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In the current work we present six hindcast Weather Research and Forecasting (WRF) simulations for the EURO-CORDEX domain with different configurations in microphysics, convection and radiation for the time period 1990-2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic biases in both temperature and precipitation linked to different physical mechanisms for the summer and winter season. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly when using Grell-Devenyi convection and the CAM radiation scheme, intensifies the negative summer temperature bias in northern Europe (max -2.5 °C). Conversely, a strong positive downward shortwave summer bias in central (40-60 %) and southern Europe mitigates the systematic cold bias in WRF over these regions, signifying a typical case of error compensation. Maximum winter cold bias is over north-eastern Europe (-2.8 °C); this location is indicative of land-atmosphere rather than cloud-radiation interactions. Precipitation is systematically overestimated in summer by all model configurations, especially the higher quantiles, which are associated with summertime deep cumulus convection. The Kain-Fritsch convection scheme produces the larger summertime precipitation biases over the Mediterranean. Winter precipitation is reproduced with lower biases by all model configurations (15-30 %). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature-precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest methodologies for model improvement. [ABSTRACT FROM AUTHOR]

As part of the terrestrial branch of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA), which aims to clarify the role and function of the Arctic terrestrial system in the climate system, and assess the influence of its changes on a global scale, this model intercomparison project (GTMIP) is planned and being conducted to (1) enhance communication and understanding between the "minds and hands" (i.e., between the modelling and field scientists) and (2) assess the uncertainty and variations stemming from variability in model implementation/design and in model outputs due to climatic and historical conditions in the Arctic terrestrial regions. This paper provides an overview and the experiment protocol of Stage 1 of the project, site simulations driven by statistically fitted data created using the GRENE-TEA site observations for the last three decades. The target metrics for the model evaluation cover key processes in both physics and biogeochemistry, including energy budgets, snow, permafrost, phenology, and carbon budgets. The preliminary results on four metrics (annual mean latent heat flux, annual maximum snow depth, gross primary production, and net ecosystem production) already demonstrate the range of variations in reproducibility among existing models and sites. Full analysis on annual as well as seasonal time scales, to be conducted upon completion of model outputs submission, will delineate inter-dependence among the key processes, and provide the clue for improving the model performance. [ABSTRACT FROM AUTHOR]

Numerical simulations provide a considerable aid in studying past climates. Out of the various approaches taken in designing numerical climate experiments, transient simulations have been found to be the most optimal when it comes to comparison with proxy data. However, multi-millennial or longer simulations using fully coupled general circulation models are computationally very expensive such that acceleration techniques are frequently applied. In this study, we compare the results from transient simulations of the present and the last interglacial with and without acceleration of the orbital forcing, using the comprehensive coupled climate model CCSM3 (Community Climate System Model 3). Our study shows that in most parts of the world, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique (with an acceleration factor 10) and, hence, large-scale model-data comparison of surface variables is not hampered. However, in high-latitude regions where the surface climate has a direct connection to the deep ocean, e.g. in the Southern Ocean or the Nordic Seas, acceleration-induced biases in sea-surface temperature evolution may occur with potential influence on the dynamics of the overlying atmosphere. [ABSTRACT FROM AUTHOR]

End to end modelling is an attractive and rapidly developing approach to solve developing strategies in marine systems science and management. However problems remain in the area of data matching and sub-model compatibility. A mechanism and novel interfacing system (Couplerlib) is presented whereby a physical/biogeochemical model (GOTM-ERSEM) that predicts dynamics of the lower trophic level (LTL) organisms in marine ecosystems is coupled to a dynamic ecosystem model (Ecosim) that predicts food-web interactions among higher trophic level (HTL) organisms. Coupling is achieved by means of a bespoke interface which handles the system incompatibilities between the models and a more generic Couplerlib library which uses metadata descriptions in extensible mark-up language (XML) to marshal data between groups, paying attention to functional group mappings and compatibility of units between models. In addition, within Couplerlib, models can be coupled across networks by means of socket mechanisms. As a demonstration of this approach, a food web model (Ecopath with Ecosim, EwE) and a physical/biogeochemical model (GOTM-ERSEM) representing the North Sea ecosystem were joined with Couplerlib. The output from GOTM-ERSEM varies between years dependent on oceanographic and meteorological conditions. Although inter-annual variability was clearly present, there was always the tendency for an annual cycle consisting of a peak of diatoms in spring, followed by (less nutritious) flagellates and dinoflagellates through the summer resulting in an early summer peak in the mesozooplankton biomass. Pelagic productivity, predicted by the LTL model, was highly seasonal with little winter food for the higher trophic levels. The Ecosim model was originally based on the assumption of constant annual inputs and, consequently, when coupled, pelagic species suffered population loss over the winter months. By contrast, benthic populations were more stable (although the benthic linkage modelled was purely at the detritus level). The coupled model was used to examine long term effects of environmental change, and showed the system to be nutrient limited, relatively unaffected by forecast climate change, especially in the benthos. The stability of an Ecosim formulation for large higher tropic level food webs is discussed and it is concluded that this kind of coupled model formulation is better for examining the effects of long term environmental change than short term perturbations. [ABSTRACT FROM AUTHOR]

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

In atmospheric modelling applications the aerosol particle size distribution is commonly represented by modal approach, in which particles in different size ranges are described with log-normal modes within predetermined size ranges. Such method in- cludes numerical reallocation of particles from a mode to another for example during particle growth, leading to potentially artificial changes in the aerosol size distribution. In this study we analysed how this reallocation affects climatologically relevant parameters: cloud droplet number concentration, aerosol-cloud interaction coefficient and light extinction coefficient. We compared these parameters between a modal model with and without reallocation routines, and a high resolution sectional model that was considered as a reference model. We analysed the relative differences of the parameters in different experiments that were designed to cover a wide range of dynamic aerosol processes occurring in the atmosphere. According to our results, limiting the allowed size ranges of the modes and the following numerical remapping of the distribution by reallocation, leads on average to underestimation of cloud droplet number concentration (up to 100 %) and overestimation of light extinction (up to 20 %). The analysis of aerosol first indirect effect is more complicated as the ACI parameter can be either over- or underestimated by the reallocating model, depending on the conditions. However, for example in the case of atmospheric new particle formation events followed by rapid particle growth, the reallocation can cause around average 10% overestimation of the ACI parameter. Thus it is shown that the reallocation affects the ability of a model to estimate aerosol climate effects accurately, and this should be taken into account when using and developing aerosol models. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The article presents a study which explored the mid-Pliocene and pre-indusrial atmosphere general circulation models (AGCM) simulations, with Norwegian Earth System Model (NorESM-L). The study evaluated he potential uncertainties in the analysis of climate anomalies in the mid-Pliocene period. Results showed that the uncertainties in mid-Pliocene climate anomaly analyses are large in terms of regional scale, but small on a global scale.

A convolution based method of spectral nudging of atmospheric fields is developed in the Australian Community Climate and Earth Systems Simulator (ACCESS) version 1.3 which uses the UK Met Office Unified Model version 7.3 as its atmospheric component. The use of convolutions allow flexibility in application to different atmospheric grids. An approximation using one-dimensional convolutions is applied, improving the time taken by the nudging scheme by 10 to 30 times compared with a version using a twodimensional convolution, without measurably degrading its performance. Care needs to be taken in the order of the convolutions and the frequency of nudging to obtain the best outcome. The spectral nudging scheme is benchmarked against a Newtonian relaxation method, nudging winds and air temperature towards ERA-Interim reanalyses. We find that the convolution approach can produce results that are competitive with Newtonian relaxation in both the effectiveness and efficiency of the scheme, while giving the added flexibility of choosing which length scales to nudge. [ABSTRACT FROM AUTHOR]

The article presents a tagging method, which helps in calculating contribution of individual processes or quantities on state variables for application in climatechemistry models. It also presents 15 differential equations for these contributions or tagged quantities or species. It also discusses possibilities and limitations of this method.

The article presents a study that demonstrates the applications of the Biogeochemical Transport and Reactions (CLM4-BeTR) in regional and global biogeochemistry modeling and climate predictability. It outlines the functions of the model in which its transport code are evaluated through several analytical test cases. The study shows that the method provides detailed comparison between ecosystem observation and predictions.

The article focuses on the different simulation methods used in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The study introduces several simulation approaches to determine the long-term changes in the atmospheric composition between 1850 and 2100 though the ACCMIP project. It outlines the result of the study, which indicates that the present-day climate diagnostics are consistent with the state-of-the-art climate models.

The article presents a study that investigates the effectiveness of Earth System Model (ESM) in determining carbon-cycle climate feedback and the future climate. It describes the method of the study that analyzes the paleoclimate experiments proposed by the Coupled Model Intercomparison Project. It notes the result of the study, which shows that the complexity of the model requires various steps to correctly configure the experiments.

We introduce and document the first version of the Centre National de Recherches Météorologiques Earth system model (CNRM-ESM1). This model is based on the physical core of the CNRM-CM5 model and employs the Interactions between Soil, Bio-sphere and Atmosphere (ISBA) module and the Pelagic Interaction Scheme for Carbon and Ecosystem Studies (PISCES) as terrestrial and oceanic components of the global carbon cycle. We describe a preindustrial and 20th century climate simulation following the CMIP5 protocol. We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers. CNRM-ESM1 reproduces satisfactorily several aspects of the modern carbon cycle. On land, the model reasonably captures the carbon cycling through vegetation and soil, resulting in a net terrestrial carbon sink of 2.2 PgCy-1. In the ocean, the large-scale distribution of hydrodynamical and biogeochemical tracers agrees well with a modern climatology from the World Ocean Atlas. The combination of biological and physical processes induces a net CO2 uptake of 1.7 PgCy-1 that falls within the range of recent estimates. Our analysis shows that the atmospheric climate of CNRM-ESM1 compares well with that of CNRM-CM5. Biases in precipitation and shortwave radiation over the Tropics generate errors in gross primary productivity and ecosystem respiration. Compared to CNRM-CM5, the revised ocean-sea ice coupling has modified the sea-ice cover and ocean ventilation, unrealistically strengthening the flow of North Atlantic deep water (26.1±2 Sv). It results in an accumulation of anthropogenic carbon in the deep ocean. [ABSTRACT FROM AUTHOR]

The article presents a study that examines the capabilities of the Norwegian Climate Center's Earth System Model (NorESM1-M). It states that the model was based on the Community Climate System Model version 4 (CCSM4) of the University Corporation for Atmospheric 5 Research, and it provides advanced chemistry-aerosol-cloud-radiation interaction schemes. It also provides further analysis of the performance of the model along with climate response and scenario projections.

The article presents a study that demonstrates the usefulness of the Norwegian Climate Center's Earth System Model (NorESM1-M) in the coupled model intercomparison project phase 5 (CMIP5). It outlines the role of the model in providing complementary results to the evaluation of possible man made climate change. It also demonstrates the effectiveness of the model in accurately depicting the changes in the atmospheric water cycle in precipitation events.

The article presents a research which investigates the proposed framework for downscaling coarse climate change projections for oceans in the Australian region. It explores significance of the downscaling model in projecting marine impacts of climate change. The restoration of the ocean feedback on the air-sea fluxes to surface temperature and salinity is explored. It notes that the framework offers an attractive way to explore the impact of climate change on mesoscale ocean environment.

Simple climate models play an integral role in policy and scientific communities. They are used for climate mitigation scenarios within integrated assessment models, complex climate model emulation, and uncertainty analyses. Here we describe Hector v0.1, an open source, object-oriented, simple global climate carbon-cycle model. This model runs essentially instantaneously while still representing the most critical global scale earth system processes. Hector has three main carbon pools: an atmosphere, land, and ocean. The model's terrestrial carbon cycle includes respiration and primary production, accommodating arbitrary geographic divisions into, e.g., ecological biomes or political units. Hector's actively solves the inorganic carbon system in the surface ocean, directly calculating air-sea fluxes of carbon and ocean pH. Hector reproduces the global historical trends of atmospheric [CO2] and surface temperatures. The model simulates all four Representative Concentration Pathways with high correlations (R > 0.7) with current observations, MAGICC (a well-known simple climate model), and the Coupled Model Intercomparison Project version 5. Hector is freely available under an open source license, and its modular design will facilitate a broad range of research in various areas. [ABSTRACT FROM AUTHOR]

This work presents a framework, WRF4G, to manage the experiment workflow of the Weather Research and Forecasting (WRF) modelling system. WRF4G provides a flexible design, execution and monitoring for a general class of scientific experiments. It has been designed with the aim of facilitating the management and reproducibility of complex experiments. Furthermore, the concepts behind the design of this framework can be straightforwardly extended to other models. We describe the user interface and the new concepts required to design parametersweep, hindcast and climate simulation experiments. A number of examples are provided, based on the design used for existing (published) WRF experiments. This software is open-source and publicly available (http: //www.meteo.unican.es/software/wrf4g). [ABSTRACT FROM AUTHOR]

We present the new 3.5 version of the Louvain-la-Neuve sea ice model (LIM) integrated in NEMO 3.6. The main novelty is the improvement of model robustness and versatility for a wide range of applications, from global to regional scales. Several modifications to the code were required. First, the time stepping scheme of the model was changed from parallel to sequential (ice dynamics first, then thermodynamics). Such a scheme enables to diagnose the different physical processes responsible for exchanges through the air–ice–ocean interfaces, as well as the online inspection of mass, heat and salt conservation properties of the code. In the course of these developments, several minor conservation leaks were found and fixed, so that LIM3.5 is exactly conservative. Second, lateral boundary conditions for regional ice-covered configurations have been implemented. To illustrate the new capabilities, two simulations are performed. One is a global simulation at a nominal 2° resolution forced by atmospheric climatologies and is found reasonably realistic although no specific tuning was done. The other is a regional simulation at 2 km resolution around the Svalbard Archipelago in the Arctic Ocean, with prescribed conditions at the four boundaries including tides. The simulation is able to resolve small-scale features and transient events such as the opening and closing of coastal polynyas. The ice mass budgets for both simulations are illustrated and mostly differ by the strength of ice formation in open water. LIM3.5 now forms a solid base for future scientific studies and model developments. [ABSTRACT FROM AUTHOR]

The article presents a research which investigates the software quality of climate models, defined as an executable theory of the climate. An analysis of defect reports and defect fixes in a variety of versions of climate models by collecting defect data from bug tracking systems and version control repository comments is performed. The implication of the findings of the research for the assessment of trustworthiness of climate model software is discussed.

The article presents a study on parallel computational uncertainty on Coupled General Climate Model (CGCM) simulations. It provides an investigation of the uncertainty on climate simulations through the Community Climate System Model Version 3 (CCSM3). It mentions a series of sensitivity analyses focused on global and Nino3.4 sea surface temperatures (SSTs). It also notes that the impact can be neglected through 30-year simulation in climatology.

The article presents a study on the ocean-atmosphere general circulation low resolution model, Fast Met Office/UK Universities Simulator (FAMOUS). It mentions an update of its description for modifications due to its application in the CMIP5 EMIC model intercomparison project (EMICmip). It notes its various version such as XFXWB, XFHCC and XDBUA. It also points out that the first version has a good-conserved water budget and cooling in high latitude areas while the other improves climatology.

The article discusses the experimental design and initial results relevant to the simulation of the mid-Pliocene warm period (MPWP) using MIROC, an atmosphere-ocean general circulation model (AOGCM). It relates that simulating MPWP is part of the Pliocene Model Intercomparison Project (PlioMIP). It identifies MPWP as the period in earth's history in which global increase in temperature had reached the predicted magnitude for the late 21st century duration.

The article offers strategies relevant to mapping climate and climate change information, including uncertainty climatic condition. It proposes a clear technique designed to follow standard cartographic practicse to map climate variables. It relates that the proposed strategy is visible to color blind people and is easy to replicate and understand.

The article discusses the Hadley Centre Global Environment Model version 2 (HadGEM2) family of climate configurations that comprises a range of specific model configurations. It offers a detailed descriptions and evaluations of HadGEM2 family members and its overall performance using a set of model metrics. It notes that HadGEM2 family of configurations includes atmosphere and ocean components with well-resolved stratosphere and earth-system.

Four simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model have been evaluated with the Earth System Model Validation Tool (ESMValTool) to identify differences in simulated ozone and selected climate parameters that resulted from (i) different setups of the EMAC model (nudged vs. free-running) and (ii) different boundary conditions (emissions, sea surface temperatures (SSTs) and sea-ice concentrations (SICs)). To assess the relative performance of the simulations, quantitative performance metrics are calculated consistently for the climate parameters and ozone. This is important for the interpretation of the evaluation results since biases in climate can impact on biases in chemistry and vice versa. The observational datasets used for the evaluation include ozonesonde and aircraft data, meteorological reanalyses and satellite measurements. The results from a previous EMAC evaluation of a model simulation with weak nudging towards realistic meteorology in the troposphere have been compared to new simulations with different model setups and updated emission datasets in free-running timeslice and nudged Quasi Chemistry-Transport Model (QCTM) mode. The latter two configurations are particularly important for chemistry-climate projections and for the quantification of individual sources (e.g. transport sector) that lead to small chemical perturbations of the climate system, respectively. With the exception of some specific features which are detailed in this study, no large differences that could be related to the different setups of the EMAC simulations (nudged vs. free-running) were found, which offers the possibility to evaluate and improve the overall model with the help of shorter nudged simulations. The main differences between the two setups is a better representation of the tropospheric and stratospheric temperature in the nudged simulations, which also better reproduce stratospheric water vapour concen trations, due to the improved simulation of the temperature in the tropical tropopause layer. Ozone and ozone precursor concentrations on the other hand are very similar in the different model setups, if similar boundary conditions are used. Different boundary conditions however lead to relevant differences in the four simulations. SSTs and SICs, which are prescribed in all simulations, play a key role in the representation of the ozone hole, which is significantly underestimated in some experiments. A bias that is present in all simulations is an overestimation of tropospheric column ozone, which is significantly reduced when lower lightning emissions of nitrogen oxides are used. To further investigate possible other reasons for such bias, two sensitivity simulations with an updated scavenging routine and the addition of a newly proposed HNO3-forming channel of the HO2 +NO reaction were performed. The update in the scavenging routine resulted in a slightly better representation of ozone compared to the reference simulation. The introduction of the new HNO3-forming channel significantly reduces this bias. Therefore, including the new reaction rate could potentially be important for a realistic simulation of tropospheric ozone, although laboratory experiments and other models studies need to confirm this hypothesis and some modifications to the rate, which has a strong dependence on water vapour, might also still be needed. [ABSTRACT FROM AUTHOR]

The article investigates the biogeochemistry-climate interactions through the evaluation of four plant functional types (PFT) datasets which were based on land-cover information from three satellite sensors. It relates that the concept of PFT is important to the dynamic global vegetation models (DGVM) in grouping plant species. It mentions that PFT is also significant in reducing uncertainty of terrestrial biogeochemistry to climate variability.

The article presents a study which focuses on creating a simulation of the extra-tropical climate variability in the Southern Hemisphere (SH) using a combined atmosphere-ocean model. It relates that the said model combines the idealized quasi-geographic model of SH's wintertime atmospheric circulation with a general ocean circulation model. It notes that the model's development is motivated by the need to determine the role of atmosphere-ocean interaction in shaping climate variability.

The article discusses the impact of the upgraded version of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 3 reduced-resolution (Mk3L) climate system model on existing atmospheric variables such as near-surface air temperature. It relates that the new model integrates the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, replacing the default surface model in Mk3L. It shows that the upgraded model offers an improved near surface-climatology.

The article focuses on a new version of the M&#00E9;téo-France CNRM Chemistry-Climate Model (CCM) with emphasis on its heritage, specifications and deficiencies. It highlights the inclusion of the stratospheric chemistry of the authors' Chemistry-Transport model MOCAGE on-line within the GCM. Also discussed is the elimination of the erroneous representation of aerosols from volcanoes.

The article discusses a research study which presents the GEOCLIM reloaded, a new version of the coupled Earth system model GEOCLIM. The said model is designed to examine the short- and long-term responses between diagenesis, continental inputs and climatic conditions. The performance of GEOCLIM reloaded is assessed through comparing steady-state simulation with global estimates of bio-element cycling and comprehensive set of oceanic data.

The article presents a study on a regional climate model (RegCM) coupled with the University of Washington (UW) turbulence parameterization. It describes improvements in the coastal and non-coastal climatology of the model along with enhancements in its representation of stratiform clouds. It also notes that the model later known as RegCM-UW is proper to use in regional climate research and ameliorates the creation of the marine boundary layer.

The article discusses the use of Consortium for Small Scale Modelling's (COSMO) numerical weather prediction model. It notes that the model is connected with the Modular Earth Submodel System (MESSy), offering diagnostic submodels for atmospheric chemistry simulations. The implementation of MESSy regular submodels and their descriptions as well as the representation of distinct meteorological situations are tackled.

The article describes the development and examination of an Earth system model that is suitable for centennial-scale prediction of climates. It notes that the terrestrial and ocean ecosystems and gas-phase tropospheric chemistry along with coupled interactions are the main new components added to the physical climate model. It concludes that the said model is capable of evaluating the strenghts of biogeochemical feedbacks.

The article discusses a research study which describes the design and implementation of Hadley Centre Global Environmental Model (HadGEM3). The said climate model system couples the Nucleus for European Modelling of the Ocean (NEMO), the Los Alamos sea ice model (CICE) and the Met Office Unified Model atmospheric component. Findings reveal that the implementation of the HadGEM3 model could result to the accurate conservation of heat and freshwater throughout the model components used.

The article discusses the role of atmospheric aerosols for the increase in human mortality and morbidity. It explores the size-resolved particle dry deposition scheme that is designed for inclusion of air quality and climate models. It examines the validation of the scheme along with the existing measurements performed on desert, grass, and coniferous forest. It offers a comparison of this model with measurements on snow and further measures are needed to assure the model accuracy.

The article explores the evaluation and description of the global Community Atmosphere Model (CAM) version 4 for atmospheric chemistry in Community Earth System Model (CESM). It reports that the atmospheric chemistry is responsible for the distribution of non-carbon dioxide gases and aerosols which influence the climate and air quality. Details on topics including the offline meteorology, chemical mechanisms, and emissions are discussed.

The article discusses the optimization of FAst Met Office/UK Universities Simulator (FAMOUS) climate model's atmospheric radiation algorithm in Great Britain. The translation of Fortran code to the programming code of C and the restructuring of algorithm to the calculation of a single column are also tackled. It also notes the elements of Intel-compatible 10 processors.

The article discusses the Paleoclimate Model Intercomparison Project Phase III (PMIPP3) experiments on climate forcings. It offers updates on the reconstructions of the land use and the changes in land cover, and the solar activity calibration. It also discusses the radiative forcing used to estimate actual forcing in a climate model.

The Coupled Model Intercomparison Project (CMIP) is one of the biggest international efforts to better understand past, present and future climate changes in a multi-model context. A total of 21 Model Intercomparison Projects (MIPs) were endorsed in its 6th phase (CMIP6), which included 190 different experiments that were used to simulate 40000 years and produced around 40 PB of data in total. This paper shows the main results obtained from the collection of performance metrics done for CMIP6 (CPMIP). The document provides the list of partners involved, the CPMIP metrics per institution/model, and the approach used for the collection and the coordination behind this process. Furthermore, a section has been included to analyze the results and prove the usefulness of the metrics for the community. Moreover, we describe the main difficulties faced during the collection and propose recommendations for future exercises. [ABSTRACT FROM AUTHOR]

This paper describes a new satellite simulator for the Satellite Application Facility on Climate Monitoring (CM SAF) cLoud, Albedo and RAdiation dataset (CLARA), Advanced Very High Resolution Radiometer (AVHRR)-based, version 2 (CLARA-A2) Climate Data Record (CDR). This simulator takes into account the variable skill in cloud detection in the CLARA-A2 CDR by using a different approach to other similar satellite simulators to emulate the ability to detect clouds. In particular, the paper describes three methods to filter out clouds from climate models undetectable by observations. The first method, compared to the simulators in Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP), relies on one global visible cloud optical depth at 550nm (τc) threshold to delineate cloudy and cloud-free conditions. Method two and three apply long/lat -gridded values separated by day and nighttime conditions. Method two uses gridded varying τc as opposed to method one that uses just a single τc threshold, and method three uses a cloud Probability of Detection (POD) depending on the model τc. Method two and three replicate the relative ease or difficulty for cloud retrievals depending on the region and illumination by increasing the cloud sensitivity where the cloud retrievals are relatively straightforward, such as over mid-latitude oceans, and by decreasing the sensitivity where cloud retrievals are notoriously tricky, such as over the Arctic region during the polar night. Method three has the added advantage that it indirectly takes into account that cloud retrievals in some areas are more likely than others to miss some clouds. This situation is common in cold regions where even thick clouds may be inseparable from cold, snow-covered surfaces and also in areas with an abundance of broken and small scale cumulus clouds such as the atmospheric subsidence regions over the ocean. The simulator, together with the International Satellite Cloud Climatology Project (ISCCP) simulator of COSP, is used to assess Arctic clouds in the EC-Earth climate model compared to the CLARA-A2 and ISCCP-H CDRs. Compared to CLARA-A2, EC-Earth is shown to underestimate cloudiness in the Arctic generally. However, compared to ISCCP and its simulator, the opposite conclusion is reached. Previous studies have found that the CLARA-A2 CDR performs well in the Arctic during the summer months, and this paper shows that the simulated cloud mask of CLARA-A2 using method three is more representative of the CDR than method one used in COSP, using a global τc threshold to simulate clouds. Therefore, the conclusion that EC-Earth underpredicts clouds in the Arctic is the more likely one. The simulator substantially improves the simulation of the CLARA-A2 detected clouds, especially in the polar regions, by accounting for the variable cloud detection skill over the year. The approach to cloud simulation based on the POD of clouds depending on their cloud optical depth, location, and illumination is the preferred one as it reduces cloudiness over a range of cloud optical depths. Climate model comparisons with satellite-derived information can be significantly improved by this approach, mainly by reducing the risk of misinterpreting problems with satellite retrievals as cloudiness features. [ABSTRACT FROM AUTHOR]

This paper describes GCAM v5.1, an open source model that represents the linkages between energy, water, land, climate, and economic systems. GCAM is a market equilibrium model, is global in scope, and operates from 1990 to 2100 in five-year time steps. It can be used to examine, for example, how changes in population, income, or technology cost might alter crop production, energy demand, or water withdrawals, or how changes in one region's demand for energy affect energy, water, and land in other regions. This paper describes the model, including its assumptions, inputs, and outputs. We then use eleven scenarios, varying socioeconomic and climate policy assumptions, to illustrate the results from the model. The resulting scenarios illustrate a wide range of potential future energy, water, and land uses. We compare the results from GCAM v5.1 to historical data and to future scenario simulations from earlier versions of GCAM and from other models. Finally, we provide information on how to obtain the model. [ABSTRACT FROM AUTHOR]

This paper describes the solar forcing dataset for CMIP6 and highlights in particular changes with respect to the CMIP5 recommendation. The solar forcing is provided for radiative properties, i.e., total solar irradiance (TSI) and solar spectral irradiance (SSI), and F10.7 cm radio flux, as well as particle forcing, i.e., geomagnetic indices Ap and Kp, and ionisation rates to account for effects of solar protons, electrons and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing is provided for a CMIP exercise. The solar forcing dataset is provided at daily and monthly resolution separately for the CMIP6 Historical Simulation (1850-2014), for the future (2015-2300), including an additional extreme Maunder Minimum-like sensitivity scenario, as well as for a constant and a time-varying forcing for the preindustrial control simulation. The paper not only describes the forcing dataset, but also provides detailed recommendations for how to implement the different forcing components in climate models. The TSI and SSI time series are defined as averages of two (semi-) empirical solar irradiance models, namely the NRLTSI2/NRLSSI2 and SATIRE-TS. A new and lower TSI value is recommended: the contemporary solar cycle-average is now 1361.0 W/m². The slight negative trend in TSI during the last three solar cycles in CMIP6 is statistically indistinguishable from available observations and only leads to a small global radiative forcing of -0.04 W/m². In the 200-400 nm range, which is also important for ozone photochemistry, CMIP6 shows a larger solar cycle variability contribution to TSI than CMIP5 (50 % as compared to 35 %). The CMIP6 dataset is tested and compared to its CMIP5 predecessor using timeslice experiments of two chemistry-climate models and a reference radiative transfer model. The changes in the background SSI in the CMIP6 dataset, as compared to CMIP5, impact on climatological stratospheric conditions (lower shortwave heating rates (-0.35 K/day at the stratopause), cooler stratospheric temperatures (-1.5 K in the upper stratosphere), lower ozone abundances in the lower stratosphere (-3 %), and higher ozone abundances (+1.5 % in the upper stratosphere and lower mesosphere). Between the maximum and minimum phases of the 11-year solar cycle, there is an increase in shortwave heating rates (+0.2 K/day at the stratopause), temperatures (~1 K at the stratopause), and ozone (+2.5 % in the upper stratosphere) in the tropical upper stratosphere using the CMIP6 forcing dataset. This solar cycle response is slightly larger, but not statistically significantly different from that for the CMIP5 forcing dataset. CMIP6 models with a well-resolved shortwave radiation scheme are encouraged to use SSI, as well as solar-induced ozone signals, in order to better represent solar climate variability compared to models that only prescribe TSI and/or exclude the solar-ozone response. Monthly mean solar-induced ozone variations will also be incorporated into the CCMI CMIP6 Ozone Database for climate models that do not calculate ozone interactively. CMIP6 models with interactive chemistry are encouraged to use the particle forcing which will allow the potential long-term effect of particles to be addressed for the first time. The consideration of particle forcing has been shown to significantly improve the representation of reactive nitrogen and ozone variability in the polar middle atmosphere, eventually resulting in further improvements of the representation of solar climate variability. [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and their coupling, as well as various aspects of model development, including tuning, optimization and a reproducibility strategy. We also document the stability of the model using a long control simulation, quantify the model's ability to reproduce large scale features of the historical climate, and evaluate the response of the model to external forcing. CanESM5 is comprised of three dimensional atmosphere (T63 spectral resolution/2.8°) and ocean (nominally 1°) general circulation models, a sea ice model, a land surface scheme, and explicit land and ocean carbon cycle models. The model features relatively coarse resolution and high throughput, which facilitates the production of large ensembles. CanESM5 has a notably higher equilibrium climate sensitivity (5.7 K) than its predecessor CanESM2 (3.8 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations are contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6), and will be employed for climate science and service applications in Canada. [ABSTRACT FROM AUTHOR]

This paper presents a new version of HCLIM, a regional climate modelling system based on the ALADIN-HIRLAM numerical weather prediction (NWP) system. HCLIM uses atmospheric physics packages from three NWP model configurations, HARMONIE-AROME, ALARO and ALADIN, which are designed for use at different horizontal resolutions. The main focus of HCLIM is convection permitting climate modelling, i.e. developing the climate version of HARMONIE-AROME. In HCLIM, the ALADIN and ALARO physics packages are used for coarser resolutions where convection needs to be parameterized. Here we describe the structure, development and performance of the current recommended HCLIM version, cycle 38. HCLIM38 is a new system for regional climate modelling and it is being used in a number of national and international projects over different domains and climates, ranging from equatorial to polar regions. Our initial evaluation indicates that HCLIM38 is applicable in different conditions and provides satisfactory results without additional region-specific tuning. HCLIM is developed by a consortium of national meteorological institutes in close collaboration with the ALADIN-HIRLAM NWP model development. While the current HCLIM cycle has considerable differences in model setup compared to the NWP version (primarily in the description of the surface), it is planned for the next cycle release that the two versions will use a very similar setup. This will ensure a feasible and timely climate model development and updates in the future and provide evaluation of long-term model biases to both NWP and climate model developers. [ABSTRACT FROM AUTHOR]

Due to its extension, geography and the presence of several under-developed or developing economies, the Central Asia domain of the Coordinated Regional climate Downscaling Experiment (CORDEX) is one of the most vulnerable regions on Earth to the effects of climate changes. Reliable information on potential future changes with high spatial resolution acquire significant importance for the development of effective adaptation and mitigation strategies for the region. In this context, Regional Climate Models (RCMs) play a fundamental role. In this paper, the results of a set of sensitivity experiments with the regional climate model COSMO-CLM version 5.0, for the Central Asia CORDEX domain, are presented. Starting from a reference model setup, general model performance is evaluated for present-days, testing the effects of a set of singular physical parameterizations and their mutual interaction on the simulation of monthly and seasonal values of three variables that are important for impact studies: 2-meter temperature, precipitation and diurnal temperature range. The final goal of this study is two-fold: having a general overview of model performance and its uncertainties for the considered region and determining at the same time an optimal model configuration. Results show that the model presents remarkable deficiencies over different areas of the domain. The combined change of the albedo taking into consideration the ratio of forest fractions and the soil conductivity taking into account the ratio of liquid water and ice in the soil, allows to achieve the best improvements in model performance in terms of climatological means. Importantly, the model seems to be particularly sensitive to those parameterizations that deal with soil and surface features, and that could positively affect the repartition of incoming radiation. The results for the mean climate appear to be independent of the observational dataset used for evaluation and of the boundary data employed to force the simulations. On the other hand, due to the large uncertainties in the variability estimates from observations, the use of different boundaries and the model internal variability, it has not been possible to rank the different simulations according to their representation of the monthly variability. This work is the first ever sensitivity study of an RCM for the CORDEX Central Asia domain and its results are of fundamental importance for further model development and for future climate projections over the area. [ABSTRACT FROM AUTHOR]

The need for assessing the risk of extreme weather events is ever increasing. In addition to quantification of risk today, the role of aggravating factors such as high population growth and changing climate conditions do matter, too. We present the open source software CLIMADA, which integrates hazard, exposure and vulnerability to compute the necessary metrics to assess risk and to quantify socio-economic impact. The software design is modular and object-oriented, offering a simple collaborative framework and a parallelization strategy which allows for scalable computations on clusters. CLIMADA supports multi-hazard calculations and provides an event-based probabilistic approach that is globally consistent for a wide range of resolutions, suitable for whole-country to detailed local studies. This paper uses the platform to estimate and contextualize the damage of hurricane Irma in the Caribbean in 2017. Most of the affected islands are non-sovereign countries and do also rely on overseas support in case disaster strikes. The risk assessment performed for this region, based on remotely available data available shortly before or hours after landfall of Irma, proves to be close to reported damage and hence demonstrates a method to provide readily available impact estimates and associated uncertainties in real time. [ABSTRACT FROM AUTHOR]

This paper presents a system to perform large ensembles climate stochastic forecasts. The system is based on random analogue sampling of sea-level pressure data from the NCEP reanalysis. It is tested to forecast an NAO index and the daily average temperature in five European stations. We simulated 100 member ensembles of averages over lead times from 5 days to 80 days in a hindcast mode, i.e. from a meteorological to a seasonal forecast. We tested the hindcast simulations with usual forecast skill scores (CRPSS or correlation), against persistence and climatology. We find significantly positive skill scores for all time scales. Although this model cannot outperform numerical weather prediction, it presents an interesting benchmark that could complement climatology or persistence forecast. [ABSTRACT FROM AUTHOR]

The extent to which climate conditions influenced the spatial distribution of hominin populations in the past is highly debated. General Circulation Models (GCMs) and archaeological data have been used to address this issue. Most GCMs are not currently capable of simulating past surface climate conditions with sufficiently detailed spatial resolution to distinguish areas of potential hominin habitat, however. In this paper we propose a Statistical Downscaling Methods (SDM) for increasing the resolution of climate model outputs in a computationally efficient way. Our method uses a generalized additive model (GAM), calibrated over present-day data, to statistically downscale temperature and precipitation from the outputs of a GCM simulating the climate of the Last Glacial Maximum (19-23 000 BP) over Western Europe. Once the SDM is calibrated, we first interpolate the coarse-scale GCM outputs to the final resolution and then use the GAM to compute surface air temperature and precipitation levels using these interpolated GCM outputs and fine resolution geographical variables such as topography and distance from an ocean. The GAM acts as a transfer function, capturing non-linear relationships between variables at different spatial scales. We tested three different techniques for the first interpolation of GCM output: bilinear, bicubic, and kriging. The results were evaluated by comparing downscaled temperature and precipitation at local sites with paleoclimate reconstructions based on paleoclimate archives (archaeozoological and palynological data). Our results show that the simulated, downscaled temperature and precipitation values are in good agreement with paleoclimate reconstructions at local sites confirming that our method for producing fine-grained paleoclimate simulations suitable for conducting paleo-anthropological research is sound. In addition, the bilinear and bicubic interpolation techniques were shown to distort either the temporal variability or the values of the response variables, while the kriging method offers the best compromise. Since climate variability is an aspect of their environment to which human populations may have responded in the past this is an important distinction. [ABSTRACT FROM AUTHOR]