We evaluate and compare the simulation of summer precipitation in China and the East Asian summer monsoon (EASM) by eight climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) and the corresponding eight previous models from CMIP5. Skill metrics are calculated to assess the climatology, interannual variation and linear trends during the time period 1961–2005. The CMIP6 multimodel ensemble (MME) is more skillful than the CMIP5 MME in the spatial correlation and standard deviation (SD) of the climatological precipitation over Eastern China. All the CMIP6 models improve the skill scores in the climatological pattern of the EASM relative to the previous models of CMIP5, which is related to their smaller sea surface temperature (SST) biases over the Northwestern Pacific Ocean. The models with a higher capability in reproducing the climatological pattern of the EASM tend to have a better skill in simulating summer precipitation over Eastern China. Most (six of eight) of the CMIP6 models have advantages over the previous CMIP5 models in reproducing the interannual anomalous rainfall pattern over Eastern China related to the EASM. Ten of the 16 models partly reproduce the weakening trend of the EASM during 1961–2005. The high‐skill models (GISS‐E2‐H, GISS‐E2‐1‐H) that simulate a clear weakening trend in the EASM also reasonably simulate the negative correlation between the EASM and the SST over Eastern Indian and the Western Pacific Oceans (EIWP). By contrast, the two models (CESM2 and CESM2‐WACCM) that simulate a positive correlation over the EIWP both produce increasing trends in the EASM indices. This indicates the importance of climate models in simulating the relationship between the EASM and the SST over the EIWP. Among the 16 models, only 2 CMIP6 models (BCC‐CSM2‐MR and GISS‐E2‐1‐H) partly reproduce the linear trend of precipitation over Eastern China, featured by the pattern of “southern flood and northern drought.”

The historical simulation of phase five of the Coupled Model Intercomparison Project (CMIP5) experiments performed by the Beijing Climate Center climate system model (BCC_CSM1.1) is evaluated regarding the time evolutions of the global and China mean surface air temperature (SAT) and surface climate change over China in recent decades. BCC_CSM1.1 has better capability at reproducing the time evolutions of the global and China mean SAT than BCC_CSM1.0. By the year 2005, the BCC_CSM1.1 model simulates a warming amplitude of approximately 1°C in China over the 1961– 1990 mean, which is consistent with observation. The distributions of the warming trend over China in the four seasons during 1958–2004 are basically reproduced by BCC_CSM1.1, with the warmest occurring in winter. Although the cooling signal of Southwest China in spring is partly reproduced by BCC_CSM1.1, the cooling trend over central eastern China in summer is omitted by the model. For the precipitation change, BCC_CSM1.1 has good performance in spring, with drought in Southeast China. After removing the linear trend, the interannual correlation map between the model and the observation shows that the model has better capability at reproducing the summer SAT over China and spring precipitation over Southeast China.

This study evaluates the ability of 23 climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating extreme climate events over China. The multimodel ensemble (MME) performs better than most individual models in reproducing the climatological mean distribution of all extreme indices. The MME can reproduce well the climatological mean distributions of five extreme climate indices over China, including annual total precipitation (PTOT), maximum consecutive 5‐day precipitation (RX5), simple daily intensity (SDII), maximum daily maximum temperature (TXX), and minimum daily minimum temperature (TNN), with Taylor skill scores exceeding 0.7. SDII and TXX are the most skilful precipitation and temperature extreme indices simulated by the MME, respectively. The MME has relatively lower skill in simulating the climatological mean distribution of warm days (TX90P) and cold nights (TN10P) over China. Future projections of these extreme climate indices by the end of the 21st century are explored with the MME under the SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5 scenarios. The PTOT and RX5 in northwestern China are all projected to increase by more than 30% under SSP5‐8.5. R20 is projected to increase by 4–5 days over southeastern China under SSP5‐8.5. There are fewer (more) consecutive dry days over north China (south China), with a change of 5 days under SSP5‐8.5. The extreme temperature indices, including TX90P, TXX, and TNN, all increase with time and higher SSP scenarios. The three indices increase by 40–55%, 4–6°C, and 4–7°C under SSP5‐8.5 over east China, respectively. The TN10P decreases by more than 6% over east China. The changes in these extreme indices under SSP1‐2.6 and SSP2‐4.5 are similar to those under SSP5‐8.5 but with a smaller magnitude. Large uncertainties still exist in the future projections, especially under the high SSP scenarios.

Climate models participated in the High Resolution Model Intercomparison Project (HighResMIP) of Coupled Model Intercomparison Project 6 (CMIP6) are evaluated to reveal the impact of enhanced resolution in simulating the climatological distribution of precipitation over China. The multi-model mean (MME) of five models with 30–50 km horizontal resolution in the atmosphere (MME-50) had a better performance in reproducing the observed spatial patterns of precipitation over Northwest China and Southwest China than the MME of their lower-resolution (70–140 km) models (MME-100). Such an improvement is mainly attributed to the topographical rainfall reproduced by the higher-resolution models, which have the superiority of reproducing the local vertical circulation over the complex terrain. The MME-50 also improves the skill score of the 850-hPa southwesterly of the Indian-Burma trough relative to the MME-100, which may contribute to better simulation skill of precipitation over Southwest China. The MME-50 (0.92) has a close skill score to the MME-100 (0.91) in the simulation of East Asian summer monsoon, which explains why the MME-50 cannot improve the simulation skill of the precipitation over Southeast China and Northern China. The skill score of the precipitation over the Tibetan Plateau (TP) simulated by the MME-50 is even lower than the MME-100, revealing that simulating the climate over the high plateau is still a challenge for the high-resolution models.

The forecast skill of BCC‐CSM1.1 model in summer East Asian climate was evaluated with the decadal prediction experiments launched annually during 1961–2005. Results of the decadal prediction were compared with those of the historical simulation to estimate contribution of the initialization. Improved prediction skill is found for summer surface air temperature (SAT) in central eastern China measured by both root mean square error (RMSE) and anomaly correlation coefficient (ACC) for the forecast years 2–5. The decadal hindcast of precipitation in central eastern China shows increased skill in RMSE but not ACC. Such improvement in East Asia is related to enhanced prediction skill of the western Pacific (WP) sea surface temperature (SST) originated from the oceanic initialization. In the decadal hindcast, the lower tropospheric atmospheric circulation associated with warm WP exhibits an anticyclone over the South China Sea, which resembles the observation. The southwesterly increases over southeast China associated with warm WP, favouring higher SAT in central eastern China. This reveals that the decadal predictions could more realistically reproduce the relationship between summer East Asian atmospheric circulation and WP SST. The 4‐year average forecast within a decade shows that the initialization increases the ACC skill up to forecast years 4–7 for summer SAT in central eastern China.