scholarly journals COSMO-CLM Regional Climate Simulations in the CORDEX framework: a review

2021 ◽  
Author(s):  
Silje Lund Sørland ◽  
Roman Brogli ◽  
Praveen Kumar Pothapakula ◽  
Emmanuele Russo ◽  
Jonas Van de Walle ◽  
...  
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Parameter Tuning ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Limited Area ◽  
Climate Projections ◽  
Climate Modelling ◽  
Near Surface ◽  
Climate Simulations

Abstract. In the last decade, the Climate Limited-area Modeling (CLM) Community has contributed to the Coordinated Re- gional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM community model, ERA-Interim reanalysis and eight Global Climate Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44° (∼50 km), 0.22° (∼25 km) and 0.11° (∼12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Fed- eration (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modelling communities is needed to increase the reliability of the GCM-RCM modelling chain.

scholarly journals COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

2021 ◽  
Vol 14 (8) ◽  
pp. 5125-5154
Author(s):  
Silje Lund Sørland ◽  
Roman Brogli ◽  
Praveen Kumar Pothapakula ◽  
Emmanuele Russo ◽  
Jonas Van de Walle ◽  
...  
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Parameter Tuning ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Limited Area ◽  
Climate Projections ◽  
Near Surface ◽  
Climate Simulations ◽  
Climate Downscaling

Abstract. In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km), and 0.11∘ (∼ 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM–RCM modeling chain.

scholarly journals Design of a regional climate modelling projection ensemble experiment – NARCliM

2014 ◽  
Vol 7 (2) ◽  
pp. 621-629 ◽  
Author(s):  
J. P. Evans ◽  
F. Ji ◽  
C. Lee ◽  
P. Smith ◽  
D. Argüeso ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Selection Process ◽  
Regional Climate ◽  
Global Climate Models ◽  
Regional Climate Modelling ◽  
Future Research ◽  
Climate Projections ◽  
Climate Modelling ◽  
Future Change

Abstract. Including the impacts of climate change in decision making and planning processes is a challenge facing many regional governments including the New South Wales (NSW) and Australian Capital Territory (ACT) governments in Australia. NARCliM (NSW/ACT Regional Climate Modelling project) is a regional climate modelling project that aims to provide a comprehensive and consistent set of climate projections that can be used by all relevant government departments when considering climate change. To maximise end user engagement and ensure outputs are relevant to the planning process, a series of stakeholder workshops were run to define key aspects of the model experiment including spatial resolution, time slices, and output variables. As with all such experiments, practical considerations limit the number of ensemble members that can be simulated such that choices must be made concerning which global climate models (GCMs) to downscale from, and which regional climate models (RCMs) to downscale with. Here a methodology for making these choices is proposed that aims to sample the uncertainty in both GCM and RCM ensembles, as well as spanning the range of future climate projections present in the GCM ensemble. The RCM selection process uses performance evaluation metrics to eliminate poor performing models from consideration, followed by explicit consideration of model independence in order to retain as much information as possible in a small model subset. In addition to these two steps the GCM selection process also considers the future change in temperature and precipitation projected by each GCM. The final GCM selection is based on a subjective consideration of the GCM independence and future change. The created ensemble provides a more robust view of future regional climate changes. Future research is required to determine objective criteria that could replace the subjective aspects of the selection process.

scholarly journals Assessment of the Canary current upwelling system in a regionally coupled climate model

2021 ◽  
Author(s):  
Ruben Vazquez ◽  
Ivan Parras-Berrocal ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Rafael Mañanes ◽  
...  
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Climate Change Signal ◽  
Climate Modelling ◽  
Near Surface ◽  
Upwelling System ◽  
The Impact ◽  
Mesoscale Processes

AbstractThe Canary current upwelling is one of the major eastern boundary coastal upwelling systems in the world, bearing a high productive ecosystem and commercially important fisheries. The Canary current upwelling system (CCUS) has a large latitudinal extension, usually divided into upwelling zones with different characteristics. Eddies, filaments and other mesoscale processes are known to have an impact in the upwelling productivity, thus for a proper representation of the CCUS and high horizontal resolution are required. Here we assess the CCUS present climate in the atmosphere–ocean regionally coupled model. The regional coupled model presents a global oceanic component with increased horizontal resolution along the northwestern African coast, and its performance over the CCUS is assessed against relevant reanalysis data sets and compared with an ensemble of global climate models (GCMs) and an ensemble of atmosphere-only regional climate models (RCMs) in order to assess the role of the horizontal resolution. The coupled system reproduces the larger scale pattern of the CCUS and its latitudinal and seasonal variability over the coastal band, improving the GCMs outputs. Moreover, it shows a performance comparable to the ensemble of RCMs in representing the coastal wind stress and near-surface air temperature fields, showing the impact of the higher resolution and coupling for CCUS climate modelling. The model is able of properly reproducing mesoscale structures, being able to simulate the upwelling filaments events off Cape Ghir, which are not well represented in most of GCMs. Our results stress the ability of the regionally coupled model to reproduce the larger scale as well as mesoscale processes over the CCUS, opening the possibility to evaluate the climate change signal there with increased confidence.

scholarly journals Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble

2021 ◽  
Author(s):  
Guillaume Evin ◽  
Samuel Somot ◽  
Benoit Hingray
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Uncertainty Assessment ◽  
Global Climate Models ◽  
Climate Projections ◽  
Total Uncertainty ◽  
Near Surface

Abstract. Large Multiscenarios Multimodel Ensembles (MMEs) of regional climate model (RCM) experiments driven by Global Climate Models (GCM) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse Scenario-GCM-RCM matrices, these large ensembles are however very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest ensemble ever produced for regional projections in Europe. This analysis provides i) the most up-to-date and balanced estimates of mean changes for near-surface temperature and precipitation in Europe, ii) the total uncertainty of projections and its partition as a function of time, and iii) the list of the most important contributors to the model uncertainty. For changes of total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071–2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in Central-Eastern Europe for instance, the difference between balanced and direct estimates are up to 0.8 °C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century.

scholarly journals A regional climate modelling projection ensemble experiment – NARCliM

2013 ◽  
Vol 6 (3) ◽  
pp. 5117-5139 ◽  
Author(s):  
J. P. Evans ◽  
F. Ji ◽  
C. Lee ◽  
P. Smith ◽  
D. Argüeso ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Planning Process ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Regional Climate Modelling ◽  
Climate Projections ◽  
Climate Modelling ◽  
User Engagement

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

scholarly journals Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble

2021 ◽  
Vol 12 (4) ◽  
pp. 1543-1569
Author(s):  
Guillaume Evin ◽  
Samuel Somot ◽  
Benoit Hingray
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Uncertainty Assessment ◽  
Global Climate Models ◽  
Climate Projections ◽  
Total Uncertainty ◽  
Near Surface

Abstract. Large multiscenario multimodel ensembles (MMEs) of regional climate model (RCM) experiments driven by global climate models (GCMs) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse scenario–GCM–RCM matrices, these large ensembles, however, are very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest MME based on regional climate models ever produced in Europe. This analysis provides a detailed description of this MME, including (i) balanced estimates of mean changes for near-surface temperature and precipitation in Europe, (ii) the total uncertainty of projections and its partition as a function of time, and (iii) the list of the most important contributors to the model uncertainty. For changes in total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071–2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in central–eastern Europe for instance, the difference between balanced and direct estimates is up to 0.8 ∘C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century.

Comparison of different infiltration schemes in the regional climate model REMO

2021 ◽  
Author(s):  
Daniel Abel ◽  
Katrin Ziegler ◽  
Felix Pollinger ◽  
Heiko Paeth
Keyword(s):  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Root Zone ◽  
Regional Climate ◽  
Climate Projections ◽  
Soil Hydrology ◽  
Spatiotemporal Resolution ◽  
Development Fund ◽  
Near Surface

<p>The European Regional Development Fund-Project BigData@Geo aims to create highly resolved climate projections for the model region of Lower Franconia in Bavaria, Germany. These projections are analyzed and made available to local stakeholders of agriculture, forestry, and viniculture as well as general public. Since regional climate models’ spatiotemporal resolution often is too coarse to deal with such local issues, the regional climate model REMO is improved within the frame of the project in cooperation with the Climate Service Center Germany (GERICS).</p><p>Accurate and highly resolved climate projections require realistic modeling of soil hydrology. Thus, REMO’s original bucket scheme is replaced by a 5-layer soil scheme. It allows for the representation of water below the root zone. Evaporation is possible solely from the top layer instead of the entire bucket and water can flow vertically between the layers. Consequently, the properties and processes change significantly compared to the bucket scheme. Both, the bucket and the 5-layer scheme, use the improved Arno scheme to separate throughfall into infiltration and surface runoff.</p><p>In this study, we examine if this scheme is suitable for use with the improved soil hydrology or if other schemes lead to better results. For this, we (1) modify the improved Arno scheme and further introduce the infiltration equations of (2) Philip as well as (3) Green and Ampt. First results of the comparison of these four different schemes and their influence on soil moisture and near-surface atmospheric variables are presented.</p>

scholarly journals Evaluation of the impacts of climate variability on rainfed maize production over the Wami-Ruvu basin of Tanzania

2017 ◽  
Vol 9 (1) ◽  
pp. 207-222 ◽  
Author(s):  
Philbert Luhunga
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Pearson Correlation ◽  
Regional Climate ◽  
Maximum Temperature ◽  
Climate Projections ◽  
Historical Climate ◽  
Climate Simulations ◽  
Maize Yields ◽  
The Impact

AbstractIn this study, the impact of inter-seasonal climate variability on rainfed maize (Zea mays) production over the Wami-Ruvu basin of Tanzania is evaluated. Daily high-resolution climate simulations from the Coordinated Regional Climate Downscaling Experiment_Regional Climate Models (CORDEX_RCMs) are used to drive the Decision Support System for Agro-technological Transfer (DSSAT) to simulate maize yields. Climate simulations for the base period of 35 years (1971–2005) are used to drive DSSAT to simulate maize yields during the historical climate. On the other hand, climate projections for the period 2010–2039 (current), 2040–2069 (mid), and 2070–2099 centuries for two Representative Concentration Pathway (RCP45 and 85) emission scenarios are used to drive DSSAT to simulate maize yields in respective centuries. Statistical approaches based on Pearson correlation coefficient and the coefficients of determination are used in the analysis. Results show that rainfall, maximum temperature, and solar radiation are the most important climate variables that determine variation in rainfed maize yields over the Wami-Ruvu basin of Tanzania. They explain the variability in maize yields in historical climate condition (1971–2005), present century under RCP 4.5, and mid and end centuries under both RCP 4.5 and RCP 8.5.

scholarly journals Assessment of The Canary Current Upwelling System In A Regionally Coupled Climate Model

2021 ◽  
Author(s):  
Ruben Vazquez ◽  
Ivan Parras-Berrocal ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Rafael Mañanes ◽  
...  
Keyword(s):  
Climate Models ◽  
Coastal Upwelling ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Temperature Fields ◽  
Climate Change Signal ◽  
Near Surface ◽  
Upwelling System ◽  
Spatial Coverage ◽  
Mesoscale Processes

Abstract The Canary current upwelling is one of the major eastern boundary coastal upwelling systems in the world, bearing a high productive ecosystem and commercially important fisheries. The Canary current upwelling system (CCUS) has a large latitudinal extension, usually divided into upwelling zones with different characteristics. Eddies, filaments and other mesoscale processes are known to have an impact in the upwelling productivity, thus for a proper representation of the CCUS a large spatial coverage and high horizontal resolution are required. Here we assess the CCUS present climate in the atmosphere-ocean regionally coupled model ROM (REMO-OASIS-MPIOM). ROM presents a global oceanic component with increased horizontal resolution along the northwestern African coast, and its performance over the CCUS is assessed against relevant reanalysis data sets and compared with an ensemble of global climate models (GCMs) and an ensemble of atmosphere-only regional climate models (RCMs) in order to assess the role of the horizontal resolution. ROM reproduces the larger scale pattern of the CCUS and its latitudinal and seasonal variability over the coastal band, improving the GCMs outputs. ROM shows a performance comparable to the ensemble of RCMs in representing the coastal wind stress and near-surface air temperature fields. ROM is able of properly reproducing mesoscale structures, being able to simulate the upwelling filaments events off Cape Ghir, which are not well represented in most of GCMs. Our results stress the ability of ROM to reproduce the larger scale as well as mesoscale processes over the CCUS, opening the possibility to evaluate the climate change signal there with increased confidence.

scholarly journals Ensemble analysis of frost damage on vegetation caused by spring backlashes in a warmer Europe

2011 ◽  
Vol 11 (2) ◽  
pp. 401-418 ◽  
Author(s):  
A. M. Jönsson ◽  
L. Bärring
Keyword(s):  
Climate Models ◽  
Emission Scenario ◽  
Regional Climate ◽  
Frost Damage ◽  
Global Climate Models ◽  
Climate Modelling ◽  
Climate Data ◽  
Spring Frost ◽  
Increased Risk ◽  
Freezing Temperatures

Abstract. Tree dehardening and budburst will occur earlier in a warmer climate, and this could lead to an increased risk of frost damage caused by temperature backlashes. By using a spring backlash index and a cold hardiness model, we assessed different aspects of risk for frost damage in Norway spruce forests during the present climate and for one future emission scenario. Uncertainties associated with climate modelling were quantified by using temperature data from three climate data sets: (1) E-Obs gridded observed climate data, (2) an ensemble of data from eight regional climate models (RCM) forced by ERA-40 reanalysis data, (3) an ensemble of regional climate scenarios produced by the regional climate model RCA3 driven at the boundary conditions by seven global climate models (GCM), all representing the SRES A1B emission scenario. The frost risk was analysed for three periods, 1961–1990, 2011–2040 and 2070–2097. The RCA3_GCM ensemble indicated that the risk for spring frost damage may increase in the boreo-nemoral forest zone of southern Scandinavia and the Baltic states/Belarus. This is due to an increased frequency of backlashes, lower freezing temperatures after the onset of the vegetation period and the last spring frost occurring when the trees are closer to budburst. The changes could be transient due to the fine balance between an increased risk of frost damage caused by dehardening during a period when freezing temperatures are common and a decreased risk caused by warmer temperatures. In the nemoral zone, the zone with highest risk for spring backlashes during the reference period (1961–1990), the spring frost severity may increase due to frost events occurring when the trees are closer to budburst. However, the risk in terms of frequency of backlashes and freezing temperature were projected to become lower already in the beginning of this century.

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