scholarly journals Can high-resolution GCMs reach the level of information provided by 12–50 km CORDEX RCMs in terms of daily precipitation distribution?

Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  
Silje L. Sørland ◽  
Malcolm J. Roberts ◽  
Urs Beyerle ◽  
...  

Abstract. In this study, we perform an evaluation of PRIMAVERA high-resolution (25–50 km) Global Climate Models (GCMs) relative to CORDEX Regional Climate Models (RCMs) over Europe (12–50 km resolutions). It is the first time such assessment is performed for regional climate information using ensembles of GCMs and RCMs at similar horizontal resolutions. We perform this exercise for the distribution of daily precipitation contributions to rainfall bins over Europe under current climate conditions. Both ensembles are evaluated against high quality national gridded observations in terms of resolution and station density. We show that PRIMAVERA GCMs simulate very similar distribution to CORDEX RCMs that CMIP5 cannot because of their coarse resolutions. PRIMAVERA and CORDEX ensembles generally show similar strengths and weaknesses. They are of good quality in summer and autumn in most European regions, but tend to overestimate precipitation in winter and spring. PRIMAVERA show improvements in the latter bias by reducing mid-rain rate biases in Central and Eastern Europe. Moreover, CORDEX simulate less light rainfall than PRIMAVERA in most regions and seasons, which improves this common GCM bias. Finally, PRIMAVERA simulate less heavy precipitation than CORDEX in most regions and seasons, especially in summer. PRIMAVERA appear to be closer to observations. However, when we apply an averaged precipitation undercatch error of 20 %, CORDEX become closer to these synthetic datasets. Considering 50 km resolution GCM or RCM datasets over Europe results in large benefits compared to CMIP5 models for impact studies at the regional scale. The effect of increasing resolution from 50 km to 12 km in CORDEX simulations is, in comparison, small in most regions and seasons outside mountainous regions (due to the importance of orography) and coastal regions (mostly depending on the resolution of the land-sea contrast). Now that GCMs are able to reach the level of information provided by CORDEX RCMs run at similar resolutions, there is an opportunity to better coordinate GCM and RCM simulations for future model intercomparison projects.

2020 ◽  
Vol 13 (11) ◽  
pp. 5485-5506
Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  
Jesús Fernández ◽  
Silje L. Sørland ◽  
Roman Brogli ◽  
...  

Abstract. In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale.


2021 ◽  
Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  

<p>In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events.</p><p>The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale.</p>


2020 ◽  
Vol 59 (2) ◽  
pp. 207-235 ◽  
Author(s):  
Lei Zhang ◽  
YinLong Xu ◽  
ChunChun Meng ◽  
XinHua Li ◽  
Huan Liu ◽  
...  

AbstractIn aiming for better access to climate change information and for providing climate service, it is important to obtain reliable high-resolution temperature simulations. Systematic comparisons are still deficient between statistical and dynamic downscaling techniques because of their inherent unavoidable uncertainties. In this paper, 20 global climate models (GCMs) and one regional climate model [Providing Regional Climates to Impact Studies (PRECIS)] are employed to evaluate their capabilities in reproducing average trends of mean temperature (Tm), maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature range (DTR), and extreme events represented by frost days (FD) and heat-wave days (HD) across China. It is shown generally that bias of temperatures from GCMs relative to observations is over ±1°C across more than one-half of mainland China. PRECIS demonstrates better representation of temperatures (except for HD) relative to GCMs. There is relatively better performance in Huanghuai, Jianghuai, Jianghan, south Yangzi River, and South China, whereas estimation is not as good in Xinjiang, the eastern part of northwest China, and the Tibetan Plateau. Bias-correction spatial disaggregation is used to downscale GCMs outputs, and bias correction is applied for PRECIS outputs, which demonstrate better improvement to a bias within ±0.2°C for Tm, Tmax, Tmin, and DTR and ±2 days for FD and HD. Furthermore, such improvement is also verified by the evidence of increased spatial correlation coefficient and symmetrical uncertainty, decreased root-mean-square error, and lower standard deviation for reproductions. It is seen from comprehensive ranking metrics that different downscaled models show the most improvement across different climatic regions, implying that optional ensembles of models should be adopted to provide sufficient high-quality climate information.


2018 ◽  
Vol 12 (10) ◽  
pp. 3287-3292 ◽  
Author(s):  
Edward Hanna ◽  
Xavier Fettweis ◽  
Richard J. Hall

Abstract. Recent studies note a significant increase in high-pressure blocking over the Greenland region (Greenland Blocking Index, GBI) in summer since the 1990s. Such a general circulation change, indicated by a negative trend in the North Atlantic Oscillation (NAO) index, is generally highlighted as a major driver of recent surface melt records observed on the Greenland Ice Sheet (GrIS). Here we compare reanalysis-based GBI records with those from the Coupled Model Intercomparison Project 5 (CMIP5) suite of global climate models over 1950–2100. We find that the recent summer GBI increase lies well outside the range of modelled past reconstructions and future GBI projections (RCP4.5 and RCP8.5). The models consistently project a future decrease in GBI (linked to an increase in NAO), which highlights a likely key deficiency of current climate models if the recently observed circulation changes continue to persist. Given well-established connections between atmospheric pressure over the Greenland region and air temperature and precipitation extremes downstream, e.g. over northwest Europe, this brings into question the accuracy of simulated North Atlantic jet stream changes and resulting climatological anomalies over densely populated regions of northern Europe as well as of future projections of GrIS mass balance produced using global and regional climate models.


2018 ◽  
Author(s):  
Edward Hanna ◽  
Xavier Fettweis ◽  
Richard J. Hall

Abstract. Recent studies note a significant increase in high-pressure blocking over the Greenland region (Greenland Blocking Index, GBI) in summer since the 1990s. Such a general circulation change, indicated by a negative trend in the North Atlantic Oscillation (NAO) index, is generally highlighted as a major driver of recent surface melt records observed on the Greenland Ice Sheet (GrIS). Here we compare reanalysis-based GBI records with those from the Coupled Model Intercomparison Project 5 (CMIP5) suite of global climate models over 1950–2100. We find that the recent summer GBI increase lies well outside the range of modelled past reconstructions (Historical scenario) and future GBI projections (RCP4.5 and RCP8.5). The models consistently project a future decrease in GBI (linked to an increase in NAO), which highlights a likely key deficiency of current climate models if the recently-observed circulation changes continue to persist. Given well-established connections between atmospheric pressure over the Greenland region and air temperature and precipitation extremes downstream, e.g. over Northwest Europe, this brings into question the accuracy of simulated North Atlantic jet stream changes and resulting climatological anomalies over densely populated regions of northern Europe as well as of future projections of GrIS mass balance produced using global and regional climate models.


2020 ◽  
Vol 162 (2) ◽  
pp. 645-665
Author(s):  
Melissa S. Bukovsky ◽  
Linda O. Mearns

Abstract The climate sensitivity of global climate models (GCMs) strongly influences projected climate change due to increased atmospheric carbon dioxide. Reasonably, the climate sensitivity of a GCM may be expected to affect dynamically downscaled projections. However, there has been little examination of the effect of the climate sensitivity of GCMs on regional climate model (RCM) ensembles. Therefore, we present projections of temperature and precipitation from the ensemble of projections produced as a part of the North American branch of the international Coordinated Regional Downscaling Experiment (NA-CORDEX) in the context of their relationship to the climate sensitivity of their parent GCMs. NA-CORDEX simulations were produced at 50-km and 25-km resolutions with multiple RCMs which downscaled multiple GCMs that spanned nearly the full range of climate sensitivity available in the CMIP5 archive. We show that climate sensitivity is a very important source of spread in the NA-CORDEX ensemble, particularly for temperature. Temperature projections correlate with driving GCM climate sensitivity annually and seasonally across North America not only at a continental scale but also at a local-to-regional scale. Importantly, the spread in temperature projections would be reduced if only low, mid, or high climate sensitivity simulations were considered, or if only the ensemble mean were considered. Precipitation projections correlate with climate sensitivity, but only at a continental scale during the cold season, due to the increasing influence of other processes at finer scales. Additionally, it is shown that the RCMs do alter the projection space sampled by their driving GCMs.


2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio

2018 ◽  
Vol 22 (1) ◽  
pp. 673-687 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.


2019 ◽  
Vol 41 (4) ◽  
pp. 374-387 ◽  
Author(s):  
Nguyen Thi Tuyet ◽  
Ngo Duc Thanh ◽  
Phan Van Tan

The study examined the performance of six regional climate experiments conducted under the framework of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment-Southeast Asia (SEACLID/CORDEX-SEA) project and their ensemble product (ENS) in simulating temperature at 2 m (T2m) and rainfall (R) in seven climatic sub-regions of Vietnam. The six experiments were named following the names of their driving Global Climate Models (GCMs), i.e., CNRM, CSIRO, ECEA, GFDL, HADG and MPI. The observation data for the period 1986–2005 from 66 stations in Vietnam were used to compare with the model outputs. Results showed that cold biases were prominent among the experiments and ENS well reproduced the seasonal cycle of temperature in the Northeast, Red River Delta, North Central and Central Highlands regions. For rainfall, all the experiments showed wet biases and CSIRO exhibited the best. A scoring system was elaborated to objectively rank the performance of the experiments and the ENS experiment was reported to be the best.


2017 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.


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