ALBERT

Description: A Lagrangian advection scheme with shape matrix (LASM) for solving advection problems Geoscientific Model Development, 7, 2951-2968, 2014 Author(s): L. Dong, B. Wang, and L. Liu A new Lagrangian advection scheme with shape matrix (LASM) is proposed to take advantage of the extreme low numerical diffusion of the Lagrangian methods. The tracer is discretized into finite parcels, which move along the downstream trajectories. Different from other Lagrangian schemes, the parcel shape is simulated explicitly by a linear transformation matrix. By doing so, the aliasing error in the Lagrangian schemes is largely reduced without introducing substantial interparcel mixing in the pure advection stage, because the flow information will be respected when remapping tracer density onto the fixed model grids. An adaptive interparcel mixing algorithm is constructed to ensure the validity of the linear approximation of the parcel shape, where the mixing is only triggered when it is necessary and resembles the physical mixing. The total tracer mass on the parcels is conserved exactly. The new scheme is validated by using several test cases.

Description: Sensitivity of the Mediterranean sea level to atmospheric pressure and free surface elevation numerical formulation in NEMO Geoscientific Model Development, 7, 3001-3015, 2014 Author(s): P. Oddo, A. Bonaduce, N. Pinardi, and A. Guarnieri The sensitivity of the dynamics of the Mediterranean Sea to atmospheric pressure and free surface elevation formulation using NEMO (Nucleus for European Modelling of the Ocean) was evaluated. Four different experiments were carried out in the Mediterranean Sea using filtered or explicit free surface numerical schemes and accounting for the effect of atmospheric pressure in addition to wind and buoyancy fluxes. Model results were evaluated by coherency and power spectrum analysis with tide gauge data. We found that atmospheric pressure plays an important role for periods shorter than 100 days. The free surface formulation is important to obtain the correct ocean response for periods shorter than 30 days. At frequencies higher than 15 days −1 the Mediterranean basin's response to atmospheric pressure was not coherent and the performance of the model strongly depended on the specific area considered. A large-amplitude seasonal oscillation observed in the experiments using a filtered free surface was not evident in the corresponding explicit free surface formulation case, which was due to a phase shift between mass fluxes in the Gibraltar Strait and at the surface. The configuration with time splitting and atmospheric pressure always performed best; the differences were enhanced at very high frequencies.

Description: Gaseous chemistry and aerosol mechanism developments for version 3.5.1 of the online regional model, WRF-Chem Geoscientific Model Development, 7, 2557-2579, 2014 Author(s): S. Archer-Nicholls, D. Lowe, S. Utembe, J. Allan, R. A. Zaveri, J. D. Fast, Ø. Hodnebrog, H. Denier van der Gon, and G. McFiggans We have made a number of developments to the Weather, Research and Forecasting model coupled with Chemistry (WRF-Chem), with the aim of improving model prediction of trace atmospheric gas-phase chemical and aerosol composition, and of interactions between air quality and weather. A reduced form of the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) has been added, using the Kinetic Pre-Processor (KPP) interface, to enable more explicit simulation of VOC degradation. N 2 O 5 heterogeneous chemistry has been added to the existing sectional MOSAIC aerosol module, and coupled to both the CRIv2-R5 and existing CBM-Z gas-phase schemes. Modifications have also been made to the sea-spray aerosol emission representation, allowing the inclusion of primary organic material in sea-spray aerosol. We have worked on the European domain, with a particular focus on making the model suitable for the study of nighttime chemistry and oxidation by the nitrate radical in the UK atmosphere. Driven by appropriate emissions, wind fields and chemical boundary conditions, implementation of the different developments are illustrated, using a modified version of WRF-Chem 3.4.1, in order to demonstrate the impact that these changes have in the Northwest European domain. These developments are publicly available in WRF-Chem from version 3.5.1 onwards.

Description: Changes in extreme regional sea surface height due to an abrupt weakening of the Atlantic meridional overturning circulation Ocean Science, 10, 881-891, 2014 Author(s): S.-E. Brunnabend, H. A. Dijkstra, M. A. Kliphuis, B. van Werkhoven, H. E. Bal, F. Seinstra, J. Maassen, and M. van Meersbergen As an extreme scenario of dynamical sea level changes, regional sea surface height (SSH) changes that occur in the North Atlantic due to an abrupt weakening of the Atlantic meridional overturning circulation (AMOC) are simulated. Two versions of the same ocean-only model are used to study the effect of ocean model resolution on these SSH changes: a high-resolution (HR) strongly eddying version and a low-resolution (LR) version in which the effect of eddies is parameterised. The weakening of the AMOC is induced in both model versions by applying strong freshwater perturbations around Greenland. A rapid decrease of the AMOC in the HR version induces much shorter return times of several specific regional and coastal extremes in North Atlantic SSH than in the LR version. This effect is caused by a change in main eddy pathways associated with a change in separation latitude of the Gulf Stream.

Description: A strategy for GIS-based 3-D slope stability modelling over large areas Geoscientific Model Development, 7, 2969-2982, 2014 Author(s): M. Mergili, I. Marchesini, M. Alvioli, M. Metz, B. Schneider-Muntau, M. Rossi, and F. Guzzetti GIS-based deterministic models may be used for landslide susceptibility mapping over large areas. However, such efforts require specific strategies to (i) keep computing time at an acceptable level, and (ii) parameterize the geotechnical data. We test and optimize the performance of the GIS-based, 3-D slope stability model r.slope.stability in terms of computing time and model results. The model was developed as a C- and Python-based raster module of the open source software GRASS GIS and considers the 3-D geometry of the sliding surface. It calculates the factor of safety (FoS) and the probability of slope failure ( P f ) for a number of randomly selected potential slip surfaces, ellipsoidal or truncated in shape. Model input consists of a digital elevation model (DEM), ranges of geotechnical parameter values derived from laboratory tests, and a range of possible soil depths estimated in the field. Probability density functions are exploited to assign P f to each ellipsoid. The model calculates for each pixel multiple values of FoS and P f corresponding to different sliding surfaces. The minimum value of FoS and the maximum value of P f for each pixel give an estimate of the landslide susceptibility in the study area. Optionally, r.slope.stability is able to split the study area into a defined number of tiles, allowing parallel processing of the model on the given area. Focusing on shallow landslides, we show how multi-core processing makes it possible to reduce computing times by a factor larger than 20 in the study area. We further demonstrate how the number of random slip surfaces and the sampling of parameters influence the average value of P f and the capacity of r.slope.stability to predict the observed patterns of shallow landslides in the 89.5 km 2 Collazzone area in Umbria, central Italy.

Description: A century of sea level data and the UK's 2013/14 storm surges: an assessment of extremes and clustering using the Newlyn tide gauge record Ocean Science, 10, 1031-1045, 2014 Author(s): M. P. Wadey, I. D. Haigh, and J. M. Brown For the UK's longest and most complete sea level record (Newlyn), we assess extreme high waters and their temporal clustering; prompted by the 2013/2014 winter of storms and flooding. These are set into context against this almost 100-year record. We define annual periods for which storm activity and high sea levels can be compared on a year-by-year basis. Amongst the storms and high tides which affected Newlyn, the recent winter produced the largest recorded high water level (3 February 2014) and five other high water events above a 1 in 1-year return period. The large magnitude of tide and mean sea level, and the close inter-event spacings (of large return period high waters), suggests that the 2013/2014 extreme high water level "season" can be considered the most extreme on record. However, storm and sea level events may be classified in different ways. For example, in the context of sea level rise (which we calculate linearly as 1.81 ± 0.1 mm yr −1 from records between 1915 to 2014), a lower probability combination of surge and tide occurred on 29 January 1948, whilst the 1995/1996 storm surge season saw the most high waters of ≥ the 1 in 1-year return period. We provide a basic categorisation of the four types of extreme high water level cluster, ranging from consecutive tidal cycles to multiple years. The assessment is extended to other UK sites (with shorter sea level records and different tide-surge characteristics), which suggests 2013/2014 was particularly unusual. Further work will assess clustering mechanisms and flood system "memory".

Description: Tropical troposphere to stratosphere transport of carbon monoxide and long-lived trace species in the Chemical Lagrangian Model of the Stratosphere (CLaMS) Geoscientific Model Development, 7, 2895-2916, 2014 Author(s): R. Pommrich, R. Müller, J.-U. Grooß, P. Konopka, F. Ploeger, B. Vogel, M. Tao, C. M. Hoppe, G. Günther, N. Spelten, L. Hoffmann, H.-C. Pumphrey, S. Viciani, F. D'Amato, C. M. Volk, P. Hoor, H. Schlager, and M. Riese Variations in the mixing ratio of trace gases of tropospheric origin entering the stratosphere in the tropics are of interest for assessing both troposphere to stratosphere transport fluxes in the tropics and the impact of these transport fluxes on the composition of the tropical lower stratosphere. Anomaly patterns of carbon monoxide (CO) and long-lived tracers in the lower tropical stratosphere allow conclusions about the rate and the variability of tropical upwelling to be drawn. Here, we present a simplified chemistry scheme for the Chemical Lagrangian Model of the Stratosphere (CLaMS) for the simulation, at comparatively low numerical cost, of CO, ozone, and long-lived trace substances (CH 4 , N 2 O, CCl 3 F (CFC-11), CCl 2 F 2 (CFC-12), and CO 2 ) in the lower tropical stratosphere. For the long-lived trace substances, the boundary conditions at the surface are prescribed based on ground-based measurements in the lowest model level. The boundary condition for CO in the lower troposphere (below about 4 km) is deduced from MOPITT measurements. Due to the lack of a specific representation of mixing and convective uplift in the troposphere in this model version, enhanced CO values, in particular those resulting from convective outflow are underestimated. However, in the tropical tropopause layer and the lower tropical stratosphere, there is relatively good agreement of simulated CO with in situ measurements (with the exception of the TROCCINOX campaign, where CO in the simulation is biased low ≈10–15 ppbv). Further, the model results (and therefore also the ERA-Interim winds, on which the transport in the model is based) are of sufficient quality to describe large scale anomaly patterns of CO in the lower stratosphere. In particular, the zonally averaged tropical CO anomaly patterns (the so called "tape recorder" patterns) simulated by this model version of CLaMS are in good agreement with observations, although the simulations show a too rapid upwelling compared to observations as a consequence of the overestimated vertical velocities in the ERA-Interim reanalysis data set. Moreover, the simulated tropical anomaly patterns of N 2 O are in good agreement with observations. In the simulations, anomaly patterns of CH 4 and CFC-11 were found to be very similar to those of N 2 O; for all long-lived tracers, positive anomalies are simulated because of the enhanced tropical upwelling in the easterly shear phase of the quasi-biennial oscillation.

Description: Influence of frontal cyclone evolution on the 2009 (Ekman) and 2010 (Franklin) Loop Current eddy detachment events Ocean Science, 10, 947-965, 2014 Author(s): Y. S. Androulidakis, V. H. Kourafalou, and M. Le Hénaff The anticyclonic Loop Current Eddy (LCE) shedding events are strongly associated with the evolution of Loop Current Frontal Eddies (LCFEs) over the eastern Gulf of Mexico (GoM). A numerical simulation, in tandem with in situ measurements and satellite data, was used to investigate the Loop Current (LC) evolution and the surrounding LCFE formation, structure, growth and migration during the Eddy Ekman and Eddy Franklin shedding events in the summers of 2009 and 2010, respectively. During both events, northern GoM LCFEs appeared vertically coherent to at least 1500 m in temperature observations. They propagated towards the base of the LC, where, together with the migration of Campeche Bank (southwest GoM shelf) eddies from south of the LC, contributed to its "necking-down". Growth of Campeche Bank LCFEs involved in Eddy Franklin was partially attributed to Campeche Bank waters following upwelling events. Slope processes associated with such upwelling included offshore exports of high positive potential vorticity that may trigger cyclone formation and growth. The advection and growth of LCFEs, originating from the northern and southern GoM, and their interaction with the LC over the LCE detachment area favor shedding conditions and may contribute to the final separation of the LCE.

Description: The Rossby radius in the Arctic Ocean Ocean Science, 10, 967-975, 2014 Author(s): A. J. G. Nurser and S. Bacon The first (and second) baroclinic deformation (or Rossby) radii are presented north of ~60° N, focusing on deep basins and shelf seas in the high Arctic Ocean, the Nordic seas, Baffin Bay, Hudson Bay and the Canadian Arctic Archipelago, derived from climatological ocean data. In the high Arctic Ocean, the first Rossby radius increases from ~5 km in the Nansen Basin to ~15 km in the central Canadian Basin. In the shelf seas and elsewhere, values are low (1–7 km), reflecting weak density stratification, shallow water, or both. Seasonality strongly impacts the Rossby radius only in shallow seas, where winter homogenization of the water column can reduce it to below 1 km. Greater detail is seen in the output from an ice–ocean general circulation model, of higher resolution than the climatology. To assess the impact of secular variability, 10 years (2003–2012) of hydrographic stations along 150° W in the Beaufort Gyre are also analysed. The first-mode Rossby radius increases over this period by ~20%. Finally, we review the observed scales of Arctic Ocean eddies.

Description: Evaluation of the ECHAM family radiation codes performance in the representation of the solar signal Geoscientific Model Development, 7, 2859-2866, 2014 Author(s): T. Sukhodolov, E. Rozanov, A. I. Shapiro, J. Anet, C. Cagnazzo, T. Peter, and W. Schmutz Solar radiation is the main source of energy for the Earth's atmosphere and in many respects defines its composition, photochemistry, temperature profile and dynamics. The magnitude of the solar irradiance variability strongly depends on the wavelength, making difficult its representation in climate models. Due to some deficiencies in the applied radiation codes, several models fail to show a clear response in middle stratospheric heating rates to solar spectral irradiance variability; therefore, it is important to evaluate model performance in this respect before doing multiple runs. In this work we evaluate the performance of three generations of ECHAM (4, 5 and 6) solar radiation schemes by a comparison with the reference high-resolution libRadtran code. We found that all original ECHAM radiation codes miss almost all solar signals in the heating rates in the mesosphere. In the stratosphere the two-band ECHAM4 code (E4) has an almost negligible radiative response to solar irradiance changes and the six-band ECHAM5 code (E5c) reproduces only about half of the reference signal, while representation in the ECHAM6 code (E6) is better – it misses a maximum of about 15% in the upper stratosphere. On the basis of the comparison results we suggest necessary improvements to the ECHAM family codes by the inclusion of available parameterizations of the heating rate due to absorption by oxygen (O 2 ) and ozone (O 3 ). Improvement is presented for E5c and E6, and both codes, with the introduced parameterizations, represent the heating rate response to the spectral solar irradiance variability simulated with libRadtran much better without a substantial increase in computer time. The suggested parameterizations are recommended to be applied in the middle-atmosphere version of the ECHAM-5 and 6 models for the study of the solar irradiance influence on climate.

Description: GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects Geoscientific Model Development, 7, 2831-2857, 2014 Author(s): S. Endrizzi, S. Gruber, M. Dall'Amico, and R. Rigon GEOtop is a fine-scale grid-based simulator that represents the heat and water budgets at and below the soil surface. It describes the three-dimensional water flow in the soil and the energy exchange with the atmosphere, considering the radiative and turbulent fluxes. Furthermore, it reproduces the highly non-linear interactions between the water and energy balance during soil freezing and thawing, and simulates the temporal evolution of the water and energy budgets in the snow cover and their effect on soil temperature. Here, we present the core components of GEOtop 2.0 and demonstrate its functioning. Based on a synthetic simulation, we show that the interaction of processes represented in GEOtop 2.0 can result in phenomena that are significant and relevant for applications involving permafrost and seasonally frozen soils, both in high altitude and latitude regions.

Description: The North American Carbon Program Multi-scale Synthesis and Terrestrial Model Intercomparison Project – Part 2: Environmental driver data Geoscientific Model Development, 7, 2875-2893, 2014 Author(s): Y. Wei, S. Liu, D. N. Huntzinger, A. M. Michalak, N. Viovy, W. M. Post, C. R. Schwalm, K. Schaefer, A. R. Jacobson, C. Lu, H. Tian, D. M. Ricciuto, R. B. Cook, J. Mao, and X. Shi Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model–model and model–observation comparisons. This paper describes the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO 2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5° × 0.5° resolution) and regional (North American: 0.25° × 0.25° resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. The data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov ) to provide long-term data management and distribution.

Description: Evaluation of the new UKCA climate-composition model – Part 2: The Troposphere Geoscientific Model Development, 7, 41-91, 2014 Author(s): F. M. O'Connor, C. E. Johnson, O. Morgenstern, N. L. Abraham, P. Braesicke, M. Dalvi, G. A. Folberth, M. G. Sanderson, P. J. Telford, A. Voulgarakis, P. J. Young, G. Zeng, W. J. Collins, and J. A. Pyle In this paper, we present a description of the tropospheric chemistry component of the UK Chemistry and Aerosols (UKCA) model which has been coupled to the Met Office Hadley Centre's HadGEM family of climate models. We assess the model's transport and scavenging processes, in particular focussing on convective transport, boundary layer mixing, wet scavenging and inter-hemispheric exchange. Simulations with UKCA of the short-lived radon tracer suggest that modelled distributions are comparable to those of other models and the comparison with observations indicate that apart from a few locations, boundary layer mixing and convective transport are effective in the model as a means of vertically redistributing surface emissions of radon. Comparisons of modelled lead tracer concentrations with observations suggest that UKCA captures surface concentrations in both hemispheres very well, although there is a tendency to underestimate the observed geographical and interannual variability in the Northern Hemisphere. In particular, UKCA replicates the shape and absolute concentrations of observed lead profiles, a key test in the evaluation of a model's wet scavenging scheme. The timescale for inter-hemispheric transport, calculated in the model using a simple krypton tracer experiment, does appear to be long relative to other models and could indicate deficiencies in tropical deep convection and/or insufficient boundary layer mixing. We also describe the main components of the tropospheric chemistry and evaluate it against observations and other tropospheric chemistry models. In particular, from a climate forcing perspective, present-day observed surface methane concentrations and tropospheric ozone concentrations are reproduced very well by the model, thereby making it suitable for long centennial integrations as well as studies of biogeochemical feedbacks. Results from both historical and future simulations with UKCA tropospheric chemistry are presented. Future projections of tropospheric ozone vary with the Representative Concentration Pathway (RCP). In RCP2.6, for example, tropospheric ozone increases up to 2010 and then declines by 13% of its year-2000 global mean by the end of the century. In RCP8.5, tropospheric ozone continues to rise steadily throughout the 21st century, with methane being the main driving factor. Finally, we highlight aspects of the UKCA model which are undergoing and/or have undergone recent developments and are suitable for inclusion in a next-generation Earth System Model.

Description: A fast input/output library for high-resolution climate models Geoscientific Model Development, 7, 93-103, 2014 Author(s): X. M. Huang, W. C. Wang, H. H. Fu, G. W. Yang, B. Wang, and C. Zhang We describe the design and implementation of climate fast input/output (CFIO), a fast input/output (I/O) library for high-resolution climate models. CFIO provides a simple method for modelers to overlap the I/O phase with the computing phase automatically, so as to shorten the running time of numerical simulations. To minimize the code modifications required for porting, CFIO provides similar interfaces and features to parallel Network Common Data Form (PnetCDF), which is one of the most widely used I/O libraries in climate models. We deployed CFIO in three high-resolution climate models, including two ocean models (POP and LICOM) and one sea ice model (CICE). The experimental results show that CFIO improves the performance of climate models significantly versus the original serial I/O approach. When running with CFIO at 0.1° resolution with about 1000 CPU cores, we managed to reduce the running time by factors of 7.9, 4.6 and 2.0 for POP, CICE, and LICOM, respectively. We also compared the performance of CFIO against two existing libraries, PnetCDF and parallel I/O (PIO), in different scenarios. For scenarios with both data output and computations, CFIO decreases the I/O overhead compared to PnetCDF and PIO.

Description: A standard test case suite for two-dimensional linear transport on the sphere: results from a collection of state-of-the-art schemes Geoscientific Model Development, 7, 105-145, 2014 Author(s): P. H. Lauritzen, P. A. Ullrich, C. Jablonowski, P. A. Bosler, D. Calhoun, A. J. Conley, T. Enomoto, L. Dong, S. Dubey, O. Guba, A. B. Hansen, E. Kaas, J. Kent, J.-F. Lamarque, M. J. Prather, D. Reinert, V. V. Shashkin, W. C. Skamarock, B. Sørensen, M. A. Taylor, and M. A. Tolstykh Recently, a standard test case suite for 2-D linear transport on the sphere was proposed to assess important aspects of accuracy in geophysical fluid dynamics with a "minimal" set of idealized model configurations/runs/diagnostics. Here we present results from 19 state-of-the-art transport scheme formulations based on finite-difference/finite-volume methods as well as emerging (in the context of atmospheric/oceanographic sciences) Galerkin methods. Discretization grids range from traditional regular latitude–longitude grids to more isotropic domain discretizations such as icosahedral and cubed-sphere tessellations of the sphere. The schemes are evaluated using a wide range of diagnostics in idealized flow environments. Accuracy is assessed in single- and two-tracer configurations using conventional error norms as well as novel diagnostics designed for climate and climate–chemistry applications. In addition, algorithmic considerations that may be important for computational efficiency are reported on. The latter is inevitably computing platform dependent. The ensemble of results from a wide variety of schemes presented here helps shed light on the ability of the test case suite diagnostics and flow settings to discriminate between algorithms and provide insights into accuracy in the context of global atmospheric/ocean modeling. A library of benchmark results is provided to facilitate scheme intercomparison and model development. Simple software and data sets are made available to facilitate the process of model evaluation and scheme intercomparison.

Description: Geostrophic currents and kinetic energies in the Black Sea estimated from merged drifter and satellite altimetry data Ocean Science, 10, 155-165, 2014 Author(s): M. Menna and P.-M. Poulain Drifter measurements and satellite altimetry data are merged to reconstruct the surface geostrophic circulation of the Black Sea in the period 1999–2009. This combined data set is used to estimate pseudo-Eulerian velocity statistics for different time periods. Seasonal and interannual variability of currents and kinetic energy fields are described with particular attention to the mesoscale and sub-basin coastal eddies. The mean currents are generally stronger in winter and enhanced speeds are observed in the period 2002–2006. The most intense activity of sub-basin Batumi Eddy occurs in summer with greater speeds and dimensions in 2006 and 2008. The sub-basin Sevastopol Eddy is generated in spring from a meander of the Rim Current. Mesoscale eddies located along the Anatolia, Caucasus and Crimea coasts are permanent, quasi-permanent or intermittent features and can interact and merge with each other, showing high values of kinetic energy.

Description: Optimisation of the simulation particle number in a Lagrangian ice microphysical model Geoscientific Model Development, 7, 695-709, 2014 Author(s): S. Unterstrasser and I. Sölch This paper presents various techniques to speed up the Lagrangian ice microphysics code EULAG-LCM. The amount of CPU time (and also memory and storage data) depends heavily on the number of simulation ice particles (SIPs) used to represent the bulk of real ice crystals. It was found that the various microphysical processes require different numbers of SIPs to reach statistical convergence (in a sense that a further increase of the SIP number does not systematically change the physical outcome of a cirrus simulation). Whereas deposition/sublimation and sedimentation require only a moderate number of SIPs, the (nonlinear) ice nucleation process is only well represented, when a large number of SIPs is generated. We introduced a new stochastic nucleation implementation which mimics the stochastic nature of nucleation and greatly reduces numerical sensitivities. Furthermore several strategies (SIP merging and splitting) are presented which flexibly adjust and reduce the number of SIPs. These efficiency measures reduce the computational costs of present cirrus studies and allow extending the temporal and spatial scales of upcoming studies.

Description: The Finite Element Sea Ice-Ocean Model (FESOM) v.1.4: formulation of an ocean general circulation model Geoscientific Model Development, 7, 663-693, 2014 Author(s): Q. Wang, S. Danilov, D. Sidorenko, R. Timmermann, C. Wekerle, X. Wang, T. Jung, and J. Schröter The Finite Element Sea Ice-Ocean Model (FESOM) is the first global ocean general circulation model based on unstructured-mesh methods that has been developed for the purpose of climate research. The advantage of unstructured-mesh models is their flexible multi-resolution modelling functionality. In this study, an overview of the main features of FESOM will be given; based on sensitivity experiments a number of specific parameter choices will be explained; and directions of future developments will be outlined. It is argued that FESOM is sufficiently mature to explore the benefits of multi-resolution climate modelling and that its applications will provide information useful for the advancement of climate modelling on unstructured meshes.

Description: A 24-variable low-order coupled ocean–atmosphere model: OA-QG-WS v2 Geoscientific Model Development, 7, 649-662, 2014 Author(s): S. Vannitsem and L. De Cruz A new low-order coupled ocean–atmosphere model for midlatitudes is derived. It is based on quasi-geostrophic equations for both the ocean and the atmosphere, coupled through momentum transfer at the interface. The systematic reduction of the number of modes describing the dynamics leads to an atmospheric low-order component of 20 ordinary differential equations, already discussed in Reinhold and Pierrehumbert (1982), and an oceanic low-order component of four ordinary differential equations, as proposed by Pierini (2011). The coupling terms for both components are derived and all the coefficients of the ocean model are provided. Its dynamics is then briefly explored, through the analysis of its mean field, its variability and its instability properties. The wind-driven ocean displays a decadal variability induced by the atmospheric chaotic wind forcing. The chaotic behavior of the coupled system is highly sensitive to the ocean–atmosphere coupling for low values of the thermal forcing affecting the atmosphere (corresponding to a weakly chaotic coupled system). But it is less sensitive for large values of the thermal forcing (corresponding to a highly chaotic coupled system). In all the cases explored, the number of positive exponents is increasing with the coupling. Two codes in Fortran and Lua of the model integration are provided as Supplement.

Description: On the analytic approximation of bulk collision rates of non-spherical hydrometeors Geoscientific Model Development, 7, 463-478, 2014 Author(s): A. Seifert, U. Blahak, and R. Buhr Analytic approximations of the binary collision rates of hydrometeors are derived for use in bulk microphysical parameterizations. Special attention is given to non-spherical hydrometeors like raindrops and snowflakes. The terminal fall velocity of these particles cannot be sufficiently well approximated by power-law relations which are used in most microphysical parameterizations, and therefore an improved formulation is needed. The analytic approximations of the bulk collision rates given in this paper are an alternative to look-up tables and can replace the Wisner approximation, which is used in many atmospheric models.

Description: Changes in ventilation of the Mediterranean Sea during the past 25 year Ocean Science, 10, 1-16, 2014 Author(s): A. Schneider, T. Tanhua, W. Roether, and R. Steinfeldt Significant changes in the overturning circulation of the Mediterranean Sea has been observed during the last few decades, the most prominent phenomena being the Eastern Mediterranean Transient (EMT) in the early 1990s and the Western Mediterranean Transition (WMT) during the mid-2000s. During both of these events unusually large amounts of deep water were formed, and in the case of the EMT, the deep water formation area shifted from the Adriatic to the Aegean Sea. Here we synthesize a unique collection of transient tracer (CFC-12, SF 6 and tritium) data from nine cruises conducted between 1987 and 2011 and use these data to determine temporal variability of Mediterranean ventilation. We also discuss biases and technical problems with transient tracer-based ages arising from their different input histories over time; particularly in the case of time-dependent ventilation. We observe a period of low ventilation in the deep eastern (Levantine) basin after it was ventilated by the EMT so that the age of the deep water is increasing with time. In the Ionian Sea, on the other hand, we see evidence of increased ventilation after year 2001, indicating the restarted deep water formation in the Adriatic Sea. This is also reflected in the increasing age of the Cretan Sea deep water and decreasing age of Adriatic Sea deep water since the end of the 1980s. In the western Mediterranean deep basin we see the massive input of recently ventilated waters during the WMT. This signal is not yet apparent in the Tyrrhenian Sea, where the ventilation seems to be fairly constant since the EMT. Also the western Alboran Sea does not show any temporal trends in ventilation.

Description: Methodological aspects of a pattern-scaling approach to produce global fields of monthly means of daily maximum and minimum temperature Geoscientific Model Development, 7, 249-266, 2014 Author(s): S. Kremser, G. E. Bodeker, and J. Lewis A Climate Pattern-Scaling Model (CPSM) that simulates global patterns of climate change, for a prescribed emissions scenario, is described. A CPSM works by quantitatively establishing the statistical relationship between a climate variable at a specific location (e.g. daily maximum surface temperature, T max ) and one or more predictor time series (e.g. global mean surface temperature, T global ) – referred to as the "training" of the CPSM. This training uses a regression model to derive fit coefficients that describe the statistical relationship between the predictor time series and the target climate variable time series. Once that relationship has been determined, and given the predictor time series for any greenhouse gas (GHG) emissions scenario, the change in the climate variable of interest can be reconstructed – referred to as the "application" of the CPSM. The advantage of using a CPSM rather than a typical atmosphere–ocean global climate model (AOGCM) is that the predictor time series required by the CPSM can usually be generated quickly using a simple climate model (SCM) for any prescribed GHG emissions scenario and then applied to generate global fields of the climate variable of interest. The training can be performed either on historical measurements or on output from an AOGCM. Using model output from 21st century simulations has the advantage that the climate change signal is more pronounced than in historical data and therefore a more robust statistical relationship is obtained. The disadvantage of using AOGCM output is that the CPSM training might be compromised by any AOGCM inadequacies. For the purposes of exploring the various methodological aspects of the CPSM approach, AOGCM output was used in this study to train the CPSM. These investigations of the CPSM methodology focus on monthly mean fields of daily temperature extremes ( T max and T min ). The methodological aspects of the CPSM explored in this study include (1) investigation of the advantage gained in having five predictor time series over having only one predictor time series, (2) investigation of the time dependence of the fit coefficients and (3) investigation of the dependence of the fit coefficients on GHG emissions scenario. Key conclusions are (1) overall, the CPSM trained on simulations based on the Representative Concentration Pathway (RCP) 8.5 emissions scenario is able to reproduce AOGCM simulations of T max and T min based on predictor time series from an RCP 4.5 emissions scenario; (2) access to hemisphere average land and ocean temperatures as predictors improves the variance that can be explained, particularly over the oceans; (3) regression model fit coefficients derived from individual simulations based on the RCP 2.6, 4.5 and 8.5 emissions scenarios agree well over most regions of the globe (the Arctic is the exception); (4) training the CPSM on concatenated time series from an ensemble of simulations does not result in fit coefficients that explain significantly more of the variance than an approach that weights results based on single simulation fits; and (5) the inclusion of a linear time dependence in the regression model fit coefficients improves the variance explained, primarily over the oceans.

Description: Temporal variations of zooplankton biomass in the Ligurian Sea inferred from long time series of ADCP data Ocean Science, 10, 93-105, 2014 Author(s): R. Bozzano, E. Fanelli, S. Pensieri, P. Picco, and M. E. Schiano Three years of 300 kHz acoustic doppler current profiler data collected in the central Ligurian Sea are analysed to investigate the variability of the zooplankton biomass and the diel vertical migration in the upper thermocline. After a pre-processing phase aimed at avoiding the slant range attenuation, hourly volume backscattering strength time series are obtained. Despite the lack of concurrent net samples collection, different migration patterns are identified and their temporal variability examined by means of time–frequency analysis. The effect of changes in the environmental condition is also investigated. The highest zooplankton biomasses are observed in April–May just after the peak of surface primary production in March–April. The main migration pattern found here points to a "nocturnal" migration, with zooplankton organisms occurring deeper in the water column during the day and shallower at night. Also, twilight migration is highlighted during this study. The largest migrations are recorded in November–December, corresponding to lowest backscattering strength values and they are likely attributable to larger and more active organisms (i.e. euphausiids and mesopelagic fish). The results suggest further applications of the available historical acoustic doppler current profiler time series.

Description: Inherently mass-conservative version of the semi-Lagrangian absolute vorticity (SL-AV) atmospheric model dynamical core Geoscientific Model Development, 7, 407-417, 2014 Author(s): V. V. Shashkin and M. A. Tolstykh The semi-Lagrangian absolute vorticity (SL-AV) atmospheric model is the global semi-Lagrangian hydrostatic model used for operational medium-range and seasonal forecasts at the Hydrometeorological Centre of Russia. The distinct feature of the SL-AV dynamical core is the semi-implicit, semi-Lagrangian vorticity-divergence formulation on the unstaggered grid. A semi-implicit, semi-Lagrangian approach allows for long time steps but violates the global and local mass conservation. In particular, the total mass in simulations with semi-Lagrangian models can drift significantly if no a posteriori mass-fixing algorithm is applied. However, the global mass-fixing algorithms degrade the local mass conservation. The new inherently mass-conservative version of the SL-AV model dynamical core presented here ensures global and local mass conservation without mass-fixing algorithms. The mass conservation is achieved with the introduction of the finite-volume, semi-Lagrangian discretization for a continuity equation based on the 3-D extension of the conservative cascade semi-Lagrangian transport scheme (CCS). Numerical experiments show that the new version of the SL-AV dynamical core presented combines the accuracy and stability of the standard SL-AV dynamical core with the mass-conservation properties. The results of the mountain-induced Rossby-wave test and baroclinic instability test for the mass-conservative dynamical core are found to be in agreement with the results available in the literature.

Description: Decadal variability of heat content in the South China Sea inferred from observation data and an ocean data assimilation product Ocean Science, 10, 135-139, 2014 Author(s): Wei Song, Jian Lan, Qinyan Liu, Dandan Sui, Lili Zeng, and Dongxiao Wang Using an observation data set of temperature and the Simple Ocean Data Assimilation (SODA), the decadal variability of upper ocean heat content (0–400 m; hereafter, OHC) in the South China Sea (SCS) was investigated for the period from 1958 to 2007. Decadal variability was identified as the dominant mode of upper OHC besides the seasonal cycle. According to decreasing or increasing OHC, four periods were chosen to discuss detailed processes behind OHC variability in the SCS; the four periods are 1958–1968, 1969–1981, 1982–1992, and 1993–2003. Results show that advection was the major factor for decreasing (increasing) OHC during 1958–1968 (1968–1981). During 1982–1992 and 1993–2003, the net surface heat flux was the main contributor to the variability of OHC besides the advection. The OHC, advection and net surface heat flux had significant positive trends during 1992–2003. The spatial characteristics of OHC variability and heat budget in the Luzon Strait, west of Luzon Island, and in the Xisha warm eddy region are also discussed.

Description: Atmospheric inverse modeling with known physical bounds: an example from trace gas emissions Geoscientific Model Development, 7, 303-315, 2014 Author(s): S. M. Miller, A. M. Michalak, and P. J. Levi Many inverse problems in the atmospheric sciences involve parameters with known physical constraints. Examples include nonnegativity (e.g., emissions of some urban air pollutants) or upward limits implied by reaction or solubility constants. However, probabilistic inverse modeling approaches based on Gaussian assumptions cannot incorporate such bounds and thus often produce unrealistic results. The atmospheric literature lacks consensus on the best means to overcome this problem, and existing atmospheric studies rely on a limited number of the possible methods with little examination of the relative merits of each. This paper investigates the applicability of several approaches to bounded inverse problems. A common method of data transformations is found to unrealistically skew estimates for the examined example application. The method of Lagrange multipliers and two Markov chain Monte Carlo (MCMC) methods yield more realistic and accurate results. In general, the examined MCMC approaches produce the most realistic result but can require substantial computational time. Lagrange multipliers offer an appealing option for large, computationally intensive problems when exact uncertainty bounds are less central to the analysis. A synthetic data inversion of US anthropogenic methane emissions illustrates the strengths and weaknesses of each approach.

Description: TopoSCALE v.1.0: downscaling gridded climate data in complex terrain Geoscientific Model Development, 7, 387-405, 2014 Author(s): J. Fiddes and S. Gruber Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by, for example, topography, and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that uses the well-resolved description of the atmospheric column provided by climate models, together with high-resolution digital elevation models (DEMs), to downscale coarse-grid climate variables to a fine-scale subgrid. The main aim of this approach is to provide high-resolution driving data for a land-surface model (LSM). The method makes use of an interpolation of pressure-level data according to topographic height of the subgrid. An elevation and topography correction is used to downscale short-wave radiation. Long-wave radiation is downscaled by deriving a cloud-component of all-sky emissivity at grid level and using downscaled temperature and relative humidity fields to describe variability with elevation. Precipitation is downscaled with a simple non-linear lapse and optionally disaggregated using a climatology approach. We test the method in comparison with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure levels: air temperature, relative humidity, wind speed and incoming long-wave radiation. This method may be of use in improving inputs to numerical simulations in heterogeneous and/or remote terrain, especially when statistical methods are not possible, due to lack of observations (i.e. remote areas or future periods).

Description: A database and tool for boundary conditions for regional air quality modeling: description and evaluation Geoscientific Model Development, 7, 339-360, 2014 Author(s): B. H. Henderson, F. Akhtar, H. O. T. Pye, S. L. Napelenok, and W. T. Hutzell Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available observations are too sparse vertically to provide boundary information, particularly for ozone precursors, but global simulations can be used to generate spatially and temporally varying lateral boundary conditions (LBC). This study presents a public database of global simulations designed and evaluated for use as LBC for air quality models (AQMs). The database covers the contiguous United States (CONUS) for the years 2001–2010 and contains hourly varying concentrations of ozone, aerosols, and their precursors. The database is complemented by a tool for configuring the global results as inputs to regional scale models (e.g., Community Multiscale Air Quality or Comprehensive Air quality Model with extensions). This study also presents an example application based on the CONUS domain, which is evaluated against satellite retrieved ozone and carbon monoxide vertical profiles. The results show performance is largely within uncertainty estimates for ozone from the Ozone Monitoring Instrument and carbon monoxide from the Measurements Of Pollution In The Troposphere (MOPITT), but there were some notable biases compared with Tropospheric Emission Spectrometer (TES) ozone. Compared with TES, our ozone predictions are high-biased in the upper troposphere, particularly in the south during January. This publication documents the global simulation database, the tool for conversion to LBC, and the evaluation of concentrations on the boundaries. This documentation is intended to support applications that require representation of long-range transport of air pollutants.

Description: Can sparse proxy data constrain the strength of the Atlantic meridional overturning circulation? Geoscientific Model Development, 7, 419-432, 2014 Author(s): T. Kurahashi-Nakamura, M. Losch, and A. Paul In a feasibility study, the potential of proxy data for the temperature and salinity during the Last Glacial Maximum (LGM, about 19 000 to 23 000 years before present) in constraining the strength of the Atlantic meridional overturning circulation (AMOC) with a general ocean circulation model was explored. The proxy data were simulated by drawing data from four different model simulations at the ocean sediment core locations of the Multiproxy Approach for the Reconstruction of the Glacial Ocean surface (MARGO) project, and perturbing these data with realistic noise estimates. The results suggest that our method has the potential to provide estimates of the past strength of the AMOC even from sparse data, but in general, paleo-sea-surface temperature data without additional prior knowledge about the ocean state during the LGM is not adequate to constrain the model. On the one hand, additional data in the deep-ocean and salinity data are shown to be highly important in estimating the LGM circulation. On the other hand, increasing the amount of surface data alone does not appear to be enough for better estimates. Finally, better initial guesses to start the state estimation procedure would greatly improve the performance of the method. Indeed, with a sufficiently good first guess, just the sea-surface temperature data from the MARGO project promise to be sufficient for reliable estimates of the strength of the AMOC.

Description: Development and exploitation of a controlled vocabulary in support of climate modelling Geoscientific Model Development, 7, 479-493, 2014 Author(s): M.-P. Moine, S. Valcke, B. N. Lawrence, C. Pascoe, R. W. Ford, A. Alias, V. Balaji, P. Bentley, G. Devine, S. A. Callaghan, and E. Guilyardi There are three key components for developing a metadata system: a container structure laying out the key semantic issues of interest and their relationships; an extensible controlled vocabulary providing possible content; and tools to create and manipulate that content. While metadata systems must allow users to enter their own information, the use of a controlled vocabulary both imposes consistency of definition and ensures comparability of the objects described. Here we describe the controlled vocabulary (CV) and metadata creation tool built by the METAFOR project for use in the context of describing the climate models, simulations and experiments of the fifth Coupled Model Intercomparison Project (CMIP5). The CV and resulting tool chain introduced here is designed for extensibility and reuse and should find applicability in many more projects.

Description: Improving predictive power of physically based rainfall-induced shallow landslide models: a probabilistic approach Geoscientific Model Development, 7, 495-514, 2014 Author(s): S. Raia, M. Alvioli, M. Rossi, R. L. Baum, J. W. Godt, and F. Guzzetti Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws. These models extend spatially the static stability models adopted in geotechnical engineering, and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the operation of the existing models lays in the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of rainfall-induced shallow landslides. For this purpose, we have modified the transient rainfall infiltration and grid-based regional slope-stability analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a probabilistic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs of several model runs obtained varying the input parameters are analyzed statistically, and compared to the original (deterministic) model output. The comparison suggests an improvement of the predictive power of the model of about 10% and 16% in two small test areas, that is, the Frontignano (Italy) and the Mukilteo (USA) areas. We discuss the computational requirements of TRIGRS-P to determine the potential use of the numerical model to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides in very large areas, extending for several hundreds or thousands of square kilometers. Parallel execution of the code using a simple process distribution and the message passing interface (MPI) on multi-processor machines was successful, opening the possibly of testing the use of TRIGRS-P for the operational forecasting of rainfall-induced shallow landslides over large regions.

Description: An improved non-iterative surface layer flux scheme for atmospheric stable stratification conditions Geoscientific Model Development, 7, 515-529, 2014 Author(s): Y. Li, Z. Gao, D. Li, L. Wang, and H. Wang Parameterization of turbulent fluxes under stably stratified conditions has always been a challenge. Current surface fluxes calculation schemes either need iterations or suffer low accuracy. In this paper, a non-iterative scheme is proposed to approach the classic iterative computation results using multiple regressions. It can be applied to the full range of roughness status 10 ≤ z / z 0 ≤ 10 5 and −0.5 ≤ log ( z 0 / z 0 h ) ≤ 30 under stable conditions 0 〈 Ri B ≤ 2.5. The maximum (average) relative errors for the turbulent transfer coefficients for momentum and sensible heat are 12% (1%) and 9% (1%), respectively.

Description: AnaWEGE: a weather generator based on analogues of atmospheric circulation Geoscientific Model Development, 7, 531-543, 2014 Author(s): P. Yiou This paper presents a stochastic weather generator based on analogues of circulation (AnaWEGE). Analogues of circulation have been a promising paradigm to analyse climate variability and its extremes. The weather generator uses precomputed analogues of sea-level pressure over the North Atlantic. The stochastic rules of the generator constrain the continuity in time of the simulations. The generator then simulates spatially coherent time series of a climate variable, drawn from meteorological observations. The weather generator is tested for European temperatures, and for winter and summer seasons. The biases in temperature quantiles and autocorrelation are rather small compared to observed variability. The ability of simulating extremely hot summers and cold winters is also assessed.

Description: On the sensitivity of 3-D thermal convection codes to numerical discretization: a model intercomparison Geoscientific Model Development, 7, 2065-2076, 2014 Author(s): P.-A Arrial, N. Flyer, G. B. Wright, and L. H. Kellogg Fully 3-D numerical simulations of thermal convection in a spherical shell have become a standard for studying the dynamics of pattern formation and its stability under perturbations to various parameter values. The question arises as to how the discretization of the governing equations affects the outcome and thus any physical interpretation. This work demonstrates the impact of numerical discretization on the observed patterns, the value at which symmetry is broken, and how stability and stationary behavior is dependent upon it. Motivated by numerical simulations of convection in the Earth's mantle, we consider isoviscous Rayleigh–Bénard convection at infinite Prandtl number, where the aspect ratio between the inner and outer shell is 0.55. We show that the subtleties involved in developing mantle convection models are considerably more delicate than has been previously appreciated, due to the rich dynamical behavior of the system. Two codes with different numerical discretization schemes – an established, community-developed, and benchmarked finite-element code (CitcomS) and a novel spectral method that combines Chebyshev polynomials with radial basis functions (RBFs) – are compared. A full numerical study is investigated for the following three cases. The first case is based on the cubic (or octahedral) initial condition (spherical harmonics of degree ℓ = 4). How this pattern varies to perturbations in the initial condition and Rayleigh number is studied. The second case investigates the stability of the dodecahedral (or icosahedral) initial condition (spherical harmonics of degree ℓ = 6). Although both methods first converge to the same pattern, this structure is ultimately unstable and systematically degenerates to cubic or tetrahedral symmetries, depending on the code used. Lastly, a new steady-state pattern is presented as a combination of third- and fourth-order spherical harmonics leading to a five-cell or hexahedral pattern and stable up to 70 times the critical Rayleigh number. This pattern can provide the basis for a new accuracy benchmark for 3-D spherical mantle convection codes.

Description: Optimization of NWP model closure parameters using total energy norm of forecast error as a target Geoscientific Model Development, 7, 1889-1900, 2014 Author(s): P. Ollinaho, H. Järvinen, P. Bauer, M. Laine, P. Bechtold, J. Susiluoto, and H. Haario We explore the use of dry total energy norm in improving numerical weather prediction (NWP) model forecast skill. The Ensemble Prediction and Parameter Estimation System (EPPES) is utilized to estimate ECHAM5 atmospheric GCM (global circulation models) closure parameters related to clouds and precipitation. The target criterion in the optimization is the dry total energy norm of 3-day forecast error with respect to the ECMWF (European Centre for Medium-Range Weather Forecasts) operational analyses. The results are summarized as follows: (i) forecast error growth in terms of energy norm is slower in the optimized than in the default model up to day 10 forecasts (and beyond), (ii) headline forecast skill scores are improved in the training sample as well as in independent samples, (iii) the decrease of the forecast error energy norm at day three is mainly because of smaller kinetic energy error in the tropics, and (iv) this impact is spread into midlatitudes at longer ranges and appears as a smaller forecast error of potential energy. The interpretation of these results is that the parameter optimization has reduced the model error so that the forecasts remain longer in the vicinity of the analyzed state.

Description: SimSphere model sensitivity analysis towards establishing its use for deriving key parameters characterising land surface interactions Geoscientific Model Development, 7, 1873-1887, 2014 Author(s): G. P. Petropoulos, H. M. Griffiths, T. N. Carlson, P. Ioannou-Katidis, and T. Holt Being able to accurately estimate parameters characterising land surface interactions is currently a key scientific priority due to their central role in the Earth's global energy and water cycle. To this end, some approaches have been based on utilising the synergies between land surface models and Earth observation (EO) data to retrieve relevant parameters. One such model is SimSphere, the use of which is currently expanding, either as a stand-alone application or synergistically with EO data. The present study aimed at exploring the effect of changing the atmospheric sounding profile on the sensitivity of key variables predicted by this model assuming different probability distribution functions (PDFs) for its inputs/outputs. To satisfy this objective and to ensure consistency and comparability to analogous studies conducted previously on the model, a sophisticated, cutting-edge sensitivity analysis (SA) method adopting Bayesian theory was implemented on SimSphere. Our results did not show dramatic changes in the nature or ranking of influential model inputs in comparison to previous studies. Model outputs examined using SA were sensitive to a small number of the inputs; a significant amount of first-order interactions between the inputs was also found, suggesting strong model coherence. Results showed that the assumption of different PDFs for the model inputs/outputs did not have an important bearing on mapping the most responsive model inputs and interactions, but only the absolute SA measures. This study extends our understanding of SimSphere's structure and further establishes its coherence and correspondence to that of a natural system's behaviour. Consequently, the present work represents a significant step forward in the global efforts on SimSphere verification, especially those focusing on the development of global operational products from the model synergy with EO data.

Description: Refinement of a model for evaluating the population exposure in an urban area Geoscientific Model Development, 7, 1855-1872, 2014 Author(s): J. Soares, A. Kousa, J. Kukkonen, L. Matilainen, L. Kangas, M. Kauhaniemi, K. Riikonen, J.-P. Jalkanen, T. Rasila, O. Hänninen, T. Koskentalo, M. Aarnio, C. Hendriks, and A. Karppinen A mathematical model is presented for the determination of human exposure to ambient air pollution in an urban area; the model is a refined version of a previously developed mathematical model EXPAND (EXposure model for Particulate matter And Nitrogen oxiDes). The model combines predicted concentrations, information on people's activities and location of the population to evaluate the spatial and temporal variation of average exposure of the urban population to ambient air pollution in different microenvironments. The revisions of the modelling system containing the EXPAND model include improvements of the associated urban emission and dispersion modelling system, an improved treatment of the time use of population, and better treatment for the infiltration coefficients from outdoor to indoor air. The revised model version can also be used for estimating intake fractions for various pollutants, source categories and population subgroups. We present numerical results on annual spatial concentration, time activity and population exposures to PM 2.5 in the Helsinki Metropolitan Area and Helsinki for 2008 and 2009, respectively. Approximately 60% of the total exposure occurred at home, 17% at work, 4% in traffic and 19% in other microenvironments in the Helsinki Metropolitan Area. The population exposure originating from the long-range transported background concentrations was responsible for a major fraction, 86%, of the total exposure in Helsinki. The largest local contributors were vehicular emissions (12%) and shipping (2%).

Description: Air quality forecast of PM 10 in Beijing with Community Multi-scale Air Quality Modeling (CMAQ) system: emission and improvement Geoscientific Model Development, 7, 2243-2259, 2014 Author(s): Q. Wu, W. Xu, A. Shi, Y. Li, X. Zhao, Z. Wang, J. Li, and L. Wang The MM5-SMOKE-CMAQ model system, which was developed by the United States Environmental Protection Agency (US EPA) as the MODELS-3 system, has been used for daily air quality forecasts in the Beijing Municipal Environmental Monitoring Center (Beijing MEMC), as a part of the Ensemble air quality Modeling forecast System for Beijing (EMS-Beijing) since the 2008 Olympic Games. According to the daily forecast results for the entire duration of 2010, the model shows good performance in the PM 10 forecast on most days but clearly underestimates PM 10 concentration during some air pollution episodes. A typical air pollution episode from 11–20 January 2010 was chosen, in which the observed air pollution index of particulate matter (PM 10 -API) reached 180 while the forecast PM 10 -API was about 100. In this study, three numerical methods are used for model improvement: first, by enhancing the inner domain with 3 km resolution grids, and expanding the coverage from only Beijing to an area including Beijing and its surrounding cities; second, by adding more regional point source emissions located at Baoding, Landfang and Tangshan, to the south and east of Beijing; third, by updating the area source emissions, including the regional area source emissions in Baoding and Tangshan and the local village/town-level area source emissions in Beijing. The last two methods are combined as the updated emissions method. According to the model sensitivity testing results by the CMAQ model, the updated emissions method and expanded model domain method can both improve the model performance separately. But the expanded model domain method has better ability to capture the peak values of PM 10 than the updated emissions method due to better reproduction of the pollution transport process in this episode. As a result, the hindcast results ("New(CMAQ)"), which are driven by the updated emissions in the expanded model domain, show a much better model performance in the national standard station-averaged PM 10 -API. The daily hindcast PM 10 -API reaches 180 and is much closer to the observed value, and has a high correlation coefficient of 0.93. The correlation coefficient of the PM 10 -API in all Beijing MEMC stations between the hindcast and observation is 0.82, clearly higher than the forecast 0.54. The FAC2 increases from 56% in the forecast to 84% in the hindcast, and the NMSE decreases from 0.886 to 0.196. The hindcast also has better model performance in PM 10 hourly concentrations during the typical air pollution episode. The updated emissions method accompanied by a suitable domain in this study improved the model performance for the Beijing area significantly.

Description: C-Coupler1: a Chinese community coupler for Earth system modeling Geoscientific Model Development, 7, 2281-2302, 2014 Author(s): L. Liu, G. Yang, B. Wang, C. Zhang, R. Li, Z. Zhang, Y. Ji, and L. Wang A coupler is a fundamental software tool for Earth system modeling. Targeting the requirements of 3-D coupling, high-level sharing, common model software platform and better parallel performance, we started to design and develop a community coupler (C-Coupler) from 2010 in China, and finished the first version (C-Coupler1) recently. C-Coupler1 is a parallel 3-D coupler that achieves the same (bitwise-identical) results with any number of processes. Guided by the general design of C-Coupler, C-Coupler1 enables various component models and various coupled models to be integrated on the same common model software platform to achieve a higher-level sharing, where the component models and the coupler can keep the same code version in various model configurations for simulation. Moreover, it provides the C-Coupler platform, a uniform runtime environment for operating various kinds of model simulations in the same manner. C-Coupler1 is ready for Earth system modeling, and it is publicly available. In China, there are more and more modeling groups using C-Coupler1 for the development and application of models.

Description: Simulations of direct and reflected wave trajectories for ground-based GNSS-R experiments Geoscientific Model Development, 7, 2261-2279, 2014 Author(s): N. Roussel, F. Frappart, G. Ramillien, J. Darrozes, C. Desjardins, P. Gegout, F. Pérosanz, and R. Biancale The detection of Global Navigation Satellite System (GNSS) signals that are reflected off the surface, along with the reception of direct GNSS signals, offers a unique opportunity to monitor water level variations over land and ocean. The time delay between the reception of the direct and reflected signals gives access to the altitude of the receiver over the reflecting surface. The field of view of the receiver is highly dependent on both the orbits of the GNSS satellites and the configuration of the study site geometries. A simulator has been developed to determine the location of the reflection points on the surface accurately by modeling the trajectories of GNSS electromagnetic waves that are reflected by the surface of the Earth. Only the geometric problem was considered using a specular reflection assumption. The orbit of the GNSS constellation satellites (mainly GPS, GLONASS and Galileo), and the position of a fixed receiver, are used as inputs. Four different simulation modes are proposed, depending on the choice of the Earth surface model (local plane, osculating sphere or ellipsoid) and the consideration of topography likely to cause masking effects. Angular refraction effects derived from adaptive mapping functions are also taken into account. This simulator was developed to determine where the GNSS-R receivers should be located to monitor a given study area efficiently. In this study, two test sites were considered: the first one at the top of the 65 m Cordouan lighthouse in the Gironde estuary, France, and the second one on the shore of Lake Geneva (50 m above the reflecting surface), at the border between France and Switzerland. This site is hidden by mountains in the south (orthometric altitude up to 2000 m), and overlooking the lake in the north (orthometric altitude of 370 m). For this second test site configuration, reflections occur until 560 m from the receiver. The planimetric (arc length) differences (or altimetric difference as WGS84 ellipsoid height) between the positions of the specular reflection points obtained considering the Earth's surface as an osculating sphere or as an ellipsoid were found to be on average 9 cm (or less than 1 mm) for satellite elevation angles greater than 10°, and 13.9 cm (or less than 1 mm) for satellite elevation angles between 5 and 10°. The altimetric and planimetric differences between the plane and sphere approximations are on average below 1.4 cm (or less than 1 mm) for satellite elevation angles greater than 10° and below 6.2 cm (or 2.4 mm) for satellite elevation angles between 5 and 10°. These results are the means of the differences obtained during a 24 h simulation with a complete GPS and GLONASS constellation, and thus depend on how the satellite elevation angle is sampled over the day of simulation. The simulations highlight the importance of the digital elevation model (DEM) integration: average planimetric differences (or altimetric) with and without integrating the DEM (with respect to the ellipsoid approximation) were found to be about 6.3 m (or 1.74 m), with the minimum elevation angle equal to 5°. The correction of the angular refraction due to troposphere on the signal leads to planimetric (or altimetric) differences of an approximately 18 m (or 6 cm) maximum for a 50 m receiver height above the reflecting surface, whereas the maximum is 2.9 m (or 7 mm) for a 5 m receiver height above the reflecting surface. These errors increase deeply with the receiver height above the reflecting surface. By setting it to 300 m, the planimetric errors reach 116 m, and the altimetric errors reach 32 cm for satellite elevation angles lower than 10°. The tests performed with the simulator presented in this paper highlight the importance of the choice of the Earth's representation and also the non-negligible effect of angular refraction due to the troposphere on the specular reflection point positions. Various outputs (time-varying reflection point coordinates, satellite positions and ground paths, wave trajectories, first Fresnel zones, etc.) are provided either as text or KML files for visualization with Google Earth.

Description: Variability of water mass properties in the Strait of Sicily in summer period of 1998–2013 Ocean Science, 10, 759-770, 2014 Author(s): A. Bonanno, F. Placenti, G. Basilone, R. Mifsud, S. Genovese, B. Patti, M. Di Bitetto, S. Aronica, M. Barra, G. Giacalone, R. Ferreri, I. Fontana, G. Buscaino, G. Tranchida, E. Quinci, and S. Mazzola The Strait of Sicily plays a crucial role in determining the water-mass exchanges and related properties between the western and eastern Mediterranean. Hydrographic measurements carried out from 1998 to 2013 allowed the identification of the main water masses present in the Strait of Sicily: a surface layer composed of Atlantic water (AW) flowing eastward, intermediate and deep layers mainly composed of Levantine intermediate water (LIW), and transitional eastern Mediterranean deep water (tEMDW) flowing in the opposite direction. Furthermore, for the first time, the signature of intermittent presence of western intermediate water (WIW) is also highlighted in the northwestern part of the study area (12.235° E, 37.705° N). The excellent area coverage allowed to highlight the high horizontal and vertical inter-annual variability affecting the study area and also to recognize the permanent character of the main mesoscale phenomena present in the surface water layer. Moreover, strong temperature-salinity correlations in the intermediate layer, for specific time intervals, seem to be linked to the reversal of surface circulation in the central Ionian Sea. The analysis of CTD data in deeper water layer indicates the presence of a large volume of tEMDW in the Strait of Sicily during the summers of 2006 and 2009.

Description: Qualified temperature, salinity and dissolved oxygen climatologies in a changing Adriatic Sea Ocean Science, 10, 771-797, 2014 Author(s): M. Lipizer, E. Partescano, A. Rabitti, A. Giorgetti, and A. Crise An updated climatology, based on a comprehensive data set (1911–2009) of temperature, salinity and dissolved oxygen, has been produced for the whole Adriatic Sea with the variational inverse method using the DIVA (Data-Interpolating Variational Analysis) software. Climatological maps were produced at 26 levels and validated with ordinary cross-validation and with a real vs. synthetic temperature–salinity diagram intercomparison. The concept of climatology–observation misfit (COM) has been introduced as an estimate of the physical variability associated with the climatological structures. In order to verify the temporal stability of the climatology, long-term variability has been investigated in the Middle Adriatic and the South Adriatic pits, regarded as the most suitable records of possible long-term changes. Compared with previous climatologies, this study allows a clear identification of the seasonal dynamic of the southern Adriatic, where a clear oxygen minimum is typically observed in the centre of the South Adriatic Gyre. New and better resolved features emerged from this analysis: (1) below 100 m all properties profoundly differ between the central and the southern Adriatic and seem characterized by different biogeochemical dynamics; (2) the South Adriatic Pit clearly shows the remote effects of the Eastern Mediterranean Transient, while no effect is observed in the Middle Adriatic Pit; (3) the deepest part of the southern Adriatic seems now to be significantly saltier (+0.18 psu since the period 1910–1914, with an increase of +0.018 decade −1 since the late 1940s) and warmer (+0.54 °C since 1910–1914) even though a long-term temperature trend could not be statistically demonstrated; (4) the Middle Adriatic Pit shows a long-term increase in apparent oxygen utilization (+0.77 mL L −1 since 1910–1914, with a constant increase of +0.2 mL L −1 decade −1 after the 1970s).

Description: Simulation of tropospheric chemistry and aerosols with the climate model EC-Earth Geoscientific Model Development, 7, 2435-2475, 2014 Author(s): T. P. C. van Noije, P. Le Sager, A. J. Segers, P. F. J. van Velthoven, M. C. Krol, W. Hazeleger, A. G. Williams, and S. D. Chambers We have integrated the atmospheric chemistry and transport model TM5 into the global climate model EC-Earth version 2.4. We present an overview of the TM5 model and the two-way data exchange between TM5 and the IFS model from the European Centre for Medium-Range Weather Forecasts (ECMWF), the atmospheric general circulation model of EC-Earth. In this paper we evaluate the simulation of tropospheric chemistry and aerosols in a one-way coupled configuration. We have carried out a decadal simulation for present-day conditions and calculated chemical budgets and climatologies of tracer concentrations and aerosol optical depth. For comparison we have also performed offline simulations driven by meteorological fields from ECMWF's ERA-Interim reanalysis and output from the EC-Earth model itself. Compared to the offline simulations, the online-coupled system produces more efficient vertical mixing in the troposphere, which reflects an improvement of the treatment of cumulus convection. The chemistry in the EC-Earth simulations is affected by the fact that the current version of EC-Earth produces a cold bias with too dry air in large parts of the troposphere. Compared to the ERA-Interim driven simulation, the oxidizing capacity in EC-Earth is lower in the tropics and higher in the extratropics. The atmospheric lifetime of methane in EC-Earth is 9.4 years, which is 7% longer than the lifetime obtained with ERA-Interim but remains well within the range reported in the literature. We further evaluate the model by comparing the simulated climatologies of surface radon-222 and carbon monoxide, tropospheric and surface ozone, and aerosol optical depth against observational data. The work presented in this study is the first step in the development of EC-Earth into an Earth system model with fully interactive atmospheric chemistry and aerosols.

Description: Assessing optimal set of implemented physical parameterization schemes in a multi-physics land surface model using genetic algorithm Geoscientific Model Development, 7, 2517-2529, 2014 Author(s): S. Hong, X. Yu, S. K. Park, Y.-S. Choi, and B. Myoung Optimization of land surface models has been challenging due to the model complexity and uncertainty. In this study, we performed scheme-based model optimizations by designing a framework for coupling "the micro-genetic algorithm" (micro-GA) and "the Noah land surface model with multiple physics options" (Noah-MP). Micro-GA controls the scheme selections among eight different land surface parameterization categories, each containing 2–4 schemes, in Noah-MP in order to extract the optimal scheme combination that achieves the best skill score. This coupling framework was successfully applied to the optimizations of evapotranspiration and runoff simulations in terms of surface water balance over the Han River basin in Korea, showing outstanding speeds in searching for the optimal scheme combination. Taking advantage of the natural selection mechanism in micro-GA, we explored the model sensitivity to scheme selections and the scheme interrelationship during the micro-GA evolution process. This information is helpful for better understanding physical parameterizations and hence it is expected to be effectively used for further optimizations with uncertain parameters in a specific set of schemes.

Description: Evaluation of the eastern equatorial Pacific SST seasonal cycle in CMIP5 models Ocean Science, 10, 837-843, 2014 Author(s): Z. Y. Song, H. L. Liu, C. Z. Wang, L. P. Zhang, and F. L. Qiao The annual cycle of sea surface temperature (SST) in the eastern equatorial Pacific (EEP) has the largest amplitude in the tropical oceans, but it is poorly represented in the coupled general circulation models (CGCMs) of the Coupled Model Intercomparison Project Phase 3 (CMIP3). In this study, 18 models from CMIP5 are evaluated in terms of their capability of simulating the SST annual cycle in the EEP. Fourteen models are able to simulate the annual cycle fairly well, which suggests that the performances of CGCMs have been improved. The results of multi-model ensemble (MME) mean show that CMIP5 CGCMs can capture the annual cycle signal in the EEP with a correlation coefficient up to 0.9. Moreover, the CMIP5 models can simulate the westward propagation character of the EEP SST – in particular, EEP region 1 (EP1) near the eastern coast leading EEP region 2 (EP2) near the central equatorial Pacific by 1 to 2 months in spring. However, the models fail to reproduce the in-phase SST relationship between EP1 and EP2 in August and September. For amplitude simulations, the model SST in EP1 shows weaker seasonal variation than the observations due to the large warm SST biases from the southeastern tropical Pacific in the boreal autumn. In EP2, the simulated SST amplitudes are nearly the same as the observations while there is the presence of a quasi-constant cold bias associated with poor cold tongue simulation in the CGCMs. To improve CGCM simulation of a realistic SST seasonal cycle, local and remote SST biases that exist in both CMIP3 and CMIP5 CGCMs must be resolved at least for simulating the SSTs in the central equatorial Pacific and the southeastern tropical Pacific.

Description: Development of a variational flux inversion system (INVICAT v1.0) using the TOMCAT chemical transport model Geoscientific Model Development, 7, 2485-2500, 2014 Author(s): C. Wilson, M. P. Chipperfield, M. Gloor, and F. Chevallier We present a new variational inverse transport model, named INVICAT (v1.0), which is based on the global chemical transport model TOMCAT, and a new corresponding adjoint transport model, ATOMCAT. The adjoint model is constructed through manually derived discrete adjoint algorithms, and includes subroutines governing advection, convection and boundary layer mixing, all of which are linear in the TOMCAT model. We present extensive testing of the adjoint and inverse models, and also thoroughly assess the accuracy of the TOMCAT forward model's representation of atmospheric transport through comparison with observations of the atmospheric trace gas SF 6 . The forward model is shown to perform well in comparison with these observations, capturing the latitudinal gradient and seasonal cycle of SF 6 to within acceptable tolerances. The adjoint model is shown, through numerical identity tests and novel transport reciprocity tests, to be extremely accurate in comparison with the forward model, with no error shown at the level of accuracy possible with our machines. The potential for the variational system as a tool for inverse modelling is investigated through an idealised test using simulated observations, and the system demonstrates an ability to retrieve known fluxes from a perturbed state accurately. Using basic off-line chemistry schemes, the inverse model is ready and available to perform inversions of trace gases with relatively simple chemical interactions, including CH 4 , CO 2 and CO.

Description: Development of a semi-parametric PAR (Photosynthetically Active Radiation) partitioning model for the United States, version 1.0 Geoscientific Model Development, 7, 2477-2484, 2014 Author(s): J. C. Kathilankal, T. L. O'Halloran, A. Schmidt, C. V. Hanson, and B. E. Law A semi-parametric PAR diffuse radiation model was developed using commonly measured climatic variables from 108 site-years of data from 17 AmeriFlux sites. The model has a logistic form and improves upon previous efforts using a larger data set and physically viable climate variables as predictors, including relative humidity, clearness index, surface albedo and solar elevation angle. Model performance was evaluated by comparison with a simple cubic polynomial model developed for the PAR spectral range. The logistic model outperformed the polynomial model with an improved coefficient of determination and slope relative to measured data (logistic: R 2 = 0.76; slope = 0.76; cubic: R 2 = 0.73; slope = 0.72), making this the most robust PAR-partitioning model for the United States currently available.

Description: A method to generate fully multi-scale optimal interpolation by combining efficient single process analyses, illustrated by a DINEOF analysis spiced with a local optimal interpolation Ocean Science, 10, 845-862, 2014 Author(s): J.-M. Beckers, A. Barth, I. Tomazic, and A. Alvera-Azcárate We present a method in which the optimal interpolation of multi-scale processes can be expanded into a succession of simpler interpolations. First, we prove how the optimal analysis of a superposition of two processes can be obtained by different mathematical formulations involving iterations and analysis focusing on a single process. From the different mathematical equivalent formulations, we then select the most efficient ones by analyzing the behavior of the different possibilities in a simple and well-controlled test case. The clear guidelines deduced from this experiment are then applied to a real situation in which we combine large-scale analysis of hourly Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite images using data interpolating empirical orthogonal functions (DINEOF) with a local optimal interpolation using a Gaussian covariance. It is shown that the optimal combination indeed provides the best reconstruction and can therefore be exploited to extract the maximum amount of useful information from the original data.

Description: Effects of bottom topography on dynamics of river discharges in tidal regions: case study of twin plumes in Taiwan Strait Ocean Science, 10, 863-879, 2014 Author(s): K. A. Korotenko, A. A. Osadchiev, P. O. Zavialov, R.-C. Kao, and C.-F. Ding The Princeton Ocean Model (POM) is used to investigate the intratidal variability of currents and turbulent mixing and their impact on the characteristics and evolution of the plumes of two neighbouring rivers, the Zhuoshui River and the Wu River, at the central eastern coast of Taiwan Strait. The two estuaries are located close to each other and their conditions are similar in many respects, and yet the two plumes exhibit significantly different behaviour. We explain this through differences of the bottom topography in the areas adjacent to the two river mouths. The Zhuoshui River runs into a shallow area that is permanently exposed to strong tidal mixing, while the Wu River mouth is located in a deeper, stratified area outside the region of intense mixing. This destruction of the plume by tidal mixing is confirmed by the results of numerical modeling with POM. The spatial and temporal variability of turbulent kinetic energy, the rates of its production by shear and destruction rate by buoyancy in the study, as well as the horizontal diffusivity, are analysed with the emphasis given to the dependence of the turbulence parameters on the bottom topography on the one hand and their influence on the river plumes on the other. The results of the study support the central hypothesis of this paper: the dynamic behaviours of the Zhuoshui and Wu plumes are different because their evolution occurs under different regimes of bottom-generated turbulent mixing. Further, we use a Lagrangian particle tracking model in combination with POM to investigate the effect of the tidal wetting-and-drying (WAD) near the Zhuoshui River estuary, and demonstrate that WAD leads to significant reduction of the plume extent and surface salinity deficit near the river mouth. We use observational data from a short field campaign in the study area to tune and validate the model experiments.

Description: Corrigendum to "Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia" published in Geosci. Model Dev., 7, 2121–2140, 2014 Geoscientific Model Development, 7, 2501-2501, 2014 Author(s): J. Kala, J. P. Evans, A. J. Pitman, C. B. Schaaf, M. Decker, C. Carouge, D. Mocko, and Q. Sun No abstract available.

Description: Sensitivity of aerosol radiative effects to different mixing assumptions in the AEROPT 1.0 submodel of the EMAC atmospheric-chemistry–climate model Geoscientific Model Development, 7, 2503-2516, 2014 Author(s): K. Klingmüller, B. Steil, C. Brühl, H. Tost, and J. Lelieveld The modelling of aerosol radiative forcing is a major cause of uncertainty in the assessment of global and regional atmospheric energy budgets and climate change. One reason is the strong dependence of the aerosol optical properties on the mixing state of aerosol components, such as absorbing black carbon and, predominantly scattering sulfates. Using a new column version of the aerosol optical properties and radiative-transfer code of the ECHAM/MESSy atmospheric-chemistry–climate model (EMAC), we study the radiative transfer applying various mixing states. The aerosol optics code builds on the AEROPT (AERosol OPTical properties) submodel, which assumes homogeneous internal mixing utilising the volume average refractive index mixing rule. We have extended the submodel to additionally account for external mixing, partial external mixing and multilayered particles. Furthermore, we have implemented the volume average dielectric constant and Maxwell Garnett mixing rule. We performed regional case studies considering columns over China, India and Africa, corroborating much stronger absorption by internal than external mixtures. Well-mixed aerosol is a good approximation for particles with a black-carbon core, whereas particles with black carbon at the surface absorb significantly less. Based on a model simulation for the year 2005, we calculate that the global aerosol direct radiative forcing for homogeneous internal mixing differs from that for external mixing by about 0.5 W m −2 .

Description: Implementation and scaling of the fully coupled Terrestrial Systems Modeling Platform (TerrSysMP v1.0) in a massively parallel supercomputing environment – a case study on JUQUEEN (IBM Blue Gene/Q) Geoscientific Model Development, 7, 2531-2543, 2014 Author(s): F. Gasper, K. Goergen, P. Shrestha, M. Sulis, J. Rihani, M. Geimer, and S. Kollet Continental-scale hyper-resolution simulations constitute a grand challenge in characterizing nonlinear feedbacks of states and fluxes of the coupled water, energy, and biogeochemical cycles of terrestrial systems. Tackling this challenge requires advanced coupling and supercomputing technologies for earth system models that are discussed in this study, utilizing the example of the implementation of the newly developed Terrestrial Systems Modeling Platform (TerrSysMP v1.0) on JUQUEEN (IBM Blue Gene/Q) of the Jülich Supercomputing Centre, Germany. The applied coupling strategies rely on the Multiple Program Multiple Data (MPMD) paradigm using the OASIS suite of external couplers, and require memory and load balancing considerations in the exchange of the coupling fields between different component models and the allocation of computational resources, respectively. Using the advanced profiling and tracing tool Scalasca to determine an optimum load balancing leads to a 19% speedup. In massively parallel supercomputer environments, the coupler OASIS-MCT is recommended, which resolves memory limitations that may be significant in case of very large computational domains and exchange fields as they occur in these specific test cases and in many applications in terrestrial research. However, model I/O and initialization in the petascale range still require major attention, as they constitute true big data challenges in light of future exascale computing resources. Based on a factor-two speedup due to compiler optimizations, a refactored coupling interface using OASIS-MCT and an optimum load balancing, the problem size in a weak scaling study can be increased by a factor of 64 from 512 to 32 768 processes while maintaining parallel efficiencies above 80% for the component models.

Description: On linking an Earth system model to the equilibrium carbon representation of an economically optimizing land use model Geoscientific Model Development, 7, 2545-2555, 2014 Author(s): B. Bond-Lamberty, K. Calvin, A. D. Jones, J. Mao, P. Patel, X. Y. Shi, A. Thomson, P. Thornton, and Y. Zhou Human activities are significantly altering biogeochemical cycles at the global scale, and the scope of these activities will change with both future climate and socioeconomic decisions. This poses a significant challenge for Earth system models (ESMs), which can incorporate land use change as prescribed inputs but do not actively simulate the policy or economic forces that drive land use change. One option to address this problem is to couple an ESM with an economically oriented integrated assessment model, but this is challenging because of the radically different goals and underpinnings of each type of model. This study describes the development and testing of a coupling between the terrestrial carbon cycle of an ESM (CESM) and an integrated assessment (GCAM) model, focusing on how CESM climate effects on the carbon cycle could be shared with GCAM. We examine the best proxy variables to share between the models, and we quantify how carbon flux changes driven by climate, CO 2 fertilization, and land use changes (e.g., deforestation) can be distinguished from each other by GCAM. The net primary production and heterotrophic respiration outputs of the Community Land Model (CLM), the land component of CESM, were found to be the most robust proxy variables by which to recalculate GCAM's assumptions of equilibrium ecosystem steady-state carbon. Carbon cycle effects of land use change are spatially limited relative to climate effects, and thus we were able to distinguish these effects successfully in the model coupling, passing only the latter to GCAM. This paper does not present results of a fully coupled simulation but shows, using a series of offline CLM simulations and an additional idealized Monte Carlo simulation, that our CESM–GCAM proxy variables reflect the phenomena that we intend and do not contain erroneous signals due to land use change. By allowing climate effects from a full ESM to dynamically modulate the economic and policy decisions of an integrated assessment model, this work will help link these models in a robust and flexible framework capable of examining two-way interactions between human and Earth system processes.

Description: A scale-dependent blending scheme for WRFDA: impact on regional weather forecasting Geoscientific Model Development, 7, 1819-1828, 2014 Author(s): H. Wang, X.-Y. Huang, D. Xu, and J. Liu Due to limitation of the domain size and limited observations used in regional data assimilation and forecasting systems, regional forecasts suffer a general deficiency in effectively representing large-scale features such as those in global analyses and forecasts. In this paper, a scale-dependent blending scheme using a low-pass Raymond tangent implicit filter was implemented in the Data Assimilation system of the Weather Research and Forecasting model (WRFDA) to reintroduce large-scale weather features from global model analysis into the WRFDA analysis. The impact of the blending method on regional forecasts was assessed by conducting full cycle data assimilation and forecasting experiments for a 2-week-long period in September 2012. It is found that there are obvious large-scale forecast errors in the regional WRFDA system running in full cycle mode without the blending scheme. The scale-dependent blending scheme can efficiently reintroduce the large-scale information from National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analyses, and keep small-scale information from WRF analyses. The blending scheme is shown to reduce analysis and forecasting error of wind, temperature and humidity up to 24 h compared to the full cycle experiments without blending. It is also shown to increase precipitation prediction skills in the first 6 h forecasts.

Description: Optimization of a prognostic biosphere model for terrestrial biomass and atmospheric CO 2 variability Geoscientific Model Development, 7, 1829-1840, 2014 Author(s): M. Saito, A. Ito, and S. Maksyutov This study investigates the capacity of a prognostic biosphere model to simulate global variability in atmospheric CO 2 concentrations and vegetation carbon dynamics under current environmental conditions. Global data sets of atmospheric CO 2 concentrations, above-ground biomass (AGB), and net primary productivity (NPP) in terrestrial vegetation were assimilated into the biosphere model using an inverse modeling method combined with an atmospheric transport model. In this process, the optimal physiological parameters of the biosphere model were estimated by minimizing the misfit between observed and modeled values, and parameters were generated to characterize various biome types. Results obtained using the model with the optimized parameters correspond to the observed seasonal variations in CO 2 concentration and their annual amplitudes in both the Northern and Southern Hemispheres. In simulating the mean annual AGB and NPP, the model shows improvements in estimating the mean magnitudes and probability distributions for each biome, as compared with results obtained using prior simulation parameters. However, the model is less efficient in its simulation of AGB for forest type biomes. This misfit suggests that more accurate values of input parameters, specifically, grid mean AGB values and seasonal variabilities in physiological parameters, are required to improve the performance of the simulation model.

Description: An orthogonal terrain-following coordinate and its preliminary tests using 2-D idealized advection experiments Geoscientific Model Development, 7, 1767-1778, 2014 Author(s): Y. Li, B. Wang, D. Wang, J. Li, and L. Dong We have designed an orthogonal curvilinear terrain-following coordinate (the orthogonal σ coordinate, or the OS coordinate) to reduce the advection errors in the classic σ coordinate. First, we rotate the basis vectors of the z coordinate in a specific way in order to obtain the orthogonal, terrain-following basis vectors of the OS coordinate, and then add a rotation parameter b to each rotation angle to create the smoother vertical levels of the OS coordinate with increasing height. Second, we solve the corresponding definition of each OS coordinate through its basis vectors; and then solve the 3-D coordinate surfaces of the OS coordinate numerically, therefore the computational grids created by the OS coordinate are not exactly orthogonal and its orthogonality is dependent on the accuracy of a numerical method. Third, through choosing a proper b , we can significantly smooth the vertical levels of the OS coordinate over a steep terrain, and, more importantly, we can create the orthogonal, terrain-following computational grids in the vertical through the orthogonal basis vectors of the OS coordinate, which can reduce the advection errors better than the corresponding hybrid σ coordinate. However, the convergence of the grid lines in the OS coordinate over orography restricts the time step and increases the numerical errors. We demonstrate the advantages and the drawbacks of the OS coordinate relative to the hybrid σ coordinate using two sets of 2-D linear advection experiments.

Description: A flexible three-dimensional stratocumulus, cumulus and cirrus cloud generator (3DCLOUD) based on drastically simplified atmospheric equations and the Fourier transform framework Geoscientific Model Development, 7, 1779-1801, 2014 Author(s): F. Szczap, Y. Gour, T. Fauchez, C. Cornet, T. Faure, O. Jourdan, G. Penide, and P. Dubuisson The 3DCLOUD algorithm for generating stochastic three-dimensional (3-D) cloud fields is described in this paper. The generated outputs are 3-D optical depth (τ) for stratocumulus and cumulus fields and 3-D ice water content (IWC) for cirrus clouds. This model is designed to generate cloud fields that share some statistical properties observed in real clouds such as the inhomogeneity parameter ρ (standard deviation normalized by the mean of the studied quantity), the Fourier spectral slope β close to −5/3 between the smallest scale of the simulation to the outer L out (where the spectrum becomes flat). Firstly, 3DCLOUD assimilates meteorological profiles (humidity, pressure, temperature and wind velocity). The cloud coverage C , defined by the user, can also be assimilated, but only for stratocumulus and cumulus regime. 3DCLOUD solves drastically simplified basic atmospheric equations, in order to simulate 3-D cloud structures of liquid or ice water content. Secondly, the Fourier filtering method is used to constrain the intensity of ρ, β, L out and the mean of τ or IWC of these 3-D cloud structures. The 3DCLOUD model was developed to run on a personal computer under Matlab environment with the Matlab statistics toolbox. It is used to study 3-D interactions between cloudy atmosphere and radiation.

Description: Formulation, calibration and validation of the DAIS model (version 1), a simple Antarctic ice sheet model sensitive to variations of sea level and ocean subsurface temperature Geoscientific Model Development, 7, 1803-1818, 2014 Author(s): G. Shaffer The DCESS (Danish Center for Earth System Science) Antarctic Ice Sheet (DAIS) model is presented. Model hindcasts of Antarctic ice sheet (AIS) sea level equivalent are forced by reconstructed Antarctic temperatures, global mean sea level and high-latitude, ocean subsurface temperatures, the latter calculated using the DCESS model forced by reconstructed global mean atmospheric temperatures. The model is calibrated by comparing such hindcasts for different model configurations with paleoreconstructions of AIS sea level equivalent from the last interglacial, the last glacial maximum and the mid-Holocene. The calibrated model is then validated against present estimates of the rate of AIS ice loss. It is found that a high-order dependency of ice flow at the grounding line on water depth there is needed to capture the observed response of the AIS at ice age terminations. Furthermore, it is found that a dependency of this ice flow on ocean subsurface temperature by way of ice shelf demise and a resulting buttressing decrease is needed to explain the contribution of the AIS to global mean sea level rise at the last interglacial. When forced and calibrated in this way, model hindcasts of the rate of present-day AIS ice loss agree with recent, data-based estimates of this ice loss rate.

Description: FLEXINVERT: an atmospheric Bayesian inversion framework for determining surface fluxes of trace species using an optimized grid Geoscientific Model Development, 7, 2223-2242, 2014 Author(s): R. L. Thompson and A. Stohl We present a new modular Bayesian inversion framework, called FLEXINVERT, for estimating the surface fluxes of atmospheric trace species. FLEXINVERT can be applied to determine the spatio-temporal flux distribution of any species for which the atmospheric loss (if any) can be described as a linear process and can be used on continental to regional and even local scales with little or no modification. The relationship between changes in atmospheric mixing ratios and fluxes (the so-called source–receptor relationship) is described by a Lagrangian Particle Dispersion Model (LPDM) run in a backwards-in-time mode. In this study, we use FLEXPART but any LPDM could be used. The framework determines the fluxes on a nested grid of variable resolution, which is optimized based on the source–receptor relationships for the given observation network. Background mixing ratios are determined by coupling FLEXPART to the output of a global Eulerian model (or alternatively, from the observations themselves) and are also optionally optimized in the inversion. Spatial and temporal error correlations in the fluxes are taken into account using a simple model of exponential decay with space and time and, additionally, the aggregation error from the variable grid is accounted for. To demonstrate the use of FLEXINVERT, we present one case study in which methane fluxes are estimated in Europe in 2011 and compare the results to those of an independent inversion ensemble.

Description: The coupled atmosphere–chemistry–ocean model SOCOL-MPIOM Geoscientific Model Development, 7, 2157-2179, 2014 Author(s): S. Muthers, J. G. Anet, A. Stenke, C. C. Raible, E. Rozanov, S. Brönnimann, T. Peter, F. X. Arfeuille, A. I. Shapiro, J. Beer, F. Steinhilber, Y. Brugnara, and W. Schmutz The newly developed atmosphere–ocean–chemistry–climate model SOCOL-MPIOM is presented by demonstrating the influence of chemistry–climate interactions on the climate state and the variability. Therefore, we compare pre-industrial control simulations with (CHEM) and without (NOCHEM) interactive chemistry. In general, the influence of the chemistry on the mean state and the variability is small and mainly restricted to the stratosphere and mesosphere. The atmospheric dynamics mainly differ in polar regions, with slightly stronger polar vortices in the austral and boreal winter, respectively. The strengthening of the vortex is related to larger stratospheric temperature gradients, which are attributed to a parameterisation of the absorption of ozone and oxygen in different wavelength intervals, which is considered in the version with interactive chemistry only. A second reason for the temperature differences between CHEM and NOCHEM is related to diurnal variations in the ozone concentrations in the higher atmosphere, which are missing in NOCHEM. Furthermore, stratospheric water vapour concentrations substantially differ between the two experiments, but their effect on temperature is small. In both setups, the simulated intensity and variability of the northern polar vortex is inside the range of present-day observations. Additionally, the performance of SOCOL-MPIOM under changing external forcings is assessed for the period 1600–2000 using an ensemble of simulations. In the industrial period from 1850 onward SOCOL-MPIOM overestimates the global mean surface air temperature increase in comparison to observational data sets. Sensitivity simulations show that this overestimation can be attributed to a combination of factors: the solar forcing reconstruction, the simulated ozone changes, and incomplete aerosol effects and land use changes.

Description: Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts Geoscientific Model Development, 7, 2613-2638, 2014 Author(s): E. W. Blockley, M. J. Martin, A. J. McLaren, A. G. Ryan, J. Waters, D. J. Lea, I. Mirouze, K. A. Peterson, A. Sellar, and D. Storkey The Forecast Ocean Assimilation Model (FOAM) is an operational ocean analysis and forecast system run daily at the Met Office. FOAM provides modelling capability in both deep ocean and coastal shelf sea regimes using the NEMO (Nucleus for European Modelling of the Ocean) ocean model as its dynamical core. The FOAM Deep Ocean suite produces analyses and 7-day forecasts of ocean tracers, currents and sea ice for the global ocean at 1/4° resolution. Satellite and in situ observations of temperature, salinity, sea level anomaly and sea ice concentration are assimilated by FOAM each day over a 48 h observation window. The FOAM Deep Ocean configurations have recently undergone a major upgrade which has involved the implementation of a new variational, first guess at appropriate time (FGAT) 3D-Var, assimilation scheme (NEMOVAR); coupling to a different, multi-thickness-category, sea ice model (CICE); the use of coordinated ocean-ice reference experiment (CORE) bulk formulae to specify the surface boundary condition; and an increased vertical resolution for the global model. In this paper the new FOAM Deep Ocean system is introduced and details of the recent changes are provided. Results are presented from 2-year reanalysis integrations of the Global FOAM configuration including an assessment of short-range ocean forecast accuracy. Comparisons are made with both the previous FOAM system and a non-assimilative FOAM system. Assessments reveal considerable improvements in the new system to the near-surface ocean and sea ice fields. However there is some degradation to sub-surface tracer fields and in equatorial regions which highlights specific areas upon which to focus future improvements.

Description: On the computation of planetary boundary-layer height using the bulk Richardson number method Geoscientific Model Development, 7, 2599-2611, 2014 Author(s): Y. Zhang, Z. Gao, D. Li, Y. Li, N. Zhang, X. Zhao, and J. Chen Experimental data from four field campaigns are used to explore the variability of the bulk Richardson number of the entire planetary boundary layer (PBL), Ri bc , which is a key parameter for calculating the PBL height (PBLH) in numerical weather and climate models with the bulk Richardson number method. First, the PBLHs of three different thermally stratified boundary layers (i.e., strongly stable boundary layers, weakly stable boundary layers, and unstable boundary layers) from the four field campaigns are determined using the turbulence method, the potential temperature gradient method, the low-level jet method, and the modified parcel method. Then for each type of boundary layer, an optimal Ri bc is obtained through linear fitting and statistical error minimization methods so that the bulk Richardson method with this optimal Ri bc yields similar estimates of PBLHs as the methods mentioned above. We find that the optimal Ri bc increases as the PBL becomes more unstable: 0.24 for strongly stable boundary layers, 0.31 for weakly stable boundary layers, and 0.39 for unstable boundary layers. Compared with previous schemes that use a single value of Ri bc in calculating the PBLH for all types of boundary layers, the new values of Ri bc proposed by this study yield more accurate estimates of PBLHs.

Description: Model–data fusion across ecosystems: from multisite optimizations to global simulations Geoscientific Model Development, 7, 2581-2597, 2014 Author(s): S. Kuppel, P. Peylin, F. Maignan, F. Chevallier, G. Kiely, L. Montagnani, and A. Cescatti This study uses a variational data assimilation framework to simultaneously constrain a global ecosystem model with eddy covariance measurements of daily net ecosystem exchange (NEE) and latent heat (LE) fluxes from a large number of sites grouped in seven plant functional types (PFTs). It is an attempt to bridge the gap between the numerous site-specific parameter optimization works found in the literature and the generic parameterization used by most land surface models within each PFT. The present multisite approach allows deriving PFT-generic sets of optimized parameters enhancing the agreement between measured and simulated fluxes at most of the sites considered, with performances often comparable to those of the corresponding site-specific optimizations. Besides reducing the PFT-averaged model–data root-mean-square difference (RMSD) and the associated daily output uncertainty, the optimization improves the simulated CO 2 balance at tropical and temperate forests sites. The major site-level NEE adjustments at the seasonal scale are reduced amplitude in C3 grasslands and boreal forests, increased seasonality in temperate evergreen forests, and better model–data phasing in temperate deciduous broadleaf forests. Conversely, the poorer performances in tropical evergreen broadleaf forests points to deficiencies regarding the modelling of phenology and soil water stress for this PFT. An evaluation with data-oriented estimates of photosynthesis (GPP – gross primary productivity) and ecosystem respiration ( R eco ) rates indicates distinctively improved simulations of both gross fluxes. The multisite parameter sets are then tested against CO 2 concentrations measured at 53 locations around the globe, showing significant adjustments of the modelled seasonality of atmospheric CO 2 concentration, whose relevance seems PFT-dependent, along with an improved interannual variability. Lastly, a global-scale evaluation with remote sensing NDVI (normalized difference vegetation index) measurements indicates an improvement of the simulated seasonal variations of the foliar cover for all considered PFTs.

Description: A skill assessment of the biogeochemical model REcoM2 coupled to the Finite Element Sea Ice–Ocean Model (FESOM 1.3) Geoscientific Model Development, 7, 2769-2802, 2014 Author(s): V. Schourup-Kristensen, D. Sidorenko, D. A. Wolf-Gladrow, and C. Völker In coupled biogeochmical–ocean models, the choice of numerical schemes in the ocean circulation component can have a large influence on the distribution of the biological tracers. Biogeochemical models are traditionally coupled to ocean general circulation models (OGCMs), which are based on dynamical cores employing quasi-regular meshes, and therefore utilize limited spatial resolution in a global setting. An alternative approach is to use an unstructured-mesh ocean model, which allows variable mesh resolution. Here, we present initial results of a coupling between the Finite Element Sea Ice–Ocean Model (FESOM) and the biogeochemical model REcoM2 (Regulated Ecosystem Model 2), with special focus on the Southern Ocean. Surface fields of nutrients, chlorophyll a and net primary production (NPP) were compared to available data sets with a focus on spatial distribution and seasonal cycle. The model produces realistic spatial distributions, especially regarding NPP and chlorophyll a , whereas the iron concentration becomes too low in the Pacific Ocean. The modelled NPP is 32.5 Pg C yr −1 and the export production 6.1 Pg C yr −1 , which is lower than satellite-based estimates, mainly due to excessive iron limitation in the Pacific along with too little coastal production. The model performs well in the Southern Ocean, though the assessment here is hindered by the lower availability of observations. The modelled NPP is 3.1 Pg C yr −1 in the Southern Ocean and the export production 1.1 Pg C yr −1 . All in all, the combination of a circulation model on an unstructured grid with a biogeochemical–ocean model shows similar performance to other models at non-eddy-permitting resolution. It is well suited for studies of the Southern Ocean, but on the global scale deficiencies in the Pacific Ocean would have to be taken into account.

Description: The spectral element method (SEM) on variable-resolution grids: evaluating grid sensitivity and resolution-aware numerical viscosity Geoscientific Model Development, 7, 2803-2816, 2014 Author(s): O. Guba, M. A. Taylor, P. A. Ullrich, J. R. Overfelt, and M. N. Levy We evaluate the performance of the Community Atmosphere Model's (CAM) spectral element method on variable-resolution grids using the shallow-water equations in spherical geometry. We configure the method as it is used in CAM, with dissipation of grid scale variance, implemented using hyperviscosity. Hyperviscosity is highly scale selective and grid independent, but does require a resolution-dependent coefficient. For the spectral element method with variable-resolution grids and highly distorted elements, we obtain the best results if we introduce a tensor-based hyperviscosity with tensor coefficients tied to the eigenvalues of the local element metric tensor. The tensor hyperviscosity is constructed so that, for regions of uniform resolution, it matches the traditional constant-coefficient hyperviscosity. With the tensor hyperviscosity, the large-scale solution is almost completely unaffected by the presence of grid refinement. This later point is important for climate applications in which long term climatological averages can be imprinted by stationary inhomogeneities in the truncation error. We also evaluate the robustness of the approach with respect to grid quality by considering unstructured conforming quadrilateral grids generated with a well-known grid-generating toolkit and grids generated by SQuadGen, a new open source alternative which produces lower valence nodes.

Description: Characterisation and quantification of regional diurnal SST cycles from SEVIRI Ocean Science, 10, 745-758, 2014 Author(s): I. Karagali and J. L. Høyer Hourly SST (sea surface temperature) fields from the geostationary Spinning Enhanced Visible and Infrared Imager (SEVIRI) offer a unique opportunity for the characterisation and quantification of the diurnal cycle of SST in the Atlantic Ocean, the Mediterranean Sea and the northern European shelf seas. Six years of SST fields from SEVIRI are validated against the Advanced Along-Track Scanning Radiometer (AATSR) Reprocessed for Climate (ARC) data set. The overall SEVIRI–AATSR bias is −0.07 K, and the standard deviation is 0.51 K, based on more than 53 × 10 6 match-ups. Identification of the diurnal signal requires an SST foundation temperature field representative of well-mixed conditions which typically occur at night-time or under moderate and strong winds. Such fields are generated from the SEVIRI archive and are validated against pre-dawn SEVIRI SSTs and night-time SSTs from drifting buoys. The different methodologies tested for the foundation temperature fields reveal variability introduced by averaging night-time SSTs over many days compared to single-day, pre-dawn values. Diurnal warming is most pronounced in the Mediterranean and Baltic seas while weaker diurnal signals are found in the tropics. Longer diurnal warming duration is identified in the high latitudes compared to the tropics. The maximum monthly mean diurnal signal can be up to 0.5 K in specific regions.

Description: Modeling radiocarbon dynamics in soils: SoilR version 1.1 Geoscientific Model Development, 7, 1919-1931, 2014 Author(s): C. A. Sierra, M. Müller, and S. E. Trumbore Radiocarbon is an important tracer of the global carbon cycle that helps to understand carbon dynamics in soils. It is useful to estimate rates of organic matter cycling as well as the mean residence or transit time of carbon in soils. We included a set of functions to model the fate of radiocarbon in soil organic matter within the SoilR package for the R environment for computing. Here we present the main system equations and functions to calculate the transfer and release of radiocarbon from different soil organic matter pools. Similarly, we present functions to calculate the mean transit time for different pools and the entire soil system. This new version of SoilR also includes a group of data sets describing the amount of radiocarbon in the atmosphere over time, data necessary to estimate the incorporation of radiocarbon in soils. Also, we present examples on how to obtain parameters of pool-based models from radiocarbon data using inverse parameter estimation. This implementation is general enough so it can also be used to trace the incorporation of radiocarbon in other natural systems that can be represented as linear dynamical systems.

Description: A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions Geoscientific Model Development, 7, 1901-1918, 2014 Author(s): J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders, and S. A. McKenna The characterization of fossil-fuel CO 2 (ffCO 2 ) emissions is paramount to carbon cycle studies, but the use of atmospheric inverse modeling approaches for this purpose has been limited by the highly heterogeneous and non-Gaussian spatiotemporal variability of emissions. Here we explore the feasibility of capturing this variability using a low-dimensional parameterization that can be implemented within the context of atmospheric CO 2 inverse problems aimed at constraining regional-scale emissions. We construct a multiresolution (i.e., wavelet-based) spatial parameterization for ffCO 2 emissions using the Vulcan inventory, and examine whether such a~parameterization can capture a realistic representation of the expected spatial variability of actual emissions. We then explore whether sub-selecting wavelets using two easily available proxies of human activity (images of lights at night and maps of built-up areas) yields a low-dimensional alternative. We finally implement this low-dimensional parameterization within an idealized inversion, where a sparse reconstruction algorithm, an extension of stagewise orthogonal matching pursuit (StOMP), is used to identify the wavelet coefficients. We find that (i) the spatial variability of fossil-fuel emission can indeed be represented using a low-dimensional wavelet-based parameterization, (ii) that images of lights at night can be used as a proxy for sub-selecting wavelets for such analysis, and (iii) that implementing this parameterization within the described inversion framework makes it possible to quantify fossil-fuel emissions at regional scales if fossil-fuel-only CO 2 observations are available.

Description: Direct numerical simulations of particle-laden density currents with adaptive, discontinuous finite elements Geoscientific Model Development, 7, 1945-1960, 2014 Author(s): S. D. Parkinson, J. Hill, M. D. Piggott, and P. A. Allison High-resolution direct numerical simulations (DNSs) are an important tool for the detailed analysis of turbidity current dynamics. Models that resolve the vertical structure and turbulence of the flow are typically based upon the Navier–Stokes equations. Two-dimensional simulations are known to produce unrealistic cohesive vortices that are not representative of the real three-dimensional physics. The effect of this phenomena is particularly apparent in the later stages of flow propagation. The ideal solution to this problem is to run the simulation in three dimensions but this is computationally expensive. This paper presents a novel finite-element (FE) DNS turbidity current model that has been built within Fluidity, an open source, general purpose, computational fluid dynamics code. The model is validated through re-creation of a lock release density current at a Grashof number of 5 × 10 6 in two and three dimensions. Validation of the model considers the flow energy budget, sedimentation rate, head speed, wall normal velocity profiles and the final deposit. Conservation of energy in particular is found to be a good metric for measuring model performance in capturing the range of dynamics on a range of meshes. FE models scale well over many thousands of processors and do not impose restrictions on domain shape, but they are computationally expensive. The use of adaptive mesh optimisation is shown to reduce the required element count by approximately two orders of magnitude in comparison with fixed, uniform mesh simulations. This leads to a substantial reduction in computational cost. The computational savings and flexibility afforded by adaptivity along with the flexibility of FE methods make this model well suited to simulating turbidity currents in complex domains.

Description: Probabilistic calibration of a Greenland Ice Sheet model using spatially resolved synthetic observations: toward projections of ice mass loss with uncertainties Geoscientific Model Development, 7, 1933-1943, 2014 Author(s): W. Chang, P. J. Applegate, M. Haran, and K. Keller Computer models of ice sheet behavior are important tools for projecting future sea level rise. The simulated modern ice sheets generated by these models differ markedly as input parameters are varied. To ensure accurate ice sheet mass loss projections, these parameters must be constrained using observational data. Which model parameter combinations make sense, given observations? Our method assigns probabilities to parameter combinations based on how well the model reproduces the Greenland Ice Sheet profile. We improve on the previous state of the art by accounting for spatial information and by carefully sampling the full range of realistic parameter combinations, using statistically rigorous methods. Specifically, we estimate the joint posterior probability density function of model parameters using Gaussian process-based emulation and calibration. This method is an important step toward calibrated probabilistic projections of ice sheet contributions to sea level rise, in that it uses data–model fusion to learn about parameter values. This information can, in turn, be used to make projections while taking into account various sources of uncertainty, including parametric uncertainty, data–model discrepancy, and spatial correlation in the error structure. We demonstrate the utility of our method using a perfect model experiment, which shows that many different parameter combinations can generate similar modern ice sheet profiles. This result suggests that the large divergence of projections from different ice sheet models is partly due to parametric uncertainty. Moreover, our method enables insight into ice sheet processes represented by parameter interactions in the model.

Description: Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models Geoscientific Model Development, 7, 1961-1977, 2014 Author(s): H. Wan, P. J. Rasch, K. Zhang, Y. Qian, H. Yan, and C. Zhao This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivity of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model, version 5. In the first example, the method is used to characterize sensitivities of the simulated clouds to time-step length. Results show that 3-day ensembles of 20 to 50 members are sufficient to reproduce the main signals revealed by traditional 5-year simulations. A nudging technique is applied to an additional set of simulations to help understand the contribution of physics–dynamics interaction to the detected time-step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol life cycle are perturbed simultaneously in order to find out which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. It turns out that 12-member ensembles of 10-day simulations are able to reveal the same sensitivities as seen in 4-year simulations performed in a previous study. In both cases, the ensemble method reduces the total computational time by a factor of about 15, and the turnaround time by a factor of several hundred. The efficiency of the method makes it particularly useful for the development of high-resolution, costly, and complex climate models.

Description: Air quality forecasts on a kilometer-scale grid over complex Spanish terrains Geoscientific Model Development, 7, 1979-1999, 2014 Author(s): M. T. Pay, F. Martínez, M. Guevara, and J. M. Baldasano The CALIOPE Air Quality Forecast System (CALIOPE-AQFS) represents the current state of the art in air quality forecasting systems of high-resolution running on high-performance computing platforms. It provides a 48 h forecast of NO 2 , O 3 , SO 2 , PM 10 , PM 2.5 , CO, and C 6 H 6 at a 4 km horizontal resolution over all of Spain, and at a 1 km horizontal resolution over the most populated areas in Spain with complex terrains (the Barcelona (BCN), Madrid (MAD) and Andalusia (AND) domains). Increased horizontal resolution from 4 to 1 km over the aforementioned domains leads to finer textures and more realistic concentration maps, which is justified by the increase in NO 2 /O 3 spatial correlation coefficients from 0.79/0.69 (4 km) to 0.81/0.73 (1 km). High-resolution emissions using the bottom-up HERMESv2.0 model are essential for improving model performance when increasing resolution on an urban scale, but it is still insufficient. Decreasing grid spacing does not reveal the expected improvement in hourly statistics, i.e., decreasing NO 2 bias by only ~ 2 μg m −3 and increasing O 3 bias by ~ 1 μg m −3 . The grid effect is less pronounced for PM 10 , because part of its mass consists of secondary aerosols, which are less affected than the locally emitted primary components by a decreasing grid size. The resolution increase has the highest impact over Barcelona, where air flow is controlled mainly by mesoscale phenomena and a lower planetary boundary layer (PBL). Despite the merits and potential uses of the 1-km simulation, the limitations of current model formulations do not allow confirmation of their expected superiority close to highly urbanized areas and large emissions sources. Future work should combine high grid resolutions with techniques that decrease subgrid variability (e.g., stochastic field methods), and also include models that consider urban morphology and thermal parameters.

Description: Corrigendum to "Probabilistic calibration of a Greenland Ice Sheet model using spatially resolved synthetic observations: toward projections of ice mass loss with uncertainties" published in Geosci. Model Dev., 7, 1933–1943, 2014 Geoscientific Model Development, 7, 2001-2001, 2014 Author(s): W. Chang, P. J. Applegate, M. Haran, and K. Keller No abstract available.

Description: Ice sheet dynamics within an earth system model: downscaling, coupling and first results Geoscientific Model Development, 7, 2003-2013, 2014 Author(s): D. Barbi, G. Lohmann, K. Grosfeld, and M. Thoma We present first results from a coupled model setup, consisting of the state-of-the-art ice sheet model RIMBAY (Revised Ice Model Based on frAnk pattYn), and the community earth system model COSMOS. We show that special care has to be provided in order to ensure physical distributions of the forcings as well as numeric stability of the involved models. We demonstrate that a suitable statistical downscaling is crucial for ice sheet stability, especially for southern Greenland where surface temperatures are close to the melting point. The downscaling of net snow accumulation is based on an empirical relationship between surface slope and rainfall. The simulated ice sheet does not show dramatic loss of ice volume for pre-industrial conditions and is comparable with present-day ice orography. A sensitivity study with high CO 2 level is used to demonstrate the effects of dynamic ice sheets onto climate compared to the standard setup with prescribed ice sheets.

Description: Description and basic evaluation of Beijing Normal University Earth System Model (BNU-ESM) version 1 Geoscientific Model Development, 7, 2039-2064, 2014 Author(s): D. Ji, L. Wang, J. Feng, Q. Wu, H. Cheng, Q. Zhang, J. Yang, W. Dong, Y. Dai, D. Gong, R.-H. Zhang, X. Wang, J. Liu, J. C. Moore, D. Chen, and M. Zhou An earth system model has been developed at Beijing Normal University (Beijing Normal University Earth System Model, BNU-ESM); the model is based on several widely evaluated climate model components and is used to study mechanisms of ocean-atmosphere interactions, natural climate variability and carbon-climate feedbacks at interannual to interdecadal time scales. In this paper, the model structure and individual components are described briefly. Further, results for the CMIP5 (Coupled Model Intercomparison Project phase 5) pre-industrial control and historical simulations are presented to demonstrate the model's performance in terms of the mean model state and the internal variability. It is illustrated that BNU-ESM can simulate many observed features of the earth climate system, such as the climatological annual cycle of surface-air temperature and precipitation, annual cycle of tropical Pacific sea surface temperature (SST), the overall patterns and positions of cells in global ocean meridional overturning circulation. For example, the El Niño-Southern Oscillation (ENSO) simulated in BNU-ESM exhibits an irregular oscillation between 2 and 5 years with the seasonal phase locking feature of ENSO. Important biases with regard to observations are presented and discussed, including warm SST discrepancies in the major upwelling regions, an equatorward drift of midlatitude westerly wind bands, and tropical precipitation bias over the ocean that is related to the double Intertropical Convergence Zone (ITCZ).

Description: A model using marginal efficiency of investment to analyze carbon and nitrogen interactions in terrestrial ecosystems (ACONITE Version 1) Geoscientific Model Development, 7, 2015-2037, 2014 Author(s): R. Q. Thomas and M. Williams Carbon (C) and nitrogen (N) cycles are coupled in terrestrial ecosystems through multiple processes including photosynthesis, tissue allocation, respiration, N fixation, N uptake, and decomposition of litter and soil organic matter. Capturing the constraint of N on terrestrial C uptake and storage has been a focus of the Earth System Modeling community. However, there is little understanding of the trade-offs and sensitivities of allocating C and N to different tissues in order to optimize the productivity of plants. Here we describe a new, simple model of ecosystem C–N cycling and interactions (ACONITE), that builds on theory related to plant economics in order to predict key ecosystem properties (leaf area index, leaf C : N, N fixation, and plant C use efficiency) based on the outcome of assessments of the marginal change in net C or N uptake associated with a change in allocation of C or N to plant tissues. We simulated and evaluated steady-state ecosystem stocks and fluxes in three different forest ecosystems types (tropical evergreen, temperate deciduous, and temperate evergreen). Leaf C : N differed among the three ecosystem types (temperate deciduous 〈 tropical evergreen 〈 temperature evergreen), a result that compared well to observations from a global database describing plant traits. Gross primary productivity (GPP) and net primary productivity (NPP) estimates compared well to observed fluxes at the simulation sites. Simulated N fixation at steady-state, calculated based on relative demand for N and the marginal return on C investment to acquire N, was an order of magnitude higher in the tropical forest than in the temperate forest, consistent with observations. A sensitivity analysis revealed that parameterization of the relationship between leaf N and leaf respiration had the largest influence on leaf area index and leaf C : N. A parameter governing how photosynthesis scales with day length had the largest influence on total vegetation C, GPP, and NPP. Multiple parameters associated with photosynthesis, respiration, and N uptake influenced the rate of N fixation. Overall, our ability to constrain leaf area index and allow spatially and temporally variable leaf C : N can help address challenges simulating these properties in ecosystem and Earth System models. Furthermore, the simple approach with emergent properties based on coupled C–N dynamics has potential for use in research that uses data-assimilation methods to integrate data on both the C and N cycles to improve C flux forecasts.

Description: Uncertainty in Lagrangian pollutant transport simulations due to meteorological uncertainty from a mesoscale WRF ensemble Geoscientific Model Development, 7, 2817-2829, 2014 Author(s): W. M. Angevine, J. Brioude, S. McKeen, and J. S. Holloway Lagrangian particle dispersion models require meteorological fields as input. Uncertainty in the driving meteorology is one of the major uncertainties in the results. The propagation of uncertainty through the system is not simple, and it has not been thoroughly explored. Here, we take an ensemble approach. Six different configurations of the Weather Research and Forecast (WRF) model drive otherwise identical simulations with FLEXPART-WRF for 49 days over eastern North America. The ensemble spreads of wind speed, mixing height, and tracer concentration are presented. Uncertainty of tracer concentrations due solely to meteorological uncertainty is 30–40%. Spatial and temporal averaging reduces the uncertainty marginally. Tracer age uncertainty due solely to meteorological uncertainty is 15–20%. These are lower bounds on the uncertainty, because a number of processes are not accounted for in the analysis.

Description: Sensitivity of simulated CO 2 concentration to regridding of global fossil fuel CO 2 emissions Geoscientific Model Development, 7, 2867-2874, 2014 Author(s): X. Zhang, K. R. Gurney, P. Rayner, Y. Liu, and S. Asefi-Najafabady Errors in the specification or utilization of fossil fuel CO 2 emissions within carbon budget or atmospheric CO 2 inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO 2 concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO 2 emissions (FFCO 2 ) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO 2 concentration driven by two different approaches to regridding fossil fuel CO 2 emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO 2 concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell −1 yr −1 (−3.39 kgC m −2 yr −1 ) to +30.0 TgC grid cell −1 yr −1 (+2.6 kgC m −2 yr −1 ) along coastal margins. Maximum simulated annual mean CO 2 concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO 2 monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO 2 concentration, such as atmospheric CO 2 inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.

Description: Predicting the response of the Amazon rainforest to persistent drought conditions under current and future climates: a major challenge for global land surface models Geoscientific Model Development, 7, 2933-2950, 2014 Author(s): E. Joetzjer, C. Delire, H. Douville, P. Ciais, B. Decharme, R. Fisher, B. Christoffersen, J. C. Calvet, A. C. L. da Costa, L. V. Ferreira, and P. Meir While a majority of global climate models project drier and longer dry seasons over the Amazon under higher CO 2 levels, large uncertainties surround the response of vegetation to persistent droughts in both present-day and future climates. We propose a detailed evaluation of the ability of the ISBA CC (Interaction Soil–Biosphere–Atmosphere Carbon Cycle) land surface model to capture drought effects on both water and carbon budgets, comparing fluxes and stocks at two recent throughfall exclusion (TFE) experiments performed in the Amazon. We also explore the model sensitivity to different water stress functions (WSFs) and to an idealized increase in CO 2 concentration and/or temperature. In spite of a reasonable soil moisture simulation, ISBA CC struggles to correctly simulate the vegetation response to TFE whose amplitude and timing is highly sensitive to the WSF. Under higher CO 2 concentrations, the increased water-use efficiency (WUE) mitigates the sensitivity of ISBA CC to drought. While one of the proposed WSF formulations improves the response of most ISBA CC fluxes, except respiration, a parameterization of drought-induced tree mortality is missing for an accurate estimate of the vegetation response. Also, a better mechanistic understanding of the forest responses to drought under a warmer climate and higher CO 2 concentration is clearly needed.

Description: Coupling the high-complexity land surface model ACASA to the mesoscale model WRF Geoscientific Model Development, 7, 2917-2932, 2014 Author(s): L. Xu, R. D. Pyles, K. T. Paw U, S. H. Chen, and E. Monier In this study, the Weather Research and Forecasting (WRF) model is coupled with the Advanced Canopy–Atmosphere–Soil Algorithm (ACASA), a high-complexity land surface model. Although WRF is a state-of-the-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF, such as the popular NOAH model, are simple and lack the capability of representing the canopy structure. In contrast, ACASA is a complex multilayer land surface model with interactive canopy physiology and high-order turbulence closure that allows for an accurate representation of heat, momentum, water, and carbon dioxide fluxes between the land surface and the atmosphere. It allows for microenvironmental variables such as surface air temperature, wind speed, humidity, and carbon dioxide concentration to vary vertically within and above the canopy. Surface meteorological conditions, including air temperature, dew point temperature, and relative humidity, simulated by WRF-ACASA and WRF-NOAH are compared and evaluated with observations from over 700 meteorological stations in California. Results show that the increase in complexity in the WRF-ACASA model not only maintains model accuracy but also properly accounts for the dominant biological and physical processes describing ecosystem–atmosphere interactions that are scientifically valuable. The different complexities of physical and physiological processes in the WRF-ACASA and WRF-NOAH models also highlight the impact of different land surface models on atmospheric and surface conditions.

Description: Wave-induced mixing and transport of buoyant particles: application to the Statfjord A oil spill Ocean Science, 10, 977-991, 2014 Author(s): M. Drivdal, G. Broström, and K. H. Christensen This study focuses on how wave–current and wave–turbulence interactions modify the transport of buoyant particles in the ocean. Here the particles can represent oil droplets, plastic particles, or plankton such as fish eggs and larvae. Using the General Ocean Turbulence Model (GOTM), modified to take surface wave effects into account, we investigate how the increased mixing by wave breaking and Stokes shear production, as well as the stronger veering by the Coriolis–Stokes force, affects the drift of the particles. The energy and momentum fluxes, as well as the Stokes drift, depend on the directional wave spectrum obtained from a wave model. As a first test, the depth and velocity scales from the model are compared with analytical solutions based on a constant eddy viscosity (i.e., classical Ekman theory). Secondly, the model is applied to a case in which we investigate the oil drift after an oil spill off the west coast of Norway in 2007. During this accident the average net drift of oil was observed to be both slower and more deflected away from the wind direction than predicted by oil-drift models. In this case, using wind and wave forcing from the ERA Interim archive it is shown that the wave effects are important for the resultant drift and have the potential to improve drift forecasting.

Description: A global finite-element shallow-water model supporting continuous and discontinuous elements Geoscientific Model Development, 7, 3017-3035, 2014 Author(s): P. A. Ullrich This paper presents a novel nodal finite-element method for either continuous and discontinuous elements, as applied to the 2-D shallow-water equations on the cubed sphere. The cornerstone of this method is the construction of a robust derivative operator that can be applied to compute discrete derivatives even over a discontinuous function space. A key advantage of the robust derivative is that it can be applied to partial differential equations in either a conservative or a non-conservative form. However, it is also shown that discontinuous penalization is required to recover the correct order of accuracy for discontinuous elements. Two versions with discontinuous elements are examined, using either the g 1 and g 2 flux correction function for distribution of boundary fluxes and penalty across nodal points. Scalar and vector hyperviscosity (HV) operators valid for both continuous and discontinuous elements are also derived for stabilization and removal of grid-scale noise. This method is validated using four standard shallow-water test cases, including geostrophically balanced flow, a mountain-induced Rossby wave train, the Rossby–Haurwitz wave and a barotropic instability. The results show that although the discontinuous basis requires a smaller time step size than that required for continuous elements, the method exhibits better stability and accuracy properties in the absence of hyperviscosity.

Description: Sensitivity of phytoplankton distributions to vertical mixing along a North Atlantic transect Ocean Science, 10, 993-1011, 2014 Author(s): L. Hahn-Woernle, H. A. Dijkstra, and H. J. Van der Woerd Using in situ data of upper ocean vertical mixing along a transect in the North Atlantic and a one-dimensional phytoplankton growth model, we study the sensitivity of the surface phytoplankton concentration to vertical mixing distributions. The study is divided into two parts. In the first part, the model is calibrated to the observations. The optical model parameters are determined from measurements of the light attenuation. The biological parameters are calibrated to three different reference stations with observed vertical profiles of the chlorophyll a (Chl a ) concentration and the nutrient concentration. In the second part, the sensitivity of the three model calibrations to the vertical mixing is studied. Therefore measured vertical mixing profiles are applied to the model. These mixing profiles are based on the measurements along the transect and are treated as a set of possible mixing situations of the North Atlantic. Results show that shifts in vertical mixing are able to induce a transition from an upper chlorophyll maximum to a deep one and vice versa. Furthermore, a clear correlation between the surface phytoplankton concentration and the mixing induced nutrient flux is found for nutrient-limited cases. This may open up the possibility to extract characteristics of vertical mixing from satellite ocean colour data using data-assimilation methods.

Description: Forecasting the mixed-layer depth in the Northeast Atlantic: an ensemble approach, with uncertainties based on data from operational ocean forecasting systems Ocean Science, 10, 1013-1029, 2014 Author(s): Y. Drillet, J. M. Lellouche, B. Levier, M. Drévillon, O. Le Galloudec, G. Reffray, C. Regnier, E. Greiner, and M. Clavier Operational systems operated by Mercator Ocean provide daily ocean forecasts, and combining these forecasts we can produce ensemble forecast and uncertainty estimates. This study focuses on the mixed-layer depth in the Northeast Atlantic near the Porcupine Abyssal Plain for May 2013. This period is of interest for several reasons: (1) four Mercator Ocean operational systems provide daily forecasts at a horizontal resolution of 1/4, 1/12 and 1/36° with different physics; (2) glider deployment under the OSMOSIS project provides observation of the changes in mixed-layer depth; (3) the ocean stratifies in May, but mixing events induced by gale force wind are observed and forecast by the systems. Statistical scores and forecast error quantification for each system and for the combined products are presented. Skill scores indicate that forecasts are consistently better than persistence, and temporal correlations between forecast and observations are greater than 0.8 even for the 4-day forecast. The impact of atmospheric forecast error, and for the wind field in particular (miss or time delay of a wind burst forecast), is also quantified in terms of occurrence and intensity of mixing or stratification events.

Description: The regional MiKlip decadal forecast ensemble for Europe: the added value of downscaling Geoscientific Model Development, 7, 2983-2999, 2014 Author(s): S. Mieruch, H. Feldmann, G. Schädler, C.-J. Lenz, S. Kothe, and C. Kottmeier The prediction of climate on time scales of years to decades is attracting the interest of both climate researchers and stakeholders. The German Ministry for Education and Research (BMBF) has launched a major research programme on decadal climate prediction called MiKlip (Mittelfristige Klimaprognosen, Decadal Climate Prediction) in order to investigate the prediction potential of global and regional climate models (RCMs). In this paper we describe a regional predictive hindcast ensemble, its validation, and the added value of regional downscaling. Global predictions are obtained from an ensemble of simulations by the MPI-ESM-LR model (baseline 0 runs), which were downscaled for Europe using the COSMO-CLM regional model. Decadal hindcasts were produced for the 5 decades starting in 1961 until 2001. Observations were taken from the E-OBS data set. To identify decadal variability and predictability, we removed the long-term mean, as well as the long-term linear trend from the data. We split the resulting anomaly time series into two parts, the first including lead times of 1–5 years, reflecting the skill which originates mainly from the initialisation, and the second including lead times from 6–10 years, which are more related to the representation of low frequency climate variability and the effects of external forcing. We investigated temperature averages and precipitation sums for the summer and winter half-year. Skill assessment was based on correlation coefficient and reliability. We found that regional downscaling preserves, but mostly does not improve the skill and the reliability of the global predictions for summer half-year temperature anomalies. In contrast, regionalisation improves global decadal predictions of half-year precipitation sums in most parts of Europe. The added value results from an increased predictive skill on grid-point basis together with an improvement of the ensemble spread, i.e. the reliability.

Description: MeteoIO 2.4.2: a preprocessing library for meteorological data Geoscientific Model Development, 7, 3135-3151, 2014 Author(s): M. Bavay and T. Egger Using numerical models which require large meteorological data sets is sometimes difficult and problems can often be traced back to the Input/Output functionality. Complex models are usually developed by the environmental sciences community with a focus on the core modelling issues. As a consequence, the I/O routines that are costly to properly implement are often error-prone, lacking flexibility and robustness. With the increasing use of such models in operational applications, this situation ceases to be simply uncomfortable and becomes a major issue. The MeteoIO library has been designed for the specific needs of numerical models that require meteorological data. The whole task of data preprocessing has been delegated to this library, namely retrieving, filtering and resampling the data if necessary as well as providing spatial interpolations and parameterizations. The focus has been to design an Application Programming Interface (API) that (i) provides a uniform interface to meteorological data in the models, (ii) hides the complexity of the processing taking place, and (iii) guarantees a robust behaviour in the case of format errors, erroneous or missing data. Moreover, in an operational context, this error handling should avoid unnecessary interruptions in the simulation process. A strong emphasis has been put on simplicity and modularity in order to make it extremely easy to support new data formats or protocols and to allow contributors with diverse backgrounds to participate. This library is also regularly evaluated for computing performance and further optimized where necessary. Finally, it is released under an Open Source license and is available at http://models.slf.ch/p/meteoio . This paper gives an overview of the MeteoIO library from the point of view of conceptual design, architecture, features and computational performance. A scientific evaluation of the produced results is not given here since the scientific algorithms that are used have already been published elsewhere.

Description: Multi-model ensemble: technique and validation Geoscientific Model Development, 7, 2333-2343, 2014 Author(s): J. R. Rozante, D. S. Moreira, R. C. M. Godoy, and A. A. Fernandes In this study, a method of numerical weather prediction by ensemble for the South American region is proposed. This method takes into account combinations of the numerical predictions of various models, assigning greater weight to models that exhibit the best performance. Nine operational numerical models were used to perform this study. The main objective of the study is to obtain a weather forecasting product (short-to-medium range) that combines what is best in each of the nine models used in the study, thus producing more reliable predictions. The proposed method was evaluated during austral summer (December 2012, and January and February 2013) and winter (June, July and August 2013). The results show that the proposed method can significantly improve the results provided by the numerical models and consequently has promising potential for operational applications in any weather forecasting center.

Description: Droplet activation parameterization: the population-splitting concept revisited Geoscientific Model Development, 7, 2345-2357, 2014 Author(s): R. Morales Betancourt and A. Nenes In this work, we postulate, implement and evaluate modifications to the "population-splitting" concept, introduced by Nenes and Seinfeld (2003), for calculation of water-condensation rates in droplet-activation parameterizations. The population-splitting approximation consists of dividing the population of growing droplets into two categories: those that experience significant growth after exposed to a supersaturation larger than their critical supersaturation, and those that do not grow much larger than their critical diameter. The modifications introduced here lead to an improved accuracy and precision of the parameterization-derived maximum supersaturation, s max , and droplet-number concentration, N d , as determined by comparing against those of detailed numerical simulations of the activation process. A numerical computation of the first-order derivatives ∂ N d /∂ χ j of the parameterized N d to input variables χ i was performed and compared against the corresponding parcel-model-derived sensitivities, providing a thorough evaluation of the impacts of the introduced modifications in the parameterization ability to respond to aerosol characteristics. An evaluation of the parameterization computation of N d and s max against detailed numerical simulations of the activation process showed a relative error of −6.0% ± 6.2% for s max , and −2.7% ± 4.8% for N d , which represents a considerable reduction in prediction bias when compared to earlier versions of the parameterization. The proposed modifications require only minor changes for their numerical implementation in existing codes based on the population-splitting concept.

Description: Flow dynamics around downwelling submarine canyons Ocean Science, 10, 799-819, 2014 Author(s): J. M. Spurgin and S. E. Allen Flow dynamics around a downwelling submarine canyon were analysed with the Massachusetts Institute of Technology general circulation model. Blanes Canyon (northwestern Mediterranean) was used for topographic and initial forcing conditions. Fourteen scenarios were modelled with varying forcing conditions. Rossby and Burger numbers were used to determine the significance of Coriolis acceleration and stratification (respectively) and their impacts on flow dynamics. A new non-dimensional parameter (χ) was introduced to determine the significance of vertical variations in stratification. Some simulations do see brief periods of upwards displacement of water during the 10-day model period; however, the presence of the submarine canyon is found to enhance downwards advection of density in all model scenarios. High Burger numbers lead to negative vorticity and a trapped anticyclonic eddy within the canyon, as well as an increased density anomaly. Low Burger numbers lead to positive vorticity, cyclonic circulation, and weaker density anomalies. Vertical variations in stratification affect zonal jet placement. Under the same forcing conditions, the zonal jet is pushed offshore in more uniformly stratified domains. The offshore jet location generates upwards density advection away from the canyon, while onshore jets generate downwards density advection everywhere within the model domain. Increasing Rossby values across the canyon axis, as well as decreasing Burger values, increase negative vertical flux at shelf break depth (150 m). Increasing Rossby numbers lead to stronger downwards advection of a passive tracer (nitrate), as well as stronger vorticity within the canyon. Results from previous studies are explained within this new dynamic framework.

Description: Methods to evaluate CaCO 3 cycle modules in coupled global biogeochemical ocean models Geoscientific Model Development, 7, 2393-2408, 2014 Author(s): W. Koeve, O. Duteil, A. Oschlies, P. Kähler, and J. Segschneider The marine CaCO 3 cycle is an important component of the oceanic carbon system and directly affects the cycling of natural and the uptake of anthropogenic carbon. In numerical models of the marine carbon cycle, the CaCO 3 cycle component is often evaluated against the observed distribution of alkalinity. Alkalinity varies in response to the formation and remineralization of CaCO 3 and organic matter. However, it also has a large conservative component, which may strongly be affected by a deficient representation of ocean physics (circulation, evaporation, and precipitation) in models. Here we apply a global ocean biogeochemical model run into preindustrial steady state featuring a number of idealized tracers, explicitly capturing the model's CaCO 3 dissolution, organic matter remineralization, and various preformed properties (alkalinity, oxygen, phosphate). We compare the suitability of a variety of measures related to the CaCO 3 cycle, including alkalinity (TA), potential alkalinity and TA * , the latter being a measure of the time-integrated imprint of CaCO 3 dissolution in the ocean. TA * can be diagnosed from any data set of TA, temperature, salinity, oxygen and phosphate. We demonstrate the sensitivity of total and potential alkalinity to the differences in model and ocean physics, which disqualifies them as accurate measures of biogeochemical processes. We show that an explicit treatment of preformed alkalinity (TA 0 ) is necessary and possible. In our model simulations we implement explicit model tracers of TA 0 and TA * . We find that the difference between modelled true TA * and diagnosed TA * was below 10% (25%) in 73% (81%) of the ocean's volume. In the Pacific (and Indian) Oceans the RMSE of A * is below 3 (4) mmol TA m −3 , even when using a global rather than regional algorithms to estimate preformed alkalinity. Errors in the Atlantic Ocean are significantly larger and potential improvements of TA 0 estimation are discussed. Applying the TA * approach to the output of three state-of-the-art ocean carbon cycle models, we demonstrate the advantage of explicitly taking preformed alkalinity into account for separating the effects of biogeochemical processes and circulation on the distribution of alkalinity. In particular, we suggest to use the TA * approach for CaCO 3 cycle model evaluation.

Description: Grassland production under global change scenarios for New Zealand pastoral agriculture Geoscientific Model Development, 7, 2359-2391, 2014 Author(s): E. D. Keller, W. T. Baisden, L. Timar, B. Mullan, and A. Clark We adapt and integrate the Biome-BGC and Land Use in Rural New Zealand models to simulate pastoral agriculture and to make land-use change, intensification of agricultural activity and climate change scenario projections of New Zealand's pasture production at time slices centred on 2020, 2050 and 2100, with comparison to a present-day baseline. Biome-BGC model parameters are optimised for pasture production in both dairy and sheep/beef farm systems, representing a new application of the Biome-BGC model. Results show up to a 10% increase in New Zealand's national pasture production in 2020 under intensification and a 1–2% increase by 2050 from economic factors driving land-use change. Climate change scenarios using statistically downscaled global climate models (GCMs) from the IPCC Fourth Assessment Report also show national increases of 1–2% in 2050, with significant regional variations. Projected out to 2100, however, these scenarios are more sensitive to the type of pasture system and the severity of warming: dairy systems show an increase in production of 4% under mild change but a decline of 1% under a more extreme case, whereas sheep/beef production declines in both cases by 3 and 13%, respectively. Our results suggest that high-fertility systems such as dairying could be more resilient under future change, with dairy production increasing or only slightly declining in all of our scenarios. These are the first national-scale estimates using a model to evaluate the joint effects of climate change, CO 2 fertilisation and N-cycle feedbacks on New Zealand's unique pastoral production systems that dominate the nation's agriculture and economy. Model results emphasise that CO 2 fertilisation and N-cycle feedback effects are responsible for meaningful differences in agricultural systems. More broadly, we demonstrate that our model output enables analysis of decoupled land-use change scenarios: the Biome-BGC data products at a national or regional level can be re-sampled quickly and cost-effectively for specific land-use change scenarios and future projections.

Description: Improved simulation of fire–vegetation interactions in the Land surface Processes and eXchanges dynamic global vegetation model (LPX-Mv1) Geoscientific Model Development, 7, 2411-2433, 2014 Author(s): D. I. Kelley, S. P. Harrison, and I. C. Prentice The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18% respectively compared to LPX.

Description: Springtime zooplankton size structure over the continental shelf of the Bay of Biscay Ocean Science, 10, 821-835, 2014 Author(s): P. Vandromme, E. Nogueira, M. Huret, Á. Lopez-Urrutia, G. González-Nuevo González, M. Sourisseau, and P. Petitgas Linking lower and higher trophic levels requires special focus on the essential role played by mid-trophic levels, i.e., the zooplankton. One of the most relevant pieces of information regarding zooplankton in terms of flux of energy lies in its size structure. In this study, an extensive data set of size measurements is presented, covering parts of the western European continental shelf and slope, from the Galician coast to the Ushant front, during the springs from 2005 to 2012. Zooplankton size spectra were estimated using measurements carried out in situ with the Laser Optical Plankton Counter (LOPC) and with an image analysis of WP2 net samples (200 μm mesh size) performed following the ZooScan methodology. The LOPC counts and sizes particles within 100–2000 μm of spherical equivalent diameter (ESD), whereas the WP2/ZooScan allows for counting, sizing and identification of zooplankton from ~ 400 μm ESD. The difference between the LOPC (all particles) and the WP2/ZooScan (zooplankton only) was assumed to provide the size distribution of non-living particles, whose descriptors were related to a set of explanatory variables (including physical, biological and geographic descriptors). A statistical correction based on these explanatory variables was further applied to the LOPC size distribution in order to remove the non-living particles part, and therefore estimate the size distribution of zooplankton. This extensive data set provides relevant information about the zooplankton size distribution variability, productivity and trophic transfer efficiency in the pelagic ecosystem of the Bay of Biscay at a regional and interannual scale.

Description: The Wageningen Lowland Runoff Simulator (WALRUS): a lumped rainfall–runoff model for catchments with shallow groundwater Geoscientific Model Development, 7, 2313-2332, 2014 Author(s): C. C. Brauer, A. J. Teuling, P. J. J. F. Torfs, and R. Uijlenhoet We present the Wageningen Lowland Runoff Simulator (WALRUS), a novel rainfall–runoff model to fill the gap between complex, spatially distributed models which are often used in lowland catchments and simple, parametric (conceptual) models which have mostly been developed for sloping catchments. WALRUS explicitly accounts for processes that are important in lowland areas, notably (1) groundwater–unsaturated zone coupling, (2) wetness-dependent flow routes, (3) groundwater–surface water feedbacks and (4) seepage and surface water supply. WALRUS consists of a coupled groundwater–vadose zone reservoir, a quickflow reservoir and a surface water reservoir. WALRUS is suitable for operational use because it is computationally efficient and numerically stable (achieved with a flexible time step approach). In the open source model code default relations have been implemented, leaving only four parameters which require calibration. For research purposes, these defaults can easily be changed. Numerical experiments show that the implemented feedbacks have the desired effect on the system variables.

Description: A robust method for inverse transport modeling of atmospheric emissions using blind outlier detection Geoscientific Model Development, 7, 2303-2311, 2014 Author(s): M. Martinez-Camara, B. Béjar Haro, A. Stohl, and M. Vetterli Emissions of harmful substances into the atmosphere are a serious environmental concern. In order to understand and predict their effects, it is necessary to estimate the exact quantity and timing of the emissions from sensor measurements taken at different locations. There are a number of methods for solving this problem. However, these existing methods assume Gaussian additive errors, making them extremely sensitive to outlier measurements. We first show that the errors in real-world measurement data sets come from a heavy-tailed distribution, i.e., include outliers. Hence, we propose robustifying the existing inverse methods by adding a blind outlier-detection algorithm. The improved performance of our method is demonstrated on a real data set and compared to previously proposed methods. For the blind outlier detection, we first use an existing algorithm, RANSAC, and then propose a modification called TRANSAC, which provides a further performance improvement.

Description: Numerical modelling of physical processes governing larval transport in the southern North Sea Ocean Science, 10, 357-376, 2014 Author(s): M. C. H. Tiessen, L. Fernard, T. Gerkema, J. van der Molen, P. Ruardij, and H. W. van der Veer A three-dimensional hydrodynamic model (GETM) was coupled with a particle tracking routine (GITM) to study the inter-annual variability in transport paths of particles in the North Sea and English Channel. For validation, a comparison with observed drifter trajectories is also presented here. This research investigated to what extent variability in the hydrodynamic conditions alone (reflecting passive particle transport) contributed to inter-annual variability in the transport of eggs and larvae. In this idealised study, no a priori selection of specific spawning grounds or periods was made and no active behaviour (vertical migration) or mortality was included. In this study, egg and larval development towards coastal nursery areas was based solely on sea water temperature, while settlement areas were defined by a threshold water depth. Results showed strong inter-annual variability in drift direction and distance, caused by a combination of wind speed and direction. Strong inter-annual variability was observed both in absolute amount of settlement in several coastal areas, and in the relative importance of the different areas. The effects of wind and temperature variability are minor for settlement along the western shores of the North Sea and in the English Channel, but have a very significant impact on settlement along the eastern shores of the North Sea. Years with strong south-westerly winds across the Dover Straight resulted in higher settlement figures along its eastern shores of the North Sea (standard deviation 37% of the mean annual settlement value). Settlement in the western Dutch Wadden Sea did not only show inter-annual variability, but patterns were also variable within each year and revealed seasonal changes in the origin of particles: during winter, stronger currents along with colder temperatures generally result in particles originating from further away.

Description: Evaluation of MERIS products from Baltic Sea coastal waters rich in CDOM Ocean Science, 10, 377-396, 2014 Author(s): J. M. Beltrán-Abaunza, S. Kratzer, and C. Brockmann In this study, retrievals of the medium resolution imaging spectrometer (MERIS) reflectances and water quality products using four different coastal processing algorithms freely available are assessed by comparison against sea-truthing data. The study is based on a pair-wise comparison using processor-dependent quality flags for the retrieval of valid common macro-pixels. This assessment is required in order to ensure the reliability of monitoring systems based on MERIS data, such as the Swedish coastal and lake monitoring system ( http://vattenkvalitet.se ). The results show that the pre-processing with the Improved Contrast between Ocean and Land (ICOL) processor, correcting for adjacency effects, improves the retrieval of spectral reflectance for all processors. Therefore, it is recommended that the ICOL processor should be applied when Baltic coastal waters are investigated. Chlorophyll was retrieved best using the FUB (Free University of Berlin) processing algorithm, although overestimations in the range 18–26.5%, dependent on the compared pairs, were obtained. At low chlorophyll concentrations ( 〈 2.5 mg m −3 ), data dispersion dominated in the retrievals with the MEGS (MERIS ground segment processor) processor. The lowest bias and data dispersion were obtained with MEGS for suspended particulate matter, for which overestimations in the range of 8–16% were found. Only the FUB retrieved CDOM (coloured dissolved organic matter) correlate with in situ values. However, a large systematic underestimation appears in the estimates that nevertheless may be corrected for by using a local correction factor. The MEGS has the potential to be used as an operational processing algorithm for the Himmerfjärden bay and adjacent areas, but it requires further improvement of the atmospheric correction for the blue bands and better definition at relatively low chlorophyll concentrations in the presence of high CDOM attenuation.

Description: A variational data assimilation system for soil–atmosphere flux estimates for the Community Land Model (CLM3.5) Geoscientific Model Development, 7, 1025-1036, 2014 Author(s): C. M. Hoppe, H. Elbern, and J. Schwinger This paper presents the development and implementation of a spatio-temporal variational data assimilation system (4D-var) for the soil–vegetation–atmosphere transfer model "Community Land Model" (CLM3.5), along with the development of the adjoint code for the core soil–atmosphere transfer scheme of energy and soil moisture. The purpose of this work is to obtain an improved estimation technique for the energy fluxes (sensible and latent heat fluxes) between the soil and the atmosphere. Optimal assessments of these fluxes are neither available from model simulations nor measurements alone, while a 4D-var data assimilation has the potential to combine both information sources by a Best Linear Unbiased Estimate (BLUE). The 4D-var method requires the development of the adjoint model of the CLM which is established in this work. The new data assimilation algorithm is able to assimilate soil temperature and soil moisture measurements for one-dimensional columns of the model grid. Numerical experiments were first used to test the algorithm under idealised conditions. It was found that the analysis delivers improved results whenever there is a dependence between the initial values and the assimilated quantity. Furthermore, soil temperature and soil moisture from in situ field measurements were assimilated. These calculations demonstrate the improved performance of flux estimates, whenever soil property parameters are available of sufficient quality. Misspecifications could also be identified by the performance of the variational scheme.

Description: Modelling methane emissions from natural wetlands by development and application of the TRIPLEX-GHG model Geoscientific Model Development, 7, 981-999, 2014 Author(s): Q. Zhu, J. Liu, C. Peng, H. Chen, X. Fang, H. Jiang, G. Yang, D. Zhu, W. Wang, and X. Zhou A new process-based model TRIPLEX-GHG was developed based on the Integrated Biosphere Simulator (IBIS), coupled with a new methane (CH 4 ) biogeochemistry module (incorporating CH 4 production, oxidation, and transportation processes) and a water table module to investigate CH 4 emission processes and dynamics that occur in natural wetlands. Sensitivity analysis indicates that the most sensitive parameters to evaluate CH 4 emission processes from wetlands are r (defined as the CH 4 to CO 2 release ratio) and Q 10 in the CH 4 production process. These two parameters were subsequently calibrated to data obtained from 19 sites collected from approximately 35 studies across different wetlands globally. Being heterogeneously spatially distributed, r ranged from 0.1 to 0.7 with a mean value of 0.23, and the Q 10 for CH 4 production ranged from 1.6 to 4.5 with a mean value of 2.48. The model performed well when simulating magnitude and capturing temporal patterns in CH 4 emissions from natural wetlands. Results suggest that the model is able to be applied to different wetlands under varying conditions and is also applicable for global-scale simulations.

Description: Mechanisms of Atlantic Meridional Overturning Circulation variability simulated by the NEMO model Ocean Science, 10, 645-656, 2014 Author(s): V. N. Stepanov and K. Haines We have investigated mechanisms for the Atlantic Meridional Overturning Circulation (AMOC) variability at 26.5° N (other than the Ekman component) that can be related to external forcings, in particular wind variability. Resolution dependence is studied using identical experiments with 1° and 1/4° NEMO model runs over 1960–2010. The analysis shows that much of the variability in the AMOC at 26° N can be related to the wind strength over the North Atlantic, through mechanisms lagged on different timescales. At ~ 1-year lag the January–June difference of mean sea level pressure between high and mid-latitudes in the North Atlantic explains 35–50% of the interannual AMOC variability (with negative correlation between wind strength and AMOC). At longer lead timescales ~ 4 years, strong (weak) winds over the northern North Atlantic (specifically linked to the NAO index) are followed by higher (lower) AMOC transport, but this mechanism only works in the 1/4° model. Analysis of the density correlations suggests an increase (decrease) in deep water formation in the North Atlantic subpolar gyre to be the cause. Therefore another 30% of the AMOC variability at 26° N can be related to density changes in the top 1000 m in the Labrador and Irminger seas occurring ~ 4 years earlier.