Future precipitation changes in California: Comparison of CMIP5 and CMIP6 intermodel spread and its drivers

Ensembles of climate change projections created by general circulation models (GCMs) with high resolution are increasingly needed to develop adaptation strategies for regional climate change. The Meteorological Research Institute atmospheric GCM version 3.2 (MRI-AGCM3.2), which is listed in the Coupled Model Intercomparison Project phase 5 (CMIP5), has been typically run with resolutions of 60 km and 20 km. Ensembles of MRI-AGCM3.2 consist of members with multiple cumulus convection schemes and different patterns of future sea surface temperature, and are utilized together with their downscaled data; however, the limited size of the high-resolution ensemble may lead to undesirable biases and uncertainty in future climate projections that will limit its appropriateness and effectiveness for studies on climate change and impact assessments. In this study, to develop a comprehensive understanding of the regional precipitation simulated with MRI-AGCM3.2, we investigate how well MRI-AGCM3.2 simulates the present-day regional precipitation around the globe and compare the uncertainty in future precipitation changes and the change projection itself between MRI-AGCM3.2 and the CMIP5 multiple atmosphere–ocean coupled GCM (AOGCM) ensemble. MRI-AGCM3.2 reduces the bias of the regional mean precipitation obtained with the high-performing CMIP5 models, with a reduction of approximately 20% in the bias over the Tibetan Plateau through East Asia and Australia. When 26 global land regions are considered, MRI-AGCM3.2 simulates the spatial pattern and the regional mean realistically in more regions than the individual CMIP5 models. As for the future projections, in 20 of the 26 regions, the sign of annual precipitation change is identical between the 50th percentiles of the MRI-AGCM3.2 ensemble and the CMIP5 multi-model ensemble. In the other six regions around the tropical South Pacific, the differences in modeling with and without atmosphere–ocean coupling may affect the projections. The uncertainty in future changes in annual precipitation from MRI-AGCM3.2 partially overlaps the maximum–minimum uncertainty range from the full ensemble of the CMIP5 models in all regions. Moreover, on average over individual regions, the projections from MRI-AGCM3.2 spread over roughly 0.8 of the uncertainty range from the high-performing CMIP5 models compared to 0.4 of the range of the full ensemble.

ABSTRACTA set of 27 global climate models from the Coupled Model Inter‐comparison Project Phase 5 (CMIP5) ensemble are assessed for their performance for the purpose of making future climate projection studies in the western tropical Pacific and differences to Coupled Model Inter‐comparison Project Phase 3 (CMIP3) are assessed. The CMIP5 models show some improvements upon CMIP3 in the simulation of the climate in the western tropical Pacific in the late 20th century. There are fewer CMIP5 models with very poor skill scores than in CMIP3 for some measures and a small group of the well‐performing models in CMIP5 have lower biases than in an equivalent group from CMIP3. These best‐performing models could be particularly informative for studying certain climate sensitivities and feedbacks in the region. There is evidence to reject one model as unsuitable for making regional climate projections in the region, and another two models unsuitable for analysis of the South Pacific Convergence Zone (SPCZ). However, while there have been improvements, many of the systematic model biases in the mean climate in CMIP3 are also present in the CMIP5 models. They are primarily related to the shape of the transition between the Indo‐Pacific warm pool and equatorial cold tongue, and the associated biases in the position and orientation of the SPCZ and Inter‐Tropical Convergence Zone, as well as in the spatial pattern, variability and teleconnections of the West Pacific monsoon, and the simulation of El Niño Southern Oscillation. Overall, the results show that careful interpretation and consideration of biases is required when using CMIP5 outputs for generating regional climate projections for the western tropical Pacific, particularly at the country scale, just as there was with CMIP3.

As the world's fifth‐largest economy entity, California (CA) is vulnerable to climate changes especially the magnitude of winter (wet season) precipitation that is closely linked to regional drought severity, vegetation growth, and wildfire activities. However, the fate of CA precipitation in the future remains highly uncertain, for example, the state‐of‐the‐art Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) projected −3% to +42% and −27% to +63% precipitation changes in northern and central‐southern CA, respectively, under the high greenhouse gas (GHG) emission scenario (SSP585). In this work, we applied the Pareto optimality concept and used observed teleconnection patterns (causal relationships between ocean regions and CA precipitation) to mechanistically constrain CMIP6 projected CA precipitations. We estimated that precipitation will robustly increase by 0.4–1.3 mm d−1 (10–34%) over northern CA and increase by 0.1–0.5 mm d−1 (7–32%) over central‐southern CA by the end of the 21st century compared with present‐day. Up to 71% of ESM projection uncertainties were reduced mainly due to the strong and consistent causal relationship between North American west coast sea level pressure and CA precipitation in both observations and CMIP6 models. Our results suggest that teleconnection patterns are powerful mechanistic constraints that can help explain and reduce uncertainties in ESM projections.

The effects of future tropical Pacific sea surface temperature (SST) changes on regional precipitation projections are statistically studied for December–January–February (DJF) and June–July–August (JJA) in the Coupled Model Intercomparison Project phase 3 (CMIP3) experiments. The present climate precipitation responses to Niño3 SST variability appear as an uncertainty with regards to future regional precipitation changes among the CMIP3 model projections. Compared with the CMIP3 models projecting La Niña-like Pacific SST changes, the models projecting El Niño-like Pacific SST changes tend to simulate more precipitation in future DJF over the tropical central Pacific, southeastern North America and the tropical western Indian Ocean, and less over the tropical northwestern Pacific, the tropical South Pacific and tropical South America. For JJA, the models projecting El Niño-like Pacific SST changes tend to simulate greater future precipitation in the tropical central Pacific and less over the Maritime Continent and around Central America. Interestingly, the present climate features of the delayed JJA precipitation response to previous DJF Niño3 SST variability also appear as differences in future JJA precipitation changes between the models projecting future El Niño-like and La Niña-like Pacific SST changes in DJF. Compared to the later models, the former models have a tendency to show more precipitation south of Japan and south of the equator in the central to eastern Pacific, and less in the subtropical northwestern Pacific. CMIP3 model analysis indicates that the projected El Niño-like SST changes are related to the present precipitation climatology of the models in the near-equatorial eastern Pacific for each DJF and JJA season, suggesting the importance of realistically simulating present precipitation climatology in the tropical Pacific for future projections.

<p><span>The Coupled Model Intercomparison Project Phase 5 (CMIP5) models have showed substantial inter-model spread in estimating annual global-mean precipitation change per one-degree greenhouse-gas-induced warming (precipitation sensitivity), ranging from -4.5</span><span>–4.2</span><span>%</span><sup><span>o</span></sup><span>C<sup>-1</sup>in the Representative Concentration Pathway (RCP) 2.6, the lowest emission scenario, to 0.2–4.0</span><span>%</span><sup><span>o</span></sup><span>C<sup>-1</sup>in the RCP 8.5, the highest emission scenario. The observed-based estimations in the global-mean land precipitation sensitivity during last few decades even show much larger spread due to the considerable natural interdecadal variability, role of anthropogenic aerosol forcing, and uncertainties in observation. This study tackles to better quantify and constrain global land precipitation change in response to global warming by analyzing the new range of Shared Socio-economic Pathway (SSP) scenarios in the </span><span>Coupled Model Intercomparison Project Phase 6 (CMIP6) compared with RCP scenarios in the CMIP5. We show that the range of projected change in annual global-mean land (ocean) precipitation by the end of the 21<sup>st</sup>century relative to the recent past (1995-2014) in the 23 CMIP6 models is over 50% (20%) larger than that in corresponding scenarios of the 40 CMIP5 models. The estimated ranges of precipitation sensitivity in four Tier-1 SSPs are also larger than those in corresponding CMIP5 RCPs. The large increase in projected precipitation change in the highest quartile over ocean is mainly due to the increased number of high equilibrium climate sensitivity (ECS) models in CMIP6 compared to CMIP5, but not over land due to different response of thermodynamic moisture convergence and dynamic processes to global warming. We further discuss key challenges in constraining future precipitation change and source of uncertainties in land precipitation change.</span></p>

An assessment is made of the modes of interannual variability in the seasonal mean summer and winter Southern Hemisphere (SH) 500-hPa geopotential height in the twentieth century in models from the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) dataset. Modes of variability of both the slow (signal) and intraseasonal (noise) components in the CMIP5 models are evaluated against those estimated from reanalysis data. There is general improvement in the leading modes of the slow (signal) component in CMIP5 models compared with the CMIP phase 3 (CMIP3) dataset. The largest improvement is in the spatial structures of the modes related to El Niño–Southern Oscillation variability in SH summer. An overall score metric is significantly higher for CMIP5 over CMIP3 in both seasons. The leading modes in the intraseasonal noise component are generally well reproduced in CMIP5 models, and there are few differences from CMIP3. A new total overall score metric is used to rank the CMIP5 models over both seasons. Weighting the seasons by the relative spread of overall scores is shown to be suitable for generating multimodel ensembles for further analysis of interannual variability. In multimodel ensembles, it is found that an ensemble of size 5 or 6 is sufficient in SH summer to reproduce well the dominant modes. In contrast, about 13 models are typically are required in SH winter. It is shown that it is necessary that the selected models individually reproduce well the leading modes of the slow component.

Intensive study of diurnal precipitation variations can improve our understanding of how global warming affects precipitation patterns. Here, we use the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG V07 final run) observations and the Coupled Model Intercomparison Project phase 6 (CMIP6) simulations to explore the global diurnal precipitation cycles and trends over land and ocean. The IMERG high-resolution gridded data reveal a complex diurnal cycle of precipitation over the global land and ocean, whereas CMIP6 models have limited performance to simulate this feature. We divided precipitation into daytime and nighttime and analyzed diurnal precipitation differences using the Mann–Kendall test and Sen’s slope estimation. IMERG (1998–2023) and CMIP6 (1979–2014) both exhibit diurnal asymmetries in precipitation trends. Over land, IMERG shows a daytime increase and slight nighttime decrease, while CMIP6 shows daytime precipitation increases exceeding nighttime. Over the ocean, IMERG shows decreasing daytime and increasing nighttime trends, whereas CMIP6 shows nighttime precipitation increases exceeding daytime. As greenhouse gas emissions increase, the diurnal asymmetry in precipitation increasing trends weakens over land but strengthens over the ocean. Simulations from the Detection and Attribution Model Intercomparison Project (DAMIP) show that this asymmetry over the ocean is primarily driven by forcing from anthropogenic greenhouse gases (GHGs) and is expected to persist and intensify with increasing emissions. These findings underscore the critical role of greenhouse gas forcing in shaping diurnal precipitation asymmetries, offering valuable insights for understanding future precipitation changes under global warming scenarios. Significance Statement The trend of precipitation under global warming has been widely studied. However, the precipitation trends in daytime and nighttime and the diurnal differences have received limited attention due to the constraints of spatial and temporal resolutions in observations and model simulations. This study shows the diurnal cycle of global precipitation and reveals asymmetric diurnal precipitation trends that contribute to an increasing land–ocean diurnal contrast. As warming intensifies, the diurnal asymmetry in precipitation increasing trends weakens over land but strengthens over the ocean. This phenomenon is of great scientific significance to the study of the possible abnormality of the water cycle in the global climate change.

Climate models have projected an overall drying in Mediterranean climate zones, with the exception of California, where the models have been split between predicting wetter or drier future conditions. This uncertainty is problematic for a major economy, where water scarcity, especially in southern California, has been an issue of concern during the last few decades. Here we compare the future projections of California’s winter (December, January, February) precipitation changes from the latest Coupled Model Intercomparison Project Phases 6 (CMIP6) and 5 (CMIP5). Over northern California the models from both ensembles agree on wetter future conditions. However, over southern California the models are almost equally divided between wetter or drier conditions, with projections ranging from -30% to +70% in CMIP5 and -20% to +80% in CMIP6 for the end of the century. The CMIP6 ensemble indicates wetter overall conditions, and features a larger model disagreement compared to CMIP5.Interannual precipitation indicates more extremely wet or dry years over southern California in CMIP6 than in CMIP5. Some models even suggest that the five wettest years will account for as much as ~55% of the total 20-year rainfall considered, and the five driest for as little as ~5%. Dynamically, both ensembles project weakened subsidence over Baja California. This effect is stronger in CMIP6 than in CMIP5, consistent with the wetter mean conditions in CMIP6. In the western tropical Pacific our results point to strengthening of the Hadley circulation in CMIP6 that is not seen in CMIP5, and El Niño conditions prevailing over La Niña. CMIP6 models also project a stronger overall impact of ENSO on California’s precipitation than CMIP5 models.

As the major renewable energy, wind can greatly reduce carbon emissions. Following the “carbon neutral” strategy, wind power could help to achieve the realization of energy transformation and green development. Based on ERA5 reanalysis data and the multi-ensemble historical and scenario simulations of the Coupled Model Intercomparison Project Phase 6 (CMIP6), a variety of statistical analyses are used to evaluate the performance of CMIP6 simulating the wind speed in China. The conclusions are as follows: spatial patterns of the nine CMIP6 models are similar with ERA5, but BCC-CSM2-MR and MRI-ESM2-0 highly overestimate the wind speed in northwest China. CESM2-WACCM, NorESM2-MM, and HadGEM3-GC31-MM behave better than the other six CMIP6 models in four specific regions are chosen for detailed study. CESM2-WACCM, NorESM2-MM, and HadGEM3-GC31-MM tend to simulate a larger wind speed than ERA5 except the yearly averaged wind speed in region II and region IV. CESM2-WACCM and NorESM2-MM simulate a large monthly mean wind speed, but the value is relatively close with ERA5 in the summer. HadGEM3-GC31-MM overestimates wind speed in region I and region II from April to October, but gets closer with ERA during winter. CESM2-WACCM, NorESM2-MM, and HadGEM3-GC31-MM simulate an increasing trend in Tibetan Plateau and Xinjiang in the next 100 years, while NorESM2-MM projects rising wind speed in the eastern part of Inner Mongolia, and HadGEM3-GC31-MM simulates increasing wind speed in the northeast and central China. The future wind speed in three models is projected to decline in region I, and the value of HadGEM3-GC31-MM is much larger. In region II, wind speed simulated by three models is projected to decrease, but the wind speed from HadGEM3-GC31-MM in region III and modeled wind speed in region IV from NorESM2-MM would climb with the slope equal to 0.0001 and 0.0012, respectively. This study indicates that the CMIP6 models have certain limitations to perform realistic wind changes, but CMIP6 could provide available reference for the projection of wind in specific areas.

This is the first study to show the global Cut-off Low (COL) activity in 46 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). The COL historical simulations for the period 1979–2005 obtained from the CMIP5 and CMIP6 models and their ensembles are compared with the ERA5 reanalysis using an objective feature-tracking algorithm. The results show that the CMIP6 models simulate the spatial distribution of COLs more realistically than the CMIP5 models. Some improvements include reduced equatorward bias and underestimation over regions of high COL density. Reduced biases in CMIP6 are mainly attributed to the improved representation of the zonal wind due to the poleward shift of the subtropical jet streams. The CMIP5 models systematically underestimate the COL intensity as measured by the T42 vorticity at 250 hPa. In CMIP6, the intensity is still underestimated in summer, but overestimated in winter in part due to increased westerlies. The overestimation is enhanced by the finer spatial resolution models that identify more of the strong systems compared to coarser resolution models. Other aspects of COLs such as their temporal and lifetime distributions are modestly improved in CMIP6 compared to CMIP5. Finally, the predictive skill of climate models is evaluated using five variables and the Taylor diagram. We find that 15 out of the 20 (75%) best coupled models belong to CMIP6, and this highlights the overall improvement compared to its predecessor CMIP5. Despite this, the use of the multi-model ensemble average seems to be better in simulating COLs than individual models.

Intercomparison of the expected change in the temperature and the precipitation retrieved from CMIP6 and CMIP5 climate projections: A Mediterranean hot spot case, Turkey

Abstract. By regulating the global transport of heat, freshwater, and carbon, the Atlantic meridional overturning circulation (AMOC) serves as an important component of the climate system. During the late 20th and early 21st centuries, indirect observations and models suggest a weakening of the AMOC. Direct AMOC observations also suggest a weakening during the early 21st century but with substantial interannual variability. Long-term weakening of the AMOC has been associated with increasing greenhouse gases (GHGs), but some modeling studies suggest the build up of anthropogenic aerosols (AAs) may have offset part of the GHG-induced weakening. Here, we quantify 1900–2020 AMOC variations and assess the driving mechanisms in state-of-the-art climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6). The CMIP6 forcing (GHGs, anthropogenic and volcanic aerosols, solar variability, and land use and land change) multi-model mean shows negligible AMOC changes up to ∼ 1950, followed by robust AMOC strengthening during the second half of the 20th century (∼ 1950–1990) and weakening afterwards (1990–2020). These multi-decadal AMOC variations are related to changes in North Atlantic atmospheric circulation, including an altered sea level pressure gradient, storm track activity, surface winds, and heat fluxes, which drive changes in the subpolar North Atlantic surface density flux. To further investigate these AMOC relationships, we perform a regression analysis and decompose these North Atlantic climate responses into an anthropogenic aerosol-forced component and a subsequent AMOC-related feedback. Similar to previous studies, CMIP6 GHG simulations yield robust AMOC weakening, particularly during the second half of the 20th century. Changes in natural forcings, including solar variability and volcanic aerosols, yield negligible AMOC changes. In contrast, CMIP6 AA simulations yield robust AMOC strengthening (weakening) in response to increasing (decreasing) anthropogenic aerosols. Moreover, the CMIP6 all-forcing AMOC variations and atmospheric circulation responses also occur in the CMIP6 AA simulations, which suggests these are largely driven by changes in anthropogenic aerosol emissions. More specifically, our results suggest that AMOC multi-decadal variability is initiated by North Atlantic aerosol optical thickness perturbations to net surface shortwave radiation and sea surface temperature (and hence sea surface density), which in turn affect sea level pressure gradient and surface wind and – via latent and sensible heat fluxes – sea surface density flux through its thermal component. AMOC-related feedbacks act to reinforce this aerosol-forced AMOC response, largely due to changes in sea surface salinity (and hence sea surface density), with temperature-related (and cloud-related) feedbacks acting to mute the initial response. Although aspects of the CMIP6 all-forcing multi-model mean response resembles observations, notable differences exist. This includes CMIP6 AMOC strengthening from ∼ 1950 to 1990, when the indirect estimates suggest AMOC weakening. The CMIP6 multi-model mean also underestimates the observed increase in North Atlantic ocean heat content, and although the CMIP6 North Atlantic atmospheric circulation responses – particularly the overall patterns – are similar to observations, the simulated responses are weaker than those observed, implying they are only partially externally forced. The possible causes of these differences include internal climate variability, observational uncertainties, and model shortcomings, including excessive aerosol forcing. A handful of CMIP6 realizations yield AMOC evolution since 1900 similar to the indirect observations, implying the inferred AMOC weakening from 1950 to 1990 (and even from 1930 to 1990) may have a significant contribution from internal (i.e., unforced) climate variability. Nonetheless, CMIP6 models yield robust, externally forced AMOC changes, the bulk of which are due to anthropogenic aerosols.

Выполнена оценка возможных изменений среднегодовой приповерхностной температуры воздуха (ПТВ) в Дальневосточном регионе, включающем территорию и окраинные моря России, а также северо-западную часть Тихого океана, до 2099 г., для чего используются осредненные по ансамблю данные 33 моделей проекта CMIP6 (Coupled Model Intercomparison Project Phase 6), полученные в рамках четырех сценариев, отвечающих разным уровням антропогенного радиационного форсинга (слабого, умеренного и значительного). Анализируются различия между осредненными за 30-летние периоды аномалиями ПТВ. Для верификации модельных результатов проанализировано потепление, произошедшее в регионе с 1940–1969 до 1994–2023 гг., для чего использованы данные реанализа ERA5 и эксперимента Historical CMIP6. По обоим видам данных средняя ПТВ в регионе выросла на 1.1 °С: с 1940–1969 к 1994–2023 гг.; это сходство обосновывает оценки будущих изменений ПТВ по моделям CMIP6. Все сценарии SSP (Shared Socio-economic Pathways) будущего радиационного форсинга показывают приблизительно одинаковое повышение ПТВ с 1994–2023 по 2024–2053 гг., оно составляет в среднем по региону 1.2–1.5 °С. К 2070–2099 гг. средняя ПТВ в рассматриваемом регионе возрастет соответственно темпу эмиссии парниковых газов – на 1.7, 2.7, 3.8 и 4.8 °С. Как показывают данные реанализа ERA5, от 1940–1969 к 1994–2023 гг. увеличение ПТВ над морскими акваториями региона происходило весьма неравномерно: наибольшие темпы наблюдались в северной части Охотского моря (до 2 °С и более) и в прибрежных районах северо-западной части Берингова моря (до 1.0–1.2 °С). Увеличение ПТВ ослабевало в направлении с северо-запада на юго-восток, т.е. с удалением от суши, и составило 0.2–0.6 °С в северо-западной части Тихого океана. Картина потепления над морскими акваториями по данным CMIP6 выражена сильнее, чем по данным реанализа ERA5, но при этом качественно им соответствует. An assessment of possible changes in the annual mean surface air temperature (SAT) in the Far East Region (35°–65° N, 130°–180° E) is made from the present to 2099, using ensemble-averaged data from 33 CMIP6 (Coupled Model Intercomparison Project Phase 6) models obtained within the framework of four scenarios corresponding to the weak, moderate, or significant anthropogenic radiative forcing resulting from СО2 emissions. To elucidate long-term climate change, SAT averaged for 30-year periods, namely, 1994–2023, 2024–2053 and 2070–2099 are analyzed. To verify the model results, the warming that occurred in the region from the mid-20th century (1940–1969) to the early 21st century (1994–2023) is analyzed, using ERA5 data with the fine spatial resolution of 0.25°, and CMIP6 data with the coarser resolution, mostly 1.0°–2.0°. According to both data types, the regional SAT increased, on average by 1.1 °C from 1940–1969 to 1994–2023, justifying the use of forecast estimates based on the CMIP6 models in this work. All scenarios of possible radiative forcing show the similar SAT increase from the 1994–2023 to 2024–2053, on average 1.2–1.5 °C. On the contrary, by the 2070–2099, the regional SAT will increase in accordance with the emission rates on average by 1.7, 2.7, 3.8 and 4.8 °C, respectively. As for the Russian Far East land area, ERA5 and CMIP6 show similar spatial warming patterns, with the warming, on average, of 1.2 °C from 1940–1969 to 1994–2023, i.e. higher than that for the entire considered region including marine areas. From 1940–1969 to 1994–2023 negative annual mean SAT changed to positive one in some areas of the Primorsky, Khabarovsky and Kamchatksky provinces, implying the permafrost melting. According to the CMIP6 models, the land warming of 2.0–2.1 °C, 3.0–3.5 °C, 4.7–5.3 °C, and 6.1–6.6 °C is expected by the end of the 21st century for the scenarios with the different levels of radiative forcing. As shown by the ERA5 data, the SAT increase from 1940–1969 to 1994–2023 was very uneven for the marine areas: the highest rates were observed in the northern Okhotsk Sea (up to 2 °C and more) and in the coastal northwestern Bering Sea (up to 1.0–1.2 °C), which can be explained by the ice cover decrease. The SAT increase weakened in the direction from the northwest to southeast, i.e. with the distance from the land, and amounted to only 0.2–0.6 °C in the northwestern Pacific, which can be attributed to the effect of Pacific Decadal Oscillation (PDO). The coastal Okhotsk Sea off the Sakhalin Island is the only area where SAT decreased by 0.2–0.6 °C from 1940–1969 to 1994–2023, which probably can be attributed to the changes in the East Sakhalin Current transporting Amur River water southward along the coast but this suggestion should be verified. The warming pattern over the marine areas according to CMIP6 data qualitatively corresponds to that one based on ERA5 data, keeping in mind the lower resolution of the modeled data. The warming in the Northwest Pacific from the modeled data exceeds that one from ERA5, which can be explained by elimination of the PDO effects when averaging CMIP6 multi-model data.

Based on four reanalyses or gridded data sets (ERA5, 20CR, APHRODITE and REGEN), we provide an overview of 23 Historical and 7 HighResMIP experiments’ performance from the Coupled Model Intercomparison Project Phase 6 (CMIP6) (for short, 6-Hist, HighRes) in simulating seven extreme precipitation indices over Asia defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). We compare them with 28 Historical experiments in CMIP5 (5-Hist). CMIP5 and CMIP6 models are generally able to reproduce extreme precipitation’s spatial distribution and their trend patterns in comparison to the benchmark data set (APHRODITE). The overall performance of individual model is summarized by a “portrait” diagram based on four statistics for each index. We divide all 58 models into three groups (A, the top 20%; B, the median 60% and C group, the last 20%) according to MR rankings (the comprehensive ranking measure). Based on the “portrait” diagram and MR rankings, models that perform relatively well for all seven extreme precipitation indices include HadCM3, HadGEM2-AO, HadGEM2-CC and HadGEM2-ES from 5-Hist, EC-Earth3, EC-Earth3-Veg from 6-Hist and ECMWF-IFS-HR, ECMWF-IFS-LR, ECMWF-IFS-MR from HighRes. The simulated performance of CMIP6 is polarized, for the top four and the last five ranking models are both from CMIP6. Compared with the counterpart models in CMIP6 and CMIP5, the improvement of PCC (pattern correlation coefficient) is more obvious. Furthermore, the dry biases of CMIP6 (both 6-Hist and HighRes) in Southern China and India and the wet biases of CMIP6 in Tibet are reduced compared to CMIP5. This may benefit from the improvement that CMIP6 models can capture the characteristics of meridional moisture flux convergence, and improve the overestimation or underestimation of meridional and zonal specific humidity eddies compared to CMIP5.

Cold winters in Eurasia considerably affect transportation, agriculture, energy, and public health. This study utilizes 31 global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and 33 CMIP5 models to evaluate the historical surface air temperature, sea level pressure, 500‐hPa geopotential height, 150‐hPa meridional and zonal wind, and polar vortex indices during cold winters. Our research quantifies the advancements of CMIP6 over CMIP5. Additionally, future changes in these variables under three different Shared Socioeconomic Pathways (SSPs), that is, SSP 1–2.6, SSP 2–4.5, and SSP 5–8.5, are projected based on 20 out of the 31 CMIP6 models. The results indicate that the multimodel ensemble means from both CMIP5 and CMIP6 effectively capture the main features of the observed Eurasian cold winters and their associated factors with good simulation agreement. The CMIP6 ensemble mean outperforms its CMIP5 counterpart, and both ensemble means (CMIP5 and CMIP6) perform better than individual CMIP6 models. Among CMIP6 models, 500‐hPa geopotential height achieves the highest simulation skill, whereas sea level pressure shows the lowest. Compared with same‐institute models from CMIP5, CMIP6 models show overall improvements with sea level pressure simulation being notably advanced. Under the three SSPs, the occurrence probability of cold winters is projected to decrease as the area and intensity indices of the polar vortex decline. Moreover, surface temperature anomalies are projected to exhibit a “warm Arctic and cold Eurasia” pattern, and the anticyclonic anomalies at 500 hPa and 150 hPa are projected to be centered at high latitudes.