ALBERT

Description: Influence of microphysical schemes on atmospheric water in the Weather Research and Forecasting model Geoscientific Model Development Discussions, 6, 4563-4601, 2013 Author(s): F. Cossu and K. Hocke This study examines how different microphysical parameterization schemes influence orographically-induced precipitation and the distributions of hydrometeors and water vapour for mid-latitude summer conditions in the Weather Research and Forecasting (WRF) model. A high-resolution two-dimensional idealized simulation is used to assess the differences between the schemes in which a moist air flow is interacting with a bell-shaped 2 km high mountain. Periodic lateral boundary conditions are chosen to recirculate atmospheric water in the domain. It is found that the 13 selected microphysical schemes conserve the water in the model domain. The gain or loss of water is less than 0.81% over a simulation time interval of 61 days. The differences of the microphysical schemes in terms of the distributions of water vapour, hydrometeors and accumulated precipitation are presented and discussed. The Kessler scheme, the only scheme without ice-phase processes, shows final values of cloud liquid water 14 times greater than the other schemes. The differences among the other schemes are not as extreme, but still they differ up to 79% in water vapour, up to 10 times in hydrometeors and up to 64% in accumulated precipitation at the end of the simulation. The microphysical schemes also differ in the surface evaporation rate. The WRF single-moment 3-class scheme has the highest surface evaporation rate compensated by the highest precipitation rate. The different distributions of hydrometeors and water vapour of the microphysical schemes induce differences up to 49 W m −2 in the downwelling shortwave radiation and up to 33 W m −2 in the downwelling longwave radiation.

Description: AnaWEGE: a weather generator based on analogues of atmospheric circulation Geoscientific Model Development Discussions, 6, 4745-4774, 2013 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: Methodological aspects of a pattern-scaling approach to produce global fields of monthly means of daily maximum and minimum temperature Geoscientific Model Development Discussions, 6, 4833-4882, 2013 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 ). 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: Modeling different freeze/thaw processes in heterogeneous landscapes of the Arctic polygonal tundra using an ecosystem model Geoscientific Model Development Discussions, 6, 4883-4932, 2013 Author(s): given_name prefix surname suffix, S. Yi, K. Wischnewski, M. Langer, S. Muster, and J. Boike Freeze/thaw (F/T) processes can be quite different under the various land surface types found in the heterogeneous polygonal tundra of the Arctic. Proper simulation of these different processes is essential for accurate prediction of the release of greenhouse gases under a warming climate scenario. In this study we have modified the dynamic organic soil version of the Terrestrial Ecosystem Model (DOS-TEM) to simulate F/T processes beneath the polygon rims, polygon centers (with and without water), and lakes that are common features in Arctic lowland regions. We first verified the F/T algorithm in the DOS-TEM against analytical solutions, and then compared the results with in situ measurements from Samoylov Island, Siberia. In the final stage, we examined the different responses of the F/T processes for different water levels at the various land surface types. The simulations revealed that (1) the DOS-TEM was very efficient and its results compared very well with analytical solutions for idealized cases, (2) the simulations compared reasonably well with in situ measurements although there were a number of model limitations and uncertainties, (3) the DOS-TEM was able to successfully simulate the differences in F/T dynamics under different land surface types, and (4) permafrost beneath water bodies was found to respond highly sensitive to changes in water depths between 1 and 2 m. Our results indicate that water is very important in the thermal processes simulated by the DOS-TEM; the heterogeneous nature of the landscape and different water depths therefore need to be taken into account when simulating methane emission responses to a warming climate.

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 Discussions, 6, 4983-5076, 2013 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: On the analytic approximation of bulk collision rates of non-spherical hydrometeors Geoscientific Model Development Discussions, 6, 5077-5116, 2013 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: Ensemble initialization of the oceanic component of a coupled model through bred vectors at seasonal-to-interannual time scales Geoscientific Model Development Discussions, 6, 5189-5214, 2013 Author(s): J. Baehr and R. Piontek We evaluate the ensemble spread at seasonal-to-interannual time scales for two perturbation techniques implemented into the ocean component of a coupled model: (1) lagged initial conditions as commonly used for decadal predictions, (2) bred vectors as commonly used for weather and seasonal forecasting. We show that relative to an uninitialized reference simulation the implementation for bred vectors can improve the ensemble spread compared to lagged initialization at time scales from one months up to three years. As bred vectors have so far mostly been used at short time scales, we initially focus on the implementation of the bred vectors into the ocean component. We introduce a depth-dependent vertical rescaling norm, accounting for the vertical dependence of the variability, and extending the commonly used upper-ocean rescaling norm to the full water column. We further show that it is sufficient for the (sub-surface) ocean to breed temperature and salinity (i.e., scalar quantities), and rely on the governing physics to carry the temperature and salinity perturbations to the flow field. Using these bred vectors with a rescaling interval of 12 months, we initialize hindcast simulations and compare them to hindcast simulations initialized with lagged initial conditions. We quantify the ensemble spread by analyzing Talagrand diagrams and spread-error ratios. For both temperature and salinity, the lagged initialized ensemble is particularly under-dispersive for the first few months of predictable lead time. The ensemble initialized with bred vectors improves the spread for temperature and salinity for the 0–700 m and 1000–3500 m means, compared to the lagged ensemble at lead times of several months to one year. As the lead time increases to years, the differences between the two ensemble initialization techniques becomes more difficult to discern. While the results need to be confirmed in an initialized framework, the present analysis represents a first step towards an improved ensemble generation at the transition from seasonal-to-interannual time scales, in particular at lead times up to one year.

Description: Understanding the performance of the FLake model over the African Great Lakes Geoscientific Model Development Discussions, 6, 5141-5187, 2013 Author(s): W. Thiery, A. Martynov, F. Darchambeau, J.-P. Descy, P.-D. Plisnier, L. Sushama, and N. P. M. van Lipzig The ability of the one-dimensional lake model FLake to represent the mixolimnion temperatures for tropical conditions was tested for three locations in East Africa: Lake Kivu, Lake Tanganyika's northern and southern basins. Meteorological observations from surrounding Automatic Weather Stations were corrected and used to drive FLake, whereas a comprehensive set of water temperature profiles served to evaluate the model at each site. Careful forcing data correction and model configuration allowed to reproduce the observed mixed layer seasonality at Lake Kivu and Lake Tanganyika (northern and southern basins), with correct representation of both the mixed layer depth and temperature structure. At Lake Kivu, mixolimnion temperatures predicted by FLake were found sensitive both to minimal variations in the external parameters (lake depth and water transparency) as to small changes in the meteorological driving data, in particular wind velocity. In each case, small modifications may already lead to a regime switch from the correctly represented seasonal mixed layer deepening to either completely mixed (down to the model lake bottom) or permanently stratified (from ~10 m downwards) conditions. In contrast, model temperatures are found robust close to the surface, with acceptable predictions of near-surface water temperatures even when the seasonal mixing regime is not reproduced. FLake can thus be a suitable tool to parameterize tropical lake water surface temperatures within atmospheric prediction models, but may be less appropriate, in its current form, to study complex limnological processes within tropical lakes. Furthermore, a study of different initial conditions showed that for tropical lakes lacking reliable initial data, a fully mixed, artificially warm initialisation is to be preferred, but only if the model is allowed to spin up until convergence is reached. Finally, FLake was used to attribute the seasonal mixing cycle at Lake Kivu to variations in the near-surface meteorological conditions. It was found that the annual mixing down to 60 m during the main dry season is primarily due to enhanced lake evaporation and secondarily due to the decreased incoming long wave radiation, both causing a significant heat loss from the lake surface and associated mixolimnion cooling.

Description: The mid-Pliocene climate simulated by FGOALS-g2 Geoscientific Model Development Discussions, 6, 2403-2428, 2013 Author(s): W. Zheng, Z. Zhang, L. Chen, and Y. Yu Within the framework of Pliocene Model Intercomparison Project (PlioMIP), the mid-Pliocene (3.264–3.025 Ma) climate simulated by the Flexible Global Ocean-Atmosphere-Land System model grid-point version 2 (FGOALS-g2) are analyzed in this study. Results show that the model reproduces the large-scale features of the global warming over the land and ocean. The simulated mid-Pliocene global annual mean surface air temperature (TAS) and sea surface temperature (SST) are 4.17 and 2.62°C warmer than the pre-Industrial simulation, respectively. In particular, the feature of larger warming over mid-high latitudes is well captured. In the simulated warm mid-Pliocene climate, the Atlantic Meridional Overturning Circulation (AMOC) and El Niño-Southern Oscillation (ENSO) become weaker.

Description: The potential of an observational data set for calibration of a computationally expensive computer model Geoscientific Model Development Discussions, 6, 2369-2401, 2013 Author(s): D. J. McNeall, P. G. Challenor, J. R. Gattiker, and E. J. Stone We measure the potential of an observational data set to constrain a set of inputs to a complex and computationally expensive computer model. We use each member in turn of an ensemble of output from a computationally expensive model, corresponding to some observable part of a modelled system, as a proxy for an observational data set. We argue that our ability to constrain uncertain parameter inputs to a model using its own output as data, provides a maximum bound for our ability to constrain the model inputs using observations of the real system. The ensemble provides a set of known parameter input and model output pairs, which we use to build a computationally efficient statistical proxy for the full computer model, termed an emulator. We use the emulator to find and rule out ''implausible" values for the inputs of held-out ensemble members, given the computer model output. As we know the true values of the inputs for the ensemble, we can compare our constraint of the model inputs with the true value of the input for any ensemble member. Measures of the quality of constraint have the potential to inform strategy for data collection campaigns, before any real-world data is collected, as well as acting as an effective sensitivity analysis. We use an ensemble of the ice sheet model Glimmer to demonstrate our measures of quality of constraint. The ensemble has 250 model runs with 5 uncertain input parameters, and an output variable representing the pattern of the thickness of ice over Greenland. We have an observation of historical ice sheet thickness that directly matches the output variable, and offers an opportunity to constrain the model. We show that different ways of summarising our output variable (ice volume, ice surface area and maximum ice thickness) offer different potential constraints on individual input parameters. We show that combining the observational data gives increased power to constrain the model. We investigate the impact of uncertainty in observations or in model biases on our measures, showing that even a modest uncertainty can seriously degrade the potential of the observational data to constrain the model.

Description: On searching for optimized set of physical parameterization schemes in a multi-physics land surface process model Geoscientific Model Development Discussions, 6, 4511-4530, 2013 Author(s): S. Hong, X. Yu, S. K. Park, Y.-S. Choi, and B. Myoung Optimization of land surface models has been very challenging due to the increasing complexity of such models. Typical parameter calibration techniques often limit the solution of the spatiotemporal discrepancy in the modeling performance levels especially for regional applications. Thus, in this study, an attempt was made to perform scheme-based model optimization by designing a framework for coupling a micro-genetic algorithm (micro-GA) with the Noah land surface model that has multiple physics options (Noah-MP). Micro-GA controls the scheme selections in 10 different land surface parameterization fields in Noah-MP in order to extract the optimal scheme combination for a certain region. This coupling framework was successfully applied to the optimization of the surface water partitioning in the Korean Peninsula, promising not only the effectiveness of the scheme-based optimization but also model diagnosis capability by exploring the scheme sensitivity during the micro-GA evolution process. Then, the method was applied to four different regions in East Asia that have different climatic characteristics. The results indicate that (1) the optimal scheme combinations vary with the regions, (2) schemes related to the surface water partitioning are important for the modeling accuracy, and (3) specialized post-parameter optimization for each region may be required.

Description: Atmospheric inverse modeling with known physical bounds: an example from trace gas emissions Geoscientific Model Development Discussions, 6, 4531-4562, 2013 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 non-negativity (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 and is also the first application of Markov chain Monte Carlo (MCMC) to estimation of atmospheric trace gas fluxes. The approaches discussed here are broadly applicable. A common method of data transformations is found to unrealistically skew estimates for the examined example application. The method of Lagrange multipliers and two 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 alternative 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: A database and tool for boundary conditions for regional air quality modeling: description and evaluation Geoscientific Model Development Discussions, 6, 4665-4704, 2013 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 2000–2010 and contains hourly varying concentrations of ozone, aerosols, and their precursors. The database is complimented 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 vertical profiles. The results show performance is largely within uncertainty estimates for the Tropospheric Emission Spectrometer (TES) with some exceptions. The major difference shows a high bias in the upper troposphere along the southern boundary in January. This publication documents the global simulation database, the tool for conversion to LBC, and the fidelity of concentrations on the boundaries. This documentation is intended to support applications that require representation of long-range transport of air pollutants.

Description: Effects of vegetation structure on biomass accumulation in a Balanced Optimality Structure Vegetation Model (BOSVM v1.0) Geoscientific Model Development Discussions, 6, 4603-4663, 2013 Author(s): Z. Yin, S. C. Dekker, B. J. J. M. van den Hurk, and H. A. Dijkstra A myriad of interactions exist between vegetation and local climate for arid and semi-arid regions. Vegetation function, structure and individual behavior have large impacts on carbon-water-energy balances, which consequently influence local climate variability that, in turn, feeds back to the vegetation. In this study, a conceptual vegetation structure scheme is formulated and tested in a new carbon-water-energy coupled model to explore the importance of vegetation structure and vegetation adaptation to water stress on equilibrium biomass states. Surface energy, water and carbon fluxes are simulated for a range of vegetation structures across a precipitation gradient in West Africa and optimal vegetation structures that maximizes biomass for each precipitation regime are determined. Two different strategies of vegetation adaptation to water stress are included. Under dry conditions vegetation tries to maximize the Water Use Efficiency and Leaf Area Index as it tries to maximize carbon gain. However, an important negative feedback mechanism is found as the vegetation also tries to minimize its cover to optimize the surrounding bare ground area from which water can be extracted, thereby forming patches of vertical vegetation. Under larger precipitation, a positive feedback mechanism is found in which vegetation tries to maximize its cover as it then can reduce water loss from bare soil while having maximum carbon gain due to a large Leaf Area Index. The competition between vegetation and bare soil determines a transition between a "survival" state to a "growing" state.

Description: A distributed computing approach to improve the performance of the Parallel Ocean Program (v2.1) Geoscientific Model Development Discussions, 6, 4705-4744, 2013 Author(s): B. van Werkhoven, J. Maassen, M. Kliphuis, H. A. Dijkstra, S. E. Brunnabend, M. van Meersbergen, F. J. Seinstra, and H. E. Bal The Parallel Ocean Program (POP) is used in many strongly eddying ocean circulation simulations. Ideally one would like to do thousand-year long simulations, but the current performance of POP prohibits this type of simulations. In this work, using a new distributed computing approach, two innovations to improve the performance of POP are presented. The first is a new block partitioning scheme for the optimization of the load balancing of POP such that it can be run efficiently in a multi-platform setting. The second is an implementation of part of the POP model code on Graphics Processing Units. We show that the combination of both innovations leads to a substantial performance increase also when running POP simultaneously over multiple computational platforms.

Description: Inherently mass-conservative version of the semi-Lagrangian Absolute Vorticity (SL-AV) atmospheric model dynamical core Geoscientific Model Development Discussions, 6, 4809-4832, 2013 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 Hydrometeorological centre of Russia. The distinct feature of SL-AV dynamical core is the semi-implicit semi-Lagrangian vorticity-divergence formulation on the unstaggered grid. Semi-implicit semi-Lagrangian approach allows for long time steps while violates the global and local mass-conservation. In particular, the total mass in simulations with semi-Lagrangian models can drift significantly if no aposteriori mass-fixing algorithms are applied. However, the global mass-fixing algorithms degrade the local mass conservation. The inherently mass-conservative version of SL-AV model dynamical core presented in the article 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 continuity equation based on the 3-D extension of the conservative cascade semi-Lagrangian transport scheme (CCS). The numerical experiments show that the presented new version of SL-AV dynamical core 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 mass-conservative dynamical core are found to be in agreement with the results available in literature.

Description: A fast input/output library for high resolution climate models Geoscientific Model Development Discussions, 6, 4775-4807, 2013 Author(s): X. Huang, W. Wang, H. Fu, G. 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 PnetCDF in different scenarios. For scenarios with both data output operations and computations, CFIO decreases the I/O overhead by a factor of 5.1 compared to PnetCDF.

Description: Application and evaluation of McICA scheme with new radiation code in BCC_AGCM2.0.1 Geoscientific Model Development Discussions, 6, 4933-4982, 2013 Author(s): given_name prefix surname suffix, H. Zhang, X. Jing, and J. Li This research incorporates the Monte Carlo Independent Column Approximation (McICA) scheme with the correlated k-distribution BCC-RAD radiation model into the climate model BCC_AGCM2.0.1 and examines the impacts on modeled climate through several simulations with variations in cloud structures. Results from experiments with consistent sub-grid cloud structures show that both clear-sky radiation fluxes and cloud radiative forcings (CRFs) calculated by the new scheme are mostly improved relative to those calculated from the original one. The modeled atmospheric temperature and specific humidity are also improved due to changes in the radiative heating rates. The vertical overlap of fractional clouds and horizontal distribution of cloud condensation are important for computing CRFs. The maximum changes in seasonal CRF using the general overlap assumption (GenO) with different decorrelation depths ( L cf ) are larger than 10 and 20 Wm 2 for longwave (LW) CRF and shortwave (SW) CRF, respectively, mostly located in the Tropics and mid-latitude storm tracks. Larger (smaller) L cf in the Tropics (mid-latitude storm tracks) yield better cloud fraction and CRF compared with observations. The inclusion of an observation-based horizontal inhomogeneity of cloud condensation has a distinct impact on LW CRF and SW CRF, with global means of ∼1.2 Wm −2 and ∼3.7 Wm −2 at the top of atmosphere, respectively, making these much closer to observations. These results prove the reliability of the new model configuration to be used in BCC_AGCM2.0.1 for climate simulations, and also indicate that more detailed real-world information on cloud structures should be obtained to constrain cloud settings in McICA in the future.

Description: A regional climate modelling projection ensemble experiment – NARCliM Geoscientific Model Development Discussions, 6, 5117-5139, 2013 Author(s): J. P. Evans, F. Ji, C. Lee, P. Smith, D. Argüeso, and L. Fita Including the impacts of climate change in decision making and planning processes is a challenge facing many regional governments including the New South Wales (NSW) and Australian Capital Territory (ACT) governments in Australia. NARCliM (NSW/ACT Regional Climate Modelling project) is a regional climate modelling project that aims to provide a comprehensive and consistent set of climate projections that can be used by all relevant government departments when considering climate change. To maximise end user engagement and ensure outputs are relevant to the planning process, a series of stakeholder workshops were run to define key aspects of the model experiment including spatial resolution, time slices, and output variables. As with all such experiments, practical considerations limit the number of ensembles members that can be simulated such that choices must be made concerning which Global Climate Models (GCMs) to downscale from, and which Regional Climate Models (RCMs) to downscale with. Here a methodology for making these choices is proposed that aims to sample the uncertainty in both GCMs and RCMs, as well as spanning the range of future climate projections present in the full GCM ensemble. The created ensemble provides a more robust view of future regional climate changes.

Description: The ICON-1.2 hydrostatic atmospheric dynamical core on triangular grids – Part 1: Formulation and performance of the baseline version Geoscientific Model Development Discussions, 6, 59-119, 2013 Author(s): H. Wan, M. A. Giorgetta, G. Zängl, M. Restelli, D. Majewski, L. Bonaventura, K. Fröhlich, D. Reinert, P. Rípodas, and L. Kornblueh A hydrostatic atmospheric dynamical core is developed for the purpose of global climate modelling. The model applies finite-difference methods to discretize the primitive equations on spherical icosahedral grids, using C-type staggering with triangles as control volumes for mass. This paper documents the numerical methods employed in the baseline version of the model, discusses their properties, and presents results from various idealized test cases. The evaluation shows that the new dynamical core is able to correctly represent the evolution of baroclinic eddies in the atmosphere as well as their role in heat and momentum transport. The simulations compare well with the reference solutions, and show a clear trend of convergence as the horizontal resolution increases. First results from two aqua-planet simulations are also presented, in which the equatorial wave spectra derived from tropical precipitation agree well with those simulated by a spectral transform model. The new dynamical core thus provides a good basis for further model development. Certain aspects of the model formulation that need further investigation and improvement are also pointed out.

Description: The GREENROOF module (v7.3) for modelling green roof hydrological and energetic performances within TEB Geoscientific Model Development Discussions, 6, 1127-1172, 2013 Author(s): C. S. de Munck, A. Lemonsu, R. Bouzouidja, V. Masson, and R. Claverie The need to prepare cities for climate change adaptation requests the urban modeller community to implement within their models sustainable adaptation strategies to be tested against specific city morphologies and scenarios. Greening city roofs is part of these strategies. In this context, a GREENROOF module for TEB (Town Energy Balance) has been developed to model the interactions between buildings and green roof systems at the scale of the city. This module allows one to describe an extensive green roof composed of four functional layers (vegetation – grasses or sedums, substrate, retention/drainage layers and artificial roof layers) and to model vegetation-atmosphere fluxes of heat, water and momentum, as well as the hydrological and thermal fluxes throughout the substrate and the drainage layers, and the thermal coupling with the structural building envelope. TEB-GREENROOF (v7.3) is therefore able to represent the impact of climate forcings on the functioning of the green roof vegetation and, conversely, the influence of the green roof on the local climate. A calibration exercise to adjust the model to the peculiar hydrological characteristics of the substrates and drainage layers commonly found on green roofs is performed for a case study located in Nancy (France) which consists of an extensive green roof with sedums. Model results for the optimum hydrological calibration show a good dynamics for the substrate water content which is nevertheless under-estimated but without impacting too much the green roof temperatures since they present a good agreement with observations. These results are encouraging with regard to modelling the impact of green roofs on thermal indoor comfort and energy consumption at the scale of cities, for which GREENROOF will be running with the building energy version of TEB, TEB-BEM. Moreover, the green roof studied for GREENROOF evaluation being a city-widespread type of extensive green roof, the hydrological characteristics derived through the evaluation exercise will be used as the standard configuration to model extensive green roofs at the scale of cities.

Description: The chemistry CATT–BRAMS model (CCATT–BRAMS 4.5): a regional atmospheric model system for integrated air quality and weather forecasting and research Geoscientific Model Development Discussions, 6, 1173-1222, 2013 Author(s): K. M. Longo, S. R. Freitas, M. Pirre, V. Marécal, L. F. Rodrigues, J. Panetta, M. F. Alonso, N. E. Rosário, D. S. Moreira, M. S. Gácita, J. Arteta, R. Fonseca, R. Stockler, D. M. Katsurayama, A. Fazenda, and M. Bela The Coupled Chemistry Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT–BRAMS, version 4.5) is an online regional chemical transport model designed for local and regional studies of atmospheric chemistry from surface to the lower stratosphere suitable both for operational and research purposes. It includes gaseous/aqueous chemistry, photochemistry, scavenging and dry deposition. The CCATT–BRAMS model takes advantages of the BRAMS specific development for the tropics/subtropics and of the recent availability of preprocessing tools for chemical mechanisms and of fast codes for photolysis rates. BRAMS includes state-of-the-art physical parameterizations and dynamic formulations to simulate atmospheric circulations of scales down to meters. The online coupling between meteorology and chemistry allows the system to be used for simultaneous atmospheric weather and chemical composition forecasts as well as potential feedbacks between them. The entire system comprises three preprocessing software tools for chemical mechanism (which are user defined), aerosol and trace gases emission fields and atmospheric and chemistry fields for initial and boundary conditions. In this paper, the model description is provided along evaluations performed using observational data obtained from ground-based stations, instruments aboard of aircrafts and retrieval from space remote sensing. The evaluation takes into account model application on different scales from megacities and Amazon Basin up to intercontinental region of the Southern Hemisphere.

Description: Parallel algorithms for planar and spherical Delaunay construction with an application to centroidal Voronoi tessellations Geoscientific Model Development Discussions, 6, 1427-1466, 2013 Author(s): D. W. Jacobsen, M. Gunzburger, T. Ringler, J. Burkardt, and J. Peterson A new algorithm, featuring overlapping domain decompositions, for the parallel construction of Delaunay and Voronoi tessellations is developed. Overlapping allows for the seamless stitching of the partial Delaunay tessellations constructed by individual processors. The algorithm is then modified, by the addition of stereographic projections, to handle the parallel construction of spherical Delaunay and Voronoi tessellations. The algorithms are then embedded into algorithms for the parallel construction of planar and spherical centroidal Voronoi tessellations that require multiple constructions of Delaunay tessellations. Computational tests are used to demonstrate the efficiency and scalability of the algorithms for spherical Delaunay and centroidal Voronoi tessellations. Compared to serial versions of the algorithm and to the STRIPACK-based approaches, the new parallel algorithm results in significant speedups for the construction of spherical centroidal Voronoi tessellations.

Description: PEATBOG: a biogeochemical model for analyzing coupled carbon and nitrogen dynamics in northern peatlands Geoscientific Model Development Discussions, 6, 1599-1688, 2013 Author(s): Y. Wu and C. Blodau Elevated nitrogen deposition and climate change alter the vegetation communities and carbon (C) and nitrogen (N) cycling in peatlands. To address this issue we developed a new process-oriented biogeochemical model (PEATBOG) for analyzing coupled carbon and nitrogen dynamics in northern peatlands. The model consists of four submodels, which simulate: (1) daily water table depth and depth profiles of soil moisture, temperature and oxygen levels; (2) competition among three plants functional types (PFTs), production and litter production of plants; (3) decomposition of peat; and (4) production, consumption, diffusion and export of dissolved C and N species in soil water. The model is novel in the integration of the C and N cycles, the explicit spatial resolution belowground, the consistent conceptualization of movement of water and solutes, the incorporation of stoichiometric controls on elemental fluxes and a consistent conceptualization of C and N reactivity in vegetation and soil organic matter. The model was evaluated for the Mer Bleue Bog, near Ottawa, Ontario, with regards to simulation of soil moisture and temperature and the most important processes in the C and N cycles. Model sensitivity was tested for nitrogen input, precipitation, and temperature, and the choices of the most uncertain parameters were justified. A simulation of nitrogen deposition over 40 yr demonstrates the advantages of the PEATBOG model in tracking biogeochemical effects and vegetation change in the ecosystem.

Description: δ 18 O water isotope in the i LOVECLIM model (version 1.0) – Part 3: A paleoperspective based on present-day data-model comparison for oxygen stable isotopes in carbonates Geoscientific Model Development Discussions, 6, 1527-1558, 2013 Author(s): T. Caley and D. M. Roche Oxygen stable isotopes ( 18 O) are among the most usual tools in paleoclimatology/paleoceanography. Simulation of oxygen stable isotopes allows testing how the past variability of these isotopes in water can be interpreted. By modelling the proxy directly in the model, the results can also be directly compared with the data. Water isotopes have been implemented in the global three-dimensional model of intermediate complexity i LOVECLIM allowing fully coupled atmosphere-ocean simulations. In this study, we present the validation of the model results for present day climate against global database for oxygen stable isotopes in carbonates. The limitation of the model together with the processes operating in the natural environment reveal the complexity of use the continental calcite 18 O signal of speleothems for a data-model comparison exercise. On the contrary, the reconstructed surface ocean calcite δ 18 O signal in i LOVECLIM does show a very good agreement with late Holocene database (foraminifers) at the global and regional scales. Our results indicate that temperature and the isotopic composition of the seawater are the main control on the fossil δ 18 O signal recorded in foraminifer shells and that depth habitat and seasonality play a role but have secondary importance. We argue that a data-model comparison for surface ocean calcite δ 18 O in past climate, such as the last glacial maximum (≈21 000 yr), could constitute an interesting tool for mapping the potential shifts of the frontal systems and circulation changes throughout time. Similarly, the potential changes in intermediate oceanic circulation systems in the past could be documented by a data (benthic foraminifers)-model comparison exercise whereas future investigations are necessary in order to quantitatively compare the results with data for the deep ocean.

Description: δ 18 O water isotope in the i LOVECLIM model (version 1.0) – Part 2: Evaluation of model results against observed δ 18 O in water samples Geoscientific Model Development Discussions, 6, 1495-1525, 2013 Author(s): D. M. Roche and T. Caley The H 2 18 O stable isotope was previously introduced in the three coupled components of the Earth System Model i LOVECLIM: atmosphere, ocean and vegetation. The results of a long (5000 yr) pre-industrial equilibrium simulation are presented and evaluated against measurement of H 2 18 O abundance in present-day water for the atmospheric and oceanic components. For the atmosphere, it is found that the model reproduces the observed spatial distribution and relationships to climate variables with some merit, though limitations following our approach are highlighted. Indeed, we obtain the main gradients with a robust representation of the Rayleigh distillation but caveats appear in Antarctica and around the Mediterranean region due to model limitation. For the oceanic component, the agreement between the modelled and observed distribution of water δ 18 O is found to be very good. Mean ocean surface latitudinal gradients are faithfully reproduced as well as the mark of the main intermediate and deep water masses. This opens large prospects for the applications in paleoclimatic context.

Description: δ 18 O water isotope in the i LOVECLIM model (version 1.0) – Part 1: Implementation and verification Geoscientific Model Development Discussions, 6, 1467-1494, 2013 Author(s): D. M. Roche A new 18 O stable water isotope scheme is developed for three components of the i LOVECLIM coupled climate model: atmospheric, oceanic and land surface. The equations required to reproduce the fractionation of stable water isotopes in the simplified atmospheric model ECBilt are developed consistently with the moisture scheme. Simplifications in the processes are made to account for the simplified vertical structure including only one moist layer. Implementation of these equations together with a passive tracer scheme for the ocean and a equilibrium fractionation scheme for the land surface leads to the closure of the (isotopic-)water budget in our climate system. Following the implementation, verification of the existence of usual δ 18 O to climatic relationships are performed for the Rayleigh distillation, the Dansgaard relationship and the δ 18 O–salinity relationship. Advantages and caveats of the approach taken are outlined.

Description: Capabilities and performance of Elmer/Ice, a new generation ice-sheet model Geoscientific Model Development Discussions, 6, 1689-1741, 2013 Author(s): O. Gagliardini, T. Zwinger, F. Gillet-Chaulet, G. Durand, L. Favier, B. de Fleurian, R. Greve, M. Malinen, C. Martín, P. Råback, J. Ruokolainen, M. Sacchettini, M. Schäfer, H. Seddik, and J. Thies The Fourth IPCC Assessment Report concluded that ice-sheet flow models are unable to forecast the current increase of polar ice sheet discharge and the associated contribution to sea-level rise. Since then, the glaciological community has undertaken a huge effort to develop and improve a new generation of ice-flow models, and as a result, a significant number of new ice-sheet models have emerged. Among them is the parallel finite-element model Elmer/Ice, based on the open-source multi-physics code Elmer. It was one of the first full-Stokes models used to make projections for the evolution of the whole Greenland ice sheet for the coming two centuries. Originally developed to solve local ice flow problems of high mechanical and physical complexity, Elmer/Ice has today reached the maturity to solve larger scale problems, earning the status of an ice-sheet model. Here, we summarise almost 10 yr of development performed by different groups. We present the components already included in Elmer/Ice, its numerical performance, selected applications, as well as developments planned for the future.

Description: WRFv3.2-SPAv2: development and validation of a coupled ecosystem-atmosphere model, scaling from surface fluxes of CO 2 and energy to atmospheric profiles Geoscientific Model Development Discussions, 6, 1559-1598, 2013 Author(s): T. L. Smallman, J. B. Moncrieff, and M. Williams The Weather Research & Forecasting meteorological (WRF) model has been coupled to the Soil Plant Atmosphere (SPA) terrestrial ecosystem model, to produce WRF-SPA. SPA generates realistic land-atmosphere exchanges through fully coupled hydrological, carbon and energy cycles. The addition of a land surface model (SPA) capable of modelling biospheric CO 2 exchange allows WRF-SPA to be used for investigating the feedbacks between biosphere carbon balance, meteorology and land management/land use change. We have extensively validated WRF-SPA using multi-annual observations of air temperature, turbulent fluxes, net radiation and net ecosystem exchange of CO 2 at three sites, representing the dominant vegetation types in Scotland (forest, managed grassland and arable agriculture). WRF-SPA generates more realistic seasonal behaviour at the site level compared to an unmodified version of WRF, and produces realistic CO 2 exchanges. WRF-SPA is also able to realistically model atmospheric profiles of CO 2 over Scotland, spanning a 3 yr period (2004–2006), capturing both profile structure, indicating realistic transport, and magnitude indicating appropriate source sink distribution and CO 2 exchange. WRF-SPA makes use of CO 2 tracer pools and can therefore identify and quantify land surface contributions to the modelled atmospheric CO 2 signal at a specified location.

Description: Sensitivities and uncertainties of modeled ground temperatures in mountain environments Geoscientific Model Development Discussions, 6, 791-840, 2013 Author(s): S. Gubler, S. Endrizzi, S. Gruber, and R. S. Purves Before operational use or for decision making, models must be validated, and the degree of trust in model outputs should be quantified. Often, model validation is performed at single locations due to the lack of spatially-distributed data. Since the analysis of parametric model uncertainties can be performed independently of observations, it is a suitable method to test the influence of environmental variability on model evaluation. In this study, the sensitivities and uncertainty of a physically-based mountain permafrost model are quantified within an artificial topography consisting of different elevations and exposures combined with six ground types characterized by their hydraulic properties. The analyses performed for all combinations of topographic factors and ground types allowed to quantify the variability of model sensitivity and uncertainty within mountain regions. We found that modeled snow duration considerably influences the mean annual ground temperature (MAGT). The melt-out day of snow (MD) is determined by processes determining snow accumulation and melting. Parameters such as the temperature and precipitation lapse rate and the snow correction factor have therefore a great impact on modeled MAGT. Ground albedo changes MAGT from 0.5 to 4°C in dependence of the elevation, the aspect and the ground type. South-exposed inclined locations are more sensitive to changes in ground albedo than north-exposed slopes since they receive more solar radiation. The sensitivity to ground albedo increases with decreasing elevation due to shorter snow cover. Snow albedo and other parameters determining the amount of reflected solar radiation are important, changing MAGT at different depths by more than 1°C. Parameters influencing the turbulent fluxes as the roughness length or the dew temperature are more sensitive at low elevation sites due to higher air temperatures and decreased solar radiation. Modeling the individual terms of the energy balance correctly is hence crucial in any physically-based permafrost model, and a separate evaluation of the energy fluxes could substantially improve the results of permafrost models. The sensitivity in the hydraulic properties change considerably for different ground types: rock or clay for instance are not sensitive while gravel or peat, accurate measurements of the hydraulic properties could significantly improve modeled ground temperatures. Further, the discretization of ground, snow and time have an impact on modeled MAGT that cannot be neglected (more than 1°C for several discretization parameters). We show that the temporal resolution should be at least one hour to ensure errors less than 0.2°C in modeled MAGT, and the uppermost ground layer should at most be 20 mm thick. Within the topographic setting, the total parametric output uncertainties expressed as the standard deviation of the Monte Carlo model simulations range from 0.1 to 0.5°C for clay, silt and rock, and from 0.1 to 0.8°C for peat, sand and gravel. These uncertainties are comparable to the variability of ground surface temperatures measured within 10 m × 10 m grids in Switzerland. The increased uncertainties for sand, peat and gravel is largely due to the high hydraulic conductivity.

Description: One-dimensional simulation of fire injection heights in contrasted meteorological scenarios with PRM and Meso-NH models Geoscientific Model Development Discussions, 6, 721-790, 2013 Author(s): S. Strada, S. R. Freitas, C. Mari, K. M. Longo, and R. Paugam Wild-fires release huge amounts of aerosol and hazardous trace gases in the atmosphere. The residence time and the dispersion of fire pollutants in the atmosphere can range from hours to days and from local to continental scales. These various scenarios highly depend on the injection height of smoke plumes. The altitude at which fire products are injected in the atmosphere is controlled by fire characteristics and meteorological conditions. Injection height however is still poorly accounted in chemistry transport models for which fires are sub-grid scale processes which need to be parametrised. Only recently, physically-based approaches for estimating the fire injection heights have been developed which consider both the convective updrafts induced by the release of fire sensible heat and the impact of background meteorological environment on the fire convection dynamics. In this work, two different models are used to simulate fire injection heights in contrasted meteorological scenarios: a Mediterranean arson fire and two Amazonian deforestation fires. A Eddy-Diffusivity/Mass-Flux approach, formerly developed to reproduce convective boundary layer in the non-hydrostatic meteorological model Meso-NH, is compared to the 1-D Plume Rise Model. For both models, radiosonde data and re-analyses from the European Center for Medium-Range Weather Forecasts (ECMWF) have been used as initial conditions to explore the sensitivity of the models responses to different meteorological forcings. The two models predict injection heights for the Mediterranean fire between 1.7 and 3.3 km with the Meso-NH/EDMF model systematically higher than the 1-D PRM model. Both models show a limited sensitivity to the meteorological forcings with a 20–30% difference in the injection height between radiosondes and ECMWF data for this case. Injection heights calculated for the two Amazonian fires ranges from 5 to 6.5 km for the 1-D PRM model and from 2 to 4 km for the Meso-NH/EDMF model. The difference of smoke plume heights between the two models can reach 3–4 km. A large difference is obtained for the windy-wet Amazonian fire by the 1-D PRM model with a injection height 1.5 km higher when ECMWF re-analyses are used compared to the run with the radiosonde forcing. For the Mediterranean case, both models forecast a plume injection height above the boundary layer, although there are evidences that this particular fire propagated near the surface, highlighting the current limitations of the two approaches.

Description: Representation of nucleation mode microphysics in global aerosol microphysics models Geoscientific Model Development Discussions, 6, 893-924, 2013 Author(s): Y. H. Lee, J. R. Pierce, and P. J. Adams In models, nucleation mode (1 nm 〈 D p 〈 10 nm) particle microphysics can be represented explicitly with aerosol microphysical processes or can be parameterized to obtain the growth and survival of nuclei to the model's lower size boundary. This study investigates how the representation of nucleation mode microphysics impacts aerosol number predictions in the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics model running with the GISS GCM II-prime by varying its lowest diameter boundary: 1 nm, 3 nm, and 10 nm. The model with the 1 nm boundary simulates the nucleation mode particles with fully resolved microphysical processes, while the model with the 10 nm and 3 nm boundaries uses a nucleation mode dynamics parameterization to account for the growth of nucleated particles to 10 nm and 3 nm, respectively. We also investigate the impact of the time step for aerosol microphysical processes (a 10-min versus a 1-h time step) to aerosol number predictions in the TOMAS models with explicit dynamics for the nucleation mode particles (i.e. 3 nm and 1 nm boundary). The model with the explicit microphysics (i.e. 1 nm boundary) with the 10-min time step is used as a numerical benchmark simulation to estimate biases caused by varying the lower size cutoff and the time step. Different representations of the nucleation mode have a significant effect on the formation rate of particles larger than 10 nm from nucleated particles ( J 10 ) and the burdens and lifetimes of ultrafine mode (10 nm 〈 D p 〈 70 nm) particles but have less impact on the burdens and lifetimes of CCN-sized particles. The models using parameterized microphysics (i.e. 10 nm and 3 nm boundaries) result in higher J 10 and shorter coagulation lifetimes of ultrafine mode particles than the model with explicit dynamics (i.e. 1 nm boundary). The spatial distributions of CN10 ( D p 〉 10 nm) and CCN(0.2%) (i.e. CCN concentrations at 0.2% supersaturation) are moderately affected, especially CN10 predictions above ~ 700 hPa where nucleation contributes most strongly to CN10 concentrations. The lowermost layer CN10 is substantially improved with the 3 nm boundary (compared to 10 nm) in most areas. The overprediction in CN10 with the 3 nm and 10 nm boundaries can be explained by the overprediction of J 10 or J 3 with the parameterized microphysics possibly due to the instantaneous growth rate assumption in the survival and growth parameterization. The errors in CN10 predictions are sensitive to the choice of the lower size boundary but not to the choice of the time step applied to the microphysical processes. The spatial distribution of CCN(0.2%) with the 3 nm boundary is almost identical to that with the 1 nm boundary, but that with the 10 nm boundary can differ more than 10–40% in some areas. We found that the deviation in the 10 nm simulations is partly due to the longer time step (i.e. 1-h time step used in the 10 nm simulations compared to 10-min time step used in the benchmark simulations) but, even with the same time step, the 10 nm cutoff showed noticeably higher errors than the 3 nm cutoff. In conclusion, we generally recommend using a lower diameter boundary of 3 nm for studies focused on aerosol indirect effects but down to 1 nm boundary for studies focused on CN10 predictions or nucleation.

Description: An optimally tuned ensemble of the "eb_go_gs" configuration of GENIE: parameter sensitivity and bifurcations in the Atlantic overturning circulation Geoscientific Model Development Discussions, 6, 925-956, 2013 Author(s): R. Marsh, A. Sóbester, E. E. Hart, K. I. C. Oliver, N. R. Edwards, and S. J. Cox The key physical parameters of the "eb_go_gs" configuration of GENIE, an Earth system Model of Intermediate Complexity (EMIC), are tuned using a multi-objective genetic algorithm. An ensemble of 90 parameter sets is tuned using two ocean and two atmospheric state variables as targets. These are "Pareto-optimal", representing a range of trade-offs between the four tuning targets. For the leading five parameter sets, simulations are further evaluated alongside a simulation with untuned "default" parameters, comparing selected variables and diagnostics that describe the state of the atmosphere, ocean and sea ice. One of these parameter sets is selected for further analysis of the objective function (error) landscape in the vicinity of its tuned values. "Cliffs" along some dimensions motivate closer inspection of corresponding variations in the Atlantic meridional overturning circulation (AMOC). This reveals that bifurcations in the AMOC are highly sensitive to parameters that are not commonly associated with MOC stability. Specifically, the state of the AMOC is sensitive to parameters governing the wind-driven circulation and atmospheric heat transport. Five optimal parameter sets are recommended for future use of GENIE in the configuration presented here.

Description: An efficient method to generate a perturbed parameter ensemble of a fully coupled AOGCM without flux-adjustment Geoscientific Model Development Discussions, 6, 841-892, 2013 Author(s): P. J. Irvine, L Gregoire, D. J. Lunt, and P. J. Valdes We present a simple method to generate a perturbed parameter ensemble (PPE) of a fully-coupled atmosphere-ocean general circulation model (AOGCM), HadCM3, without requiring flux-adjustment. The aim was to produce an ensemble that samples parametric uncertainty in some key variables and displays a similar range of behavior as seen in multi-model ensembles (MMEs). Six atmospheric parameters, a sea-ice parameter and an ocean parameter were jointly perturbed within a reasonable range to generate an initial group of 200 members. To screen out implausible ensemble members, 20 yr pre-industrial control simulations were run and members whose temperature response to the parameter perturbations was projected to be outside the range of 13.6 ± 2°C, i.e. near to the observed pre-industrial global mean, were discarded. 21 members, including the standard unperturbed model, were accepted, covering almost the entire span of the eight parameters, challenging the argument that without flux-adjustment parameter ranges would be unduly restricted. This ensemble was used in 3 experiments; a 800 yr pre-industrial, a 150 yr quadrupled CO 2 , and a 150 yr 1% CO 2 rise per annum simulation. The behavior of the PPE for the pre-industrial control compared well to the CMIP3 ensemble for a number of surface and atmospheric column variables with the exception of a few members in the Tropics. However, we find that members of the PPE with low values of the entrainment rate coefficient show very large increases in upper tropospheric and stratospheric water vapor concentrations in response to elevated CO 2 and some show implausibly high climate sensitivities, and as such some of these members will be excluded from future experiments with this ensemble. The outcome of this study is a PPE of a fully-coupled AOGCM which samples parametric uncertainty with a range of behavior similar to the CMIP3 ensemble and a simple methodology which would be applicable to other GCMs.

Description: A cloud chemistry module for the 3-D cloud-resolving mesoscale model Meso-NH with application to idealized cases Geoscientific Model Development Discussions, 6, 957-1020, 2013 Author(s): M. Leriche, J.-P. Pinty, C. Mari, and D. Gazen A complete chemical module has been developed for use in the Meso-NH three-dimensional cloud resolving mesoscale model. This module includes gaseous and aqueous phase chemical reactions that are analysed by a pre-processor generating the Fortran90 code automatically. The kinetic solver is based on a Rosenbrock algorithm, which is robust and accurate for integrating stiff systems and especially multiphase chemistry. The exchange of chemical species between the gas phase and cloud droplets and raindrops is computed kinetically by mass transfers considering non-equilibrium between the gas and the condensed phases. Microphysical transfers of chemical species are considered for the various cloud microphysics schemes available, which are based on one-moment or two-moment schemes. The pH of the droplets and of the raindrops is diagnosed separately as the root of a high order polynomial equation. The chemical concentrations in the ice phase are modelled in a single phase encompassing the two categories of precipitating ice particles (snow and graupel) of the microphysical scheme. The only process transferring chemical species in ice is retention during freezing or riming of liquid hydrometeors. Three idealized simulations are reported, which highlight the sensitivity of scavenging efficiency to the choice of the microphysical scheme and the retention coefficient in the ice phase. A two-dimensional warm, shallow convection case is used to compare the impact of the microphysical schemes on the temporal evolution and rates of acid precipitation. Acid wet deposition rates are shown to be overestimated when a one-moment microphysics scheme is used compared to a two-moment scheme. The difference is induced by a better prediction of raindrop radius and raindrop number concentration in the latter scheme. A two-dimensional mixed-phase squall line and a three-dimensional mixed-phase supercell were simulated to test the sensitivity of cloud vertical transport to the retention efficiency of gases in the ice phase. The 2-D and 3-D simulations illustrate that the retention in ice of a moderately soluble gas such as formaldehyde substantially decreases its concentration in the upper troposphere. In these simulations, retention of highly soluble species in the ice phase significantly increased the wet deposition rates.

Description: GAPPARD: a computationally efficient method of approximating gap-scale disturbance in vegetation models Geoscientific Model Development Discussions, 6, 1021-1084, 2013 Author(s): M. Scherstjanoi, J. O. Kaplan, E. Thürig, and H. Lischke Models of vegetation dynamics that are designed for application at spatial scales larger than individual forest gaps suffer from several limitations. Typically, either a population average approximation is used that results in unrealistic tree allometry and forest stand structure, or models have a high computational demand because they need to simulate both a series of age-based cohorts and a number of replicate patches to account for stochastic gap-scale disturbances. The detail required by the latter method increases the number of calculations by two to three orders of magnitude compared to the less realistic population average approach. In an effort to increase the efficiency of dynamic vegetation models without sacrificing realism, and to explore patterns of spatial scaling in forests, we developed a new method for simulating stand-replacing disturbances that is both accurate and 10-50x faster than approaches that use replicate patches. The GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) method works by postprocessing the output of deterministic, undisturbed simulations of a cohort-based vegetation model by deriving the distribution of patch ages at any point in time on the basis of a disturbance probability. With this distribution, the expected value of any output variable can be calculated from the output values of the deterministic undisturbed run at the time corresponding to the patch age. To account for temporal changes in model forcing, e.g., as a result of climate change, GAPPARD performs a series of deterministic simulations and interpolates between the results in the postprocessing step. We integrated the GAPPARD method in the forest models LPJ-GUESS and TreeM-LPJ, and evaluated these in a series of simulations along an altitudinal transect of an inner-alpine valley. With GAPPARD applied to LPJ-GUESS results were insignificantly different from the output of the original model LPJ-GUESS using 100 replicate patches, but simulation time was reduced by approximately the factor 10. Our new method is therefore highly suited rapidly approximating LPJ-GUESS results, and provides the opportunity for future studies over large spatial domains, allows easier parameterization of tree species, faster identification of areas of interesting simulation results, and comparisons with large-scale datasets and forest models.

Description: A refined statistical cloud closure using double-Gaussian probability density functions Geoscientific Model Development Discussions, 6, 1085-1125, 2013 Author(s): A. K. Naumann, A. Seifert, and J. P. Mellado We introduce a probability density function (PDF) based scheme to parameterize cloud fraction, average liquid water and liquid water flux in large-scale models, that is developed from and tested against large-eddy simulations and observational data. Because the tails of the PDFs are crucial for an appropriate parameterization of cloud properties, we use a double-Gaussian distribution that is able to represent the observed, skewed PDFs properly. Introducing two closure equations, the resulting parameterization relies on the first three moments of the subgrid variability of temperature and moisture as input parameters. The parameterization is shown to be clearly superior to a single-Gaussian approach in diagnosing the cloud fraction and average liquid water profiles and improves existing double-Gaussian closures. We find that the error of the new parameterization is smallest for a horizontal resolution of about 5–20 km and also depends on the appearance of mesoscale structures that are accompanied by higher rain rates. In combination with simple autoconversion schemes that only depend on the liquid water, the error introduced by the new parameterization is orders of magnitude smaller than the difference between various autoconversion schemes. For the liquid water flux, we introduce a parameterization that is depending on the skewness of the subgrid variability of temperature and moisture and that reproduces the profiles of the liquid water flux well.

Description: Evaluation of WRF-SFIRE performance with field observations from the FireFlux experiment Geoscientific Model Development Discussions, 6, 121-169, 2013 Author(s): A. K. Kochanski, M. A. Jenkins, J. Mandel, J. D. Beezley, C. B. Clements, and S. Krueger This study uses in-situ measurements collected during the FireFlux field experiment to evaluate and improve the performance of coupled atmosphere-fire model WRF-SFIRE. The simulation of the experimental burn shows that WRF-SFIRE is capable of providing realistic head fire rate-of-spread and the vertical temperature structure of the fire plume, and, up to 10 m above ground level, fire-induced surface flow and vertical velocities within the plume. The model captured the changes in wind speed and direction before, during, and after fire front passage, along with arrival times of wind speed, temperature, and updraft maximae, at the two instrumented flux towers used in FireFlux. The model overestimated vertical velocities and underestimated horizontal wind speeds measured at tower heights above the 10 m, and it is hypothesized that the limited model resolution over estimated the fire front depth, leading to too high a heat release and, subsequently, too strong an updraft. However, on the whole, WRF-SFIRE fire plume behavior is consistent with the interpretation of FireFlux observations. The study suggests optimal experimental pre-planning, design, and execution of future field campaigns that are needed for further coupled atmosphere-fire model development and evaluation.

Description: An improved non-iterative surface layer flux scheme for atmospheric stable stratification condition Geoscientific Model Development Discussions, 6, 6459-6492, 2013 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-iteration 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 0h ) ≤ 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: A system of conservative regridding for ice/atmosphere coupling in a GCM Geoscientific Model Development Discussions, 6, 6493-6568, 2013 Author(s): R. Fischer, S. Nowicki, M. Kelley, and G. A. Schmidt The method of elevation classes has proven to be a useful way for a low-resolution general circulation model (GCM) to produce high-resolution downscaled surface mass balance fields, for use in one-way studies coupling GCMs and ice flow models. Past uses of elevation classes have been a cause of non-conservation of mass and energy, caused by inconsistency in regridding schemes chosen to regrid to the atmosphere vs. downscaling to the ice model. This causes problems for two-way coupling. A strategy that resolves this conservation issue has been designed and is presented here. The approach identifies three grids between which data must be regridded, and five transformations between those grids required by a typical coupled GCM–ice flow model. This paper shows how each of those transformations may be achieved in a consistent, conservative manner. These transformations are implemented in GLINT2, a library used to couple GCMs with ice models. Source code and documentation are available for download. Confounding real-world issues are discussed, including the use of projections for ice modeling, how to handle dynamically changing ice geometry, and modifications required for finite element ice models.

Description: A 24-variable low-order coupled ocean–atmosphere model: OA-QG-WS v2 Geoscientific Model Development Discussions, 6, 6569-6604, 2013 Author(s): S. Vannitsem and L. De Cruz A new low-order coupled ocean–atmosphere model for mid-latitudes 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 4 ordinary differential equations, as proposed by Pierini (2012). 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. A Fortran code of the model integration is provided as Supplement.

Description: A variational data assimilation system for soil–atmosphere flux estimates for the Community Land Model (CLM3.5) Geoscientific Model Development Discussions, 6, 6605-6637, 2013 Author(s): C. M. Hoppe, H. Elbern, and J. Schwinger This article 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 was 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: A novel model evaluation approach focussing on local and advected contributions to urban PM 2.5 levels – application to Paris, France Geoscientific Model Development Discussions, 6, 6391-6457, 2013 Author(s): H. Petetin, M. Beekmann, J. Sciare, M. Bressi, A. Rosso, O. Sanchez, and V. Ghersi Aerosol simulations in chemistry transport models (CTMs) still suffer from numerous uncertainties, and diagnostic evaluations are required to point out major error sources. This paper presents an original approach to evaluate CTMs based on local and imported contributions in a large megacity rather than urban background concentrations. The study is applied to the CHIMERE model in the Paris region (France) and considers the fine particulate matter (PM 2.5 ) and its main chemical constituents (elemental and organic carbon, nitrate, sulfate and ammonium), for which daily measurements are available during a whole year at various stations (PARTICULES project). Back-trajectory data are used to locate the upwind station, from which the concentration is identified as the import, the local production being deduced from the urban concentration by subtraction. Uncertainties on these contributions are quantified. Small biases in urban background PM 2.5 simulations (bias of +16%) hide significant error compensations between local and advected contributions, as well as in PM 2.5 chemical compounds. In particular, wintertime OM imports appear strongly underestimated while local OM and EC production are overestimated all along the year. Erroneous continental woodburning emissions and missing SOA pathways may explain errors on advected OM, while carbonaceous compounds overestimation is likely to be related to errors in emissions and dynamics. A statistically significant local formation of nitrate is also highlighted from observations, but missed by the model. Together with the overestimation of nitrate imports, it leads to a bias of +51% on the local PM 2.5 contribution. Such an evaluation finally gives more detailed insights on major gaps in current CTMs on which future efforts are needed.

Description: Adding a dynamical cryosphere into i LOVECLIM (version 1.0) – Part 1: Coupling with the GRISLI ice-sheet model Geoscientific Model Development Discussions, 6, 5215-5249, 2013 Author(s): D. M. Roche, C. Dumas, M. Bügelmayer, S. Charbit, and C. Ritz We present the coupling approach and the first results of the GRISLI ice-sheet model within the i LOVECLIM coupled climate model. The climate component is a relatively low resolution Earth System Model of Intermediate complexity, well suited for long-term integrations and thus for coupled climate–cryosphere studies. We describe the coupling procedure with emphasise on the downscaling scheme and the methods to compute the snow fraction from total precipitation fields. We then present results for the Northern Hemisphere ice sheet (Greenland) under pre-industrial climate conditions at the end of a 14 000 yr-long integration. The obtained simulated ice sheet presents a too large thickness in central Greenland owing to the overestimation of precipitation in the atmospheric component. We find that including downscaling procedures for temperature improves the temperature distributions over Greenland for both summer and annual mean temperatures. Overall, we find an ice-sheet areal extent in reasonnable agreement with the observed Greenland ice sheet given the simplicity of the chosen climate model.

Description: ADISM v.1.0: an adjoint of a thermomechanical ice-sheet model obtained using an algorithmic differentiation tool Geoscientific Model Development Discussions, 6, 5251-5288, 2013 Author(s): J. McGovern, I. Rutt, J. Utke, and T. Murray A number of problems in contemporary glaciology could benefit from the application of adjoint models. On a simple level, adjoint models can be used to calculate ice-sheet sensitivities with respect to spatially varying parameters such as the basal sliding coefficient. At a more sophisticated level, adjoint models may be used as components of variational data assimilation schemes, allowing problems of model initialization and data-constrained evolution to be tackled. Fundamentally, adjoint models calculate the sensitivity of a cost function to a suite of control parameters. Such model sensitivities can alternatively be obtained by running the model many times, perturbing each control parameter separately in turn, and calculating the resulting sensitivity in each case. For large numbers of control parameters, however, such as the case where a control parameter corresponds to each point in the model domain, the computational cost becomes prohibitive. The use of adjoint models allows sensitivities to be obtained more efficiently – adjoint model sensitivities are obtained in a single run – and more accurately, since the differentiation of the model is done with machine precision. We present a finite-difference shallow ice approximation (SIA), thermomechanical ice-sheet model (the forward model), and its adjoint, as generated by using the OpenAD algorithmic differentiation tool. We verify the ice-sheet model using standard SIA benchmark tests and check the consistency between derivatives computed by OpenAD and certain numerically approximated derivatives. Typical adjoint calculations are demonstrated by application to the Greenland ice sheet.

Description: Earth System Models that simulate crops underestimate CO 2 emissions from land use by neglecting soil disturbance due to cultivation Geoscientific Model Development Discussions, 6, 6639-6658, 2013 Author(s): S. Levis, M. D. Hartman, and G. B. Bonan The Community Land Model (CLM) can simulate planting and harvesting of crops but does not include effects of cultivation on soil carbon decomposition. The biogeochemistry model DayCent does account for cultivation and provides a baseline for evaluating the CLM. With the goal of representing cultivation effects on soil carbon decomposition, we implemented the DayCent cultivation parameterization in the CLM and compared CLM and DayCent simulations at eight Midwestern United States sites with and without the cultivation parameterization. Cultivation decreases soil carbon by about 1350 g C m −2 in the CLM and 1660 g C m −2 in DayCent across the eight sites from first cultivation (early 1900s) to 2010. CLM crop simulations without cultivation have soil carbon gain, not loss, over this period, in contrast to the expected declining trends in agricultural soil carbon. A global cultivation simulation for 1973–2004 reduces ecosystem carbon by 0.4 Pg yr −1 over temperate corn, soybean, and cereal crop areas, which occupy approximately 1/3 of global crop area. Earth System Models may improve their atmospheric CO 2 and soil carbon simulations by accounting for enhanced decomposition from cultivation.

Description: Development of a plume-in-grid model for industrial point and volume sources: application to power plant and refinery sources in the Paris region Geoscientific Model Development Discussions, 6, 5863-5900, 2013 Author(s): Y. Kim, C. Seigneur, and O. Duclaux Plume-in-grid (PinG) models incorporating a host Eulerian model and a subgrid-scale model (usually a Gaussian plume or puff model) have been used for the simulations of stack emissions (e.g., fossil fuel-fired power plants and cement plants) for gaseous and particulate species such as nitrogen oxides (NO x ), sulfur dioxide (SO 2 ), particulate matter (PM) and mercury (Hg). Here, we describe the extension of a PinG model to study the impact of an oil refinery where volatile organic compound (VOC) emissions can be important. The model is based on a reactive PinG model for ozone (O 3 ), which incorporates a three-dimensional (3-D) Eulerian model and a Gaussian puff model. The model is extended to treat PM, with treatments of aerosol chemistry, particle size distribution, and the formation of secondary aerosols, which are consistent in both the 3-D Eulerian host model and the Gaussian puff model. Furthermore, the PinG model is extended to include the treatment of volume sources to simulate fugitive VOC emissions. The new PinG model is evaluated over Greater Paris during July 2009. Model performance is satisfactory for O 3 , PM 2.5 and most PM 2.5 components. Two industrial sources, a coal-fired power plant and an oil refinery, are simulated with the PinG model. The characteristics of the sources (stack height and diameter, exhaust temperature and velocity) govern the surface concentrations of primary pollutants (NO x , SO 2 and VOC). O 3 concentrations are impacted differently near the power plant than near the refinery, because of the presence of VOC emissions at the latter. The formation of sulfate is influenced by both the dispersion of SO 2 and the oxidant concentration; however, the former tends to dominate in the simulations presented here. The impact of PinG modeling on the formation of secondary organic aerosols (SOA) is small and results mostly from the effect of different oxidant concentrations on biogenic SOA formation. The investigation of the criteria for injecting plumes into the host model (fixed travel time and/or puff size) shows that a size-based criterion is recommended to treat the formation of secondary aerosols (sulfate, nitrate, and ammonium), in particular, farther downwind of the sources (from about 15 km). The impacts of the PinG modeling are less significant in a simulation with a coarse grid size (10 km) than with a fine grid size (2 km), because the concentrations of the species emitted from the PinG sources are relatively less important compared to background concentrations when injected into the host model.

Description: An orthogonal curvilinear terrain-following coordinate for atmospheric models Geoscientific Model Development Discussions, 6, 5801-5862, 2013 Author(s): Y. Li, B. Wang, and D. Wang We have designed an orthogonal curvilinear terrain-following coordinate (the orthogonal σ coordinate, or the OS coordinate) to overcome two well-known problems in the classic σ coordinate, namely, pressure gradient force (PGF) errors and advection errors. First, in the design of basis vectors, we rotate the basis vectors of the z coordinate in a particular way in order to reduce the PGF errors and add a special rotation parameter b to each rotation angel in order to reduce the advection errors. Second, the corresponding definition of each OS coordinate is solved through its basis vectors. Third, the scalar equations of the OS coordinate are solved by expanding the vector equation using the basis vectors. Since the computational form of PGF has only one term in each momentum equation of the OS coordinate, the PGF errors will be significantly reduced, according to Li et al. (2012). When a proper b is chosen, the σ levels over a steep terrain can be significantly smoothed, therefore alleviating the advection errors in the OS coordinate. This is demonstrated by a series of 2-D linear advection experiments under a unified framework.

Description: Verification of an ADER-DG method for complex dynamic rupture problems Geoscientific Model Development Discussions, 6, 5981-6034, 2013 Author(s): C. Pelties, A.-A. Gabriel, and J.-P. Ampuero We present thorough benchmarking of an arbitrary high-order derivative Discontinuous Galerkin (ADER-DG) method on unstructured meshes for advanced earthquake dynamic rupture problems. We validate the method in comparison to well-established numerical methods in a series of verification exercises, including dipping and branching fault geometries, heterogeneous initial conditions, bi-material cases and several rate-and-state friction constitutive laws. We show that the combination of meshing flexibility and high-order accuracy of the ADER-DG method makes it a competitive tool to study earthquake dynamics in complicated setups.

Description: Earth Orbit v2.1: a 3-D visualization and analysis model of Earth's orbit, Milankovitch cycles and insolation Geoscientific Model Development Discussions, 6, 5947-5980, 2013 Author(s): T. S. Kostadinov and R. Gilb Milankovitch theory postulates that periodic variability of Earth's orbital elements is a major climate forcing mechanism, causing, for example, the contemporary glacial-interglacial cycles. There are three Milankovitch orbital parameters: orbital eccentricity, precession and obliquity. The interaction of the amplitudes, periods and phases of these parameters controls the spatio-temporal patterns of incoming solar radiation (insolation) and the timing of the seasons with respect to perihelion. This complexity makes Earth–Sun geometry and Milankovitch theory difficult to teach effectively. Here, we present "Earth Orbit v2.1": an astronomically precise and accurate model that offers 3-D visualizations of Earth's orbital geometry, Milankovitch parameters and the ensuing insolation forcing. The model is developed in MATLAB® as a user-friendly graphical user interface. Users are presented with a choice between the Berger (1978a) and Laskar et al. (2004) astronomical solutions for eccentricity, obliquity and precession. A "demo" mode is also available, which allows the Milankovitch parameters to be varied independently of each other, so that users can isolate the effects of each parameter on orbital geometry, the seasons, and insolation. A 3-D orbital configuration plot, as well as various surface and line plots of insolation and insolation anomalies on various time and space scales are produced. Insolation computations use the model's own orbital geometry with no additional a priori input other than the Milankovitch parameter solutions. Insolation output and the underlying solar declination computation are successfully validated against the results of Laskar et al. (2004) and Meeus (1998), respectively. The model outputs some ancillary parameters as well, e.g. Earth's radius-vector length, solar declination and day length for the chosen date and latitude. Time-series plots of the Milankovitch parameters and EPICA ice core CO 2 and temperature data can be produced. Both research and pedagogical applications are envisioned for the model.

Description: Non-orthogonal version of the arbitrary polygonal C-grid and a new diamond grid Geoscientific Model Development Discussions, 6, 6035-6074, 2013 Author(s): H. Weller Quasi-uniform grids of the sphere have become popular recently since they avoid parallel scaling bottlenecks associated with the poles of latitude-longitude grids. However quasi-uniform grids of the sphere are often non-orthogonal. A version of the C-grid for arbitrary non-orthogonal grids is presented which gives some of the mimetic properties of the orthogonal C-grid. Exact energy conservation is sacrificed for improved accuracy and the resulting scheme numerically conserves energy and potential enstrophy well. The non-orthogonal nature means that the scheme can be used on a cubed sphere. The advantage of the cubed sphere is that it does not admit the computational modes of the hexagonal or triangular C-grids. On various shallow-water test cases the non-orthogonal scheme on a cubed sphere has accuracy less than or equal to the orthogonal scheme on an orthogonal hexagonal icosahedron. A new diamond grid is presented consisting of quasi-uniform quadrilaterals which is more orthogonal than the equal-angle cubed sphere but with otherwise similar properties. It performs better than the cubed sphere in every way and should be used instead in codes which allow a flexible grid structure.

Description: An evaluation of ambient ammonia concentrations over southern Ontario simulated with different dry deposition schemes within STILT-Chem v0.8 Geoscientific Model Development Discussions, 6, 6075-6115, 2013 Author(s): D. Wen, L. Zhang, J. C. Lin, R. Vet, and M. D. Moran A bi-directional air-surface exchange scheme for atmospheric ammonia was incorporated into the Stochastic Time-Inverted Lagrangian Transport air quality model (STILT-Chem v0.8). STILT-Chem v0.8 was then applied to simulate atmospheric ammonia concentrations at 53 measurement sites in the province of Ontario, Canada for a six-month period from 1 June to 30 November 2006. In addition to the bi-directional scheme, two uni-directional dry deposition schemes were tested. Comparisons of modeled ammonia concentrations against observations show that all three schemes can reasonably predict observations. For sites with low observed ammonia concentrations, the bi-directional scheme clearly overestimated ammonia concentrations. Although all three schemes tend to underestimate ammonia concentrations for locations with elevated observed concentrations, the bi-directional scheme performed better due mainly to its introduction of compensation points into flux calculation parameterizations. The results of additional sensitivity tests suggest that uncertainties in the input values of emission potentials in the bi-directional scheme greatly affect the accuracy of modeled ammonia concentrations. The use of much larger emission potentials than provided in the scheme is required for accurate prediction of elevated ammonia concentrations at intensive agricultural locations.

Description: Development of a new semi-empirical parameterization for below-cloud scavenging of size-resolved aerosol particles by both rain and snow Geoscientific Model Development Discussions, 6, 5901-5945, 2013 Author(s): X. Wang, L. Zhang, and M. D. Moran A parameter called the scavenging coefficient Λ is widely used in aerosol chemical transport models (CTMs) to describe below-cloud scavenging of aerosol particles by rain and snow. However, uncertainties associated with available size-resolved theoretical formulations for Λ span one to two orders of magnitude for rain scavenging and nearly three orders of magnitude for snow scavenging. Two recent reviews of below-cloud scavenging of size-resolved particles recommended that the upper range of the available theoretical formulations for Λ should be used in CTMs based on uncertainty analyses and comparison with limited field experiments. Following this recommended approach, a new semi-empirical parameterization for size-resolved Λ has been developed for below-cloud scavenging of atmospheric aerosol particles by both rain (Λ rain ) and snow (Λ snow ). The new parameterization is based on the 90th percentile of Λ values from an ensemble data set containing calculated using all possible "realizations" of available theoretical Λ formulas and covering a large range of aerosol particle sizes and precipitation intensities ( R ). For any aerosol particle size of diameter d, a strong linear relationship between the 90th-percentile log 10 (Λ) and log 10 ( R ), which is equivalent to a power-law relationship between Λ and R , is identified. The log-linear relationship, which is characterized by two parameters (slope and y-intercept), is then further parameterized by fitting these two parameters as polynomial functions of aerosol size d . A comparison of the new parameterization with limited measurements in the literature in terms of the magnitude of Λ and the relative magnitudes of Λ rain and Λ snow suggests that it is a reasonable approximation. Advantages of this new semi-empirical parameterization compared to traditional theoretical formulations for Λ include its applicability to below-cloud scavenging by both rain and snow over a wide range of particle sizes and precipitation intensities, ease of implementation in any CTM with a representation of size-distributed particulate matter, and a known representativeness based on the consideration in its development of all available theoretical formulations and field-derived estimates for Λ( d ) and their associated uncertainties.

Description: Assessing the CAM5 physics suite in the WRF-Chem model: implementation, evaluation, and resolution sensitivity Geoscientific Model Development Discussions, 6, 6157-6218, 2013 Author(s): P.-L. Ma, P. J. Rasch, J. D. Fast, R. C. Easter, W. I. Gustafson Jr., X. Liu, S. J. Ghan, and B. Singh A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with Chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem, provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

Description: Evaluating CaCO 3 -cycle modules in coupled global biogeochemical ocean models Geoscientific Model Development Discussions, 6, 6117-6155, 2013 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 remineralisation 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 remineralisation, 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. It 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 modeled true TA * and diagnosed TA * was below 10% (25%) in 73% (81%) of the ocean's volume. In the Pacific (and Indian) Oceans the RMS error of TA * 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: Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts Geoscientific Model Development Discussions, 6, 6219-6278, 2013 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 seas regimes using the NEMO 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 and at 1/12° resolution in the North Atlantic, Indian Ocean and Mediterranean Sea. 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 3D-Var, assimilation scheme (NEMOVAR); coupling to a different, multi-thickness-category, sea ice model (CICE); the use of 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 yr reanalysis integrations of the Global FOAM configuration including an assessment of 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 highlight specific areas upon which to focus future improvements.

Description: Equivalent sensor radiance generation and remote sensing from model parameters – Part 1: Equivalent sensor radiance formulation Geoscientific Model Development Discussions, 6, 4105-4136, 2013 Author(s): G. Wind, A. M. da Silva, P. M. Norris, and S. Platnick In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate). The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Description: An improved parameterization of tidal mixing for ocean models Geoscientific Model Development Discussions, 6, 4475-4509, 2013 Author(s): A. Schmittner and G. D. Egbert Two modifications to an existing scheme of tidal mixing are implemented in the coarse resolution ocean component of a global climate model. First, the vertical distribution of energy flux out of the barotropic tide is determined using high resolution bathymetry. This shifts the levels of mixing higher up in the water column and leads to a stronger mid-depth meridional overturning circulation in the model. Second, the local dissipation efficiency for diurnal tides is assumed to be larger than that for the semi-diurnal tides poleward of 30°. Both modifications are shown to improve agreement with observational estimates of diapycnal diffusivities based on microstructure measurements and circulation indices. We also assess impacts of different spatial distribution of the barotropic energy loss. Estimates based on satellite altimetry lead to larger diffusivities in the deep ocean and hence a stronger deep overturning circulation in our climate model that is in better agreement with observations compared to those based on a tidal model.

Description: divand-1.0: n -dimensional variational data analysis for ocean observations Geoscientific Model Development Discussions, 6, 4009-4051, 2013 Author(s): A. Barth, J.-M. Beckers, C. Troupin, A. Alvera-Azcárate, and L. Vandenbulcke A tool for multidimensional variational analysis (divand) is presented. It allows the interpolation and analysis of observations on curvilinear orthogonal grids in an arbitrary high dimensional space by minimizing a cost function. This cost function penalizes the deviation from the observations, the deviation from a first guess and abruptly varying fields based on a given correlation length (potentially varying in space and time). Additional constraints can be added to this cost function such as an advection constraint which forces the analysed field to align with the ocean current. The method decouples naturally disconnected areas based on topography and topology. This is useful in oceanography where disconnected water masses often have different physical properties. Individual elements of the a priori and a posteriori error covariance matrix can also be computed, in particular expected error variances of the analysis. A multidimensional approach (as opposed to stacking 2-dimensional analysis) has the benefit of providing a smooth analysis in all dimensions, although the computational cost it increased. Primal (problem solved in the grid space) and dual formulations (problem solved in the observational space) are implemented using either direct solvers (based on Cholesky factorization) or iterative solvers (conjugate gradient method). In most applications the primal formulation with the direct solver is the fastest, especially if an a posteriori error estimate is needed. However, for correlated observation errors the dual formulation with an iterative solver is more efficient. The method is tested by using pseudo observations from a global model. The distribution of the observations is based on the position of the ARGO floats. The benefit of the 3-dimensional analysis (longitude, latitude and time) compared to 2-dimensional analysis (longitude and latitude) and the role of the advection constraint are highlighted. The tool divand is free software, and is distributed under the terms of the GPL license ( http://modb.oce.ulg.ac.be/mediawiki/index.php/divand ).

Description: The Finite Element Sea ice-Ocean Model (FESOM): formulation of an unstructured-mesh ocean general circulation model Geoscientific Model Development Discussions, 6, 3893-3976, 2013 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 it provides an excellent platform for further developments required to advance the field of climate modelling on unstructured meshes.

Description: The North American Carbon Program Multi-scale synthesis and Terrestrial Model Intercomparison Project – Part 1: Overview and experimental design Geoscientific Model Development Discussions, 6, 3977-4008, 2013 Author(s): D. N. Huntzinger, C. Schwalm, A. M. Michalak, K. Schaefer, A. W. King, Y. Wei, A. Jacobson, S. Liu, R. B. Cook, W. M. Post, G. Berthier, D. Hayes, M. Huang, A. Ito, H. Lei, C. Lu, J. Mao, C. H. Peng, S. Peng, B. Poulter, D. Riccuito, X. Shi, H. Tian, W. Wang, N. Zeng, F. Zhao, and Q. Zhu Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding of land-atmosphere carbon exchange to larger regions. The North American Carbon Program (NACP) Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal model intercomparison and evaluation effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. MsTMIP builds upon current and past synthesis activities, and has a unique framework designed to isolate, interpret, and inform understanding of how model structural differences impact estimates of carbon uptake and release. Here we provide an overview of the MsTMIP effort and describe how the MsTMIP experimental design enables the assessment and quantification of TBM structural uncertainty. Model structure refers to the types of processes considered (e.g. nutrient cycling, disturbance, lateral transport of carbon), and how these processes are represented (e.g. photosynthetic formulation, temperature sensitivity, respiration) in the models. By prescribing a common experimental protocol with standard spin-up procedures and driver data sets, we isolate any biases and variability in TBM estimates of regional and global carbon budgets resulting from differences in the models themselves (i.e. model structure) and model-specific parameter values. An initial intercomparison of model structural differences is represented using hierarchical cluster diagrams (a.k.a. dendrograms), which highlight similarities and differences in how models account for carbon cycle, vegetation, energy, and nitrogen cycle dynamics. We show that, despite the standardized protocol used to derive initial conditions, models show a high degree of variation for GPP, total living biomass, and total soil carbon, underscoring the influence of differences in model structure and parameterization on model estimates.

Description: Evaluating the performance of SURFEXv5 as a new land surface scheme for the ALADINcy36 and ALARO-0 models Geoscientific Model Development Discussions, 6, 4053-4104, 2013 Author(s): R. Hamdi, D. Degrauwe, A. Duerinckx, J. Cedilnik, V. Costa, T. Dalkilic, K. Essaouini, M. Jerczynki, F. Kocaman, L. Kullmann, J.-F. Mahfouf, F. Meier, M. Sassi, S. Schneider, F. Váňa, and P. Termonia The newly developed land surface scheme SURFEX (Surface Externalisée) is implemented into a limited area numerical weather prediction model running operationally in a number of countries of the ALADIN and HIRLAM consortia. The primary question addressed is the ability of SURFEX to be used as a new land surface scheme and thus assessing its potential use in an operational configuration instead of the original ISBA (Interactions between Soil, Biosphere, and Atmosphere) scheme. The results show that the introduction of SURFEX either gives improvements or neutral impact on the 2 m temperature, 2 m relative humidity, and 10 m wind. However, it seems that SURFEX has a tendency to produce higher maximum temperatures at high elevation stations during winter daytime which degrades the scores. In addition, surface radiative and energy fluxes improve compared to observations from the Cabauw tower. The results also show that promising improvements with a demonstrated positive impact are achieved by introducing the Town Energy Balance (TEB) scheme. It was found that the use of SURFEX has a neutral impact on the precipitation scores. However, the implementation of TEB within SURFEX for a high resolution run tends to cause rainfall to be locally concentrated and the total accumulated precipitation decreases obviously during the summer. One of the novel features developed in SURFEX is the availability of a more advanced surface data assimilation using the Extended Kalman Filter. The results over Belgium show that the forecast scores are similar between the Extended Kalman Filter and the classical Optimal Interpolation scheme. Finally, concerning the upper air scores, the introduction of SURFEX either gives improvement or neutral impact in the free atmosphere.

Description: Automating the solution of PDEs on the sphere and other manifolds in FEniCS 1.2 Geoscientific Model Development Discussions, 6, 3557-3614, 2013 Author(s): M. E. Rognes, D. A. Ham, C. J. Cotter, and A. T. T. McRae Differential equations posed over immersed manifolds are of particular importance in studying geophysical flows; for instance, ocean and atmosphere simulations crucially rely on the capability to solve equations over the sphere. This paper presents the extension of the FEniCS software components to the automated solution of finite element formulations of differential equations defined over general, immersed manifolds. We describe the implementation and in particular detail how the required extensions essentially reduce to the extension of the FEniCS form compiler to cover this case. The resulting implementation has all the properties of the FEniCS pipeline and we demonstrate its flexibility by an extensive range of numerical examples covering a number of geophysical benchmark examples and test cases. The results are all in agreement with the expected values. The description here relates to DOLFIN/FEniCS 1.2.

Description: The Lagrangian particle dispersion model FLEXPART-WRF version 3.0 Geoscientific Model Development Discussions, 6, 3615-3654, 2013 Author(s): J. Brioude, D. Arnold, A. Stohl, M. Cassiani, D. Morton, P. Seibert, W. Angevine, S. Evan, A. Dingwell, J. D. Fast, R. C. Easter, I. Pisso, J. Burkhart, and G. Wotawa The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. This multiscale need has encouraged new developments in FLEXPART. In this document, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run and present special options and features that differ from its predecessor versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format with efficient data compression. In addition, test case data and the source code are provided to the reader as Supplement. This material and future developments will be accessible at http://www.flexpart.eu .

Description: Can we model observed soil carbon changes from a dense inventory? A case study over england and wales using three version of orchidee ecosystem model (AR5, AR5-PRIM and O-CN) Geoscientific Model Development Discussions, 6, 3655-3680, 2013 Author(s): B. Guenet, F. E Moyano, N. Vuichard, G.J.D. Kirk, P.H. Bellamy, S. Zaehle, and P. Ciais A widespread decrease of the top soil carbon content was observed over England and Wales during the period 1978–2003 in the National Soil Inventory (NSI), amounting to a carbon loss of 4.44 Tg yr -1 over 141 550 km 2 . Subsequent modelling studies have shown that changes in temperature and precipitation could only account for a small part of the observed decrease, and therefore that changes in land use and management and resulting changes in soil respiration or primary production were the main causes. So far, all the models used to reproduce the NSI data did not account for plant-soil interactions and were only soil carbon models with carbon inputs forced by data. Here, we use three different versions of a process-based coupled soil-vegetation model called ORCHIDEE, in order to separate the effect of trends in soil carbon input, and soil carbon mineralisation induced by climate trends over 1978–2003. The first version of the model (ORCHIDEE-AR5) used for IPCC-AR5 CMIP5 Earth System simulations, is based on three soil carbon pools defined with first order decomposition kinetics, as in the CENTURY model. The second version (ORCHIDEE-AR5-PRIM) built for this study includes a relationship between litter carbon and decomposition rates, to reproduce a priming effect on decomposition. The last version (O-CN) takes into account N-related processes. Soil carbon decomposition in O-CN is based on CENTURY, but adds N limitations on litter decomposition. We performed regional gridded simulations with these three versions of the ORCHIDEE model over England and Wales. None of the three model versions was able to reproduce the observed NSI soil carbon trend. This suggests that either climate change is not the main driver for observed soil carbon losses, or that the ORCHIDEE model even with priming or N-effects on decomposition lacks the basic mechanisms to explain soil carbon change in response to climate, which would raise a caution flag about the ability of this type of model to project soil carbon changes in response to future warming. A third possible explanation could be that the NSI measurements made on the topsoil are not representative of the total soil carbon losses integrated over the entire soil depth, and thus cannot be compared with the model output.

Description: Using the UM dynamical cores to reproduce idealised 3-D flows Geoscientific Model Development Discussions, 6, 3681-3741, 2013 Author(s): N. J. Mayne, I. Baraffe, D. M. Acreman, C. Smith, N. Wood, D. Skålid Amundsen, J. Thuburn, and D. R. Jackson We demonstrate that both the current (New Dynamics), and next generation (ENDGame) dynamical cores of the UK Met Office global circulation model, the UM, reproduce consistently, the long-term, large-scale flows found in several published idealised tests. The cases presented are the Held–Suarez test, a simplified model of Earth (including a stratosphere), and a model of a hypothetical Tidally Locked Earth (TLE). Furthermore, we show that using simplifications to the dynamical equations, which are expected to be justified for the physical domains and flow regimes we have studied, and which are supported by the ENDGame dynamical core, also produces matching long-term, large-scale flows. Finally, we present evidence for differences in the detail of the planetary (meridional) flows and circulations resulting from improvements in the ENDGame formulation over New Dynamics. Specifically, we find greater symmetry in the meridional circulations of the Tidally Locked Earth test case using the ENDGame formulation, which is a better match to our physical expectations of the flow for such a slowly rotating Earth-like system.

Description: CUDA-C implementation of the ADER-DG method for linear hyperbolic PDEs Geoscientific Model Development Discussions, 6, 3743-3786, 2013 Author(s): C. E. Castro, J. Behrens, and C. Pelties We implement the ADER-DG numerical method using the CUDA-C language to run the code in a Graphic Processing Unit (GPU). We focus on solving linear hyperbolic partial differential equations where the method can be expressed as a combination of precomputed matrix multiplications becoming a good candidate to be used on the GPU hardware. Moreover, the method is arbitrarily high-order involving intensive work on local data, a property that is also beneficial for the target hardware. We compare our GPU implementation against CPU versions of the same method observing similar convergence properties up to a threshold where the error remains fixed. This behaviour is in agreement with the CPU version but the threshold is larger that in the CPU case. We also observe a big difference when considering single and double precision where in the first case the threshold error is significantly larger. Finally, we did observe a speed up factor in computational time but this is relative to the specific test or benchmark problem.

Description: Incorporating grassland management in a global vegetation model: model description and evaluation at 11 eddy-covariance sites in Europe Geoscientific Model Development Discussions, 6, 2769-2812, 2013 Author(s): J. Chang, N. Viovy, N. Vuichard, P. Ciais, T. Wang, A. Cozic, R. Lardy, A.-I. Graux, K. Klumpp, R. Martin, and J.-F. Soussana This study describes how management of grasslands is included in the ORCHIDEE process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO 2 fluxes. The new model, ORCHIDEE-GM (Grassland Management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing, respectively. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can capture realistically the cut-induced seasonal variation in biometric variables (LAI: Leaf Area Index; AGB: Aboveground Biomass) and in CO 2 fluxes (GPP: Gross Primary Productivity; TER: Total Ecosystem Respiration; and NEE: Net Ecosystem Exchange). But improvements at grazing sites are only marginal in ORCHIDEE-GM, which relates to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. ORCHIDEE-GM is capable to model the net carbon balance (NBP) of managed grasslands better than ORCHIDEE, because the management module allows to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

Description: An approach to computing direction relations between separated object groups Geoscientific Model Development Discussions, 6, 3179-3210, 2013 Author(s): H. Yan, Z. Wang, and J. Li Direction relations between object groups play an important role in qualitative spatial reasoning, spatial computation and spatial recognition. However, none of existing models can be used to compute direction relations between object groups. To fill this gap, an approach to computing direction relations between separated object groups is proposed in this paper, which is theoretically based on Gestalt principles and the idea of multi-directions. The approach firstly triangulates the two object groups; and then it constructs the Voronoi Diagram between the two groups using the triangular network; after this, the normal of each Vornoi edge is calculated, and the quantitative expression of the direction relations is constructed; finally, the quantitative direction relations are transformed into qualitative ones. The psychological experiments show that the proposed approach can obtain direction relations both between two single objects and between two object groups, and the results are correct from the point of view of spatial cognition.

Description: Quantifying the carbon uptake by vegetation for Europe on a 1 km 2 resolution using a remote sensing driven vegetation model Geoscientific Model Development Discussions, 6, 2457-2489, 2013 Author(s): K. Wißkirchen, M. Tum, K. P. Günther, M. Niklaus, C. Eisfelder, and W. Knorr In this study we compare monthly gross primary productivity (GPP) time series (2000–2007), computed for Europe with the Biosphere Energy Transfer Hydrology (BETHY/DLR) model with monthly data from the eddy covariance measurements network FLUXNET. BETHY/DLR with a spatial resolution of 1 km 2 is designed for regional and continental applications (here Europe) and operated at the German Aerospace Center (DLR). It was adapted from the BETHY scheme to be driven by remote sensing data and meteorology. Time series of Leaf Area Index (LAI) are used to control the development of vegetation. These are taken from the CYCLOPES database. Meteorological time series are used to regulate meteorological seasonality. These comprise daily information on temperature, precipitation, wind-speed and radiation. Additionally, static maps such as land cover, elevation, and soil type are used. To validate our model results we used eddy covariance measurements from the FLUXNET network of 74 towers across Europe. For forest sites we found that our model predicts between 20% and 40% higher annual GPP sums. In contrast, for cropland sites BETHY/DLR results show about 18% less GPP than eddy covariance measurements. For grassland sites, between 10% more and 16% less GPP was calculated with BETHY/DLR. A mean total carbon uptake of 2.5 Pg C yr -1 (±0.17 Pg) was found for Europe. In addition, this study states on risks that arise from the comparison of modeled data to FLUXNET measurements and their interpretation width.

Description: Speeding up a Lagrangian ice microphysics code Geoscientific Model Development Discussions, 6, 3787-3817, 2013 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 (non-linear) ice nucleation process is only well represented, when a large number of SIPs is generated. We introduced a new stochastic nucleation implementation which reallistically 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 may well serve as an inspiration for developers of other Lagrangian particle tracking models. These efficiency measures reduce the computational costs of present cirrus studies and allow extending the temporal and spatial scales of upcoming studies.

Description: Evaluation of dust and trace metal estimates from the Community Multiscale Air Quality (CMAQ) model version 5.0 Geoscientific Model Development Discussions, 6, 1859-1899, 2013 Author(s): K. W. Appel, G. A. Pouliot, H. Simon, G. Sarwar, H. O. T. Pye, S. L. Napelenok, F. Akhtar, and S. J. Roselle The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transformation, transport and fate of the many different air pollutant species that comprise particulate matter (PM), including dust (or soil). The CMAQ model version 5.0 (CMAQv5.0) has several enhancements over the previous version of the model for estimating the emission and transport of dust, including the ability to track the specific elemental constituents of dust and have the model-derived concentrations of those elements participate in chemistry. The latest version of the model also includes a parameterization to estimate emissions of dust due to wind action. The CMAQv5.0 modeling system was used to simulate the entire year 2006 for the continental United States, and the model estimates were evaluated against daily surface based measurements from several air quality networks. The CMAQ modeling system generally did well replicating the observed soil concentrations in the western United States; however the model consistently overestimated the observed soil concentrations in the eastern United States, regardless of season. The performance of the individual trace metals was generally good at the rural network sites, with relatively small biases for Fe, Al, Si and Ti throughout the year, while Ca, K and Mn were overestimated and Mg underestimated. For the urban sites, Fe, Mg and Mn, while overestimated, had comparatively better performance throughout the year than the other trace metals, which were consistently overestimated, including very large overestimations of Al, Ti and Si in the fall. An underestimation of nighttime mixing in the urban areas appears to contribute to the overestimation of trace metals. Removing the anthropogenic fugitive dust (AFD) emissions and the effects of wind-blown dust (WBD) lowered the model soil concentrations. However, even with both AFD emissions and WBD effects removed, soil concentrations were still often overestimated, suggesting that there are other sources of errors in the modeling system that contribute to the overestimation of soil components. Efforts are underway to improve both the nighttime mixing in urban areas and the spatial and temporal distribution of dust related emissions sources in the emissions inventory.

Description: The Subgrid Importance Latin Hypercube Sampler (SILHS): a multivariate subcolumn generator Geoscientific Model Development Discussions, 6, 2137-2175, 2013 Author(s): V. E. Larson and D. P. Schanen Coarse-resolution climate and weather forecast models cannot accurately parameterize small-scale, non-linear processes without accounting for subgrid-scale variability. To do so, some models integrate over the subgrid variability analytically. Although analytic integration methods are attractive, they can be used only with physical parameterizations that have a sufficiently simple functional form. Instead, this paper introduces a method to integrate subgrid variability using a type of Monte-Carlo integration. The method generates subcolumns with suitable vertical correlations and feeds them into a microphysics parameterization. The subcolumn methodology is non-intrusive and can be used with a wide variety of physical parameterizations. Our subcolumn generator is multivariate, which is important for physical processes that involve two or more hydrometeor species, such as accretion of cloud droplets by rain drops. In order to reduce sampling noise in the integrations, our subcolumn generator employs two variance reduction methods, namely importance and stratified (Latin hypercube) sampling. For this reason, we name the subcolumn generator the Subgrid Importance Latin Hypercube Sampler (SILHS). This paper tests SILHS in interactive, single-column simulations of a marine stratocumulus case and a shallow cumulus case. The paper then compares simulations that use SILHS with those that use analytic integration. Although the SILHS solutions exhibit considerable noise from time step to time step, the noise is greatly damped in most of the time-averaged profiles.

Description: Automated tracking of shallow cumulus clouds in large domain, long duration Large Eddy Simulations Geoscientific Model Development Discussions, 6, 2287-2323, 2013 Author(s): T. Heus and A. Seifert This paper presents a method for feature tracking of fields of shallow cumulus convection in Large Eddy Simulations (LES) by connecting the projected cloud cover in space and time, and by accounting for splitting and merging of cloud objects. Existing methods tend to be either imprecise or, when using the full 3 dimensional spatial field, prohibitively expensive for large data sets. Compared to those 3-D methods, the current method reduces the memory footprint by up to a factor 100, while retaining most of the precision by correcting for splitting and merging events between different clouds. The precision of the algorithm is further enhanced by taking the vertical extent of the cloud into account. Furthermore, rain and subcloud thermals are also tracked, and links between clouds, their rain, and their subcloud thermals are made. The method compares well with results from the literature. Resolution and domain dependencies are also discussed. For the current simulations, the cloud size distribution converges for clouds larger than an effective resolution of 6Δx, and smaller than about 20% of the horizontal domains size.

Description: The Simulator of the Timing and Magnitude of Pollen Season (STaMPS) model: a pollen production model for regional emission and transport modeling Geoscientific Model Development Discussions, 6, 2325-2368, 2013 Author(s): T. R. Duhl, R. Zhang, A. Guenther, S. H. Chung, M. T. Salam, J. M. House, R. C. Flagan, E. L. Avol, F. D. Gilliland, B. K. Lamb, T. M. VanReken, Y. Zhang, and E. Salathé A pollen model that simulates the timing and production of wind-dispersed allergenic pollen by terrestrial, temperate vegetation has been developed to quantify how pollen occurrence may be affected by climate change and to investigate how pollen can interact with anthropogenic pollutants to affect human health. The Simulator of the Timing and Magnitude of Pollen Season (STaMPS) model is driven by local meteorological conditions and is designed to be sensitive to climate shifts, as well as flexible with respect to the vegetation species and plant functional types (trees, grasses, etc.) represented and the climate zones simulated. The initial focus for the model is the simulation of the pollen emission potential of important allergenic tree and grass species that typically flower between March–June in Southern California (S. CA), which is characterized by moderate Mediterranean and oceanic climate zones as well as regions of arid desert and arid steppe. Vegetation cover and species composition data are obtained from numerous datasets and a database of allergenic vegetation species, their pollen production potential and relative allergenicities has been developed. For the selected allergenic species and spring-early summer simulation period, temperature is the main driver controlling the timing of pollen release, while precipitation (and temperature, for some species) controls the magnitude of pollen produced. The model provides species-specific pollen potential maps for each day of the simulation period; these are then used by a pollen transport model to simulate ambient pollen concentrations as described in a companion paper (Zhang et al., 2013a), which also presents model evaluation results for the S. CA model domain. The STaMPS model was also used to quantify the possible impact of climate change on pollen season under the IPCC SRES A1B scenario as simulated by the ECHAM5 global climate model. Current (1995–2004) and future (2045–2054) meteorological conditions downscaled using the Weather Research and Forecasting (WRF) model were used to drive STaMPS and generate estimates of the relative magnitude and timing of pollen season for important allergenic tree and grass species that bloom from March through June in a larger domain that covers all of CA and Nevada. Differences in the simulated timing and magnitude of pollen season for the selected allergenic species under current and future climate scenarios are presented. The results suggest that across all of the simulated species, pollen season starts an average of 5–6 days earlier under predicted future climatic conditions with an associated average annual domain-wide temperature increase of about 1°C compared to simulated current conditions. Differences in the amount of pollen produced under the two scenarios vary by species and are affected by the selected simulation period (1 March–30 June). Uncertainties associated with the STaMPS model and future model development plans are also discussed.

Description: Evaluation of the new UKCA climate-composition model – Part 2: The Troposphere Geoscientific Model Development Discussions, 6, 1743-1857, 2013 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, 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 re-distributing 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 steadily rise 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: The mathematics of the total alkalinity– p H equation: pathway to robust and universal solution algorithms Geoscientific Model Development Discussions, 6, 2087-2136, 2013 Author(s): G. Munhoven The total alkalinity– p H equation, which relates total alkalinity and p H for a given set of total concentrations of the acid-base systems that contribute to total alkalinity in a given water sample, is reviewed and its mathematical properties established. We prove that the equation function is strictly monotone and always has exactly one positive root. Different commonly used approximations are discussed and compared. An original method to derive appropriate initial values for the iterative solution of the cubic polynomial equation based upon carbonate-borate-alkalinity is presented. We then review different methods that have been used to solve the total alkalinity– p H equation, with a main focus on biogeochemical models. The shortcomings and limitations of these methods are made out and discussed. We then present two variants of a new, robust and universally convergent algorithm to solve the total alkalinity– p H equation. This algorithm does not require any a priori knowledge of the solution. The iterative procedure is shown to converge from any starting value to the physical solution. The extra computational cost for the convergence security is only 10–15% compared to the fastest algorithm in our test series.

Description: A method to represent ozone response to large changes in precursor emissions using high-order sensitivity analysis in photochemical models Geoscientific Model Development Discussions, 6, 2585-2608, 2013 Author(s): G. Yarwood, C. Emery, J. Jung, U. Nopmongcol, and T. Sakulyanotvittaya Photochemical grid models (PGMs) are used to simulate tropospheric ozone and quantify its response to emission changes. PGMs are often applied for annual simulations to provide both maximum concentrations for assessing compliance with air quality standards and frequency distributions for assessing human exposure. Efficient methods for computing ozone at different emission levels can improve the quality of ozone air quality management efforts. This study demonstrates the feasibility of using the decoupled direct method (DDM) to calculate first- and second-order sensitivity of ozone to anthropogenic NOx and VOC emissions in annual PGM simulations at continental scale. Algebraic models are developed that use Taylor series to produce complete annual frequency distributions of hourly ozone at any location and any anthropogenic emission level between zero and 100%, adjusted independently for NOx and VOC. We recommend computing the sensitivity coefficients at the mid-point of the emissions range over which they are intended to be applied, in this case with 50% anthropogenic emissions. The algebraic model predictions can be improved by combining sensitivity coefficients computed at 10% and 50% anthropogenic emissions. Compared to brute force simulations, algebraic model predictions tend to be more accurate in summer than winter, at rural than urban locations, and with 100% than zero anthropogenic emissions. Equations developed to combine sensitivity coefficients computed with 10% and 50% anthropogenic emissions are able to reproduce brute force simulation results with zero and 100% anthropogenic emissions with mean bias less than 2 ppb and mean error less than 3 ppb averaged over 22 US cities.

Description: Evaluation of the United States National Air Quality Forecast Capability experimental real-time predictions in 2010 using Air Quality System ozone and NO 2 measurements Geoscientific Model Development Discussions, 6, 2609-2654, 2013 Author(s): T. Chai, H.-C. Kim, P. Lee, D. Tong, L. Pan, Y. Tang, J. Huang, J. McQueen, M. Tsidulko, and I. Stajner The National Air Quality Forecast Capability (NAQFC) project provides the US with operational and experimental real-time ozone predictions using two different versions of the three-dimensional Community Multi-scale Air Quality (CMAQ) Modeling System. Routine evaluation using near-real-time AIRNow ozone measurements through 2011 showed better performance of the operational ozone predictions. In this work, quality-controlled and -assured Air Quality System (AQS) ozone and nitrogen dioxide (NO 2 ) observations are used to evaluate the experimental predictions in 2010, with a view towards their improvement. It is found that both ozone and NO 2 are overestimated over the contiguous US (CONUS), with annual biases of +5.6 ppbv and +5.1 ppbv, respectively. The annual root mean square errors (RMSEs) are 15.4 ppbv for ozone and 13.4 ppbv for NO 2 . For both species the over-predictions are most pronounced in the summer. The locations of the AQS monitoring sites are also utilized to stratify comparisons by the degree of urbanization. Comparisons for six predefined US regions show the highest annual biases for ozone predictions in Southeast (+10.5 ppbv) and for NO 2 in the Lower Middle (+8.1 ppbv) and Pacific Coast (+7.1 ppbv) regions. The spatial distributions of the NO 2 biases in July and August show distinctively high values in Los Angeles, Houston, and New Orleans areas. In addition to the standard statistics metrics, daily maximum eight-hour ozone categorical statistics are calculated using the current US ambient air quality standard (75 ppbv) and another lower threshold (70 ppbv). Using the 75 ppbv standard, the hit rate and proportion of correct over CONUS for the entire year are 0.64 and 0.96, respectively. Summertime biases show distinctive weekly patterns for ozone and NO 2 . Diurnal comparisons show that ozone overestimation is most severe in the morning, from 07:00 to 10:00 local time. For NO 2 , the morning predictions agree with the AQS observations reasonably well, but night-time concentrations are over-predicted by around 100%. Based on the analysis presented here, experimental ozone prediction system was updated for summer 2012.

Description: A priori selection and data-based skill assessment of reanalysis data as predictors for daily air temperature on a glaciated, tropical mountain range Geoscientific Model Development Discussions, 6, 2883-2925, 2013 Author(s): M. Hofer, B. Marzeion, and T. Mölg This study presents an empirical-statistical downscaling (ESD) method for high-altitude, glaciated mountain sites. In the ESD model validation emphasis is put on appropriately considering the pitfalls of small observational data records that are typical of high mountains. An application example is shown with daily mean air temperature time series on a glaciated mountain range (Cordillera Blanca, Peru) as target variables, and an ensemble of reanalyses air temperature time series as "a priori" predictor (i.e. a predictor selected without preceding data analysis). Results reveal strong seasonal variations of the predictor's performance. With increasing data availability, the skill tends to increase. Similarly for lower temporal resolutions, the skill increases. Applied to a choice of different atmospheric reanalysis predictor variables, the ESD model identifies only air temperature and geopotential height as significant predictors with regard to local-scale air temperature variability. Accounting for natural periodicity in the data is vital in the ESD procedure to avoid spuriously high performances of certain predictors, which is demonstrated for 2 m air temperature versus air temperature in the pressure level close to the mountain station site.

Description: Development and exploitation of a controlled vocabulary in support of climate modelling Geoscientific Model Development Discussions, 6, 2967-3001, 2013 Author(s): M.-P. Moine, S. Valcke, B. N. Lawrence, C. Pascoe, R. W. Ford, A. Alias, V. Balaji, P. Bentley, G. Devine, 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 re-use and should find applicability in many more projects.

Description: Test of validity of a dynamic soil carbon model using data from leaf litter decomposition in a West African tropical forest Geoscientific Model Development Discussions, 6, 3003-3032, 2013 Author(s): G. H. S. Guendehou, J. Liski, M. Tuomi, M. Moudachirou, B. Sinsin, and R. Mäkipää We evaluated the applicability of the dynamic soil carbon model Yasso07 in tropical conditions in West Africa by simulating the litter decomposition process using as required input into the model litter mass, litter quality, temperature and precipitation collected during a litterbag experiment. The experiment was conducted over a six-month period on leaf litter of five dominant tree species, namely Afzelia africana, Anogeissus leiocarpa, Ceiba pentandra, Dialium guineense and Diospyros mespiliformis in a semi-deciduous vertisol forest in Southern Benin. Since the predictions of Yasso07 were not consistent with the observations on mass loss and chemical composition of litter, Yasso07 was fitted to the dataset composed of global data and the new experimental data from Benin. The re-parameterized versions of Yasso07 had a good predictive ability and refined the applicability of the model in Benin to estimate soil carbon stocks, its changes and CO 2 emissions from heterotrophic respiration as main outputs of the model. The findings of this research support the hypothesis that the high variation of litter quality observed in the tropics is a major driver of the decomposition and needs to be accounted in the model parameterization.

Description: A bulk parameterization of melting snowflakes with explicit liquid water fraction for the COSMO model version 4.14 Geoscientific Model Development Discussions, 6, 2927-2966, 2013 Author(s): C. Frick, A. Seifert, and H. Wernli A new snow melting parameterization is presented for the non-hydrostatic limited-area COSMO ("consortium for small-scale modelling") model version 4.14. In contrast to the standard cloud microphysics of the COSMO model, which instantaneously transfers the meltwater from the snow to the rain category, the new scheme explicitly considers the liquid water fraction of the melting snowflakes. These semi-melted hydrometeors have characteristics (e.g., shape and fall speed) that differ from those of dry snow and rain droplets. Where possible, theoretical considerations and results from vertical wind tunnel laboratory experiments of melting snowflakes are used as the basis for characterizing the melting snow as a function of its liquid water fraction. These characteristics include the capacitance, the ventilation coefficient, and the terminal fall speed. For the bulk parameterization, a critical diameter is introduced. It is assumed that particles smaller than this diameter, which increases during the melting process, have completely melted, i.e., they are converted to the rain category. The values of the bulk integrals are calculated with a finite difference method and approximatively represented by polynomial functions, which allows an efficient implementation of the parameterization. Two case studies of (wet) snowfall in Germany are presented to illustrate the potential of the new snow melting parameterization. It is shown that the new scheme (i) produces wet snow instead of rain in some regions with surface temperatures slightly above the freezing point, (ii) simulates realistic atmospheric melting layers with a gradual transition from dry snow to melting snow to rain, and (iii) leads to a slower snow melting process. In the future, it will be important to thoroughly validate the scheme, also with radar data and to further explore its potential for improved surface precipitation forecasts for various meteorological conditions.

Description: Scheme for calculation of multi-layer cloudiness and precipitation for climate models of intermediate complexity Geoscientific Model Development Discussions, 6, 3241-3287, 2013 Author(s): A. V. Eliseev, D. Coumou, A. V. Chernokulsky, V. Petoukhov, and S. Petri In this study we present a scheme for calculating the characteristics of multi-layer cloudiness and precipitation for climate models of intermediate complexity (EMICs). This scheme considers three-layer stratiform cloudiness and single column convective clouds. It distinguishes between ice and droplet clouds as well. Precipitation is calculated by using cloud life time, which depends on cloud type and phase as well as on statistics of synoptic and convective disturbances. The scheme is tuned to observations by using an ensemble simulation forced by the ERA-40-derived climatology for 1979–2001. Upon calibration, the scheme realistically reproduces basic features of fields of cloud amounts, cloud water path, and precipitation. The simulated globally and annually averaged total cloud amount is 0.59, and the simulated globally averaged annual precipitation is 109 cm yr -1 . Both values agree with empirically-derived values. Geographical distribution and seasonal changes of calculated variables are broadly realistic as well. However, some important regional biases still remain in the scheme.

Description: GO5.0: The joint NERC-Met Office NEMO global ocean model for use in coupled and forced applications Geoscientific Model Development Discussions, 6, 5747-5799, 2013 Author(s): A. Megann, D. Storkey, Y. Aksenov, S. Alderson, D. Calvert, T. Graham, P. Hyder, J. Siddorn, and B. Sinha We describe a new Global Ocean standard configuration (GO5.0) at eddy-permitting resolution, developed jointly between the National Oceanography Centre and the Met Office as part of the Joint Ocean Modelling Programme (JOMP). This programme is a working group of the UK's National Centre for Ocean Forecasting (NCOF) and part of the Joint Weather and Climate Research Programme (JWCRP). The configuration has been developed with the seamless approach to modelling in mind for ocean modelling across timescales and for a range of applications, from short-range ocean forecasting through seasonal forecasting to climate predictions as well as research use. The GO5.0 configuration has been coupled with sea-ice (GSI5.0), atmosphere (GA5.0) and land-surface (GL5.0) configurations to form a standard coupled global model (GC1). The GO5.0 model will become the basis for the ocean model component of the Forecasting Ocean Assimilation Model, which provides forced short-range forecasting services. The global coupled model (GC1) or future releases of it will be used in coupled short-range ocean forecasting, seasonal forecasting, decadal prediction and for climate prediction as part of the UK Earth System Model. A 30 yr integration of GO5.0, run with CORE2 surface forcing from 1976 to 2005, is described, and the performance of the model in the final ten years of the integration is evaluated against observations and against a comparable integration of an earlier configuration, GO1. An additional set of 10 yr sensitivity studies, carried out to attribute changes in the model performance to individual changes in the model physics, is also analysed. GO5.0 is found to have substantially reduced subsurface drift above the depth of the thermocline relative to GO1, and also shows a significant improvement in the representation of the annual cycle of surface temperature and mixed-layer depth.

Description: The regional MiKlip decadal forecast ensemble for Europe Geoscientific Model Development Discussions, 6, 5711-5745, 2013 Author(s): S. Mieruch, H. Feldmann, G. Schädler, C.-J. Lenz, S. Kothe, and C. Kottmeier Funded by the German Ministry for Education and Research (BMBF) a major research project called MiKlip (Mittelfristige Klimaprognose, Decadal Climate Prediction) was launched and global as well as regional predictive ensemble hindcasts have been generated. The aim of the project is to demonstrate for past climate change whether predictive models have the capability of predicting climate on time scales of decades. This includes the development of a decadal forecast system, on the one hand to support decision making for economy, politics and society for decadal time spans. On the other hand, the scientific aspect is to explore the feasibility and prospects of global and regional forecasts on decadal time scales. The focus of this paper lies on the description of the regional hindcast ensemble for Europe generated by COSMO-CLM and on the assessment of the decadal variability and predictability against observations. To measure decadal variability we remove the long term bias as well as the long term linear trend from the data. Further, we applied low pass filters to the original data to separate the decadal climate signal from high frequency noise. The decadal variability and predictability assessment is applied to temperature and precipitation data for the summer and winter half-year averages/sums. The best results have been found for the prediction of decadal temperature anomalies, i.e. we have detected a distinct predictive skill and reasonable reliability. Hence it is possible to predict regional temperature variability on decadal timescales, However, the situation is less satisfactory for precipitation. Here we have found regions showing good predictability, but also regions without any predictive skill.

Description: A semi-implicit, second order accurate numerical model for multiphase underexpanded volcanic jets Geoscientific Model Development Discussions, 6, 399-452, 2013 Author(s): S. Carcano, L. Bonaventura, T. Esposti Ongaro, and A. Neri An improved version of the PDAC (Pyroclastic Dispersal Analysis Code, Esposti Ongaro et al., 2007) numerical model for the simulation of multiphase volcanic flows is presented and validated for the simulation of multiphase volcanic jets in supersonic regimes. The present version of PDAC includes second-order time and space discretizations and fully multidimensional advection discretizations, in order to reduce numerical diffusion and enhance the accuracy of the original model. The model is tested on the problem of jet decompression, in both two and three dimensions. For homogeneous jets, numerical results are consistent with experimental results at the laboratory scale (Lewis and Carlson, 1964). For non-equilibrium gas-particle jets, we consider monodisperse and bidisperse mixtures and we quantify non-equilibrium effects in terms of the ratio between the particle relaxation time and a characteristic jet time scale. For coarse particles and low particle load, numerical simulations well reproduce laboratory experiments and numerical simulations carried out with an Eulerian-Lagrangian model (Sommerfeld, 1993). At the volcanic scale, we consider steady-state conditions associated to the development of Vulcanian and sub-Plinian eruptions. For the finest particles produced in these regimes, we demonstrate that the solid phase is in mechanical and thermal equilibrium with the gas phase and that the jet decompression structure is well described by a pseudogas model (Ogden et al., 2008). Coarse particles, on the contrary, display significant non-equilibrium effects, associated to their larger relaxation time. Deviations from the equilibrium regime occur especially during the rapid acceleration phases and are able to appreciably modify the average jet dynamics, with maximum velocity and temperature differences of the order of 150 m s −1 and 80 K across shock waves.

Description: Calibration of the Crop model in the Community Land Model Geoscientific Model Development Discussions, 6, 379-398, 2013 Author(s): X. Zeng, B. A. Drewniak, and E. M. Constantinescu Farming is using more terrestrial ground with increases in population and the expanding use of agriculture for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurements of gross primary productivity and net ecosystem exchange from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper we calibrate these values in order to provide a faithful projection in terms of both plant development and net carbon exchange, using a Markov chain Monte Carlo technique.

Description: Coupling between the JULES land-surface scheme and the CCATT-BRAMS atmospheric chemistry model (JULES-CCATT-BRAMS1.0): applications to numerical weather forecasting and the CO 2 budget in South America Geoscientific Model Development Discussions, 6, 453-494, 2013 Author(s): D. S. Moreira, S. R. Freitas, J. P. Bonatti, L. M. Mercado, N. M. É. Rosário, K. M. Longo, J. B. Miller, M. Gloor, and L. V. Gatti This article presents the development of a new numerical system denominated JULES-CCATT-BRAMS, which resulted from the coupling of the JULES surface model to the CCATT-BRAMS atmospheric chemistry model. The performance of this system in relation to several meteorological variables (wind speed at 10 m, air temperature at 2 m, dew point temperature at 2 m, pressure reduced to mean sea level and 6 h accumulated precipitation) and the CO 2 concentration above an extensive area of South America is also presented, focusing on the Amazon basin. The evaluations were conducted for two periods, the wet (March) and dry (September) seasons of 2010. The statistics used to perform the evaluation included bias (BIAS) and root mean squared error (RMSE). The errors were calculated in relation to observations at conventional stations in airports and automatic stations. In addition, CO 2 concentrations in the first model level were compared with meteorological tower measurements and vertical CO 2 profiles were compared with aircraft data. The results of this study show that the JULES model coupled to CCATT-BRAMS provided a significant gain in performance in the evaluated atmospheric fields relative to those simulated by the LEAF (version 3) surface model originally utilized by CCATT-BRAMS. Simulations of CO 2 concentrations in Amazonia and a comparison with observations are also discussed and show that the system presents a gain in performance relative to previous studies. Finally, we discuss a wide range of numerical studies integrating coupled atmospheric, land surface and chemistry processes that could be produced with the system described here. Therefore, this work presents to the scientific community a free tool, with good performance in relation to the observed data and re-analyses, able to produce atmospheric simulations/forecasts at different resolutions, for any period of time and in any region of the globe.

Description: Forecasts covering one month using a cut cell model Geoscientific Model Development Discussions, 6, 625-643, 2013 Author(s): J. Steppeler, S.-H. Park, and A. Dobler This paper investigates the impact and potential use of the cut cell vertical discretisation for forecasts of 5 days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 by 6 forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut cell model LMZ provides a much more accurate representation of mountains on model forecasts than the terrain following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalaya, over South East China, Korea and Japan. The LMZ has been tested so far extensively for one-day forecasts on an European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut cell discretisation on forecast quality. The cut cell model is available only of an older (2003) Version of the model LM. It was compared using a control model differing by the use of the terrain following coordinate only. The cut cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved version of the terrain following model LM has been developed since then under the name CLM. The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of cut cell model were compared also to the CLM. As the cut cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalaya, the cut cell model improved the prediction of the monthly precipitation forecast even in comparison with the modern model version CLM considerably. The cut cell discretisation seems to improve in particular the localisation of precipitation, while the improvements leading from LM to CLM had a positive effect mainly on amplitude.

Description: A site-specific agricultural water requirement and footprint estimator (SPARE:WATER 1.0) for irrigation agriculture Geoscientific Model Development Discussions, 6, 645-684, 2013 Author(s): S. Multsch, Y. A. Al-Rumaikhani, H.-G. Frede, and L. Breuer The water footprint accounting method addresses the quantification of water consumption in agriculture, whereby three types of water to grow crops are considered, namely green water (consumed rainfall), blue water (irrigation from surface or groundwater) and grey water (water needed to dilute pollutants). Most of current water footprint assessments focus on global to continental scale. We therefore developed the spatial decision support system SPARE:WATER that allows to quantify green, blue and grey water footprints on regional scale. SPARE:WATER is programmed in VB.NET, with geographic information system functionality implemented by the MapWinGIS library. Water requirement and water footprints are assessed on a grid-basis and can then be aggregated for spatial entities such as political boundaries, catchments or irrigation districts. We assume in-efficient irrigation methods rather than optimal conditions to account for irrigation methods with efficiencies other than 100%. Furthermore, grey water can be defined as the water to leach out salt from the rooting zone in order to maintain soil quality, an important management task in irrigation agriculture. Apart from a thorough representation of the modelling concept we provide a proof of concept where we assess the agricultural water footprint of Saudi Arabia. The entire water footprint is 17.0 km 3 yr −1 for 2008 with a blue water dominance of 86%. Using SPARE:WATER we are able to delineate regional hot spots as well as crop types with large water footprints, e.g. sesame or dates. Results differ from previous studies of national-scale resolution, underlining the need for regional water footprint assessments.

Description: Sensitivity of remote aerosol distributions to representation of cloud-aerosol interactions in a global climate model Geoscientific Model Development Discussions, 6, 331-378, 2013 Author(s): H. Wang, R. C. Easter, P. J. Rasch, M. Wang, X. Liu, S. J. Ghan, Y. Qian, J.-H. Yoon, P.-L. Ma, and V. Velu Many global aerosol and climate models, including the widely used Community Atmosphere Model version 5 (CAM5), have large biases in predicting aerosols in remote regions such as upper troposphere and high latitudes. In this study, we conduct CAM5 sensitivity simulations to understand the role of key processes associated with aerosol transformation and wet removal affecting the vertical and horizontal long-range transport of aerosols to the remote regions. Improvements are made to processes that are currently not well represented in CAM5, which are guided by surface and aircraft measurements together with results from a multi-scale aerosol-climate model (PNNL-MMF) that explicitly represents convection and aerosol-cloud interactions at cloud-resolving scales. We pay particular attention to black carbon (BC) due to its importance in the Earth system and the availability of measurements. We introduce into CAM5 a new unified scheme for convective transport and aerosol wet removal with explicit aerosol activation above convective cloud base. This new implementation reduces the excessive BC aloft to better simulate observed BC profiles that show decreasing mixing ratios in the mid- to upper-troposphere. After implementing this new unified convective scheme, we examine wet removal of submicron aerosols that occurs primarily through cloud processes. The wet removal depends strongly on the sub-grid scale liquid cloud fraction and the rate of conversion of liquid water to precipitation. These processes lead to very strong wet removal of BC and other aerosols over mid- to high latitudes during winter months. With our improvements, the Arctic BC burden has a10-fold (5-fold) increase in the winter (summer) months, resulting in a much better simulation of the BC seasonal cycle as well. Arctic sulphate and other aerosol species also increase but to a lesser extent. An explicit treatment of BC aging with slower aging assumptions produces an additional 30-fold (5-fold) increase in the Arctic winter (summer) BC burden. This BC aging treatment, however, has minimal effect on other under-predicted species. Interestingly, our modifications to CAM5 that aim at improving prediction of high-latitude and upper tropospheric aerosols also produce much better aerosol optical depth over various other regions globally when compared to multi-year AERONET retrievals. The improved aerosol distributions have impacts on other aspects of CAM5, improving the simulation of global mean liquid water path and cloud forcing.

Description: Failure analysis of parameter-induced simulation crashes in climate models Geoscientific Model Development Discussions, 6, 585-623, 2013 Author(s): D. D. Lucas, R. Klein, J. Tannahill, D. Ivanova, S. Brandon, D. Domyancic, and Y. Zhang Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We apply support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicts model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC 〉 0.96). The causes of the simulation failures are determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations are the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Description: Four-dimensional evaluation of regional air quality models Geoscientific Model Development Discussions, 6, 521-584, 2013 Author(s): E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, V. Matthias, P. Grossi, K. W. Appel, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, and S. Galmarini The evaluation of regional air quality models is a challenging task, not only for the intrinsic complexity of the topic but also in view of the difficulties in finding sufficiently abundant, harmonized and time/space-well-distributed measurement data. This study, conducted in the framework of AQMEII (Air Quality Model Evaluation International Initiative), evaluates 4-D model predictions obtained from 15 modelling groups and relating to the air quality of the full year of 2006 over the North American and European continents. The modelled variables are ozone, CO, wind speed and direction, temperature, and relative humidity. Model evaluation is supported by the high quality in-flight measurements collected by instrumented commercial aircrafts in the context of the MOZAIC programme. The models are evaluated at five selected domains positioned around major airports, four in North America (Portland, Philadelphia, Atlanta, Dallas) and one in Europe (Frankfurt). Due to the extraordinary scale of the exercise (number of models and variables, spatial and temporal extent), this study is primarily aimed at illustrating the potential for using MOZAIC data for regional-scale evaluation and the capabilities of models to simulate concentration and meteorological fields in the vertical rather than just at the ground. We apply various approaches, metrics, and methods to analyze this complex dataset. Results of the investigation indicate that, while the observed meteorological fields are modelled with some success, modelling CO in and above the boundary layer remains a challenge and modelling ozone also has room for significant improvement. We note, however, that the high sensitivity of models to height, season, location, and metric makes the results rather difficult to interpret and to generalize. With this work, though, we set the stage for future process-oriented and in-depth diagnostic analyses.

Description: Numerical issues associated with compensating and competing processes in climate models: an example from ECHAM-HAM Geoscientific Model Development Discussions, 6, 685-720, 2013 Author(s): H. Wan, P. J. Rasch, K. Zhang, J. Kazil, and L. R. Leung The purpose of this paper is to draw attention to the need for appropriate numerical techniques to represent process interactions in climate models. In two versions of the ECHAM-HAM model, different time integration methods are used to solve the sulfuric acid (H 2 SO 4 ) gas evolution equation, which lead to substantially different results in the H 2 SO 4 gas concentration and the aerosol nucleation rate. Using convergence tests and sensitivity simulations performed with various time stepping schemes, it is confirmed that numerical errors in the second model version are significantly smaller than those in version one. The use of sequential operator splitting in combination with long time step is identified as the main reason for the large systematic biases in the old model. The remaining errors of nucleation rate in version two, related to the competition between condensation and nucleation, have a clear impact on the simulated concentration of cloud condensation nuclei (CCN) in the lower troposphere. These errors can be significantly reduced by employing an implicit solver that handles production, condensation and nucleation at the same time. Lessons learned in this work underline the need for more caution when treating multi-time-scale problems involving compensating and competing processes, a common occurrence in current climate models.

Description: Regional atmospheric composition modeling with CHIMERE Geoscientific Model Development Discussions, 6, 203-329, 2013 Author(s): L. Menut, B. Bessagnet, D. Khvorostyanov, M. Beekmann, A. Colette, I. Coll, G. Curci, G. Foret, A. Hodzic, S. Mailler, F. Meleux, J.-L. Monge, I. Pison, S. Turquety, M. Valari, R. Vautard, and M. G. Vivanco Tropospheric trace gas and aerosol pollutants have adverse effects on health, environment and climate. In order to quantify and mitigate such effects, a wide range of processes leading to the formation and transport of pollutants must be considered, understood and represented in numerical models. Regional scale pollution episodes result from the combination of several factors: high emissions (from anthropogenic or natural sources), stagnant meteorological conditions, velocity and efficiency of the chemistry and the deposition. All these processes are highly variable in time and space, and their relative importance to the pollutants budgets can be quantified within a chemistry-transport models (CTM). The offline CTM CHIMERE model uses meteorological model fields and emissions fluxes and calculates deterministically their behavior in the troposphere. The calculated three-dimensional fields of chemical concentrations can be compared to measurements to analyze past periods or used to make air quality forecasts and CHIMERE has enabled a fine understanding of pollutants transport during numerous measurements campaigns. It is a part of the PREVAIR french national forecast platform, delivering pollutant concentrations up to three days in advance. The model also allows scenario studies and long term simulations for pollution trends. The modelling of photochemical air pollution has reached a good level of maturity, and the latest projects involving CHIMERE now aim at increasing our understanding of pollution impact on health at the urban scale or at the other end of the spectrum for long term air quality and climate change interlinkage studies, quantifying the emissions and transport of pollen, but also, at a larger scale, analyzing the transport of pollutants plumes emitted by volcanic eruptions and forest fires.

Description: Impacts of using spectral nudging on regional climate model RCA4 simulations of the Arctic Geoscientific Model Development Discussions, 6, 495-520, 2013 Author(s): P. Berg, R. Döscher, and T. Koenigk The performance of the Rossby Centre regional climate model RCA4 is investigated for the Arctic CORDEX region, with an emphasis on its suitability to be coupled to a regional ocean and sea-ice model. Large biases in mean sea level pressure (MSLP) are identified, with pronounced too high pressure centred over the North Pole in summer of over 5 hPa, and too low pressure in winter of a similar magnitude. These lead to biases in the surface winds, which will potentially lead to strong sea-ice biases in a future coupled system. The large scale circulation is believed to be the major reason for the biases, and an implementation of spectral nudging is applied to remedy the problems by constraining the large scale components of the driving fields within the interior domain. It is found that the spectral nudging generally corrects for the MSLP and wind biases, while not significantly affecting other variables such as surface radiative components, two metre temperature and precipitation.

Description: Ice sheet dynamics within an Earth system model: coupling and first results on ice stability and ocean circulation Geoscientific Model Development Discussions, 6, 1-35, 2013 Author(s): D. Barbi, G. Lohmann, K. Grosfeld, and M. Thoma We present first results from a coupled model setup, consisting of a state-of-the-art ice sheet model (RIMBAY), 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 statistical downscaling is crucial for ice sheet stability, especially for southern Greenland where surface temperature are close to the melting point. The simulated ice sheets are stable when forced with pre-industrial greenhouse gas parameters, with limits comparable with present day ice orography. A setup with high CO 2 level is used to demonstrate the effects of dynamic ice sheets compared to the standard parameterisation; the resulting changes on ocean circulation will also be discussed.

Description: On the parallelization of atmospheric inversions of CO 2 surface fluxes within a variational framework Geoscientific Model Development Discussions, 6, 37-57, 2013 Author(s): F. Chevallier The variational formulation of Bayes' theorem allows inferring CO 2 sources and sinks from atmospheric concentrations at much higher space-time resolution than the ensemble approach or the analytical one. However, it usually exhibits limited scalable parallelism. This limitation hinders global atmospheric inversions operated on decadal time scales and regional ones with kilometric spatial scales, because of the computational cost of the underlying transport model that has to be run at each iteration of the variational minimization. Here, we introduce a Physical Parallelisation (PP) of variational atmospheric inversions. In the PP, the inversion still manages a single physically and statistically consistent window, but the transport model is run in parallel overlapping sub-segments in order to massively reduce the computation wall clock time of the inversion. For global inversions, a simplification of transport modelling is described to connect the output of all segments. We demonstrate the performance of the approach on a global inversion for CO 2 with a 32-yr inversion window (1979–2010) with atmospheric measurements from 81 sites of the NOAA global cooperative air sampling network. In this case, we show that the duration of the inversion is reduced by a seven-fold factor (from months to days) while still processing the three decades consistently and with improved numerical stability.

Description: High resolution air quality simulation over Europe with the chemistry transport model CHIMERE Geoscientific Model Development Discussions, 6, 4137-4187, 2013 Author(s): E. Terrenoire, B. Bessagnet, L. Rouïl, F. Tognet, G. Pirovano, L. Létinois, A. Colette, P. Thunis, M. Amann, and L. Menut A high resolution air quality simulation (0.125° × 0.0625° horizontal resolution) performed over Europe for the year 2009 has been evaluated using both rural and urban background stations available over most of the domain. Using seasonal and yearly mean statistical indicators such as the correlation index, the fractional bias and the root mean squared error; we interpret objectively the performance of the simulation. Positive outcomes are: a very good reproduction of the daily variability at UB sites for O 3 ( R =0.73) as well as for NO 2 ( R =0.61); a very low bias calculated at UB stations for PM 2.5 (FB = −6.4%) and PM 10 concentrations (FB = −20.1%). Conversely, main weaknesses in model performance include: the underestimation of the NO 2 daily maxima at UB site (FB = −53.6%); an overall underestimation of PM 10 and PM 2.5 concentrations observed over Eastern European countries (e.g. Poland); the overestimation of sulphates concentrations at spring time (FB = 53.7%); finally, over the year, total nitrate and ammonia concentrations are better reproduced than nitrate and ammonium aerosol phase compounds. Obtained results suggest that, in order to improve the model performances, efforts should focus on the improvement of the emission inventory quality for Eastern Europeans countries and the improvement of a specific parameterisation in the model to better account for the urban effect on meteorology and air pollutants concentrations.