores; the generic (infrastructure) submodels support the atmospheric model component. The other CESM1 component models as well as the coupling between them use the original CESM1 infrastructure code and libraries, although in future developments these can also be replaced by the MESSy framework. Here, we describe the structure and capabilities of CESM1/MESSy, document the code changes in CESM1 and MESSy, and introduce several simulations as example applications of the system. The Supplements provide further comparisons with the ECHAM5/MESSy atmospheric chemistry (EMAC) model and document the technical aspects of the connection in detail.

Description: DebrisInterMixing-2.3: a Finite Volume solver for three dimensional debris flow simulations based on a single calibration parameter – Part 2: Model validation Geoscientific Model Development Discussions, 8, 6379-6415, 2015 Author(s): A. von Boetticher, J. M. Turowski, B. W. McArdell, D. Rickenmann, M. Hürlimann, C. Scheidl, and J. W. Kirchner Here we present the validation of the fluid dynamic solver presented in part one of this work (von Boetticher et al., 2015), simulating laboratory-scale and large-scale debris-flow experiments. The material properties of the experiments, including water content, sand content, clay content and its mineral composition, and gravel content and its friction angle, were known. We show that given these measured properties, a single free model parameter is sufficient for calibration, and a range of experiments with different material compositions can be reproduced by the model without recalibration. The model validation focuses on different case studies illustrating the sensitivity of debris flows to water and clay content, channel curvature, channel roughness and the angle of repose of the gravel. We characterize the accuracy of the model using experimental observations of flow head positions, front velocities, run-out patterns and basal pressures.

Description: Modeling global water use for the 21st century: Water Futures and Solutions (WFaS) initiative and its approaches Geoscientific Model Development Discussions, 8, 6417-6521, 2015 Author(s): Y. Wada, M. Flörke, N. Hanasaki, S. Eisner, G. Fischer, S. Tramberend, Y. Satoh, M. T. H. van Vliet, P. Yillia, C. Ringler, and D. Wiberg To sustain growing food demand and increasing standard of living, global water use increased by nearly 6 times during the last 100 years and continues to grow. As water demands get closer and closer to the water availability in many regions, each drop of water becomes increasingly valuable and water must be managed more efficiently and intensively. However, soaring water use worsens water scarcity condition already prevalent in semi-arid and arid regions, increasing uncertainty for sustainable food production and economic development. Planning for future development and investments requires that we prepare water projections for the future. However, estimations are complicated because the future of world's waters will be influenced by a combination of environmental, social, economic, and political factors, and there is only limited knowledge and data available about freshwater resources and how they are being used. The Water Futures and Solutions initiative (WFaS) coordinates its work with other on-going scenario efforts for the sake of establishing a consistent set of new global water scenarios based on the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). The WFaS "fast-track" assessment uses three global water models, namely H08, PCR-GLOBWB, and WaterGAP. This study assesses the state of the art for estimating and projecting water use regionally and globally in a consistent manner. It provides an overview of different approaches, the uncertainty, strengths and weaknesses of the various estimation methods, types of management and policy decisions for which the current estimation methods are useful. We also discuss additional information most needed to be able to improve water use estimates and be able to assess a greater range of management options across the water-energy-climate nexus.

Description: Influence of grid aspect ratio on planetary boundary layer turbulence in large-eddy simulations Geoscientific Model Development Discussions, 8, 6021-6094, 2015 Author(s): S. Nishizawa, H. Yashiro, Y. Sato, Y. Miyamoto, and H. Tomita We examine the influence of the grid aspect ratio of horizontal to vertical grid spacing on turbulence in the planetary boundary layer (PBL) in a large-eddy simulation (LES). In order to distinguish them as much as possible from other artificial effects caused by numerical schemes, we used a fully compressible meteorological LES model with a fully explicit scheme of temporal integration. The influences are investigated with a series of sensitivity tests with parameter sweeps of spatial resolution and grid aspect ratio. We confirmed that the mixing length of the eddy viscosity and diffusion due to sub-grid scale turbulence plays an essential role in reproducing the theoretical −5/3 slope of the energy spectrum. If we define the filter length in LES modeling based on consideration of the numerical scheme, and introduce a corrective factor for the grid aspect ratio into the mixing length, the theoretical slope of the energy spectrum can be obtained; otherwise, spurious energy piling appears at high wavenumbers. We also found that the grid aspect ratio has influence on the turbulent statistics, especially the skewness of the vertical velocity near the top of the PBL, which becomes spuriously large with large aspect ratio, even if a reasonable spectrum is obtained.

Description: The role of ecosystem function and emergent relationships in the assessment of global marine ecosystem models: a case study with ERSEM Geoscientific Model Development Discussions, 8, 6095-6141, 2015 Author(s): L. de Mora, M. Butenschön, and J. I. Allen Ecosystem models are often assessed using quantitative metrics of absolute ecosystem state, but these model-data comparisons are disproportionately vulnerable to discrepancies in the location of important circulation features. An alternative method is to demonstrate the models capacity to represent ecosystem function; the emergence of a coherent natural relationship in a simulation is a strong indication that the model has a appropriate representation of the ecosystem functions that lead to the emergent relationship. Furthermore, as emergent properties are large scale properties of the system, model validation with emergent properties is possible even when there is very little or no appropriate data for the region under study, or when the hydrodynamic component of the model differs significantly from that observed in nature at the same location and time. A selection of published meta-analyses are used to establish the validity of a complex marine ecosystem model and to demonstrate the power of validation with emergent properties. These relationships include the phytoplankton community structure, the ratio of carbon to chlorophyll in phytoplankton and particulate organic matter, the ratio of particulate organic carbon to particulate organic nitrogen and the stoichiometric balance of the ecosystem. These metrics can also inform aspects of the marine ecosystem model not available from traditional quantitative and qualitative methods. For instance, these emergent properties can be used to validate the design decisions of the model, such as the range of phytoplankton functional types and their behaviour, the stoichiometric flexibility with regards to each nutrient, and the choice of fixed or variable carbon to nitrogen ratios.

Description: A semi-Lagrangian advection scheme for radioactive tracers in a regional spectral model Geoscientific Model Development Discussions, 8, 4221-4243, 2015 Author(s): E.-C. Chang and K. Yoshimura In this study, the non-iteration dimensional-split semi-Lagrangian (NDSL) advection scheme is applied to the National Centers for Environmental Prediction (NCEP) regional spectral model (RSM) to alleviate the Gibbs phenomenon. The Gibbs phenomenon is a problem wherein negative values of positive-definite quantities (e.g., moisture and tracers) are generated by the spectral space transformation in a spectral model system. To solve this problem, the spectral prognostic specific humidity and radioactive tracer advection scheme is replaced by the NDSL advection scheme, which considers advection of tracers in a grid system without spectral space transformations. A regional version of the NDSL is developed in this study and is applied to the RSM. Idealized experiments show that the regional version of the NDSL is successful. The model runs for an actual case study suggest that the NDSL can successfully advect radioactive tracers (iodine-131 and cesium-137) without noise from the Gibbs phenomenon. The NDSL can also remove negative specific humidity values produced in spectral calculations without losing detailed features.

Description: Open-source modular solutions for flexural isostasy: gFlex v1.0 Geoscientific Model Development Discussions, 8, 4245-4292, 2015 Author(s): A. D. Wickert Isostasy is one of the oldest and most widely applied concepts in the geosciences, but the geoscientific community lacks a coherent, easy-to-use tool to simulate flexure of a realistic (i.e. laterally heterogeneous) lithosphere under an arbitrary set of surface loads. Such a model is needed for studies of mountain-building, sedimentary basin formation, glaciation, sea-level change, and other tectonic, geodynamic, and surface processes. Here I present gFlex, an open-source model that can produce analytical and finite difference solutions for lithospheric flexure in one (profile) and two (map view) dimensions. To simulate the flexural isostatic response to an imposed load, it can be used by itself or within GRASS GIS for better integration with field data. gFlex is also a component with the Community Surface Dynamics Modeling System (CSDMS) and Landlab modeling frameworks for coupling with a wide range of Earth-surface-related models, and can be coupled to additional models within Python scripts. As an example of this in-script coupling, I simulate the effects of spatially variable lithospheric thickness on a modeled Iceland ice cap. Finite difference solutions in gFlex can use any of five types of boundary conditions: 0-displacement, 0-slope (i.e. clamped); 0-slope, 0-shear; 0-moment, 0-shear (i.e. broken plate); mirror symmetry; and periodic. Typical calculations with gFlex require ≪ 1s to ~1 min on a personal laptop computer. These characteristics – multiple ways to run the model, multiple solution methods, multiple boundary conditions, and short compute time – make gFlex an effective tool for flexural isostatic modeling across the geosciences.

Description: A new multiscale air quality transport model (Fluidity, 4.1.9) using fully unstructured anisotropic adaptive mesh technology Geoscientific Model Development Discussions, 8, 4337-4374, 2015 Author(s): J. Zheng, J. Zhu, Z. Wang, F. Fang, C. C. Pain, and J. Xiang A new anisotropic hr-adaptive mesh technique has been applied to modelling of multiscale transport phenomena, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been setup for two-dimensional (2-D) transport phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes.

Description: SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems Geoscientific Model Development Discussions, 8, 6143-6216, 2015 Author(s): J. A. Bradley, A. M. Anesio, J. S. Singarayer, M. R. Heath, and S. Arndt SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework which is developed as part of an interdisciplinary, iterative, model-data based approach fully integrating fieldwork and laboratory experiments with model development, testing, and application. SHIMMER is designed to simulate the establishment of microbial biomass and associated biogeochemical cycling during the initial stages of ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The model mechanistically describes and predicts transformations in carbon, nitrogen and phosphorus through aggregated components of the microbial community as a set of coupled ordinary differential equations. The rationale for development of the model arises from decades of empirical observation on the initial stages of soil development in glacier forefields. SHIMMER enables a quantitative and process focussed approach to synthesising the existing empirical data and advancing understanding of microbial and biogeochemical dynamics. Here, we provide a detailed description of SHIMMER. The performance of SHIMMER is then tested in two case studies using published data from the Damma Glacier forefield in Switzerland and the Athabasca Glacier in Canada. In addition, a sensitivity analysis helps identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q 10 values, the active fraction of microbial biomass, and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Simulation results indicate that primary production is responsible for the initial build-up of substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter are identified as important in sustaining this productivity. Microbial production in young soils is supported by labile organic matter, whereas carbon stocks in older soils are more refractory. Nitrogen fixing bacteria are responsible for the initial accumulation of available nitrates in the soil. Biogeochemical rates are highly seasonal, as observed in experimental data. The development and application of SHIMMER not only provides important new insights into forefield dynamics, but also highlights aspects of these systems that require further field and laboratory research. The most pressing advances need to come in quantifying nutrient budgets and biogeochemical rates, in exploring seasonality, the fate of allochthonous deposition in relation to autochthonous production, and empirical studies of microbial growth and cell death, to increase understanding of how glacier forefield development contributes to the global biogeochemical cycling and climate in the future.

Description: DebrisInterMixing-2.3: a Finite Volume solver for three dimensional debris flow simulations based on a single calibration parameter – Part 1: Model description Geoscientific Model Development Discussions, 8, 6349-6378, 2015 Author(s): A. von Boetticher, J. M. Turowski, B. W. McArdell, D. Rickenmann, and J. W. Kirchner Here we present a three-dimensional fluid dynamic solver that simulates debris flows as a mixture of two phases (gravel and fine material suspension) with a third unmixed phase representing the air and the free surface. We link all rheological parameters to the material composition, i.e., to water content, clay content and mineral composition, content of sand and gravel, and the gravel's friction angle; the user must specify only a single free model parameter. The Volume-Of-Fluid (VOF) approach is used to combine the three phases into a single cell-averaged Navier–Stokes equation for incompressible flow, based on code adapted from standard solvers of the Open-Source CFD software OpenFOAM. We present a stable implementation of a Coulomb-Viscoplastic model that represents the pressure-dependent flow behavior of the granular phase, and a Herschel–Bulkley representation of the interstitial fluid. The VOF method saves computational costs compared to drag-force based multiphase models. Thus depth-averaging is not necessary and complex three-dimensional flow structures can be simulated.

Description: Representativeness errors in comparing chemistry transport and chemistry climate models with satellite UV/Vis tropospheric column retrievals Geoscientific Model Development Discussions, 8, 7821-7877, 2015 Author(s): K. F. Boersma, G. C. M. Vinken, and H. J. Eskes UV/Vis satellite retrievals of trace gas columns of nitrogen dioxide (NO 2 ), sulphur dioxide (SO 2 ), and formaldehyde (HCHO) are useful to test and improve models of atmospheric composition, for data assimilation, air quality hindcasting and forecasting, and to provide top-down constraints on emissions. However, because models and satellite measurements do not represent the exact same geophysical quantities, the process of confronting model fields with satellite measurements is complicated by representativeness errors, which degrade the quality of the comparison beyond contributions from modelling and measurement errors alone. Here we discuss three types of representativeness errors that arise from the act of carrying out a model-satellite comparison: (1) horizontal representativeness errors due to imperfect collocation of the model grid cell and an ensemble of satellite pixels called superobservation, (2) temporal representativeness errors originating mostly from differences in cloud cover between the modelled and observed state, and (3) vertical representativeness errors because of reduced satellite sensitivity towards the surface accompanied with necessary retrieval assumptions on the state of the atmosphere. To minimize the impact of these representativeness errors, we recommend that models and satellite measurements be sampled as consistently as possible, and our paper provides a number of recipes to do so. A practical confrontation of tropospheric NO 2 columns simulated by the TM5 chemistry transport model (CTM) with Ozone Monitoring Instrument (OMI) tropospheric NO 2 retrievals suggests that horizontal representativeness errors, while unavoidable, are limited to within 5–10 % in most cases and of random nature. These errors should be included along with the individual retrieval errors in the overall superobservation error. Temporal sampling errors from mismatches in cloud cover, and, consequently, in photolysis rates, are on the order of 10 % for NO 2 and HCHO, and systematic, but partly avoidable. In the case of air pollution applications where sensitivity down to the ground is required, we recommend that models should be sampled on the same mostly cloud-free days as the satellite retrievals. The most relevant representativeness error is associated with the vertical sensitivity of Ultraviolet-visible (UV/Vis) satellite retrievals. Simple vertical integration of modelled profiles leads to systematically different model columns compared to application of the appropriate averaging kernel. In comparing OMI NO 2 to GEOS-Chem NO 2 simulations, these systematic differences are as large as 15–20 % in summer, but, again, avoidable.

Description: LIMA (v1.0): a two-moment microphysical scheme driven by a multimodal population of cloud condensation and ice freezing nuclei Geoscientific Model Development Discussions, 8, 7767-7820, 2015 Author(s): B. Vié, J.-P. Pinty, S. Berthet, and M. Leriche The paper describes the 2-moment microphysical scheme LIMA (Liquid Ice Multiple Aerosols), which relies on the prognostic evolution of a three-dimensional (3-D) aerosol population, and the careful description of the nucleating properties that enable cloud droplets and pristine ice crystals to form. LIMA uses the aerosol nucleating properties to form cloud droplets and pristine ice crystals. Several modes of Cloud Condensation Nuclei (CCN) and Ice Freezing Nuclei (IFN) are considered individually. A special class of partially soluble IFN is also introduced. These "aged" IFN act first as CCN and then as IFN by immersion nucleation at low temperatures. All the CCN modes are in competition with each other, as expressed by the single equation of maximum supersaturation. The IFN are insoluble aerosols that nucleate ice in several ways (condensation, deposition and immersion freezing) assuming the singular hypothesis. The scheme also includes the homogeneous freezing of cloud droplets, the Hallett–Mossop ice multiplication process and the freezing of haze at very low temperature. LIMA assumes that water vapour is in thermodynamic equilibrium with the population of cloud droplets (adjustment to saturation in warm clouds). In ice clouds, the prediction of the number concentration of the pristine ice crystals is used to compute explicit deposition and sublimation rates (leading to free under/supersaturation over ice). The formation of hydrometeors is standard. The autoconversion, accretion and self-collection processes shape the raindrop spectra. The initiation of the large crystals and aggregates category is the result of the depositional growth of large crystals beyond a critical size. Aggregation and riming are computed explicitly. Heavily rimed crystals (graupel) can experience a dry or wet growth mode. An advanced version of the scheme includes a separate hail category of particles forming and growing exclusively in the wet growth mode. The sedimentation of all particle types is included. The LIMA scheme is inserted in the cloud-resolving mesoscale model Meso-NH. The flexibility of LIMA is illustrated by two 2-D experiments. The first one highlights the sensitivity of orographic ice clouds to IFN types and IFN concentrations. Then a squall line case discusses the microstructure of a mixed-phase cloud and the impacts of pure CCN and IFN polluting plumes. The experiments show that LIMA captures the complex nature of aerosol-cloud interactions leading to different pathways for cloud and precipitation formation.

Description: Evaluation of improved land use and canopy representation in BEIS v3.61 with biogenic VOC measurements in California Geoscientific Model Development Discussions, 8, 8117-8154, 2015 Author(s): J. O. Bash, K. R. Baker, and M. R. Beaver Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data is based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for years from 2002 to 2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emissions estimates are used in Community Multiscale Air Quality Model (CMAQ) simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterpenes taken during multiple field campaigns in northern California. The updated canopy model coupled with improved land use and vegetation representation resulted in better agreement between CMAQ isoprene and monoterpene estimates compared with these observations.

Description: IL-GLOBO (1.0) – development and verification of the moist convection module Geoscientific Model Development Discussions, 8, 8239-8261, 2015 Author(s): D. Rossi, A. Maurizi, and M. Fantini The development and verification of the convective module of IL-GLOBO, a Lagrangian transport model coupled online with the Eulerian general circulation model GLOBO, is described. The online-coupling promotes the full consistency between the Eulerian and the Lagrangian components of the model. The Lagrangian convective scheme is derived based on the Kain–Fritsch convective parameterisation used in GLOBO. A transition probability matrix is computed using the fluxes provided by the Eulerian KF parameterisation. Then, the convection redistribution of Lagrangian particles is implemented via a Monte Carlo scheme. The formal derivation is described in details and, consistently with the Eulerian module, includes the environmental flux in the transition probability matrix to avoid splitting of the convection and subsidence processes. Consistency of the Lagrangian implementation with its Eulerian counterpart is verified by computing environment fluxes from the transition probability matrix and comparing them to those computed by the Eulerian module. Assessment of the impact of the module is made for different latitudinal belts, showing that the major impact is found in the tropics, as expected. Concerning vertical distribution, the major impact is observed in the boundary layer at every latitude, while in the tropical area, the influence extends to very high levels.

Description: Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3 Geoscientific Model Development Discussions, 8, 6931-6986, 2015 Author(s): S. Westermann, M. Langer, J. Boike, M. Heikenfeld, M. Peter, B. Etzelmüller, and G. Krinner Thawing of permafrost in a warming climate is governed by a complex interplay of different processes, of which only conductive heat transfer is taken into account in most model studies. However, observations in many permafrost landscapes demonstrate that lateral and vertical movement of water can have a pronounced influence on the thaw trajectories, creating distinct landforms like thermokarst ponds and lakes even in areas where permafrost is otherwise thermally stable. Novel process parameterizations are required to include such phenomena in future projections of permafrost thaw and hereby triggered climatic feedbacks. In this study, we present a new land-surface scheme designed for permafrost applications, CryoGrid 3, which constitutes a flexible platform to explore new parameterizations for a range of permafrost processes. We document the model physics and employed parameterizations for the basis module CryoGrid 3, and compare model results with in-situ observations of surface energy balance, surface temperatures, and ground thermal regime from the Samoylov permafrost observatory in NE Siberia. The comparison suggests that CryoGrid 3 can not only model the evolution of the ground thermal regime in the last decade, but also consistently reproduce the chain of energy transfer processes from the atmosphere to the ground. In addition, we demonstrate a simple 1-D parameterization for thaw process in permafrost areas rich in ground ice, which can phenomenologically reproduce both formation of thermokarst ponds and subsidence of the ground following thawing of ice-rich subsurface layers. Long-term simulation from 1901–2100 driven by reanalysis data and climate model output demonstrate that the hydrological regime can both accelerate and delay permafrost thawing. If meltwater from thawed ice-rich layers can drain, the ground subsides while at the same time the formation of a talik is delayed. If the meltwater pools at the surface, a pond is formed which enhances heat transfer in the ground and leads to the formation of a talik. The model results suggest that the trajectories of future permafrost thaw are strongly influenced by the cryostratigraphy, as determined by the late quaternary history of a site.

Description: Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2) Geoscientific Model Development Discussions, 8, 9193-9227, 2015 Author(s): B. Guenet, F. E. Moyano, P. Peylin, P. Ciais, and I. A. Janssens Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first order kinetics. We then compared the PRIM model and the standard first order decay model incorporated into the global land biosphere model ORCHIDEE. A test of both models was performed at ecosystem scale using litter manipulation experiments from 5 sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming ( R 2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.

Description: Treatment of non-ideality in the multiphase model SPACCIM – Part 1: Model development Geoscientific Model Development Discussions, 8, 4155-4219, 2015 Author(s): A. J. Rusumdar, R. Wolke, A. Tilgner, and H. Herrmann Ambient tropospheric deliquesced particles generally comprise a complex mixture of electrolytes, organic compounds, and water. Dynamic modeling of physical and chemical processes in this complex matrix is challenging. Thus, up-to-date multiphase chemistry models do generally not consider non-ideal solution effects. Therefore, the present study was aimed at the further development of the SPACCIM model to treat both complex multiphase chemistry and phase transfer processes considering newly non-ideality properties of concentrated aerosol solutions. The present paper describes firstly, the performed model development including (i) the kinetic implementation of the non-ideality in the SPACCIM framework, (ii) the advancements in the coupling scheme of microphysics and multiphase chemistry and (iii) the required adjustments of the numerical schemes, especially in the sparse linear solver and the calculation of the Jacobian. Secondly, results of performed sensitivity investigations are outlined aiming at the evaluation of different activity coefficient modules and the examination of the contributions of different intermolecular forces to the overall activity coefficients. Finally, first results obtained with the new model framework are presented. The main product of the performed model development is the new kinetic model approach SPACCIM-SpactMod, which utilizes activities in reaction terms instead of aqueous concentrations. Based on an intercomparison of different activity coefficient models and the comparison with experimental data, AIOMFAC was selected as base model and extended by additional interaction parameters from literature for mixed organic–inorganic systems. Moreover, the performance and the capability of the applied activity coefficient module were evaluated by means of water activity measurements, literature data and results of other thermodynamic equilibrium models. Comprehensive comparison studies showed that the SpactMod (SPACCIM activity coefficient module) is valuable to predict the thermodynamic behavior of complex mixtures of multicomponent atmospheric aerosol particles. First simulations with a detailed chemical mechanism have demonstrated the applicability of SPACCIM-SpactMod. The simulations have implied that the treatment of non-ideality should be mandatory for modeling multiphase chemistry processes in deliquesced particles. The modeled activity coefficients implicate that turnovers of chemical processes in deliquesced particles can be both decreased and increased depending on the particular species involved in the reactions. For key ions, activity coefficients on the order of 0.1–0.8 and a strong dependency on the charge state as well as the RH conditions are modeled implicating a lowered chemical ion processing in concentrated solutions. In contrast, modeled activity coefficients of organic compounds are partly 〉 1 and suggest the possibility of an increased organic processing. Moreover, the model runs have shown noticeable differences in the pH values calculated with and without consideration of non-ideality. On average, the predicted pH values of the simulations considering non-ideality are −0.27 and −0.44 pH units lower under 90 and 70% RH conditions, respectively. More comprehensive results of detailed SPACCIM-SpactMod studies on the multiphase processing in organic–inorganic mixtures of deliquesced particles are described in a companion paper.

Description: Integration of nitrogen dynamics into the Noah-MP land model v1.1 for climate and environmental predictions Geoscientific Model Development Discussions, 8, 4113-4153, 2015 Author(s): X. Cai, Z.-L. Yang, J. B. Fisher, X. Zhang, M. Barlage, and F. Chen Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station – a Long-term Ecological Research site within the U.S. Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of the carbon and water cycles (e.g., net primary productivity and evapotranspiration). The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

Description: Improved simulation of precipitation in the tropics using a modified BMJ scheme in WRF model Geoscientific Model Development Discussions, 8, 4019-4049, 2015 Author(s): R. Fonseca, T. Zhang, and T. Y. Koh The successful modelling of the observed precipitation, a very important variable for a wide range of climate applications, continues to be one of the major challenges that climate scientists face today. When the Weather Research and Forecasting (WRF) model is used to dynamically downscale the Climate Forecast System Reanalysis (CFSR) over the Indo-Pacific region, with analysis (grid-point) nudging, it is found that the cumulus scheme used, Betts–Miller–Janjić (BMJ), produces excessive rainfall suggesting that it has to be modified for this region. Experimentation has shown that the cumulus precipitation is not very sensitive to changes in the cloud efficiency but varies greatly in response to modifications of the temperature and humidity reference profiles. A new version of the scheme, denominated "modified BMJ" scheme, where the humidity reference profile is more moist, was developed and in tropical belt simulations it was found to give a better estimate of the observed precipitation, as given by the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset, than the default BMJ scheme for the whole tropics and both monsoon seasons. In fact, in some regions the model even outperforms CFSR. The advantage of modifying the BMJ scheme to produce better rainfall estimates lies in the final dynamical consistency of the rainfall with other dynamical and thermodynamical variables of the atmosphere.

Description: S 4 CAST v2.0: sea surface temperature based statistical seasonal forecast model Geoscientific Model Development Discussions, 8, 3971-4018, 2015 Author(s): R. Suárez-Moreno and B. Rodríguez-Fonseca Sea Surface Temperature is the key variable when tackling seasonal to decadal climate forecast. Dynamical models are unable to properly reproduce tropical climate variability, introducing biases that prevent a skillful predictability. Statistical methodologies emerge as an alternative to improve the predictability and reduce these biases. Recent studies have put forward the non-stationary behavior of the teleconnections between tropical oceans, showing how the same tropical mode has different impacts depending on the considered sequence of decades. To improve the predictability, the Sea Surface Temperature based Statistical Seasonal foreCAST model (S 4 CAST) introduces the novelty of considering the non-stationary links between the predictor and predictand fields. This paper describes the development of S 4 CAST model whose operation is focused on the study of the predictability of any variable related to sea surface temperature. An application focused on West African rainfall predictability has been implemented as a benchmark example.

Description: PLUME-MoM 1.0: a new 1-D model of volcanic plumes based on the method of moments Geoscientific Model Development Discussions, 8, 3745-3790, 2015 Author(s): M. de' Michieli Vitturi, A. Neri, and S. Barsotti In this paper a new mathematical model for volcanic plumes, named PlumeMoM, is presented. The model describes the steady-state 1-D dynamics of the plume in a 3-D coordinate system, accounting for continuous variability in particle distribution of the pyroclastic mixture ejected at the vent. Volcanic plumes are composed of pyroclastic particles of many different sizes ranging from a few microns up to several centimeters and more. Proper description of such a multiparticle nature is crucial when quantifying changes in grain-size distribution along the plume and, therefore, for better characterization of source conditions of ash dispersal models. The new model is based on the method of moments, which allows description of the pyroclastic mixture dynamics not only in the spatial domain but also in the space of properties of the continuous size-distribution of the particles. This is achieved by formulation of fundamental transport equations for the multiparticle mixture with respect to the different moments of the grain-size distribution. Different formulations, in terms of the distribution of the particle number, as well as of the mass distribution expressed in terms of the Krumbein log scale, are also derived. Comparison between the new moments-based formulation and the classical approach, based on the discretization of the mixture in N discrete phases, shows that the new model allows the same results to be obtained with a significantly lower computational cost (particularly when a large number of discrete phases is adopted). Application of the new model, coupled with uncertainty quantification and global sensitivity analyses, enables investigation of the response of four key output variables (mean and standard deviation (SD) of the grain-size distribution at the top of the plume, plume height and amount of mass lost by the plume during the ascent) to changes in the main input parameters (mean and SD) characterizing the pyroclastic mixture at the base of the plume. Results show that, for the range of parameters investigated, the grain-size distribution at the top of the plume is remarkably similar to that at the base and that the plume height is only weakly affected by the parameters of the grain distribution.

Description: ECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation Geoscientific Model Development Discussions, 8, 3653-3743, 2015 Author(s): G. Forget, J.-M. Campin, P. Heimbach, C. N. Hill, R. M Ponte, and C. Wunsch This paper presents the ECCO v4 non-linear inverse modeling framework and its baseline solution for the evolving ocean state over the period 1992–2011. Both components are publicly available and highly integrated with the MITgcm. They are both subjected to regular, automated regression tests. The modeling framework includes sets of global conformal grids, a global model setup, implementations of model-data constraints and adjustable control parameters, an interface to algorithmic differentiation, as well as a grid-independent, fully capable Matlab toolbox. The reference ECCO v4 solution is a dynamically consistent ocean state estimate (ECCO-Production, release 1) without un-identified sources of heat and buoyancy, which any interested user will be able to reproduce accurately. The solution is an acceptable fit to most data and has been found physically plausible in many respects, as documented here and in related publications. Users are being provided with capabilities to assess model-data misfits for themselves. The synergy between modeling and data synthesis is asserted through the joint presentation of the modeling framework and the state estimate. In particular, the inverse estimate of parameterized physics was instrumental in improving the fit to the observed hydrography, and becomes an integral part of the ocean model setup available for general use. More generally, a first assessment of the relative importance of external, parametric and structural model errors is presented. Parametric and external model uncertainties appear to be of comparable importance and dominate over structural model uncertainty. The results generally underline the importance of including turbulent transport parameters in the inverse problem.

Description: An automatic and effective parameter optimization method for model tuning Geoscientific Model Development Discussions, 8, 3791-3822, 2015 Author(s): T. Zhang, L. Li, Y. Lin, W. Xue, F. Xie, H. Xu, and X. Huang Physical parameterizations in General Circulation Models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.

Description: A new ensemble-based consistency test for the Community Earth System Model Geoscientific Model Development Discussions, 8, 3823-3859, 2015 Author(s): A. H. Baker, D. M. Hammerling, M. N. Levy, H. Xu, J. M. Dennis, B. E. Eaton, J. Edwards, C. Hannay, S. A. Mickelson, R. B. Neale, D. Nychka, J. Shollenberger, J. Tribbia, M. Vertenstein, and D. Williamson Climate simulations codes, such as the Community Earth System Model (CESM), are especially complex and continually evolving. Their on-going state of development requires frequent software verification in the form of quality assurance to both preserve the quality of the code and instill model confidence. To formalize and simplify this previously subjective and computationally-expensive aspect of the verification process, we have developed a new tool for evaluating climate consistency. Because an ensemble of simulations allows us to gauge the natural variability of the model's climate, our new tool uses an ensemble approach for consistency testing. In particular, an ensemble of CESM climate runs is created, from which we obtain a statistical distribution that can be used to determine whether a new climate run is statistically distinguishable from the original ensemble. The CESM Ensemble Consistency Test, referred to as CESM-ECT, is objective in nature and accessible to CESM developers and users. The tool has proven its utility in detecting errors in software and hardware environments and providing rapid feedback to model developers.

Description: A new sub-grid surface mass balance and flux model for continental-scale ice sheet modelling: validation and last glacial cycle Geoscientific Model Development Discussions, 8, 3037-3077, 2015 Author(s): K. Le Morzadec, L. Tarasov, M. Morlighem, and H. Seroussi To investigate ice sheet evolution over the time scale of a glacial cycle, 3-D ice sheet models (ISMs) need to be run at grid resolutions (10 to 50 km) that do not resolve individual mountains. This will introduce to-date unquantified errors in sub-grid (SG) transport, accumulation and ablation for regions of rough topography. In the past, synthetic hypsometric curves, a statistical summary of the topography, have been used in ISMs to describe the variability of these processes. However, there has yet to be detailed uncertainty analysis of this approach. We develop a new SG model using a 1 km resolution digital elevation model to compute each local hypsometric curve and to determine local parameters to represent the hypsometric levels' slopes and widths. 1-D mass-transport for the SG model is computed with the shallow ice approximation. We test this model against simulations produced by the 3-D Ice Sheet System Model (ISSM) run at 1 km grid resolution. Results show that no simple parameterization can totally capture SG surface mass balance and flux processes. Via glacial cycle ensemble results for North America, we quantify the impact of SG model coupling in an ISM and the associated parametric uncertainties related to the exchange of ice between the SG and coarse grid levels. Via glacial cycle ensemble results for North America, we quantify the impact of SG model coupling in an ISM. We show that SG process representation and associated parametric uncertainties, related to the exchange of ice between the SG and coarse grid levels, can have significant impact on modelled ice sheet evolution.

Description: Validation of reactive gases and aerosols in the MACC global analysis and forecast system Geoscientific Model Development Discussions, 8, 1117-1169, 2015 Author(s): H. Eskes, V. Huijnen, A. Arola, A. Benedictow, A.-M. Blechschmidt, E. Botek, O. Boucher, I. Bouarar, S. Chabrillat, E. Cuevas, R. Engelen, H. Flentje, A. Gaudel, J. Griesfeller, L. Jones, J. Kapsomenakis, E. Katragkou, S. Kinne, B. Langerock, M. Razinger, A. Richter, M. Schultz, M. Schulz, N. Sudarchikova, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos The European MACC (Monitoring Atmospheric Composition and Climate) project is preparing the operational Copernicus Atmosphere Monitoring Service (CAMS), one of the services of the European Copernicus Programme on Earth observation and environmental services. MACC uses data assimilation to combine in-situ and remote sensing observations with global and regional models of atmospheric reactive gases, aerosols and greenhouse gases, and is based on the Integrated Forecast System of the ECMWF. The global component of the MACC service has a dedicated validation activity to document the quality of the atmospheric composition products. In this paper we discuss the approach to validation that has been developed over the past three years. Topics discussed are the validation requirements, the operational aspects, the measurement data sets used, the structure of the validation reports, the models and assimilation systems validated, the procedure to introduce new upgrades, and the scoring methods. One specific target of the MACC system concerns forecasting special events with high pollution concentrations. Such events receive extra attention in the validation process. Finally, a summary is provided of the results from the validation of the latest set of daily global analysis and forecast products from the MACC system reported in November 2014.

Description: Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes Geoscientific Model Development Discussions, 8, 3293-3357, 2015 Author(s): R. A. Fisher, S. Muszala, M. Verteinstein, P. Lawrence, C. Xu, N. G. McDowell, R. G. Knox, C. Koven, J. Holm, B. M. Rogers, D. Lawrence, and G. Bonan We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.

Description: Revision of the convective transport module CVTRANS 2.4 in the EMAC atmospheric chemistry–climate model Geoscientific Model Development Discussions, 8, 3117-3145, 2015 Author(s): H. G. Ouwersloot, A. Pozzer, B. Steil, H. Tost, and J. Lelieveld The convective transport module, CVTRANS, of the ECHAM/MESSy Atmospheric Chemistry (EMAC) model has been revised to better represent the physical flows and incorporate recent findings on the properties of the convective plumes. The modifications involve (i) applying intermediate time stepping based on a settable criterion, (ii) using an analytic expression to account for the intra time step mixing ratio evolution below cloud base, and (iii) implementing a novel expression for the mixing ratios of atmospheric compounds at the base of an updraft. Even when averaged over a year, the predicted mixing ratios of atmospheric compounds are significantly affected by the intermediate time stepping. For example, for an exponentially decaying atmospheric tracer with a lifetime of 1 day, the zonal averages can locally differ by more than a factor of 6 and the induced root mean square deviation from the original code is, weighted by the air mass, higher than 40% of the average mixing ratio. The other modifications result in smaller differences. However, since they do not require additional computational time, their application is also recommended.

Description: Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83) Geoscientific Model Development Discussions, 8, 3235-3292, 2015 Author(s): A. L. Atchley, S. L. Painter, D. R. Harp, E. T. Coon, C. J. Wilson, A. K. Liljedahl, and V. E. Romanovsky Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.

Description: Metos3D: a marine ecosystem toolkit for optimization and simulation in 3-D – Simulation Package v0.2 Geoscientific Model Development Discussions, 8, 4401-4451, 2015 Author(s): J. Piwonski and T. Slawig A general programming interface for parameter identification for marine ecosystem models is introduced. A comprehensive solver software for periodic steady-states is implemented that includes a fixed point iteration (spin-up) and a Newton solver. The software is based on the Portable, Extensible Toolkit for Scientific Computation (PETSc) library and uses transport matrices for efficient off-line simulation in 3-D. In addition to the usage of PETSc's parallel data structures and PETSc's Newton solver, an own load balancing algorithm is implemented. A simple verification is carried out using a well investigated biogeochemical model for phosphate (PO 4 ) and dissolved organic phosphorous (DOP) with 7 parameters. The model is coupled via the interface to transport matrices that correspond to a longitudinal and latitudinal resolution of 2.8125° and 15 vertical layers. Initial tests show that both solvers and the load balancing algorithm work correctly. Further experiments demonstrate the robustness of the Newton solver with respect to parameter variations. Moreover, the numerical tests reveal that, with optimal control settings, the Newton solver converges at least 6 times faster towards a solution than the spin-up. However, additional twin experiments reveal differences between both solvers regarding a derivative-based black-box optimization. Whereas an optimization run with spin-up-based model evaluations is capable to identify model parameters of a reference solution, Newton-based model evaluations result in an inaccurate gradient approximation.

Description: Assessment of valley cold pools and clouds in a very high resolution NWP model Geoscientific Model Development Discussions, 8, 4453-4486, 2015 Author(s): J. K. Hughes, A. N. Ross, S. B. Vosper, A. P. Lock, and B. C. Jemmett-Smith The formation of cold air pools in valleys under stable conditions represents an important challenge for numerical weather prediction (NWP). The challenge is increased when the valleys which dominate cold pool formation are on scales unresolved by NWP models, which can lead to substantial local errors in temperature forecasts. In this study a two-month simulation is presented using a nested model configuration with a finest horizontal grid spacing of 100 m. The simulation is compared with observations from the recent COLPEX project and the model's ability to represent cold pool formation and the surface energy balance is assessed. The results reveal a bias in the model long-wave radiation which results from the assumptions made about the sub-grid variability in humidity in the cloud parametrization scheme. The cloud scheme assumes relative humidity thresholds below 100% to diagnose partial cloudiness, an approach common to schemes used in many other models. The biases in radiation, and resulting biases in screen temperature and cold pool properties are shown to be sensitive to the choice of critical relative humidity, suggesting that this is a key area which should be improved for very high resolution modelling.

Description: SiSeRHMap v1.0: a simulator for mapped seismic response using a hybrid model Geoscientific Model Development Discussions, 8, 4487-4544, 2015 Author(s): G. Grelle, L. Bonito, A. Lampasi, P. Revellino, L. Guerriero, G. Sappa, and F. M. Guadagno SiSeRHMap is a computerized methodology capable of drawing up prediction maps of seismic response. It was realized on the basis of a hybrid model which combines different approaches and models in a new and non-conventional way. These approaches and models are organized in a code-architecture composed of five interdependent modules. A GIS (Geographic Information System) Cubic Model (GCM), which is a layered computational structure based on the concept of lithodynamic units and zones, aims at reproducing a parameterized layered subsoil model. A metamodeling process confers a hybrid nature to the methodology. In this process, the one-dimensional linear equivalent analysis produces acceleration response spectra of shear wave velocity-thickness profiles, defined as trainers, which are randomly selected in each zone. Subsequently, a numerical adaptive simulation model (Spectra) is optimized on the above trainer acceleration response spectra by means of a dedicated Evolutionary Algorithm (EA) and the Levenberg–Marquardt Algorithm (LMA) as the final optimizer. In the final step, the GCM Maps Executor module produces a serial map-set of a stratigraphic seismic response at different periods, grid-solving the calibrated Spectra model. In addition, the spectra topographic amplification is also computed by means of a numerical prediction model. This latter is built to match the results of the numerical simulations related to isolate reliefs using GIS topographic attributes. In this way, different sets of seismic response maps are developed, on which, also maps of seismic design response spectra are defined by means of an enveloping technique.

Description: A sub-canopy structure for simulating oil palm in the Community Land Model: phenology, allocation and yield Geoscientific Model Development Discussions, 8, 4545-4597, 2015 Author(s): Y. Fan, O. Roupsard, M. Bernoux, G. Le Maire, O. Panferov, M. M. Kotowska, and A. Knohl Land surface modelling has been widely used to characterize the two-way interactions between climate and human activities in terrestrial ecosystems such as deforestation, agricultural expansion, and urbanization. Towards an effort to quantify the effects of forests to oil palm conversion occurring in the tropics on land–atmosphere carbon, water and energy fluxes, we introduce a new perennial crop plant functional type (PFT) for oil palm. Due to the modular and sequential nature of oil palm growth (around 40 stacked phytomers) and yield (fruit bunches axillated on each phytomer), we developed a specific sub-canopy structure for simulating palm's growth and yield within the framework of the Community Land Model (CLM4.5). In this structure each phytomer has its own prognostic leaf growth and fruit yield capacity like a PFT but with shared stem and root components among all phytomers. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, so that multiple fruit yields per annum are enabled in terms of carbon and nitrogen outputs. An important phenological phase is identified for the palm PFT – the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization, and leaf pruning are represented. Parameters introduced for the new PFT were calibrated and validated with field measurements of leaf area index (LAI) and yield from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched perfectly between simulation and observation (mean percentage error = 4 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites but also indicates that seasonal dynamics and site-to-site variability of yield are driven by processes not yet implemented in the model. The new sub-canopy structure and phenology and allocation functions now allow exploring the effects of tropical land use change, from natural ecosystems to oil palm plantations, on carbon, water and energy cycles and regional climate.

Description: NCAR global model topography generation software for unstructured grids Geoscientific Model Development Discussions, 8, 4623-4651, 2015 Author(s): P. H. Lauritzen, J. T. Bacmeister, P. F. Callaghan, and M. A. Taylor It is the purpose of this paper to document the NCAR global model topography generation software for unstructured grids. Given a model grid, the software computes the fraction of the grid box covered by land, the gridbox mean elevation, and associated sub-grid scale variances commonly used for gravity wave and turbulent mountain stress parameterizations. The software supports regular latitude-longitude grids as well as unstructured grids; e.g. icosahedral, Voronoi, cubed-sphere and variable resolution grids. As an example application and in the spirit of documenting model development, exploratory simulations illustrating the impacts of topographic smoothing with the NCAR-DOE CESM (Community Earth System Model) CAM5.2-SE (Community Atmosphere Model version 5.2 – Spectral Elements dynamical core) are shown.

Description: CranSLIK v2.0: improvements on the stochastic prediction of oil spill transport and fate using approximation methods Geoscientific Model Development Discussions, 8, 4949-4977, 2015 Author(s): R. Rutherford, I. Moulitsas, B. J. Snow, A. J. Kolios, and M. De Dominicis Oil spill models are used to forecast the transport and fate of oil after it has been released. CranSLIK is a model that predicts the movement and spread of a surface oil spill at sea via a stochastic approach. The aim of this work is to identify parameters that can further improve the forecasting algorithms and expand the functionality of CranSLIK, while maintaining the run time efficiency of the method. The results from multiple simulations performed using the operational, validated oil spill model, MEDSLIK-II, were analysed using multiple regression in order to identify improvements which could be incorporated into CranSLIK. This has led to a revised model, namely CranSLIK v2.0, which was validated against MEDSLIK-II forecasts for real oil spill cases. The new version of CranSLIK demonstrated significant forecasting improvements by capturing the oil spill accurately in real validation cases and also proved capable of simulating a broader range of oil spill scenarios.

Description: Upscaling with the dynamic two-layer classification concept (D2C): TreeMig-2L, an efficient implementation of the forest-landscape model TreeMig Geoscientific Model Development Discussions, 8, 5535-5575, 2015 Author(s): J. E. M. S. Nabel Models used to investigate impacts of climatic changes on spatio-temporal vegetation dynamics need to balance required accuracy with computational feasibility. To enhance the computational efficiency of these models, upscaling methods are required that maintain key fine-scale processes influencing vegetation dynamics. In this paper, an adjustable method – the dynamic two-layer classification concept (D2C) – for the upscaling of time- and space-discrete models is presented. D2C aims to separate potentially repetitive calculations from those specific to single grid cells. The underlying idea is to extract processes that do not require information about a grid cell's neighbourhood to a reduced-size non-spatial layer, which is dynamically coupled to the original two-dimensional layer. The size of the non-spatial layer is thereby adaptive and depends on dynamic classifications according to pre-specified similarity criteria. I present how D2C can be used in a model implementation on the example of TreeMig-2L, a new, efficient version of the intermediate-complexity forest-landscape model TreeMig. To discuss the trade-off between computational expenses and accuracy, as well as the applicability of D2C, I compare different model stages of TreeMig-2L via simulations of two different application scenarios. This comparison of different model stages demonstrates that applying D2C can strongly reduce computational expenses of processes calculated on the new non-spatial layer. D2C is thus a valuable upscaling method for models and applications in which processes requiring information about the neighbourhood constitute the minor share of the overall computational expenses.

Description: CESM/CAM5 improvement and application: comparison and evaluation of updated CB05_GE and MOZART-4 gas-phase mechanisms and associated impacts on global air quality and climate Geoscientific Model Development Discussions, 8, 7189-7247, 2015 Author(s): J. He, Y. Zhang, S. Tilmes, L. Emmons, J.-F. Lamarque, T. Glotfelty, A. Hodzic, and F. Vitt Atmospheric chemistry plays a key role in determining the amounts and distributions of oxidants and gaseous precursors that control the formation of secondary gaseous and aerosol pollutants; all of those species can interact with the climate system. To understand the impacts of different gas-phase mechanisms on global air quality and climate predictions, in this work, a comprehensive comparative evaluation is performed using the Community Atmosphere Model (CAM) Version 5 with comprehensive tropospheric and stratospheric chemistry (CAM5-chem) within the Community Earth System Model (CESM) with two most commonly-used gas-phase chemical mechanisms: the 2005 Carbon Bond mechanism with Global Extension (CB05_GE) and the Model of OZone and Related chemical Tracers version 4 (MOZART-4) mechanism with additional updates (MOZART-4x). MOZART-4x and CB05_GE use different approaches to represent volatile organic compounds (VOCs) and different surrogates for secondary organic aerosol (SOA) precursors. MOZART-4x includes a more detailed representation of isoprene chemistry compared to CB05_GE. CB05_GE includes additional oxidation of SO 2 by O 3 over the surface of dust particles, which is not included in MOZART-4x. The results show that the two CAM5-chem simulations with CB05_GE and MOZART-4x predict similar chemical profiles for major gases (e.g., O 3 , CO, and NO x ) compared to the aircraft measurements, with generally better agreement for NO y profile by CB05_GE than MOZART-4x. The concentrations of SOA at four sites in CONUS and organic carbon (OC) over the IMPROVE sites are well predicted by MOZART-4x (with NMBs of −1.9 and 2.1 %, respectively) but moderately underpredicted by CB05_GE (with NMBs of −23.1 and −20.7 %, respectively). This is mainly due to the higher biogenic emissions and hydroxyl radical levels simulated with MOZART-4x than with CB05_GE. The concentrations of OC over Europe are largely underpredicted by both MOZART-4x and CB05_GE, with NMBs of −73.0 and −75.1 %, respectively, indicating the uncertainties in the emissions of precursors and primary OC and relevant model treatments such as the oxidations of VOCs and SOA formation. Uncertainties in the emissions and convection scheme can contribute to the large bias in the model predictions (e.g., SO 2 , CO, black carbon, and aerosol optical depth). The two simulations also have similar cloud/radiative predictions, with slightly better performance of domain average cloud condensation nuclei (CCN) at supersaturation of 0.5 % by CB05_GE, but slightly better agreement with observed CCN (at supersaturation of 0.2 %) profile over Beijing by MOZART-4x. The two gas-phase mechanisms result in a global average difference of 0.5 W m −2 in simulated shortwave cloud radiative forcing, with significant differences (e.g., up to 13.6 W m −2 ) over subtropical regions.

Description: A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes Geoscientific Model Development Discussions, 8, 7347-7394, 2015 Author(s): J.-M. Haussaire and M. Bocquet Bocquet and Sakov (2013) have introduced a low-order model based on the coupling of the chaotic Lorenz-95 model which simulates winds along a mid-latitude circle, with the transport of a tracer species advected by this zonal wind field. This model, named L95-T, can serve as a playground for testing data assimilation schemes with an online model. Here, the tracer part of the model is extended to a reduced photochemistry module. This coupled chemistry meteorology model (CCMM), the L95-GRS model, mimics continental and transcontinental transport and the photochemistry of ozone, volatile organic compounds and nitrogen oxides. Its numerical implementation is described. The model is shown to reproduce the major physical and chemical processes being considered. L95-T and L95-GRS are specifically designed and useful for testing advanced data assimilation schemes, such as the iterative ensemble Kalman smoother (IEnKS) which combines the best of ensemble and variational methods. These models provide useful insights prior to the implementation of data assimilation methods on larger models. We illustrate their use with data assimilation schemes on preliminary, yet instructive numerical experiments. In particular, online and offline data assimilation strategies can be conveniently tested and discussed with this low-order CCMM. The impact of observed chemical species concentrations on the wind field can be quantitatively estimated. The impacts of the wind chaotic dynamics and of the chemical species non-chaotic but highly nonlinear dynamics on the data assimilation strategies are illustrated.

Description: DasPy 1.0 – the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5 Geoscientific Model Development Discussions, 8, 7395-7444, 2015 Author(s): X. Han, X. Li, G. He, P. Kumbhar, C. Montzka, S. Kollet, T. Miyoshi, R. Rosolem, Y. Zhang, H. Vereecken, and H.-J. H. Franssen Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently using the commonly used NetCDF file format. Online 1-D and 2-D visualization of data assimilation results is also implemented to facilitate the post simulation analysis. In summary, DasPy is a ready to use open source parallel multivariate land data assimilation framework.

Description: Tracking influential haze source areas in North China using an adjoint model, GRAPES–CUACE Geoscientific Model Development Discussions, 8, 7313-7345, 2015 Author(s): X. Q. An, S. X. Zhai, M. Jin, S. L. Gong, and Y. Wang Based upon the adjoint theory, the adjoint of the aerosol module in the atmospheric chemical modeling system GRAPES–CUACE (Global/Regional Assimilation and PrEdiction System coupled with the CMA Unified Atmospheric Chemistry Environment) was developed and tested for its correctness. Through statistic comparison, BC (black carbon aerosol) concentrations simulated by GRAPES–CUACE were generally consistent with observations from Nanjiao (one urban observation station) and Shangdianzi (one rural observation station) stations. To track the most influential emission-sources regions and the most influential time intervals for the high BC concentration during the simulation period, the adjoint model was adopted to simulate the sensitivity of average BC concentration over Beijing at the highest concentration time point (referred to as the Objective Function) with respect to BC emission amount over Beijing–Tianjin–Hebei region. Four types of regions were selected based on administrative division and sensitivity coefficient distribution. The adjoint model was used to quantify the effects of emission-sources reduction in different time intervals over different regions by one independent simulation. Effects of different emission reduction strategies based on adjoint sensitivity information show that the more influential regions (regions with relatively larger sensitivity coefficients) do not necessarily correspond to the administrative regions, and the influence effectiveness of sensitivity-oriented regions was greater than the administrative divisions. The influence of emissions on the objective function decreases sharply approximately for the pollutants emitted 17–18 h ago in this episode. Therefore, controlling critical emission regions during critical time intervals on the basis of adjoint sensitivity analysis is much more efficient than controlling administrative specified regions during an experiential time period.

Description: ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels Geoscientific Model Development Discussions, 8, 7063-7187, 2015 Author(s): M. Butenschön, J. Clark, J. N. Aldridge, J. I. Allen, Y. Artioli, J. Blackford, J. Bruggeman, P. Cazenave, S. Ciavatta, S. Kay, G. Lessin, S. van Leeuwen, J. van der Molen, L. de Mora, L. Polimene, S. Sailley, N. Stephens, and R. Torres The ERSEM model is one of the most established ecosystem models for the lower trophic levels of the marine food-web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North-Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic part of the marine ecosystem, including the microbial food-web, the carbonate system and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case-studies of mesocosm type simulations, water column implementations and a brief example of a full-scale application for the North-West European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.

Description: Towards convection-resolving, global atmospheric simulations with the Model for Prediction Across Scales (MPAS): an extreme scaling experiment Geoscientific Model Development Discussions, 8, 6987-7061, 2015 Author(s): D. Heinzeller, M. G. Duda, and H. Kunstmann The Model for Prediction Across Scales (MPAS) is a novel set of earth-system simulation components and consists of an atmospheric model, an ocean model and a land-ice model. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. This makes MPAS a promising tool for conducting climate-related impact studies of, for example, land use changes in a consistent approach. Here, we present an in-depth evaluation of MPAS with regards to technical aspects of performing model runs and scalability for three medium-size meshes on four different High Performance Computing sites with different architectures and compilers. We uncover model limitations and identify new aspects for the model optimisation that are introduced by the use of unstructured Voronoi meshes. We further demonstrate the model performance of MPAS in terms of its capability to reproduce the dynamics of the West African Monsoon and its associated precipitation. Comparing 11 month runs for two meshes with observations and a Weather Research & Forecasting tool (WRF) reference model, we show that MPAS can reproduce the atmospheric dynamics on global and local scales, but that further optimisation is required to address a precipitation excess for this region. Finally, we conduct extreme scaling tests on a global 3 km mesh with more than 65 million horizontal grid cells on up to half a million cores. We discuss necessary modifications of the model code to improve its parallel performance in general and specific to the HPC environment. We confirm good scaling (70 % parallel efficiency or better) of the MPAS model and provide numbers on the computational requirements for experiments with the 3 km mesh. In doing so, we show that global, convection-resolving atmospheric simulations with MPAS are within reach of current and next generations of high-end computing facilities.

Description: A moist aquaplanet variant of the Held–Suarez test for atmospheric model dynamical cores Geoscientific Model Development Discussions, 8, 8263-8340, 2015 Author(s): D. R. Thatcher and C. Jablonowski A moist idealized test case (MITC) for atmospheric model dynamical cores is presented. The MITC is based on the Held–Suarez (HS) test that was developed for dry simulations on a flat Earth and replaces the full physical parameterization package with a Newtonian temperature relaxation and Rayleigh damping of the low-level winds. This new variant of the HS test includes moisture and thereby sheds light on the non-linear dynamics-physics moisture feedbacks without the complexity of full physics parameterization packages. In particular, it adds simplified moist processes to the HS forcing to model large-scale condensation, boundary layer mixing, and the exchange of latent and sensible heat between the atmospheric surface and an ocean-covered planet. Using a variety of dynamical cores of NCAR's Community Atmosphere Model (CAM), this paper demonstrates that the inclusion of the moist idealized physics package leads to climatic states that closely resemble aquaplanet simulations with complex physical parameterizations. This establishes that the MITC approach generates reasonable atmospheric circulations and can be used for a broad range of scientific investigations. This paper provides examples of two application areas. First, the test case reveals the characteristics of the physics-dynamics coupling technique and reproduces coupling issues seen in full-physics simulations. In particular, it is shown that sudden adjustments of the prognostic fields due to moist physics tendencies can trigger undesirable large-scale gravity waves, which can be remedied by a more gradual application of the physical forcing. Second, the moist idealized test case can be used to intercompare dynamical cores. These examples demonstrate the versatility of the MITC approach and suggestions are made for further application areas. The new moist variant of the HS test can be considered a test case of intermediate complexity.

Description: Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment Geoscientific Model Development Discussions, 8, 8751-8808, 2015 Author(s): R. Séférian, M. Gehlen, L. Bopp, L. Resplandy, J. C. Orr, O. Marti, J. P. Dunne, J. R. Christian, S. C. Doney, T. Ilyina, K. Lindsay, P. Halloran, C. Heinze, J. Segschneider, and J. Tjiputra During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were carried out on the systematic assessment of the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. Mean-state assessments routinely compared model hindcasts to available modern biogeochemical observations. However, these assessments considered neither the extent of equilibrium in modeled biogeochemical reservoirs nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESM) contribute to model-to-model differences in the simulated fields. We take advantage of a 500 year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O 2 , NO 3 , Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and is consistent when confronted against a larger ensemble of CMIP5 models. This shows that drift has implications on their performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercices in order to provide realistic ESM results on marine biogeochemistry and carbon cycle feedbacks.

Description: 3-D radiative transfer in large-eddy simulations – experiences coupling the TenStream solver to the UCLA–LES Geoscientific Model Development Discussions, 8, 9021-9043, 2015 Author(s): F. Jakub and B. Mayer The recently developed three-dimensional TenStream radiative transfer solver was integrated into the UCLA–LES cloud resolving model. This work documents the overall performance of the TenStream solver as well as the technical challenges migrating from 1-D schemes to 3-D schemes. In particular the employed Monte-Carlo-Spectral-Integration needed to be re-examined in conjunction with 3-D radiative transfer. Despite the fact that the spectral sampling has to be performed uniformly over the whole domain, we find that the Monte-Carlo-Spectral-Integration remains valid. To understand the performance characteristics of the coupled TenStream solver, we conducted weak- as well as strong-scaling experiments. In this context, we investigate two matrix-preconditioner (GAMG and block-jacobi ILU) and find that algebraic multigrid preconditioning performs well for complex scenes and highly parallelized simulations. The TenStream solver is tested for up to 4096 cores and shows a parallel scaling efficiency of 80–90 % on various supercomputers. Compared to the widely employed 1-D δ-Eddington two-stream solver, the computational costs for the radiative transfer solver alone increases by a factor of five to ten.

Description: Improving data transfer for model coupling Geoscientific Model Development Discussions, 8, 8981-9020, 2015 Author(s): C. Zhang, L. Liu, G. Yang, R. Li, and B. Wang Data transfer, which means transferring data fields between two component models or rearranging data fields among processes of the same component model, is a fundamental operation of a coupler. Most of state-of-the-art coupler versions currently use an implementation based on the point-to-point (P2P) communication of the Message Passing Interface (MPI) (call such an implementation "P2P implementation" for short). In this paper, we reveal the drawbacks of the P2P implementation, including low communication bandwidth due to small message size, variable and big number of MPI messages, and jams during communication. To overcome these drawbacks, we propose a butterfly implementation for data transfer. Although the butterfly implementation can outperform the P2P implementation in many cases, it degrades the performance in some cases because the total message size transferred by the butterfly implementation is larger than that by the P2P implementation. To make the data transfer completely improved, we design and implement an adaptive data transfer library that combines the advantages of both butterfly implementation and P2P implementation. Performance evaluation shows that the adaptive data transfer library significantly improves the performance of data transfer in most cases and does not decrease the performance in any cases. Now the adaptive data transfer library is open to the public and has been imported into a coupler version C-Coupler1 for performance improvement of data transfer. We believe that it can also improve other coupler versions.

Description: Inverse transport modeling of volcanic sulfur dioxide emissions using large-scale ensemble simulations Geoscientific Model Development Discussions, 8, 9103-9146, 2015 Author(s): Y. Heng, L. Hoffmann, S. Griessbach, T. Rößler, and O. Stein An inverse transport modeling approach based on the concepts of sequential importance resampling and parallel computing is presented to reconstruct altitude-resolved time series of volcanic emissions, which often can not be obtained directly with current measurement techniques. A new inverse modeling and simulation system, which implements the inversion approach with the Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) is developed to provide reliable transport simulations of volcanic sulfur dioxide (SO 2 ). In the inverse modeling system MPTRAC is used to perform two types of simulations, i. e., large-scale ensemble simulations for the reconstruction of volcanic emissions and final transport simulations. The transport simulations are based on wind fields of the ERA-Interim meteorological reanalysis of the European Centre for Medium Range Weather Forecasts. The reconstruction of altitude-dependent SO 2 emission time series is also based on Atmospheric Infrared Sounder (AIRS) satellite observations. A case study for the eruption of the Nabro volcano, Eritrea, in June 2011, with complex emission patterns, is considered for method validation. Meteosat Visible and InfraRed Imager (MVIRI) near-real-time imagery data are used to validate the temporal development of the reconstructed emissions. Furthermore, the altitude distributions of the emission time series are compared with top and bottom altitude measurements of aerosol layers obtained by the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite instruments. The final transport simulations provide detailed spatial and temporal information on the SO 2 distributions of the Nabro eruption. The SO 2 column densities from the simulations are in good qualitative agreement with the AIRS observations. Our new inverse modeling and simulation system is expected to become a useful tool to also study other volcanic eruption events.

Description: Transient climate simulations of the deglaciation 21–9 thousand years before present; PMIP4 Core experiment design and boundary conditions Geoscientific Model Development Discussions, 8, 9045-9102, 2015 Author(s): R. F. Ivanovic, L. J. Gregoire, M. Kageyama, D. M. Roche, P. J. Valdes, A. Burke, R. Drummond, W. R. Peltier, and L. Tarasov The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 thousand years. Here, we present the design of a coordinated Core simulation over the period 21–9 thousand years before present (ka) with time varying orbital forcing, greenhouse gases, ice sheets, and other geographical changes. A choice of two ice sheet reconstructions is given, but no ice sheet or iceberg meltwater should be prescribed in the Core simulation. Additional focussed simulations will also be coordinated on an ad-hoc basis by the working group, for example to investigate the effect of ice sheet and iceberg meltwater, and the uncertainty in other forcings. Some of these focussed simulations will focus on shorter durations around specific events to allow the more computationally expensive models to take part.

Description: FORest canopy atmosphere transfer (FORCAsT) 1.0: a 1-D model of biosphere–atmosphere chemical exchange Geoscientific Model Development Discussions, 8, 5183-5234, 2015 Author(s): K. Ashworth, S. H. Chung, R. J. Griffin, J. Chen, R. Forkel, A. M. Bryan, and A. L. Steiner Biosphere-atmosphere interactions play a critical role in governing atmospheric composition, mediating the concentration of key species such as ozone and aerosol, thereby influencing air quality and climate. The exchange of reactive trace gases and their oxidation products (both gas and particle phase) is of particular importance in this process. The FORCAsT (FORest Canopy AtmoSphere Transfer) one-dimensional model is developed to study the emission, deposition, chemistry and transport of volatile organic compounds (VOCs) and their oxidation products in the atmosphere within and above the forest canopy. We include an equilibrium partitioning scheme, making FORCAsT one of the few canopy models currently capable of simulating the formation of secondary organic aerosols (SOA) from VOC oxidation in a forest environment. We evaluate the capability of FORCAsT to reproduce observed concentrations of key gas-phase species and report modeled SOA concentrations within and above a mixed forest at the University of Michigan Biological Station (UMBS) during the Community Atmosphere-Biosphere Interactions Experiment (CABINEX) field campaign in summer 2009. We examine the impact of two different gas-phase chemical mechanisms on modelled concentrations of short-lived primary emissions, such as isoprene and monoterpenes, and their oxidation products. While the two chemistry schemes perform similarly under high-NO x conditions, they diverge at the low levels of NO x at UMBS. We identify peroxy radical and alkyl nitrate chemistry as the key causes of the differences, highlighting the importance of this chemistry in understanding the fate of biogenic VOCs (bVOCs) for both the modelling and measurement communities.

Description: Implementation of an optimal stomatal conductance model in the Australian Community Climate Earth Systems Simulator (ACCESS1.3b) Geoscientific Model Development Discussions, 8, 5235-5264, 2015 Author(s): J. Kala, M. G. De Kauwe, A. J. Pitman, R. Lorenz, B. E. Medlyn, Y.-P Wang, Y.-S Lin, and G. Abramowitz We implement a new stomatal conductance model, based on the optimality approach, within the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. Coupled land-atmosphere simulations are then performed using CABLE within the Australian Community Climate and Earth Systems Simulator (ACCESS) with prescribed sea surface temperatures. As in most land surface models, the default stomatal conductance scheme only accounts for differences in model parameters in relation to the photosynthetic pathway, but not in relation to plant functional types. The new scheme allows model parameters to vary by plant functional type, based on a global synthesis of observations of stomatal conductance under different climate regimes over a wide range of species. We show that the new scheme reduces the latent heat flux from the land surface over the boreal forests during the Northern Hemisphere summer by 0.5 to 1.0 mm day -1 . This leads to warmer daily maximum and minimum temperatures by up to 1.0 °C and warmer extreme maximum temperatures by up to 1.5 °C. These changes generally improve the climate model's climatology and improve existing biases by 10–20 %. The change in the surface energy balance also affects net primary productivity and the terrestrial carbon balance. We conclude that the improvements in the global climate model which result from the new stomatal scheme, constrained by a global synthesis of experimental data, provide a valuable advance in the long-term development of the ACCESS modelling system.

Description: Importance of bitwise identical reproducibility in earth system modeling and status report Geoscientific Model Development Discussions, 8, 4375-4400, 2015 Author(s): L. Liu, S. Peng, C. Zhang, R. Li, B. Wang, C. Sun, Q. Liu, L. Dong, L. Li, Y. Shi, Y. He, W. Zhao, and G. Yang Reproducibility is a fundamental principle of scientific research. Bitwise identical reproducibility, i.e., bitwise computational results can be reproduced, guarantees the reproduction of exactly the same results. Here we show the importance of bitwise identical reproducibility to Earth system modeling but the importance has not yet been widely recognized. Modeled mean climate states, variability and trends at different scales may be significantly changed or even lead to opposing results due to a slight change in the original simulation setting during a reproduction. Out of the large body of Earth system modeling publications, few thoroughly describe the whole original simulation setting. As a result, the reproduction of a particular simulation experiment by fellow scientists heavily depends on the interaction with the original authors, which is often inconvenient or even impossible. We anticipate bitwise identical reproducibility to be promoted as a worldwide standard, to guarantee the independent reproduction of simulation results and to further improve model development and scientific research.

Description: Description and evaluation of a new 4-mode version of Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model Geoscientific Model Development Discussions, 8, 8341-8386, 2015 Author(s): X. Liu, P.-L. Ma, H. Wang, S. Tilmes, B. Singh, R. C. Easter, S. J. Ghan, and P. J. Rasch Atmospheric carbonaceous aerosols play an important role in the climate system by influencing the Earth's radiation budgets and modifying the cloud properties. Despite the importance, their representations in large-scale atmospheric models are still crude, which can influence model simulated burden, lifetime, physical, chemical and optical properties, and the climate forcing of carbonaceous aerosols. In this study, we improve the current 3-mode version of modal aerosol module (MAM3) in the Community Atmosphere Model version 5 (CAM5) by introducing an additional primary carbon mode to explicitly account for the microphysical ageing of primary carbonaceous aerosols in the atmosphere. Compared to MAM3, the 4-mode version of MAM (MAM4) significantly increases the column burdens of primary particulate organic matter (POM) and black carbon (BC) by up to 40 % in many remote regions, where in-cloud scavenging plays an important role in determining the aerosol concentrations. Differences in the column burdens for other types of aerosol (e.g., sulfate, secondary organic aerosols, mineral dust, sea salt) are less than 1 %. Evaluating the MAM4 simulation against in situ surface and aircraft observations, we find that MAM4 significantly improves the simulation of seasonal variation of BC concentrations in the polar regions, by increasing the BC concentrations in all seasons and particularly in cold seasons. However, it exacerbates the overestimation of modeled BC concentrations in the upper troposphere in the Pacific regions. The comparisons suggest that, to address the remaining model POM and BC biases, future improvements are required related to (1) in-cloud scavenging and vertical transport in convective clouds and (2) emissions of anthropogenic and biomass burning aerosols.

Description: Earth System Chemistry Integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy, version 2.51) Geoscientific Model Development Discussions, 8, 8635-8750, 2015 Author(s): P. Jöckel, H. Tost, A. Pozzer, M. Kunze, O. Kirner, C. A. M. Brenninkmeijer, S. Brinkop, D. S. Cai, C. Dyroff, J. Eckstein, F. Frank, H. Garny, K.-D. Gottschaldt, P. Graf, V. Grewe, A. Kerkweg, B. Kern, S. Matthes, M. Mertens, S. Meul, M. Neumaier, M. Nützel, S. Oberländer-Hayn, R. Ruhnke, T. Runde, R. Sander, D. Scharffe, and A. Zahn With version 2.51 of the ECHAM/MESSy Atmospheric Chemistry (EMAC) model three types of reference simulations as recommended by the Chemistry-Climate Model Initiative (CCMI) have been performed: hindcast simulations (1950–2011), hindcast simulations with specified dynamics (1978–2013), i.e., nudged towards ERA-Interim reanalysis data, and combined hindcast and projection simulations (1950–2100). The manuscript summarises the updates of the model system and details the different model setups used, including the on-line calculated diagnostics. Simulations have been performed with two different nudging setups, with and without interactive tropospheric aerosol, and with and without a coupled ocean model. Two different vertical resolutions have been applied. The on-line calculated sources and sinks of reactive species are quantified and a first evaluation of the simulation results from a global perspective is provided as a quality check of the data. The focus is on the inter-comparison of the different model setups. The simulation data will become publicly available via CCMI and the CERA database of the German Climate Computing Centre (DKRZ). This manuscript is intended to serve as an extensive reference for further analyses of the ESCiMo simulations.

Description: The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set Geoscientific Model Development Discussions, 8, 8809-8833, 2015 Author(s): J. J. Day, S. Tietsche, M. Collins, H. F. Goessling, V. Guemas, A. Guillory, W. J. Hurlin, M. Ishii, S. P. E. Keeley, D. Matei, R. Msadek, M. Sigmond, H. Tatebe, and E. Hawkins Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation.

Description: Glacial–interglacial changes of H 2 18 O, HDO and deuterium excess – results from the fully coupled Earth System Model ECHAM5/MPI-OM Geoscientific Model Development Discussions, 8, 8835-8894, 2015 Author(s): M. Werner, B. Haese, X. Xu, X. Zhang, M. Butzin, and G. Lohmann In this study we present first results of a new isotope-enabled general circulation model setup. The model consists of a fully coupled atmosphere–ocean model ECHAM5/MPI-OM, enhanced by the interactive land surface scheme JSBACH and an explicit hydrological discharge scheme to close the global water budget. Stable water isotopes H 2 18 O and HDO have been incorporated into all relevant model components. Results of two equilibrium simulations under pre-industrial and last glacial maximum conditions are analysed and compared to observational data and paleoclimate records for evaluating the model's performance of simulating spatial and temporal variations in the isotopic composition of the Earth's water cycle. For the pre-industrial climate, many aspects of the simulation results of meteoric waters are in good to very good agreement with both observations and earlier atmosphere-only simulations. The model is capable of adequately simulating the large spread in the isotopic composition of precipitation between low and high latitudes. A comparison to available ocean data also shows a good model-data agreement, however a strong bias of too depleted ocean surface waters is detected for the Arctic region. Simulation results under last glacial maximum boundary conditions also fit to the wealth of available isotope records from polar ice cores, speleothems, as well as marine calcite data. Data-model evaluation of the isotopic composition in precipitation reveals a good match of the model results and indicates that the temporal glacial–interglacial isotope–temperature relation was substantially lower than the present spatial gradient for most mid- to high-latitudinal regions. As compared to older atmosphere-only simulations, a remarkable improvement is achieved for the modelling of the deuterium excess signal in Antarctic ice cores. Our simulation results indicate that cool sub-tropical and mid-latitudinal sea surface temperatures are key for this progress. A recently discussed revised interpretation of the deuterium excess record of Antarctic ice cores in terms of marine relative humidity changes on glacial–interglacial timescales is not supported by our model results.

Description: ASHEE: a compressible, Equilibrium–Eulerian model for volcanic ash plumes Geoscientific Model Development Discussions, 8, 8895-8979, 2015 Author(s): M. Cerminara, T. Esposti Ongaro, and L. C. Berselli A new fluid-dynamic model is developed to numerically simulate the non-equilibrium dynamics of polydisperse gas-particle mixtures forming volcanic plumes. Starting from the three-dimensional N-phase Eulerian transport equations (Neri et al., 2003) for a mixture of gases and solid dispersed particles, we adopt an asymptotic expansion strategy to derive a compressible version of the first-order non-equilibrium model (Ferry and Balachandar, 2001), valid for low concentration regimes (particle volume fraction less than 10 −3 ) and particles Stokes number ( St , i.e., the ratio between their relaxation time and flow characteristic time) not exceeding about 0.2. The new model, which is called ASHEE (ASH Equilibrium Eulerian), is significantly faster than the N-phase Eulerian model while retaining the capability to describe gas-particle non-equilibrium effects. Direct numerical simulation accurately reproduce the dynamics of isotropic, compressible turbulence in subsonic regime. For gas-particle mixtures, it describes the main features of density fluctuations and the preferential concentration and clustering of particles by turbulence, thus verifying the model reliability and suitability for the numerical simulation of high-Reynolds number and high-temperature regimes in presence of a dispersed phase. On the other hand, Large-Eddy Numerical Simulations of forced plumes are able to reproduce their observed averaged and instantaneous flow properties. In particular, the self-similar Gaussian radial profile and the development of large-scale coherent structures are reproduced, including the rate of turbulent mixing and entrainment of atmospheric air. Application to the Large-Eddy Simulation of the injection of the eruptive mixture in a stratified atmosphere describes some of important features of turbulent volcanic plumes, including air entrainment, buoyancy reversal, and maximum plume height. For very fine particles ( St → 0, when non-equilibrium effects are negligible) the model reduces to the so-called dusty-gas model. However, coarse particles partially decouple from the gas phase within eddies (thus modifying the turbulent structure) and preferentially concentrate at the eddy periphery, eventually being lost from the plume margins due to the concurrent effect of gravity. By these mechanisms, gas-particle non-equilibrium processes are able to influence the large-scale behavior of volcanic plumes.

Description: A flexible importance sampling method for integrating subgrid processes Geoscientific Model Development Discussions, 8, 9147-9191, 2015 Author(s): E. K. Raut and V. E. Larson Numerical models of weather and climate need to compute grid-box-averaged rates of physical processes such as microphysics. These averages are computed by integrating subgrid variability over a grid box. For this reason, an important aspect of atmospheric modeling is integration. The needed integrals can be estimated by Monte Carlo integration. Monte Carlo integration is simple and general but requires many evaluations of the physical process rate. To reduce the number of function evaluations, this paper describes a new, flexible method of importance sampling. It divides the domain of integration into eight categories, such as the portion that contains both precipitation and cloud, or the portion that contains precipitation but no cloud. It then allows the modeler to prescribe the density of sample points within each of the eight categories. The new method is incorporated into the Subgrid Importance Latin Hypercube Sampler (SILHS). The resulting method is tested on drizzling cumulus and stratocumulus cases. In the cumulus case, the sampling error can be considerably reduced by drawing more sample points from the region of rain evaporation.

Description: Using reactive transport codes to provide mechanistic biogeochemistry representations in global land surface models: CLM-PFLOTRAN 1.0 Geoscientific Model Development Discussions, 8, 10627-10676, 2015 Author(s): G. Tang, F. Yuan, G. Bisht, G. E. Hammond, P. C. Lichtner, J. Kumar, R. T. Mills, X. Xu, B. Andre, F. M. Hoffman, S. L. Painter, and P. E. Thornton We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models; our goal is to facilitate testing of alternative models and incorporation of new understanding. A reaction network with the CLM-CN decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN code, coupled with the Community Land Model (CLM), and test at Arctic, temperate, and tropical sites. To make the reaction network designed for use in explicit time stepping in CLM compatible with the implicit time stepping used in PFLOTRAN, the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. To achieve accurate, efficient, and robust numerical solutions, care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60–100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10 −3 to 10 −9 mol m −3 , which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %; computing time can be doubled for log transformation. Caution needs to be taken in choosing the appropriate scaling factor because a small value caused by a negative update to a small concentration may diminish the update and result in false convergence even with very tight relative update tolerance. As some biogeochemical processes (e.g., methane and nitrous oxide production and consumption) involve very low half saturation and threshold concentrations, this work provides insights for addressing nonphysical negativity issues and facilitates the representation of a mechanistic biogeochemical description in earth system models to reduce climate prediction uncertainty.

Description: PLASIM-GENIE: a new intermediate complexity AOGCM Geoscientific Model Development Discussions, 8, 10677-10710, 2015 Author(s): P. B. Holden, N. R. Edwards, K. Fraedrich, E. Kirk, F. Lunkeit, and X. Zhu We describe the development, tuning and climate of PLASIM-GENIE, a new intermediate complexity Atmosphere–Ocean Global Climate Model (AOGCM), built by coupling the Planet Simulator to the GENIE earth system model. PLASIM-GENIE supersedes "GENIE-2", a coupling of GENIE to the Reading IGCM. It has been developed to join the limited number of models that bridge the gap between EMICS with simplified atmospheric dynamics and state of the art AOGCMs. A 1000 year simulation with PLASIM-GENIE requires approximately two weeks on a single node of a 2.1 GHz AMD 6172 CPU. An important motivation for intermediate complexity models is the evaluation of uncertainty. We here demonstrate the tractability of PLASIM-GENIE ensembles by deriving a "subjective" tuning of the model with a 50 member ensemble of 1000 year simulations.

Description: Coupling aerosol optics to the chemical transport model MATCH (v5.5.0) and aerosol dynamics module SALSA (v1) Geoscientific Model Development Discussions, 8, 10735-10781, 2015 Author(s): E. Andersson and M. Kahnert Modelling aerosol optical properties is a notoriously difficult task due to the particles' complex morphologies and compositions. Yet aerosols and their optical properties are important for Earth system modelling and remote sensing applications. Operational optics models often make drastic and non realistic approximations regarding morphological properties, which can introduce errors. In this study a new aerosol optics model is implemented, in which more realistic morphologies and mixing states are assumed, especially for black carbon aerosols. The model includes both external and internal mixing of all chemical species, it treats externally mixed black carbon as fractal aggregates, and it accounts for inhomogeneous internal mixing of black carbon by use of a novel "core-grey shell" model. Simulated results of radiative fluxes, backscattering coefficients and the Ångström exponent from the new optics model are compared with results from another model simulating particles as externally mixed homogeneous spheres. To gauge the impact on the optical properties from the new optics model, the known and important effects from using aerosol dynamics serves as a reference. The results show that using a more detailed description of particle morphology and mixing states influences the optical properties to the same degree as aerosol dynamics. This is an important finding suggesting that over-simplified optics models coupled to a chemical transport model can introduce considerable errors; this can strongly effect simulations of radiative fluxes in Earth-system models, and it can compromise the use of remote sensing observations of aerosols in model evaluations and chemical data assimilation.

Description: A Consistent Prescription of Stratospheric Aerosol for Both Radiation and Chemistry in the Community Earth System Model (CESM1) Geoscientific Model Development Discussions, 8, 10711-10734, 2015 Author(s): R. R. Neely III, A. Conley, F. Vitt, and J. F. Lamarque Here we describe an updated parameterization for prescribing stratospheric aerosol in the Community Earth System Model (CESM1). The need for a new parameterisation is motivated by the poor global response of most models in Coupled Model Inter-comparison Project 5 (CMIP5) to colossal volcanic perturbations to the stratospheric aerosol layer (such as the 1991 Pinatubo eruption or the 1883 Krakatau eruption) in comparison to observations. In particular, the scheme used in the CMIP5 simulations by CESM1 simulated a global temperature decrease by a factor 2 larger than was observed. The new parameterisation takes advantage of recent improvements in historical stratospheric aerosol databases to allow for varying both the mass loading and effective radius of the prescribed aerosol. Simulations utilizing the new scheme are shown to now reproduce the observed global mean temperature response as well as the temperature response of the stratosphere due to local aerosol heating after the 1991 Pinatubo eruption.

Description: High resolution land surface fluxes from satellite data (HOLAPS v1.0): evaluation and uncertainty assessment Geoscientific Model Development Discussions, 8, 10783-10841, 2015 Author(s): A. Loew, J. Peng, and M. Borsche Surface water and energy fluxes are essential components of the Earth system. Surface latent heat fluxes provide major energy input to the atmosphere. Despite the importance of these fluxes, state-of-the-art datasets of surface energy and water fluxes largely differ. The present paper introduces a new framework for the estimation of surface energy and water fluxes at the land surface, which allows for temporally and spatially high resolved flux estimates at the global scale (HOLAPS). The framework maximizes the usage of existing long-term satellite data records and ensures internally consistent estimates of the surface radiation and water fluxes. The manuscript introduces the technical details of the developed framework and provides results of a comprehensive sensitivity and evaluation study. Overall the results indicate very good agreement with in situ observations when compared against 49 FLUXNET stations worldwide. Largest uncertainties of latent heat flux and net radiation were found to result from uncertainties in the global solar radiation flux obtained from satellite data products.

Description: The Yale Interactive terrestrial Biosphere model: description, evaluation and implementation into NASA GISS ModelE2 Geoscientific Model Development Discussions, 8, 3147-3196, 2015 Author(s): X. Yue and N. Unger The land biosphere, atmospheric chemistry and climate are inextricably interconnected. We describe the Y ale I nteractive terrestrial B io s phere (YIBs) model, a land carbon cycle model that has been developed for coupling to the NASA Goddard Institute for Space Studies (GISS) ModelE2 global chemistry–climate model. The YIBs model adapts routines from the mature TRIFFID and CASA models to simulate interactive carbon assimilation, allocation, and autotrophic and heterotrophic respiration. Dynamic daily leaf area index is simulated based on carbon allocation and temperature- and drought-dependent prognostic phenology. YIBs incorporates a semi-mechanistic ozone vegetation damage scheme. Here, we validate the present day YIBs land carbon fluxes for three increasingly complex configurations: (i) off-line local site-level (ii) off-line global forced with WFDEI (WATCH Forcing Data methodology applied to ERA-Interim data) meteorology (iii) on-line coupled to the NASA ModelE2 (NASA ModelE2-YIBs). Off-line YIBs has hourly and on-line YIBs has half-hourly temporal resolution. The large observational database used for validation includes carbon fluxes from 145 flux tower sites and multiple satellite products. At the site level, YIBs simulates reasonable seasonality (correlation coefficient R 〉 0.8) of gross primary productivity (GPP) at 121 out of 145 sites with biases in magnitude ranging from −19 to 7% depending on plant function type. On the global scale, the off-line model simulates an annual GPP of 125 ± 3 petagrams of carbon (Pg C) and net ecosystem exchange (NEE) of −2.5 ± 0.7 Pg C for 1982–2011, with seasonality and spatial distribution consistent with the satellite observations. We assess present day global ozone vegetation damage using the off-line YIBs configuration. Ozone damage reduces global GPP by 2–5% annually with regional extremes of 4–10% in East Asia. The on-line model simulates annual GPP of 123 ± 1 Pg C and NEE of −2.7 ± 0.7 Pg C. NASA ModelE2-YIBs is a useful new tool to investigate coupled interactions between the land carbon cycle, atmospheric chemistry, and climate change.

Description: Representation of vegetation effects on the snow-covered albedo in the Noah land surface model with multiple physics options Geoscientific Model Development Discussions, 8, 3197-3218, 2015 Author(s): S. Park and S. K. Park Snow albedo plays a critical role in calculating the energy budget, but parameterization of the snow surface albedo is still under great uncertainty. It varies with snow grain size, snow cover thickness, snow age, forest shading factor and other variables. Snow albedo of forest is typically lower than that of short vegetation; thus snow albedo is dependent on the spatial distributions of characteristic land cover and on the canopy density and structure. In the Noah land surface model with multiple physics options (Noah-MP), almost all vegetation types in East Asia during winter have the minimum values of leaf area index (LAI) and stem area index (SAI), which are too low and do not consider the vegetation types. Because LAI and SAI are represented in terms of photosynthetic activeness, the vegetation effect rarely exerts on the surface albedo in winter in East Asia with only these parameters. Thus, we investigated the vegetation effects on the snow-covered albedo from observations and evaluated the model improvement by considering such effect. We found that calculation of albedo without proper reflection of the vegetation effect is mainly responsible for the large positive bias in winter. Therefore, we developed new parameters, called leaf index (LI) and stem index (SI), which properly manage the effect of vegetation structure on the winter albedo. As a result, the Noah-MP's performance in albedo has been significantly improved – RMSE is reduced by approximately 73%.

Description: Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2 Geoscientific Model Development Discussions, 8, 3905-3939, 2015 Author(s): B. Gantt, J. T. Kelly, and J. O. Bash Sea spray aerosols (SSA) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. Despite their importance, the emission magnitude of SSA remains highly uncertain with global estimates varying by nearly two orders of magnitude. In this study, the Community Multiscale Air Quality (CMAQ) model was updated to enhance fine mode SSA emissions, include sea surface temperature (SST) dependency, and reduce coastally-enhanced emissions. Predictions from the updated CMAQ model and those of the previous release version, CMAQv5.0.2, were evaluated using several regional and national observational datasets in the continental US. The updated emissions generally reduced model underestimates of sodium, chloride, and nitrate surface concentrations for an inland site of the Bay Regional Atmospheric Chemistry Experiment (BRACE) near Tampa, Florida. Including SST-dependency to the SSA emission parameterization led to increased sodium concentrations in the southeast US and decreased concentrations along parts of the Pacific coast and northeastern US. The influence of sodium on the gas-particle partitioning of nitrate resulted in higher nitrate particle concentrations in many coastal urban areas due to increased condensation of nitric acid in the updated simulations, potentially affecting the predicted nitrogen deposition in sensitive ecosystems. Application of the updated SSA emissions to the California Research at the Nexus of Air Quality and Climate Change (CalNex) study period resulted in modest improvement in the predicted surface concentration of sodium and nitrate at several central and southern California coastal sites. This SSA emission update enabled a more realistic simulation of the atmospheric chemistry in environments where marine air mixes with urban pollution.

Description: A fully coupled Atmosphere–Ocean Wave modeling system (WEW) for the Mediterranean Sea: interactions and sensitivity to the resolved scales and mechanisms Geoscientific Model Development Discussions, 8, 4075-4112, 2015 Author(s): P. Katsafados, A. Papadopoulos, G. Korres, and G. Varlas It is commonly accepted that there is an urgent need for a better understanding of the factors that contribute to the air–sea interaction processes and their feedbacks. In this sense it is absolutely important to develop advanced numerical prediction systems that treat the atmosphere and the ocean as a unified system. The realistic description and understanding of the exchange processes near the ocean surface, requires the exact knowledge of the sea state and its evolution. This can be achieved by considering the sea surface and the atmosphere as a continuously cross talking dynamic system. Therefore, this study aims to present the effort towards developing a new, high-resolution, two-way fully coupled atmosphere–ocean wave model in order to support operational and research activities. A specific issue that it is emphasized here is the determination and parameterization of the air–sea momentum fluxes under conditions of extremely high and time-varying winds. Software considerations, data exchange as well as computational and scientific performance of the coupled system, so-called WEW, are also discussed throughout this study. In a case study of high-impact weather and sea state event, the wind–wave parameterization scheme reduces the resulted wind speed and the significant wave height as a response to the increased aerodynamic drag over rough sea surfaces. Overall, WEW offers a more realistic representation of the momentum exchanges in the ocean wind–wave system and includes the effects of the resolved wave spectrum on the drag coefficient and its feedback on the momentum flux.

Description: Evaluation of the Community Multiscale Air Quality (CMAQ) model v5.0 against size-resolved measurements of inorganic particle composition across sites in North America Geoscientific Model Development Discussions, 8, 3861-3904, 2015 Author(s): C. G. Nolte, K. W. Appel, J. T. Kelly, P. V. Bhave, K. M. Fahey, J. L. Collett Jr., L. Zhang, and J. O. Young This work evaluates particle size-composition distributions simulated by the Community Multiscale Air Quality (CMAQ) model using Micro-Orifice Uniform Deposit Impactor (MOUDI) measurements at 18 sites across North America. Size-resolved measurements of particulate SO 4 2− , NO 3 − , NH 4 + , Na + , Cl − , Mg 2+ , Ca 2+ and K + are compared to CMAQ model output for discrete sampling periods between 2002 and 2005. The observation sites were predominantly in remote areas (e.g. National Parks) in the United States and Canada, and measurements were typically made for a period of roughly one month. For SO 4 2− and NH 4 + , model performance was consistent across the US and Canadian sites, with the model slightly overestimating the peak particle diameter and underestimating the peak particle concentration compared to the observations. Na + and Mg 2+ size distributions were generally well represented at coastal sites, indicating reasonable simulation of emissions from sea spray. CMAQ is able to simulate the displacement of Cl − in aged sea spray aerosol, though the extent of Cl − depletion relative to Na + is often underpredicted. The model performance for NO 3 − exhibited much more site-to-site variability than that of SO 4 2− and NH 4 + , with the model ranging from an underestimation to overestimation of both the peak diameter and peak particle concentration across the sites. Computing PM 2.5 from the modeled size distribution parameters rather than by summing the masses in the Aitken and accumulation modes resulted in differences in daily averages of up to 1 μg m −3 (10%), while the difference in seasonal and annual model performance compared to observations from the IMPROVE, CSN and AQS networks was very small. Two updates to the CMAQ aerosol model – changes to the assumed size and mode width of emitted particles and the implementation of gravitational settling – resulted in small improvements in modeled size distributions.

Description: A global empirical system for probabilistic seasonal climate prediction Geoscientific Model Development Discussions, 8, 3941-3970, 2015 Author(s): J. M. Eden, G. J. van Oldenborgh, E. Hawkins, and E. B. Suckling Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, NGOs and companies and relies on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO 2 -equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated using correlation and skill scores. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known ENSO teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Description: Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3 Geoscientific Model Development Discussions, 8, 4051-4073, 2015 Author(s): M. J. Prather A new approach for modeling photolysis rates ( J values) in atmospheres with fractional cloud cover has been developed and implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of cloud layers, Cloud-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations represented by four quadrature atmospheres produces mean J values in an atmospheric column with root-mean-square errors of 4% or less compared with 10–20% errors using simpler approximations. Cloud-J is practical for chemistry-climate models, requiring only an average of 2.8 Fast-J calls per atmosphere, vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into Cloud-J.

Description: Evaluation of modeled surface ozone biases as a function of cloud cover fraction Geoscientific Model Development Discussions, 8, 3219-3233, 2015 Author(s): H. C. Kim, P. Lee, F. Ngan, Y. Tang, H. L. Yoo, and L. Pan A regional air-quality forecast system's model of surface ozone variability based on cloud coverage is evaluated using satellite-observed cloud fraction (CF) information and a surface air-quality monitoring system. We compared CF and daily maximum ozone from the National Oceanic and Atmospheric Administration's National Air Quality Forecast Capability (NOAA NAQFC) with CFs from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the U.S. Environmental Protection Agency's AirNow surface ozone measurements during May to October 2014. We found that observed surface ozone shows a clear (negative) correlation with the MODIS CFs, showing around 1 ppb decrease for 10% MODIS CF change over the Contiguous United States, while the correlation of modeled surface ozone with the model CFs is much weaker, showing only −0.5 ppb per 10% NAQFC CF change. Further, daytime CF differences between MODIS and NAQFC are correlated with modeled surface-ozone biases between AirNow and NAQFC, showing −1.05 ppb per 10% CF change, implying that spatial- and temporal-misplacement of the modeled cloud field might have biased modeled surface ozone-level. Current NAQFC cloud fields seem to be too bright compared to MODIS cloud fields (mean NAQFC CF = 0.38 and mean MODIS CF = 0.55), contributing up to 35% of surface-ozone bias in the current NAQFC system.

Description: Simulating Secondary Inorganic Aerosols using the chemistry transport model MOCAGE version R2.15.0 Geoscientific Model Development Discussions, 8, 3593-3651, 2015 Author(s): J. Guth, B. Josse, V. Marécal, and M. Joly In this study we develop a Secondary Inorganic Aerosol (SIA) module for the chemistry transport model MOCAGE developed at CNRM. Based on the thermodynamic equilibrium module ISORROPIA II, the new version of the model is evaluated both at the global scale and at the regional scale. The results show high concentrations of secondary inorganic aerosols in the most polluted regions being Europe, Asia and the eastern part of North America. Asia shows higher sulfate concentrations than other regions thanks to emissions reduction in Europe and North America. Using two simulations, one with and the other without secondary inorganic aerosol formation, the model global outputs are compared to previous studies, to MODIS AOD retrievals, and also to in situ measurements from the HTAP database. The model shows a better agreement in all geographical regions with MODIS AOD retrievals when introducing SIA. It also provides a good statistical agreement with in situ measurements of secondary inorganic aerosol composition: sulfate, nitrate and ammonium. In addition, the simulation with SIA gives generally a better agreement for secondary inorganic aerosols precursors (nitric acid, sulfur dioxide, ammonia) in particular with a reduction of the Modified Normalised Mean Bias (MNMB). At the regional scale, over Europe, the model simulation with SIA are compared to the in situ measurements from the EMEP database and shows a good agreement with secondary inorganic aerosol composition. The results at the regional scale are consistent with those obtained with the global simulations. The AIRBASE database was used to compare the model to regulated air quality pollutants being particulate matter, ozone and nitrogen dioxide concentrations. The introduction of the SIA in MOCAGE provides a reduction of the PM 2.5 MNMB of 0.44 on a yearly basis and even 0.52 on a three spring months period (March, April, May) when SIA are maximum.

Description: Using satellite-based estimates of evapotranspiration and groundwater changes to determine anthropogenic water fluxes in land surface models Geoscientific Model Development Discussions, 8, 3565-3592, 2015 Author(s): R. G. Anderson, M.-H. Lo, S. Swenson, J. S. Famiglietti, Q. Tang, T. H. Skaggs, Y.-H. Lin, and R.-J. Wu Irrigation is a widely used water management practice that is often poorly parameterized in land surface and climate models. Previous studies have addressed this issue via use of irrigation area, applied water inventory data, or soil moisture content. These approaches have a variety of drawbacks including data latency, accurately prescribing irrigation intensity, and conservation of water volume for soil moisture approach. In this study, we parameterize irrigation fluxes using satellite observations of evapotranspiration (ET) against ET from a suite of land surface models without irrigation. We then apply this water flux into the Community Land Model (CLM) and use an iterative approach to estimate groundwater recharge and partition the water flux between groundwater and surface water. The ET simulated by CLM with irrigation matches the magnitude and seasonality of observed satellite ET well, with a mean difference of 6.3 mm month −1 and a correlation of 0.95. Differences between the new CLM ET values and observed ET values are always less than 30 mm month −1 and the differences show no pattern with respect to seasonality. The results reinforce the importance of accurately parameterizing anthropogenic hydrologic fluxes into land surface and climate models to assess environmental change under current and future climates and land management regimes.

Description: A 3-D RBF-FD elliptic solver for irregular boundaries: modeling the atmospheric global electric circuit with topography Geoscientific Model Development Discussions, 8, 3523-3564, 2015 Author(s): V. Bayona, N. Flyer, G. M. Lucas, and A. J. G. Baumgaertner A numerical model based on Radial Basis Function-generated Finite Differences (RBF-FD) is developed for simulating the Global Electric Circuit (GEC) within the Earth's atmosphere, represented by a 3-D variable coefficient linear elliptic PDE in a spherically-shaped volume with the lower boundary being the Earth's topography and the upper boundary a sphere at 60 km. To our knowledge, this is (1) the first numerical model of the GEC to combine the Earth's topography with directly approximating the differential operators in 3-D space, and related to this (2) the first RBF-FD method to use irregular 3-D stencils for discretization to handle the topography. It benefits from the mesh-free nature of RBF-FD, which is especially suitable for modeling high-dimensional problems with irregular boundaries. The RBF-FD elliptic solver proposed here makes no limiting assumptions on the spatial variability of the coefficients in the PDE (i.e. the conductivity profile), the right hand side forcing term of the PDE (i.e. distribution of current sources) or the geometry of the lower boundary.

Description: The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF Geoscientific Model Development Discussions, 8, 3481-3522, 2015 Author(s): P. J. H. Volker, J. Badger, A. N. Hahmann, and S. Ott We describe the theoretical basis, implementation and validation of a new parametrisation that accounts for the effect of large offshore wind farms on the atmosphere and can be used in mesoscale and large-scale atmospheric models. This new parametrisation, referred to as the Explicit Wake Parametrisation (EWP), uses classical wake theory to describe the unresolved wake expansion. The EWP scheme is validated against filtered in situ measurements from two meteorological masts situated a few kilometres away from the Danish offshore wind farm Horns Rev I. The simulated velocity deficit in the wake of the wind farm compares well to that observed in the measurements and the velocity profile is qualitatively similar to that simulated with large eddy simulation models and from wind tunnel studies. At the same time, the validation process highlights the challenges in verifying such models with real observations.

Description: The GRENE-TEA Model Intercomparison Project (GTMIP): overview and experiment protocol for Stage 1 Geoscientific Model Development Discussions, 8, 3443-3479, 2015 Author(s): S. Miyazaki, K. Saito, J. Mori, T. Yamazaki, T. Ise, H. Arakida, T. Hajima, Y. Iijima, H. Machiya, T. Sueyoshi, H. Yabuki, E. J. Burke, M. Hosaka, K. Ichii, H. Ikawa, A. Ito, A. Kotani, Y. Matsuura, M. Niwano, T. Nitta, R. O'ishi, T. Ohta, H. Park, T. Sasai, A. Sato, H. Sato, A. Sugimoto, R. Suzuki, K. Tanaka, S. Yamaguchi, and K. Yoshimura As part of the terrestrial branch of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA), which aims to clarify the role and function of the Arctic terrestrial system in the climate system, and assess the influence of its changes on a global scale, this model intercomparison project (GTMIP) is planned and being conducted to (1) enhance communication and understanding between the "minds and hands" (i.e., between the modelling and field scientists) and (2) assess the uncertainty and variations stemming from variability in model implementation/design and in model outputs due to climatic and historical conditions in the Arctic terrestrial regions. This paper provides an overview and the experiment protocol of Stage 1 of the project, site simulations driven by statistically fitted data created using the GRENE-TEA site observations for the last three decades. The target metrics for the model evaluation cover key processes in both physics and biogeochemistry, including energy budgets, snow, permafrost, phenology, and carbon budgets. The preliminary results on four metrics (annual mean latent heat flux, annual maximum snow depth, gross primary production, and net ecosystem production) already demonstrate the range of variations in reproducibility among existing models and sites. Full analysis on annual as well as seasonal time scales, to be conducted upon completion of model outputs submission, will delineate inter-dependence among the key processes, and provide the clue for improving the model performance.

Description: Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO 2 fertilisation and of water stress in continental interiors Geoscientific Model Development Discussions, 8, 4781-4821, 2015 Author(s): S. O. Los A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO 2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen–Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 〈 r

Description: Accounting for anthropic energy flux of traffic in winter urban road surface temperature simulations with TEB model Geoscientific Model Development Discussions, 8, 4737-4779, 2015 Author(s): A. Khalifa, M. Marchetti, L. Bouilloud, E. Martin, M. Bues, and K. Chancibaut A forecast of the snowfall helps winter coordination operating services, reducing the cost of the maintenance actions, and the environmental impacts caused by an inappropriate use of de-icing. In order to determine the possible accumulation of snow on pavement, the forecast of the road surface temperature (RST) is mandatory. Physical numerical models provide such forecast, and do need an accurate description of the infrastructure along with meteorological parameters. The objective of this study was to build a reliable urban RST forecast with a detailed integration of traffic in the Town Energy Balance (TEB) numerical model for winter maintenance. The study first consisted in generating a physical and consistent description of traffic in the model with all the energy interactions, with two approaches to evaluate the traffic incidence on RST. Experiments were then conducted to measure the traffic effect on RST increase with respect to non circulated areas. These field data were then used for comparison with forecast provided by this traffic-implemented TEB version.

Description: The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): simulation design and preliminary results Geoscientific Model Development Discussions, 8, 4697-4736, 2015 Author(s): B. Kravitz, A. Robock, S. Tilmes, O. Boucher, J. M. English, P. J. Irvine, A. Jones, M. G. Lawrence, M. MacCracken, H. Muri, J. C. Moore, U. Niemeier, S. J. Phipps, J. Sillmann, T. Storelvmo, H. Wang, and S. Watanabe We present a suite of new climate model experiment designs for the Geoengineering Model Intercomparison Project (GeoMIP). This set of experiments, named GeoMIP6 (to be consistent with the Coupled Model Intercomparison Project Phase 6), builds on the previous GeoMIP simulations, and has been expanded to address several further important topics, including key uncertainties in extreme events, the use of geoengineering as part of a portfolio of responses to climate change, and the relatively new idea of cirrus cloud thinning to allow more longwave radiation to escape to space. We discuss experiment designs, as well as the rationale for those designs, showing preliminary results from individual models when available. We also introduce a new feature, called the GeoMIP Testbed, which provides a platform for simulations that will be performed with a few models and subsequently assessed to determine whether the proposed experiment designs will be adopted as core (Tier 1) GeoMIP experiments. This is meant to encourage various stakeholders to propose new targeted experiments that address their key open science questions, with the goal of making GeoMIP more relevant to a broader set of communities.

Description: ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe Geoscientific Model Development Discussions, 8, 4653-4696, 2015 Author(s): X. Wu, N. Vuichard, P. Ciais, N. Viovy, N. de Noblet-Ducoudré, X. Wang, V. Magliulo, M. Wattenbach, L. Vitale, P. Di Tommasi, E. J. Moors, W. Jans, J. Elbers, E. Ceschia, T. Tallec, C. Bernhofer, T. Grünwald, C. Moureaux, T. Manise, A. Ligne, P. Cellier, B. Loubet, E. Larmanou, and D. Ripoche The responses of crop functioning to changing climate and atmospheric CO 2 concentration ([CO 2 ]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO 2 ], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO 2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m 2 m −2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.

Description: Development of a chlorine chemistry module for the Master Chemical Mechanism Geoscientific Model Development Discussions, 8, 4823-4849, 2015 Author(s): L. K. Xue, S. M. Saunders, T. Wang, R. Gao, X. F. Wang, Q. Z. Zhang, and W. X. Wang The chlorine atom (Cl·) has a high potential to perturb atmospheric photochemistry by oxidizing volatile organic compounds (VOCs), but the exact role it plays in the polluted troposphere remains unclear. The Master Chemical Mechanism (MCM) is a near explicit mechanism that has been widely applied in the atmospheric chemistry research. While it addresses comprehensively the chemistry initiated by the OH, O 3 and NO 3 radicals, its representation of the Cl· chemistry is incomplete as it only considers the reactions for alkanes. In this paper, we develop a more comprehensive Cl· chemistry module that can be directly incorporated within the MCM framework. A suite of 199 chemical reactions describes the Cl·-initiated degradation of alkenes, aromatics, aldehydes, ketones, alcohols, and some organic acids and nitrates, along with the inorganic chemistry involving Cl· and its precursors. To demonstrate the potential influence of the new chemistry module, it was incorporated into a MCM box model to evaluate the impacts of nitryl chloride (ClNO 2 ), a product of nocturnal halogen activation by nitrogen oxides (NO x ), on the following-day's atmospheric photochemistry. With constraints of recent observations collected at a coastal site in Hong Kong, southern China, the modeling analyses suggest that the Cl· produced from ClNO 2 photolysis may substantially enhance the atmospheric oxidative capacity, VOC oxidation, and O 3 formation, particularly in the early morning period. The results demonstrate the critical need for photochemical models to include more fully chlorine chemistry in order to better understand the atmospheric photochemistry in polluted environments subject to intense emissions of NO x , VOCs and chlorine-containing constituents.

Description: Sources of interannual yield variability in JULES-crop and implications for forcing with seasonal weather forecasts Geoscientific Model Development Discussions, 8, 4599-4621, 2015 Author(s): K. E. Williams and P. D. Falloon JULES-crop is a parametrisation of crops in the Joint UK Land Environment Simulator (JULES). We investigate the sources of the interannual variability in the modelled maize yield, using global runs driven by reanalysis data, with a view to understanding the impact of various approximations in the driving data and initialisation. The standard forcing dataset for JULES consists of a combination of meteorological variables describing precipitation, radiation, temperature, pressure, specific humidity and wind, at subdaily time resolution. We find that the main characteristics of the modelled yield can be reproduced with a subset of these variables and using daily forcing, with internal disaggregation to the model timestep. This has implications in particular for the use of the model with seasonal forcing data, which may not have been provided at subdaily resolution for all required driving variables. We also investigate the effect on annual yield of initialising the model with climatology on the sowing date. This approximation has the potential to considerably simplify the use of the model with seasonal forecasts, since obtaining observations or reanalysis output for all the initialisation variables required by JULES for the start date of the seasonal forecast would present significant practical challenges.

Description: Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0 Geoscientific Model Development Discussions, 8, 4851-4948, 2015 Author(s): J. R. Melton and V. K. Arora The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land–atmosphere exchange of CO 2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka–Volterra (L–V) predator–prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L–V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L–V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Description: Ice-sheet configuration in the CMIP5/PMIP3 Last Glacial Maximum experiments Geoscientific Model Development Discussions, 8, 4293-4336, 2015 Author(s): A. Abe-Ouchi, F. Saito, M. Kageyama, P. Braconnot, S. P. Harrison, K. Lambeck, B. L. Otto-Bliesner, W. R. Peltier, L. Tarasov, J.-Y. Peterschmitt, and K. Takahashi We describe the creation of boundary conditions related to the presence of ice sheets, including ice sheet extent and height, ice shelf extent, and the distribution and altitude of ice-free land, at the Last Glacial Maximum (LGM) for use in LGM experiments conducted as part of the fifth phase of the Coupled Modelling Intercomparison Project (CMIP5) and the third phase of the Palaeoclimate Modelling Intercomparison Project (PMIP3). The CMIP5/PMIP3 data sets were created from reconstructions made by three different groups, which were all obtained using a model-inversion approach but differ in the assumptions used in the modelling and in the type of data used as constraints. The ice sheet extent, and thus the albedo mask, for the Northern Hemisphere (NH) does not vary substantially between the three individual data sources. The difference in the topography of the NH ice sheets is also moderate, and smaller than the differences between these reconstructions (and the resultant composite reconstruction) and ice-sheet reconstructions used in previous generations of PMIP. Only two of the individual reconstructions provide information for Antarctica. The discrepancy between these two reconstructions is larger than the difference for the NH ice sheets although still less than the difference between the composite reconstruction and previous PMIP ice-sheet reconstructions. Differences in the climate response to the individual LGM reconstructions, and between these reconstructions and the CMIP5/PMIP3 composite, are largely confined to the ice-covered regions, but also extend over North Atlantic Ocean and Northern Hemisphere continents through atmospheric stationary waves. There are much larger differences in the climate response to the latest reconstructions (or the derived composite) and ice-sheet reconstructions used in previous phases of PMIP.

Description: Improving the ISBA CC land surface model simulation of water and carbon fluxes and stocks over the Amazon forest Geoscientific Model Development Discussions, 8, 1293-1336, 2015 Author(s): E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, D. Carrer, H. Verbeeck, M. De Weirdt, and D. Bonal We evaluate the ISBA CC land surface model over the Amazon forest, and propose a revised parameterization of photosynthesis, including new soil water stress and autotrophic respiration functions. The revised version allows the model to better capture the energy, water and carbon fluxes when compared to five Amazonian fluxtowers. The performance of ISBA CC is slightly site-dependent but similar to the widely evaluated land surface model ORCHIDEE, based on different assumptions. Changes made to the autotrophic respiration functions, including a vertical profile of leaf respiration, leads to simulate yearly carbon use efficiency and carbon stocks consistent with an ecophysiological meta analysis conducted on three Amazonian sites. Despite these major improvements, ISBA CC struggles to capture the apparent seasonality of the carbon fluxes derived from the fluxtower estimations. However, there is still no consensus on the seasonality of carbon fluxes over the Amazon, stressing a need for more observations as well as a better understanding of the main drivers of autotrophic respiration.

Description: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies Geoscientific Model Development Discussions, 8, 1375-1509, 2015 Author(s): O. Aumont, C. Ethé, A. Tagliabue, L. Bopp, and M. Gehlen PISCES-v2 is a biogeochemical model which simulates the lower trophic levels of marine ecosystem (phytoplankton, microzooplankton and mesozooplankton) and the biogeochemical cycles of carbon and of the main nutrients (P, N, Fe, and Si). The model is intended to be used for both regional and global configurations at high or low spatial resolutions as well as for short-term (seasonal, interannual) and long-term (climate change, paleoceanography) analyses. There are twenty-four prognostic variables (tracers) including two phytoplankton compartments (diatoms and nanophytoplankton), two zooplankton size-classes (microzooplankton and mesozooplankton) and a description of the carbonate chemistry. Formulations in PISCES-v2 are based on a mixed Monod–Quota formalism: on one hand, stoichiometry of C/N/P is fixed and growth rate of phytoplankton is limited by the external availability in N, P and Si. On the other hand, the iron and silicium quotas are variable and growth rate of phytoplankton is limited by the internal availability in Fe. Various parameterizations can be activated in PISCES-v2, setting for instance the complexity of iron chemistry or the description of particulate organic materials. So far, PISCES-v2 has been coupled to the NEMO and ROMS systems. A full description of PISCES-v2 and of its optional functionalities is provided here. The results of a quasi-steady state simulation are presented and evaluated against diverse observational and satellite-derived data. Finally, some of the new functionalities of PISCES-v2 are tested in a series of sensitivity experiments.

Description: SPHY v2.0: Spatial Processes in HYdrology Geoscientific Model Development Discussions, 8, 1687-1748, 2015 Author(s): W. Terink, A. F. Lutz, G. W. H. Simons, W. W. Immerzeel, and P. Droogers This paper introduces and presents the Spatial Processes in HYdrology (SPHY) model (v2.0), its development background, its underlying concepts, and some typical applications. The SPHY model is developed using the best components of existing and well-tested simulation models, and is developed with the explicit aim to simulate terrestrial hydrology at flexible scales, under various land use and climate conditions. SPHY is a spatially distributed leaky bucket type of model, and is applied on a cell-by-cell basis. The model is written in the Python programming language using the PCRaster dynamic modelling framework. Compared to other hydrological models, that typically focus on the simulation of streamflow only, the SPHY model has several advantages: it (i) integrates most relevant hydrological processes, (ii) is setup modular, (iii) is easy adjustable and applicable, (iii) can easily be linked to remote sensing data, and (iv) can be applied for operational as well as strategic decision support. The most relevant hydrological processes that are integrated in the SPHY model are rainfall–runoff processes, cryosphere processes, evapotranspiration processes, the simulation of dynamic vegetational cover, lake/reservoir outflow, and the simulation of rootzone moisture contents. Studies in which the SPHY model was successfully applied and tested are described in this paper, and range from (i) real-time soil moisture predictions to support irrigation management in lowland areas, to (ii) detailed climate change impact studies in snow and glacier-fed river basins, to (iii) operational flow forecasting in mountainous catchments.

Description: The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives Geoscientific Model Development Discussions, 8, 1539-1637, 2015 Author(s): B. Maronga, M. Gryschka, R. Heinze, F. Hoffmann, F. Kanani-Sühring, M. Keck, K. Ketelsen, M. O. Letzel, M. Sühring, and S. Raasch In this paper we present the current version of the Parallelized Large-Eddy Simulation Model (PALM) whose core has been developed at the Institute of Meteorology and Climatology at Leibniz Universität Hannover (Germany). PALM is a Fortran 95-based code with some Fortran 2003 extensions and has been applied for the simulation of a variety of atmospheric and oceanic boundary layers for more than 15 years. PALM is optimized for use on massively parallel computer architectures and was recently ported to general-purpose graphics processing units. In the present paper we give a detailed description of the current version of the model and its features, such as an embedded Lagrangian cloud model and the possibility to use Cartesian topography. Moreover, we discuss recent model developments and future perspectives for LES applications.

Description: DYNAMICO, an icosahedral hydrostatic dynamical core designed for consistency and versatility Geoscientific Model Development Discussions, 8, 1749-1800, 2015 Author(s): T. Dubos, S. Dubey, M. Tort, R. Mittal, Y. Meurdesoif, and F. Hourdin The design of the icosahedral dynamical core DYNAMICO is presented. DYNAMICO solves the multi-layer rotating shallow-water equations, a compressible variant of the same equivalent to a discretization of the hydrostatic primitive equations in a Lagrangian vertical coordinate, and the primitive equations in a hybrid mass-based vertical coordinate. The common Hamiltonian structure of these sets of equations is exploited to formulate energy-conserving spatial discretizations in a unified way. The horizontal mesh is a quasi-uniform icosahedral C-grid obtained by subdivision of a regular icosahedron. Control volumes for mass, tracers and entropy/potential temperature are the hexagonal cells of the Voronoi mesh to avoid the fast numerical modes of the triangular C-grid. The horizontal discretization is that of Ringler et al. (2010), whose discrete quasi-Hamiltonian structure is identified. The prognostic variables are arranged vertically on a Lorenz grid with all thermodynamical variables collocated with mass. The vertical discretization is obtained from the three-dimensional Hamiltonian formulation. Tracers are transported using a second-order finite volume scheme with slope limiting for positivity. Explicit Runge–Kutta time integration is used for dynamics and forward-in-time integration with horizontal/vertical splitting is used for tracers. Most of the model code is common to the three sets of equations solved, making it easier to develop and validate each piece of the model separately. Representative three-dimensional test cases are run and analyzed, showing correctness of the model. The design permits to consider several extensions in the near future, from higher-order transport to more general dynamics, especially deep-atmosphere and non-hydrostatic equations.

Description: The Lagrangian analysis tool LAGRANTO – version 2.0 Geoscientific Model Development Discussions, 8, 1893-1943, 2015 Author(s): M. Sprenger and H. Wernli Lagrangian trajectories are widely used in the atmospheric sciences, for instance to identify flow structures in extratropical cyclones (e.g., warm conveyor belts) and long-range transport pathways of moisture and trace substances. Here a new version of the Lagrangian analysis tool LAGRANTO (Wernli and Davies, 1997) is introduced, which offers considerably enhanced functionalities: (i) trajectory starting positions can be described easily based on different geometrical and/or meteorological conditions; e.g., equidistantly spaced within a prescribed region and on a stack of pressure (or isentropic) levels; (ii) a versatile selection of trajectories is offered based on single or combined criteria; these criteria are passed to LAGRANTO with a simple command language (e.g., "GT:PV:2" readily translates into a selection of all trajectories with potential vorticity (PV) greater than 2 PVU); and (iii) full versions are available for global ECMWF and regional COSMO data; core functionality is also provided for the regional WRF and UM models, and for the global 20th Century Reanalysis data set. The intuitive application of LAGRANTO is first presented for the identification of a warm conveyor belt in the North Atlantic. A further case study then shows how LAGRANTO is used to quasi-operationally diagnose stratosphere–troposphere exchange events over Europe. Whereas these example rely on the ECMWF version, the COSMO version and input fields with 7 km horizontal resolution are needed to adequately resolve the rather complex flow structure associated with orographic blocking due to the Alps. Finally, an example of backward trajectories presents the tool's application in source-receptor analysis studies. The new distribution of LAGRANTO is publicly available and includes simple tools, e.g., to visualize and merge trajectories. Furthermore, a detailed user guide exists, which describes all LAGRANTO capabilities.

Description: Multi-generational oxidation model to simulate secondary organic aerosol in a 3-D air quality model Geoscientific Model Development Discussions, 8, 1857-1891, 2015 Author(s): S. H. Jathar, C. D. Cappa, A. S. Wexler, J. H. Seinfeld, and M. J. Kleeman Multi-generational gas-phase oxidation of organic vapors can influence the abundance, composition and properties of secondary organic aerosol (SOA). Only recently have SOA models been developed that explicitly represent multi-generational SOA formation. In this work, we integrated the statistical oxidation model (SOM) into SAPRC-11 to simulate the multi-generational oxidation and gas/particle partitioning of SOA in the regional UCD/CIT air quality model. In SOM, evolution of organic vapors by reaction with the hydroxyl radical is defined by (1) the number of oxygen atoms added per reaction, (2) the decrease in volatility upon addition of an oxygen atom and (3) the probability that a given reaction leads to fragmentation of the organic molecule. These SOM parameter values were fit to laboratory "smog chamber" data for each precursor/compound class. The UCD/CIT model was used to simulate air quality over two-week periods in the South Coast Air Basin of California and the eastern United States. For the regions and episodes tested, the traditional two-product SOA model and SOM produce similar SOA concentrations but a modestly different SOA chemical composition. Predictions of the oxygen-to-carbon ratio qualitatively agree with those measured globally using aerosol mass spectrometers. Overall, the implementation of the SOM in a 3-D model provides a comprehensive framework to simulate the atmospheric evolution of OA.

Description: Par@Graph – a parallel toolbox for the construction and analysis of large complex climate networks Geoscientific Model Development Discussions, 8, 319-349, 2015 Author(s): H. Ihshaish, A. Tantet, J. C. M. Dijkzeul, and H. A. Dijkstra In this paper, we present Par@Graph, a software toolbox to reconstruct and analyze complex climate networks having a large number of nodes (up to at least O (10 6 )) and of edges (up to at least O (10 12 )). The key innovation is an efficient set of parallel software tools designed to leverage the inherited hybrid parallelism in distributed-memory clusters of multi-core machines. The performance of the toolbox is illustrated through networks derived from sea surface height (SSH) data of a global high-resolution ocean model. Less than 8 min are needed on 90 Intel Xeon E5-4650 processors to construct a climate network including the preprocessing and the correlation of 3 × 10 5 SSH time series, resulting in a weighted graph with the same number of vertices and about 3 × 10 6 edges. In less than 5 min on 30 processors, the resulted graph's degree centrality, strength, connected components, eigenvector centrality, entropy and clustering coefficient metrics were obtained. These results indicate that a complete cycle to construct and analyze a large-scale climate network is available under 13 min. Par@Graph therefore facilitates the application of climate network analysis on high-resolution observations and model results, by enabling fast network construction from the calculation of statistical similarities between climate time series. It also enables network analysis at unprecedented scales on a variety of different sizes of input data sets.

Description: The software architecture of climate models: a graphical comparison of CMIP5 and EMICAR5 configurations Geoscientific Model Development Discussions, 8, 351-379, 2015 Author(s): K. Alexander and S. M. Easterbrook We analyse the source code of eight coupled climate models, selected from those that participated in the CMIP5 (Taylor et al., 2012) or EMICAR5 (Eby et al., 2013; Zickfeld et al., 2013) intercomparison projects. For each model, we sort the preprocessed code into components and subcomponents based on dependency structure. We then create software architecture diagrams which show the relative sizes of these components/subcomponents and the flow of data between them. The diagrams also illustrate several major classes of climate model design; the distribution of complexity between components, which depends on historical development paths as well as the conscious goals of each institution; and the sharing of components between different modelling groups. These diagrams offer insights into the similarities and differences between models, and have the potential to be useful tools for communication between scientists, scientific institutions, and the public.

Description: Complementing thermosteric sea level rise estimates Geoscientific Model Development Discussions, 8, 1201-1223, 2015 Author(s): K. Lorbacher, M. Meinshausen, and A. Nauels Thermal expansion of seawater is one of the most important contributors to global sea level rise in the past 100 years. Yet, observational estimates of thermal expansion are sparse, mostly limited to the upper ocean layers, and only a part of the available climate model data is sufficiently diagnosed to complete our quantitative understanding of thermosteric sea level rise (thSLR). In order to support usage of results of the Coupled Model Intercomparison Project Phase 5 (CMIP5), complement observations and enable the development of surrogate techniques to project thSLR, we complete diagnostics of CMIP5 models. We obtain 30% more thermal expansion time series than currently published. We find that upper 700 m (2000 m) observational estimates need to be augmented by 36 ± 9% (15 ± 6%) on average to be considered for a global sea level budget. Half of the total expansion originates from depths below 480 ± 250 m – with the range indicating scenario-to-scenario variations. Lastly, to support the development of surrogate methods to project thermal expansion, we calibrate two simplified parameterisations against CMIP5 estimates of thSLR: one parameterisation is suitable for scenarios where only hemispheric ocean temperature profiles are available, the other, where total ocean heat uptake is known (goodness-of-fit: ±5 and ±9%, respectively).