http://www.geosci-model-dev.net/Geoscientific Model Development Latest Articleshttp://www.geosci-model-dev.net/3/377/2010/<b>The mechanism behind internally generated centennial-to-millennial scale climate variability in an earth system model of intermediate complexity</b><br /><br />Geoscientific Model Development, 3, 377-389, 2010<br /><br />Author(s): T. Friedrich, A. Timmermann, L. Menviel, O. Elison Timm, A. Mouchet, and D. M. Roche<br /><br />The mechanism triggering centennial-to-millennial-scale variability of the Atlantic Meridional Overturning Circulation (AMOC) in the earth system model of intermediate complexity LOVECLIM is investigated. It is found that for several climate boundary conditions such as low obliquity values (~22.1°) or LGM-albedo, internally generated centennial-to-millennial-scale variability occurs in the North Atlantic region. Stochastic excitations of the density-driven overturning circulation in the Nordic Seas can create regional sea-ice anomalies and a subsequent reorganization of the atmospheric circulation. The resulting remote atmospheric anomalies over the Hudson Bay can release freshwater pulses into the Labrador Sea and significantly increase snow fall in this region leading to a subsequent reduction of convective activity. The millennial-scale AMOC oscillations disappear if LGM bathymetry (with closed Hudson Bay) is prescribed or if freshwater pulses are suppressed artificially. Furthermore, our study documents the process of the AMOC recovery as well as the global marine and terrestrial carbon cycle response to centennial-to-millennial-scale AMOC variability.2010-08-25T00:00:00+02:00http://www.geosci-model-dev.net/3/365/2010/<b>Development of a system emulating the global carbon cycle in Earth system models</b><br /><br />Geoscientific Model Development, 3, 365-376, 2010<br /><br />Author(s): K. Tachiiri, J. C. Hargreaves, J. D. Annan, A. Oka, A. Abe-Ouchi, and M. Kawamiya<br /><br />Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO₂ concentration scenario. <br><br> By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO₂ stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).2010-08-13T00:00:00+02:00http://www.geosci-model-dev.net/3/337/2010/<b>A kinetic chemistry tagging technique and its application to modelling the stable isotopic composition of atmospheric trace gases</b><br /><br />Geoscientific Model Development, 3, 337-364, 2010<br /><br />Author(s): S. Gromov, P. Jöckel, R. Sander, and C. A. M. Brenninkmeijer<br /><br />Isotope composition, in many cases, holds unique information on the sources, chemical modification and sinks of atmospheric trace gases. Vital to the interpretation and use of an increasing number of isotope analyses is appropriate modelling. However, the exact implementation of isotopic information in chemistry-climate models is a challenge, and often studies use simplifications which limit their applicability. Here we implement a thorough isotopic extension in MECCA, a comprehensive kinetic chemistry sub-model. To this end, we devise a generic tagging technique for the kinetic chemistry mechanisms implemented as the sub-submodel MECCA-TAG. The technique is diagnostic and numerically efficient and supports the investigation of various aspects of kinetic chemistry schemes. We focus specifically on the application to the modelling of stable isotopic composition. The results of MECCA-TAG are evaluated against the reference sub-submodel MECCA-DBL, which is implicitly full-detailed, but computationally expensive and thus sub-optimal in practical applications. Furthermore, we evaluate the elaborate carbon and oxygen isotopic mechanism by simulating the multi-isotope composition of CO and other trace gases in the CAABA/MECCA box-model. The mechanism realistically simulates the oxygen isotope composition of key species, as well as the carbon isotope signature transfer. The model adequately reproduces the isotope chemistry features for CO, taking into account the limits of the modelling domain. In particular, the mass-independently fractionated (MIF) composition of CO due to reactions of ozone with unsaturated hydrocarbons (a source effect) versus its intrinsic MIF enrichment induced in the removal reaction via oxidation by OH is assessed. The simulated ozone source effect was up to +1&permil; in &Delta;¹⁷O(CO). The versatile modelling framework we employ (the Modular Earth Submodel System, MESSy) opens the way for implementation of the novel detailed isotopic chemistry treatment in the three-dimensional atmospheric-chemistry general circulation model EMAC. We therefore also present estimates of the computational gain obtained by the developed optimisations.2010-08-10T00:00:00+02:00http://www.geosci-model-dev.net/3/329/2010/<b>Efficient approximation of the incomplete gamma function for use in cloud model applications</b><br /><br />Geoscientific Model Development, 3, 329-336, 2010<br /><br />Author(s): U. Blahak<br /><br />This paper describes an approximation to the lower incomplete gamma function &gamma;<i>_l(a,x)</i> which has been obtained by nonlinear curve fitting. It comprises a fixed number of terms and yields moderate accuracy (the absolute approximation error of the corresponding normalized incomplete gamma function <i>P</i> is smaller than 0.02 in the range 0.9 &le; <i>a</i> &le; 45 and <i>x</i>&ge;0). Monotonicity and asymptotic behaviour of the original incomplete gamma function is preserved. <br><br> While providing a slight to moderate performance gain on scalar machines (depending on whether <i>a</i> stays the same for subsequent function evaluations or not) compared to established and more accurate methods based on series- or continued fraction expansions with a variable number of terms, a big advantage over these more accurate methods is the applicability on vector CPUs. Here the fixed number of terms enables proper and efficient vectorization. The fixed number of terms might be also beneficial on massively parallel machines to avoid load imbalances, caused by a possibly vastly different number of terms in series expansions to reach convergence at different grid points. For many cloud microphysical applications, the provided moderate accuracy should be enough. However, on scalar machines and if <i>a</i> is the same for subsequent function evaluations, the most efficient method to evaluate incomplete gamma functions is perhaps interpolation of pre-computed regular lookup tables (most simple example: equidistant tables).2010-07-23T00:00:00+02:00http://www.geosci-model-dev.net/3/321/2010/<b>A fast stratospheric chemistry solver: the E4CHEM submodel for the atmospheric chemistry global circulation model EMAC</b><br /><br />Geoscientific Model Development, 3, 321-328, 2010<br /><br />Author(s): A. J. G. Baumgaertner, P. Jöckel, B. Steil, H. Tost, and R. Sander<br /><br />The atmospheric chemistry general circulation model ECHAM5/MESSy (EMAC) and the atmospheric chemistry box model CAABA are extended by a computationally very efficient submodel for atmospheric chemistry, E4CHEM. It focuses on stratospheric chemistry but also includes background tropospheric chemistry. It is based on the chemistry of MAECHAM4-CHEM and is intended to serve as a simple and fast alternative to the flexible but also computationally more demanding submodel MECCA. In a model setup with E4CHEM, EMAC is now also suitable for simulations of longer time scales. The reaction mechanism contains basic O₃, CH₄, CO, HO_x, NO_x, and ClO_x gas phase chemistry. In addition, E4CHEM includes optional fast routines for heterogeneous reactions on sulphate aerosols and polar stratospheric clouds (substituting the existing submodels PSC and HETCHEM), and scavenging (substituting the existing submodel SCAV). We describe the implementation of E4CHEM into the MESSy structure of CAABA and EMAC. For some species the steady state in the box model differs by up to 100% when compared to results from CAABA/MECCA due to different reaction rates. After an update of the reaction rates in E4CHEM the mixing ratios in both boxmodel and 3-D model simulations are in satisfactory agreement with the results from a simulation where MECCA with a similar chemistry scheme was employed. Finally, a comparison against a simulation with a more complex and already evaluated chemical mechanism is presented in order to discuss shortcomings associated with the simplification of the chemical mechanism.2010-06-22T00:00:00+02:00http://www.geosci-model-dev.net/3/309/2010/<b>Assessment of bias-adjusted PM_2.5 air quality forecasts over the continental United States during 2007</b><br /><br />Geoscientific Model Development, 3, 309-320, 2010<br /><br />Author(s): D. Kang, R. Mathur, and S. Trivikrama Rao<br /><br />To develop fine particulate matter (PM_2.5) air quality forecasts for the US, a National Air Quality Forecast Capability (NAQFC) system, which linked NOAA's North American Mesoscale (NAM) meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, was deployed in the developmental mode over the continental United States during 2007. This study investigates the operational use of a bias-adjustment technique called the Kalman Filter Predictor approach for improving the accuracy of the PM_2.5 forecasts at monitoring locations. The Kalman Filter Predictor bias-adjustment technique is a recursive algorithm designed to optimally estimate bias-adjustment terms using the information extracted from previous measurements and forecasts. <br><br> The bias-adjustment technique is found to improve PM_2.5 forecasts (i.e. reduced errors and increased correlation coefficients) for the entire year at almost all locations. The NAQFC tends to overestimate PM_2.5 during the cool season and underestimate during the warm season in the eastern part of the continental US domain, but the opposite is true for the Pacific Coast. In the Rocky Mountain region, the NAQFC system overestimates PM_2.5 for the whole year. The bias-adjusted forecasts can quickly (after 2–3 days' lag) adjust to reflect the transition from one regime to the other. The modest computational requirements and systematic improvements in forecast outputs across all seasons suggest that this technique can be easily adapted to perform bias adjustment for real-time PM_2.5 air quality forecasts.2010-04-16T00:00:00+02:00http://www.geosci-model-dev.net/3/293/2010/<b>Modeling the statistical distributions of cosmogenic exposure dates from moraines</b><br /><br />Geoscientific Model Development, 3, 293-307, 2010<br /><br />Author(s): P. J. Applegate, N. M. Urban, B. J. C. Laabs, K. Keller, and R. B. Alley<br /><br />Geomorphic process modeling allows us to evaluate different methods for estimating moraine ages from cosmogenic exposure dates, and may provide a means to identify the processes responsible for the excess scatter among exposure dates on individual moraines. Cosmogenic exposure dating is an elegant method for estimating the ages of moraines, but individual exposure dates are sometimes biased by geomorphic processes. Because exposure dates may be either "too young" or "too old," there are a variety of methods for estimating the ages of moraines from exposure dates. In this paper, we present Monte Carlo-based models of moraine degradation and inheritance of cosmogenic nuclides, and we use the models to examine the effectiveness of these methods. The models estimate the statistical distributions of exposure dates that we would expect to obtain from single moraines, given reasonable geomorphic assumptions. The model of moraine degradation is based on prior examples, but the inheritance model is novel. The statistical distributions of exposure dates from the moraine degradation model are skewed toward young values; in contrast, the statistical distributions of exposure dates from the inheritance model are skewed toward old values. Sensitivity analysis shows that this difference is robust for reasonable parameter choices. Thus, the skewness can help indicate whether a particular data set has problems with inheritance or moraine degradation. Given representative distributions from these two models, we can determine which methods of estimating moraine ages are most successful in recovering the correct age for test cases where this value is known. The mean is a poor estimator of moraine age for data sets drawn from skewed parent distributions, and excluding outliers before calculating the mean does not improve this mismatch. The extreme estimators (youngest date and oldest date) perform well under specific circumstances, but fail in other cases. We suggest a simple estimator that uses the skewnesses of individual data sets to determine whether the youngest date, mean, or oldest date will provide the best estimate of moraine age. Although this method is perhaps the most globally robust of the estimators we tested, it sometimes fails spectacularly. The failure of simple methods to provide accurate estimates of moraine age points toward a need for more sophisticated statistical treatments.2010-04-12T00:00:00+02:00http://www.geosci-model-dev.net/3/275/2010/<b>Modelling sediment export, retention and reservoir sedimentation in drylands with the WASA-SED model</b><br /><br />Geoscientific Model Development, 3, 275-291, 2010<br /><br />Author(s): E. N. Mueller, A. Güntner, T. Francke, and G. Mamede<br /><br />Current soil erosion and reservoir sedimentation modelling at the meso-scale is still faced with intrinsic problems with regard to open scaling questions, data demand, computational efficiency and deficient implementations of retention and re-mobilisation processes for the river and reservoir networks. To overcome some limitations of current modelling approaches, the semi-process-based, spatially semi-distributed modelling framework WASA-SED (Vers. 1) was developed for water and sediment transport in large dryland catchments. The WASA-SED model simulates the runoff and erosion processes at the hillslope scale, the transport and retention processes of suspended and bedload fluxes in the river reaches and the retention and remobilisation processes of sediments in reservoirs. The modelling tool enables the evaluation of management options both for sustainable land-use change scenarios to reduce erosion in the headwater catchments as well as adequate reservoir management options to lessen sedimentation in large reservoirs and reservoir networks. The model concept, its spatial discretisation scheme and the numerical components of the hillslope, river and reservoir processes are described and a model application for the meso-scale dryland catchment Isábena in the Spanish Pre-Pyrenees (445 km²) is presented to demonstrate the capabilities, strengths and limits of the model framework. The example application showed that the model was able to reproduce runoff and sediment transport dynamics of highly erodible headwater badlands, the transient storage of sediments in the dryland river system, the bed elevation changes of the 93 hm³ Barasona reservoir due to sedimentation as well as the life expectancy of the reservoir under different management options.2010-04-08T00:00:00+02:00http://www.geosci-model-dev.net/3/257/2010/<b>Simulating emission and chemical evolution of coarse sea-salt particles in the Community Multiscale Air Quality (CMAQ) model</b><br /><br />Geoscientific Model Development, 3, 257-273, 2010<br /><br />Author(s): J. T. Kelly, P. V. Bhave, C. G. Nolte, U. Shankar, and K. M. Foley<br /><br />Chemical processing of sea-salt particles in coastal environments significantly impacts concentrations of particle components and gas-phase species and has implications for human exposure to particulate matter and nitrogen deposition to sensitive ecosystems. Emission of sea-salt particles from the coastal surf zone is known to be elevated compared to that from the open ocean. Despite the importance of sea-salt emissions and chemical processing, the US EPA's Community Multiscale Air Quality (CMAQ) model has traditionally treated coarse sea-salt particles as chemically inert and has not accounted for enhanced surf-zone emissions. In this article, updates to CMAQ are described that enhance sea-salt emissions from the coastal surf zone and allow dynamic transfer of HNO₃, H₂SO₄, HCl, and NH₃ between coarse particles and the gas phase. Predictions of updated CMAQ models and the previous release version, CMAQv4.6, are evaluated using observations from three coastal sites during the Bay Regional Atmospheric Chemistry Experiment (BRACE) in Tampa, FL in May 2002. Model updates improve predictions of NO₃^&minus;, SO₄^2&minus;, NH₄⁺, Na⁺, and Cl^&minus; concentrations at these sites with only a 8% increase in run time. In particular, the chemically interactive coarse particle mode dramatically improves predictions of nitrate concentration and size distributions as well as the fraction of total nitrate in the particle phase. Also, the surf-zone emission parameterization improves predictions of total sodium and chloride concentration. Results of a separate study indicate that the model updates reduce the mean absolute error of nitrate predictions at coastal CASTNET and SEARCH sites in the eastern US. Although the new model features improve performance relative to CMAQv4.6, some persistent differences exist between observations and predictions. Modeled sodium concentration is biased low and causes under-prediction of coarse particle nitrate. Also, CMAQ over-predicts geometric mean diameter and standard deviation of particle modes at the BRACE sites. These over-predictions may cause too rapid particle dry deposition and partially explain the low bias in sodium predictions. Despite these shortcomings, the updates to CMAQ enable more realistic simulations of chemical processes in environments where marine air mixes with urban pollution. The model updates described in this article are included in the public release of CMAQv4.7 (<a href="http://www.cmaq-model.org" target="_blank">http://www.cmaq-model.org</a>).2010-04-08T00:00:00+02:00http://www.geosci-model-dev.net/3/243/2010/<b>The Meteorology-Chemistry Interface Processor (MCIP) for the CMAQ modeling system: updates through MCIPv3.4.1</b><br /><br />Geoscientific Model Development, 3, 243-256, 2010<br /><br />Author(s): T. L. Otte and J. E. Pleim<br /><br />The Community Multiscale Air Quality (CMAQ) modeling system, a state-of-the-science regional air quality modeling system developed by the US Environmental Protection Agency, is being used for a variety of environmental modeling problems including regulatory applications, air quality forecasting, evaluation of emissions control strategies, process-level research, and interactions of global climate change and regional air quality. The Meteorology-Chemistry Interface Processor (MCIP) is a vital piece of software within the CMAQ modeling system that serves to, as best as possible, maintain dynamic consistency between the meteorological model and the chemical transport model (CTM). MCIP acts as both a post-processor to the meteorological model and a pre-processor to the emissions and the CTM in the CMAQ modeling system. MCIP's functions are to ingest the meteorological model output fields in their native formats, perform horizontal and vertical coordinate transformations, diagnose additional atmospheric fields, define gridding parameters, and prepare the meteorological fields in a form required by the CMAQ modeling system. This paper provides an updated overview of MCIP, documenting the scientific changes that have been made since it was first released as part of the CMAQ modeling system in 1998.2010-04-07T00:00:00+02:00http://www.geosci-model-dev.net/3/227/2010/<b>Pliocene Model Intercomparison Project (PlioMIP): experimental design and boundary conditions (Experiment 1)</b><br /><br />Geoscientific Model Development, 3, 227-242, 2010<br /><br />Author(s): A. M. Haywood, H. J. Dowsett, B. Otto-Bliesner, M. A. Chandler, A. M. Dolan, D. J. Hill, D. J. Lunt, M. M. Robinson, N. Rosenbloom, U. Salzmann, and L. E. Sohl<br /><br />In 2008 the temporal focus of the Palaeoclimate Modelling Intercomparison Project was expanded to include a model intercomparison for the mid-Pliocene warm period (3.29–2.97 million years ago). This project is referred to as PlioMIP (Pliocene Model Intercomparison Project). Two experiments have been agreed upon and comprise phase 1 of PlioMIP. The first (Experiment 1) will be performed with atmosphere-only climate models. The second (Experiment 2) will utilise fully coupled ocean-atmosphere climate models. The aim of this paper is to provide a detailed model intercomparison project description which documents the experimental design in a more detailed way than has previously been done in the literature. Specifically, this paper describes the experimental design and boundary conditions that will be utilised for Experiment 1 of PlioMIP.2010-03-26T00:00:00+01:00http://www.geosci-model-dev.net/3/205/2010/<b>Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7</b><br /><br />Geoscientific Model Development, 3, 205-226, 2010<br /><br />Author(s): K. M. Foley, S. J. Roselle, K. W. Appel, P. V. Bhave, J. E. Pleim, T. L. Otte, R. Mathur, G. Sarwar, J. O. Young, R. C. Gilliam, C. G. Nolte, J. T. Kelly, A. B. Gilliland, and J. O. Bash<br /><br />This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to observations and results from previous model versions in a series of simulations conducted to incrementally assess the effect of each change. The focus of this paper is on five major scientific upgrades: (a) updates to the heterogeneous N₂O₅ parameterization, (b) improvement in the treatment of secondary organic aerosol (SOA), (c) inclusion of dynamic mass transfer for coarse-mode aerosol, (d) revisions to the cloud model, and (e) new options for the calculation of photolysis rates. Incremental test simulations over the eastern United States during January and August 2006 are evaluated to assess the model response to each scientific improvement, providing explanations of differences in results between v4.7 and previously released CMAQ model versions. Particulate sulfate predictions are improved across all monitoring networks during both seasons due to cloud module updates. Numerous updates to the SOA module improve the simulation of seasonal variability and decrease the bias in organic carbon predictions at urban sites in the winter. Bias in the total mass of fine particulate matter (PM_2.5) is dominated by overpredictions of unspeciated PM_2.5 (PM_other) in the winter and by underpredictions of carbon in the summer. The CMAQv4.7 model results show slightly worse performance for ozone predictions. However, changes to the meteorological inputs are found to have a much greater impact on ozone predictions compared to changes to the CMAQ modules described here. Model updates had little effect on existing biases in wet deposition predictions.2010-03-26T00:00:00+01:00http://www.geosci-model-dev.net/3/189/2010/<b>Tracers and traceability: implementing the cirrus parameterisation from LACM in the TOMCAT/SLIMCAT chemistry transport model as an example of the application of quality assurance to legacy models</b><br /><br />Geoscientific Model Development, 3, 189-203, 2010<br /><br />Author(s): A. M. Horseman, A. R. MacKenzie, and M. P. Chipperfield<br /><br />A new modelling tool for the investigation of large-scale behaviour of cirrus clouds has been developed. This combines two existing models, the TOMCAT/SLIMCAT chemistry transport model (nupdate library version 0.80, script mpc346_l) and cirrus parameterisation of Ren and MacKenzie (LACM implementation not versioned). The development process employed a subset of best-practice software engineering and quality assurance processes, selected to be viable for small-scale projects whilst maintaining the same traceability objectives. The application of the software engineering and quality control processes during the development has been shown to be not a great overhead, and their use has been of benefit to the developers as well as the end users of the results. We provide a step-by-step guide to the implementation of traceability tailored to the production of geo-scientific research software, as distinct from commercial and operational software. Our recommendations include: maintaining a living "requirements list"; explicit consideration of unit, integration and acceptance testing; and automated revision/configuration control, including control of analysis tool scripts and programs. <br><br> Initial testing of the resulting model against satellite and in-situ measurements has been promising. The model produces representative results for both spatial distribution of the frequency of occurrence of cirrus ice, and the drying of air as it moves across the tropical tropopause. The model is now ready for more rigorous quantitative testing, but will require the addition of a vertical wind velocity downscaling scheme to better represent extra-tropical continental cirrus.2010-03-16T00:00:00+01:00http://www.geosci-model-dev.net/3/169/2010/<b>Sensitivity of the Community Multiscale Air Quality (CMAQ) model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers</b><br /><br />Geoscientific Model Development, 3, 169-188, 2010<br /><br />Author(s): K. W. Appel, S. J. Roselle, R. C. Gilliam, and J. E. Pleim<br /><br />This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ) and the other utilized WRF meteorology (WRF-CMAQ), while all other model inputs and options were kept the same. For January, predicted ozone (O₃) mixing ratios were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O₃ mixing ratios are attributed to less dry deposition of O₃ in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO₄^2&minus;), similar performance for nitrate (NO₃^&minus;), and slightly worse performance for nitric acid (HNO₃), total carbon (TC) and total fine particulate (PM_2.5) mass than the corresponding MM5-CMAQ results. For August, predictions of O₃ were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO₄^2&minus; were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary causes of the differences in the MM5-CMAQ and WRF-CMAQ simulations appear to be due to differences in the calculation of wind speed, planetary boundary layer height, cloud cover and the friction velocity (<I>u</I>_&lowast;) in the MM5 and WRF model simulations, while differences in the calculation of vegetation fraction and several other parameters result in smaller differences in the predicted CMAQ model concentrations. The performance for SO₄^2&minus;, NO₃^&minus; and NH₄⁺ wet deposition was similar for both simulations for January and August.2010-02-23T00:00:00+01:00http://www.geosci-model-dev.net/3/143/2010/<b>An isopycnic ocean carbon cycle model</b><br /><br />Geoscientific Model Development, 3, 143-167, 2010<br /><br />Author(s): K. M. Assmann, M. Bentsen, J. Segschneider, and C. Heinze<br /><br />The carbon cycle is a major forcing component in the global climate system. Modelling studies, aiming to explain recent and past climatic changes and to project future ones, increasingly include the interaction between the physical and biogeochemical systems. Their ocean components are generally z-coordinate models that are conceptually easy to use but that employ a vertical coordinate that is alien to the real ocean structure. Here, we present first results from a newly-developed isopycnic carbon cycle model and demonstrate the viability of using an isopycnic physical component for this purpose. As expected, the model represents well the interior ocean transport of biogeochemical tracers and produces realistic tracer distributions. Difficulties in employing a purely isopycnic coordinate lie mainly in the treatment of the surface boundary layer which is often represented by a bulk mixed layer. The most significant adjustments of the ocean biogeochemistry model HAMOCC, for use with an isopycnic coordinate, were in the representation of upper ocean biological production. We present a series of sensitivity studies exploring the effect of changes in biogeochemical and physical processes on export production and nutrient distribution. Apart from giving us pointers for further model development, they highlight the importance of preformed nutrient distributions in the Southern Ocean for global nutrient distributions. The sensitivity studies show that iron limitation for biological particle production, the treatment of light penetration for biological production, and the role of diapycnal mixing result in significant changes of nutrient distributions and liniting factors of biological production.2010-02-16T00:00:00+01:00http://www.geosci-model-dev.net/3/123/2010/<b>Bergen Earth system model (BCM-C): model description and regional climate-carbon cycle feedbacks assessment</b><br /><br />Geoscientific Model Development, 3, 123-141, 2010<br /><br />Author(s): J. F. Tjiputra, K. Assmann, M. Bentsen, I. Bethke, O. H. Otterå, C. Sturm, and C. Heinze<br /><br />We developed a complex Earth system model by coupling terrestrial and oceanic carbon cycle components into the Bergen Climate Model. For this study, we have generated two model simulations (one with climate change inclusions and the other without) to study the large scale climate and carbon cycle variability as well as its feedback for the period 1850–2100. The simulations are performed based on historical and future IPCC CO₂ emission scenarios. Globally, a pronounced positive climate-carbon cycle feedback is simulated by the terrestrial carbon cycle model, but smaller signals are shown by the oceanic counterpart. Over land, the regional climate-carbon cycle feedback is highlighted by increased soil respiration, which exceeds the enhanced production due to the atmospheric CO₂ fertilization effect, in the equatorial and northern hemisphere mid-latitude regions. For the ocean, our analysis indicates that there are substantial temporal and spatial variations in climate impact on the air-sea CO₂ fluxes. This implies feedback mechanisms act inhomogeneously in different ocean regions. In the North Atlantic subpolar gyre, the simulated future cooling of SST improves the CO₂ gas solubility in seawater and, hence, reduces the strength of positive climate carbon cycle feedback in this region. In most ocean regions, the changes in the Revelle factor is dominated by changes in surface <i>p</i>CO₂, and not by the warming of SST. Therefore, the solubility-associated positive feedback is more prominent than the buffer capacity feedback. In our climate change simulation, the retreat of Southern Ocean sea ice due to melting allows an additional ~20 Pg C uptake as compared to the simulation without climate change.2010-02-12T00:00:00+01:00http://www.geosci-model-dev.net/3/105/2010/<b>The efficient global primitive equation climate model SPEEDO V2.0</b><br /><br />Geoscientific Model Development, 3, 105-122, 2010<br /><br />Author(s): C. A. Severijns and W. Hazeleger<br /><br />The efficient primitive-equation coupled atmosphere-ocean model SPEEDO V2.0 is presented. The model includes an interactive sea-ice and land component. SPEEDO is a global earth system model of intermediate complexity. It has a horizontal resolution of T30 (triangular truncation at wave number 30) and 8 vertical layers in the atmosphere, and a horizontal resolution of 2 degrees and 20 levels in the ocean. The parameterisations in SPEEDO are developed in such a way that it is a fast model suitable for large ensembles or long runs (of <i>O</i>(10⁴) years) on a typical current workstation. The model has no flux correction. We compare the mean state and inter-annual variability of the model with observational fields of the atmosphere and ocean. In particular the atmospheric circulation, the mid-latitude patterns of variability and teleconnections from the tropics are well simulated. To show the capabilities of the model, we performed a long control run and an ensemble experiment with enhanced greenhouse gases. The long control run shows that the model is stable. CO₂ doubling and future climate change scenario experiments show a climate sensitivity of 1.84 K W^-1 m², which is within the range of state-of-the-art climate models. The spatial response patterns are comparable to state-of-the-art, higher resolution models. However, for very high greenhouse gas concentrations the parameterisations are not valid. We conclude that the model is suitable for past, current and future climate simulations and for exploring wide parameter ranges and mechanisms of variability. However, as with any model, users should be careful when using the model beyond the range of physical realism of the parameterisations and model setup.2010-02-10T00:00:00+01:00http://www.geosci-model-dev.net/3/87/2010/<b>OASIS4 – a coupling software for next generation earth system modelling</b><br /><br />Geoscientific Model Development, 3, 87-104, 2010<br /><br />Author(s): R. Redler, S. Valcke, and H. Ritzdorf<br /><br />In this article we present a new version of the Ocean Atmosphere Sea Ice Soil coupling software (OASIS4). With this new fully parallel OASIS4 coupler we target the needs of Earth system modelling in its full complexity. The primary focus of this article is to describe the design of the OASIS4 software and how the coupling software drives the whole coupled model system ensuring the synchronization of the different component models. The application programmer interface (API) manages the coupling exchanges between arbitrary climate component models, as well as the input and output from and to files of each individual component. The OASIS4 Transformer instance performs the parallel interpolation and transfer of the coupling data between source and target model components. As a new core technology for the software, the fully parallel search algorithm of OASIS4 is described in detail. First benchmark results are discussed with simple test configurations to demonstrate the efficiency and scalability of the software when applied to Earth system model components. Typically the compute time needed to perform the search is in the order of a few seconds and is only weakly dependant on the grid size.2010-01-22T00:00:00+01:00http://www.geosci-model-dev.net/3/69/2010/<b>Automatic generation of large ensembles for air quality forecasting using the Polyphemus system</b><br /><br />Geoscientific Model Development, 3, 69-85, 2010<br /><br />Author(s): D. Garaud and V. Mallet<br /><br />This paper describes a method to automatically generate a large ensemble of air quality simulations. Such an ensemble may be useful for quantifying uncertainty, improving forecasts, evaluating risks, identifying process weaknesses, etc. The objective is to take into account all sources of uncertainty: input data, physical formulation and numerical formulation. The leading idea is to build different chemistry-transport models in the same framework, so that the ensemble generation can be fully controlled. Large ensembles can be generated with a Monte Carlo simulations that address at the same time the uncertainties in the input data and in the model formulation. This is achieved using the Polyphemus system, which is flexible enough to build various different models. The system offers a wide range of options in the construction of a model: many physical parameterizations, several numerical schemes and different input data can be combined. In addition, input data can be perturbed. In this paper, some 30 alternatives are available for the generation of a model. For each alternative, the options are given a probability, based on how reliable they are supposed to be. Each model of the ensemble is defined by randomly selecting one option per alternative. In order to decrease the computational load, as many computations as possible are shared by the models of the ensemble. As an example, an ensemble of 101 photochemical models is generated and run for the year 2001 over Europe. The models' performance is quickly reviewed, and the ensemble structure is analyzed. We found a strong diversity in the results of the models and a wide spread of the ensemble. It is noteworthy that many models turn out to be the best model in some regions and some dates.2010-01-18T00:00:00+01:00http://www.geosci-model-dev.net/3/43/2010/<b>Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4)</b><br /><br />Geoscientific Model Development, 3, 43-67, 2010<br /><br />Author(s): L. K. Emmons, S. Walters, P. G. Hess, J.-F. Lamarque, G. G. Pfister, D. Fillmore, C. Granier, A. Guenther, D. Kinnison, T. Laepple, J. Orlando, X. Tie, G. Tyndall, C. Wiedinmyer, S. L. Baughcum, and S. Kloster<br /><br />The Model for Ozone and Related chemical Tracers, version 4 (MOZART-4) is an offline global chemical transport model particularly suited for studies of the troposphere. The updates of the model from its previous version MOZART-2 are described, including an expansion of the chemical mechanism to include more detailed hydrocarbon chemistry and bulk aerosols. Online calculations of a number of processes, such as dry deposition, emissions of isoprene and monoterpenes and photolysis frequencies, are now included. Results from an eight-year simulation (2000–2007) are presented and evaluated. The MOZART-4 source code and standard input files are available for download from the NCAR Community Data Portal (<a href=''http://cdp.ucar.edu'' target=''_blank''>http://cdp.ucar.edu</a>).2010-01-12T00:00:00+01:00