scholarly journals European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)

2021 ◽  
Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Daily Precipitation ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Grid Spacing ◽  
Intercomparison Project ◽  
Horizontal Grid

<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>

scholarly journals European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)

2020 ◽  
Vol 13 (11) ◽  
pp. 5485-5506
Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  
Jesús Fernández ◽  
Silje L. Sørland ◽  
Roman Brogli ◽  
...  
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Daily Precipitation ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Grid Spacing ◽  
Intercomparison Project ◽  
Horizontal Grid

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.

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

2020 ◽  
Author(s):  
Marie-Estelle Demory ◽  
Ségolène Berthou ◽  
Silje L. Sørland ◽  
Malcolm J. Roberts ◽  
Urs Beyerle ◽  
...  
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Daily Precipitation ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Scale ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Similar Distribution ◽  
Mountainous Regions

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.

scholarly journals Comparison of Statistical and Dynamic Downscaling Techniques in Generating High-Resolution Temperatures in China from CMIP5 GCMs

2020 ◽  
Vol 59 (2) ◽  
pp. 207-235 ◽  
Author(s):  
Lei Zhang ◽  
YinLong Xu ◽  
ChunChun Meng ◽  
XinHua Li ◽  
Huan Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Global Climate Models ◽  
Maximum Temperature ◽  
The Tibetan Plateau ◽  
Dynamic Downscaling

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.

scholarly journals Characterizing and Understanding Cloud Ice and Radiation Budget Biases in Global Climate Models and Reanalysis

2016 ◽  
Vol 56 ◽  
pp. 13.1-13.20 ◽  
Author(s):  
J.-L. F. Li ◽  
D. E. Waliser ◽  
G. Stephens ◽  
Seungwon Lee
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Model Intercomparison ◽  
Convective Core ◽  
Intercomparison Project ◽  
Annual Means ◽  
Cloud Ice ◽  
Ice Water

Abstract The authors present an observationally based evaluation of the vertically resolved cloud ice water content (CIWC) and vertically integrated cloud ice water path (CIWP) as well as radiative shortwave flux downward at the surface (RSDS), reflected shortwave (RSUT), and radiative longwave flux upward at top of atmosphere (RLUT) of present-day global climate models (GCMs), notably twentieth-century simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), and compare these results to those of the third phase of the Coupled Model Intercomparison Project (CMIP3) and two recent reanalyses. Three different CloudSat and/or Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined ice water products and two methods are used to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate can be obtained for model evaluations. The results show that, for annual mean CIWC and CIWP, there are factors of 2–10 (either over- or underestimate) in the differences between observations and models for a majority of the GCMs and for a number of regions. Most of the GCMs in CMIP3 and CMIP5 significantly underestimate the total ice water mass because models only consider suspended cloud mass, ignoring falling and convective core cloud mass. For the annual means of RSDS, RLUT, and RSUT, a majority of the models have significant regional biases ranging from −30 to 30 W m−2. Based on these biases in the annual means, there is virtually no progress in the simulation fidelity of RSDS, RLUT, and RSUT fluxes from CMIP3 to CMIP5, even though there is about a 50% bias reduction improvement of global annual mean CIWP from CMIP3 to CMIP5. It is concluded that at least a part of these persistent biases stem from the common GCM practice of ignoring the effects of precipitating and/or convective core ice and liquid in their radiation calculations.

scholarly journals California Wintertime Precipitation Bias in Regional and Global Climate Models

2010 ◽  
Vol 49 (10) ◽  
pp. 2147-2158 ◽  
Author(s):  
Peter Caldwell
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Model Resolution ◽  
Grid Spacing ◽  
Precipitation Frequency

Abstract In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California and compared. Several averaging methodologies are considered and all are found to give similar values when the model grid spacing is less than 3°. This suggests that California is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict California precipitation. This appears to be due mainly to the overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge–satellite observations, which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait that does not seem to be tied to model resolution. The GCM daily and interannual variabilities are generally underpredicted.

scholarly journals Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution

2020 ◽  
Vol 1 (1) ◽  
pp. 277-292 ◽  
Author(s):  
Reinhard Schiemann ◽  
Panos Athanasiadis ◽  
David Barriopedro ◽  
Francisco Doblas-Reyes ◽  
Katja Lohmann ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Development ◽  
Global Climate Models ◽  
Assessment Model ◽  
Climate Simulation ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. Global climate models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA – PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and during winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 33 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 18 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 to 20 km grid spacing, in most of the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.

scholarly journals Stratocumulus Clouds in Southeastern Pacific Simulated by Eight CMIP5–CFMIP Global Climate Models

2014 ◽  
Vol 27 (8) ◽  
pp. 3000-3022 ◽  
Author(s):  
Jia-Lin Lin ◽  
Taotao Qian ◽  
Toshiaki Shinoda
Keyword(s):  
Cloud Cover ◽  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Feedback ◽  
Global Climate Models ◽  
Temperature Structure ◽  
Model Intercomparison ◽  
Stratocumulus Clouds ◽  
Intercomparison Project

Abstract This study examines the stratocumulus clouds and associated cloud feedback in the southeast Pacific (SEP) simulated by eight global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and Cloud Feedback Model Intercomparison Project (CFMIP) using long-term observations of clouds, radiative fluxes, cloud radiative forcing (CRF), sea surface temperature (SST), and large-scale atmosphere environment. The results show that the state-of-the-art global climate models still have significant difficulty in simulating the SEP stratocumulus clouds and associated cloud feedback. Comparing with observations, the models tend to simulate significantly less cloud cover, higher cloud top, and a variety of unrealistic cloud albedo. The insufficient cloud cover leads to overly weak shortwave CRF and net CRF. Only two of the eight models capture the observed positive cloud feedback at subannual to decadal time scales. The cloud and radiation biases in the models are associated with 1) model biases in large-scale temperature structure including the lack of temperature inversion, insufficient lower troposphere stability (LTS), and insufficient reduction of LTS with local SST warming, and 2) improper model physics, especially insufficient increase of low cloud cover associated with larger LTS. The two models that arguably do best at simulating the stratocumulus clouds and associated cloud feedback are the only ones using cloud-top radiative cooling to drive boundary layer turbulence.

scholarly journals Large-scale features and evaluation of the PMIP4-CMIP6 <i>midHolocene</i> simulations

2020 ◽  
Vol 16 (5) ◽  
pp. 1847-1872 ◽  
Author(s):  
Chris M. Brierley ◽  
Anni Zhao ◽  
Sandy P. Harrison ◽  
Pascale Braconnot ◽  
Charles J. R. Williams ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Current Phase ◽  
Model Intercomparison ◽  
Global Mean Temperature ◽  
Intercomparison Project

Abstract. The mid-Holocene (6000 years ago) is a standard time period for the evaluation of the simulated response of global climate models using palaeoclimate reconstructions. The latest mid-Holocene simulations are a palaeoclimate entry card for the Palaeoclimate Model Intercomparison Project (PMIP4) component of the current phase of the Coupled Model Intercomparison Project (CMIP6) – hereafter referred to as PMIP4-CMIP6. Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the Northern Hemisphere and associated shifts in tropical rainfall. Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of −0.3 K, which is −0.2 K cooler than the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe, and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on the hydrological cycle, feedback strength, and potentially climate sensitivity.

scholarly journals Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations

2020 ◽  
Author(s):  
Chris Brierley ◽  
Anni Zhao ◽  
Sandy Harrison ◽  
Pascale Braconnot ◽  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Model Complexity ◽  
Current Phase ◽  
Model Intercomparison ◽  
Global Mean Temperature ◽  
Intercomparison Project

&lt;p&gt;The mid-Holocene (6,000 years ago) is a standard experiment for the evaluation of the simulated response of global climate models using paleoclimate reconstructions. The latest mid-Holocene simulations are a contribution by the Palaeoclimate Model Intercomparison Project (PMIP4) to the current phase of the Coupled Model Intercomparison Project (CMIP6). Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the northern hemisphere and associated shifts in tropical rainfall. &amp;#160;Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of -0.3 K, which is -0.2 K cooler that the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Neither this difference nor the improvement in model complexity and resolution seems to improve the realism of the simulations. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on climate sensitivity and feedback strength.&lt;/p&gt;

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