In this study, the performance of the Beijing Climate Center (BCC) Climate System Model version 1.1 (BCC-CSM1.1) (280-km resolution) and the BCC-CSM1.1m (110-km resolution) in simulating extreme climate events over China in the last 40 years is compared. Both models capture the main spatial distribution features of heavy precipitation (R95T), the number of consecutive wet days (CWD), the annual count of days with precipitation mm (R1), the maximum consecutive 5-day precipitation (Rx5), and the numbers of frost days (FD) and summer days (SU). The BCC-CSM1.1m has a better ability to simulate the detailed distribution of extreme climate events than the BCC-CSM1.1, including R95T, CWD, R1, and the simple precipitation intensity index (SDII). However, the BCC-CSM1.1m does not show an improvement in simulating the number of days with extreme precipitation (R90N), the number of consecutive dry days (CDD), the heat wave duration index (HWDI), the warm day frequency (TX90P), and cold night frequency (TN10P). This indicates that the simulation of the R95T, CWD, R1, and SDII climate events is more sensitive to the resolution of the model. The improved BCC-CSM1.1m is used to explore the projection of extreme climate change in China during the 21st century under the RCP4.5 (Representative Concentration Pathways) and RCP8.5 scenarios. The results show that extreme precipitation will increase dramatically over North and Southwest China in the late 21st century. The CWD index will decrease on the Tibetan Plateau and in northeastern and central China and will increase in other parts of China; R1 will increase in northern China and decrease in southern China; Rx5 will increase dramatically in southern China; FD will decrease and SU will increase over China in the late 21st century under both emission scenarios, with larger amplitudes in RCP8.5.
In this study, we first found that the few and sparse meteorological stations used in earlier comprehensive studies of building climate zoning in a complicated terrain area like Chongqing, China, may lead to the inapplicability of building energy efficiency standards in some areas. To address this issue, the study used daily data from 1908 extremely dense surface meteorological stations from 2011 to 2020 in Chongqing, China. In order to conduct fine zoning of building climate in Chongqing, China, GB50176-2016 and ASHRAE standard 169-2021 were employed, respectively. The findings indicated that by using the ASHRAE standard, the entire Chongqing region was classified into five climate zones. The Chongqing region was categorized into three different climate zones using China GB50176-2016: cold zone (CZ), hot summer and cold winter zone (HSCWZ), and mild zone (MZ). Not to be overlooked is the MZ (China’s GB50176-2016)/mixed-humid zone (ASHRAE standard), which is primarily situated at higher elevations in the southeast and northeast of Chongqing. In comparison to the HSCWZ/warm-humid zone, these zones have drastically different building energy efficiency regulations and approaches. According to preliminary projections, improved building climate zoning will to some extent increase building energy efficiency and reduce emissions in Chongqing. Finally, this study case can be replicated in different regions with complicated terrain.
This study assesses present-day extreme climate changes over China by using a set of phase 6 of the Coupled Model Intercomparison Project (CMIP6) statistical downscaled data and raw models outputs. The downscaled data is produced by the adapted spatial disaggregation and equal distance cumulative distribution function (EDCDF) method at the resolution of 0.25° × 0.25° for the present day (1961–2014) and the future period (2015–2100) under the Shared Socioeconomic Path-way (SSP) 2-4.5 than SSP5-8.5 emission scenario. The results show that the downscaling method improves the spatial distributions of extreme climate events in China with higher spatial pattern correlations, Taylor Skill Scores and closer magnitudes no matter single model or multi model ensemble (MME). In the future projections, large inter-model variability between the downscaled models still exists, particular for maximum consecutive 5-day precipitation (RX5). The downscaled MME projects that total precipitation (PTOT) and RX5, will increase with time, especially for the northwest China. The projected heavy precipitation days (R20) also increase in the future. The region of significant increase in R20 locates in the south of river Yangtze. Maxi-mum annual temperature (TXX) and percentage of warm days (TX90p) are projected to increase across the whole country with larger magnitude over the west China. Projected changes of minimum annual temperature (TNN) over the northeastern China is the most significant area. The higher of the emission scenario, the more significant of extreme climates. This reveals that the spatial distribution of extreme climate events will become more uneven in the future.
Abstract 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.
This paper evaluates the NASA Earth Exchange Global Daily Downscaled Projections' (NEX-GDDP) CMIP6 models' performance in simulating extreme climate indices across China and its eight subregions for the period 2081–2100 under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios. The models effectively reproduce the spatial patterns of extreme high temperatures, especially in northern China. They show enhanced capabilities in accurately simulating the maximum daily maximum temperature (TXx) and the number of high temperature days (T35). They improve the cold bias of the TXx index in Northwest China and warm bias in South China. In terms of precipitation, the models demonstrate strong performance, evidenced by significant spatial correlations in total wet day precipitation (PTOT) simulations. They reduce the biases of PTOT and simple daily intensity (SDII) compared to CMIP6 models. Regionally, they enhance PTOT accuracy along southern coasts and in Yunnan, better captures very heavy precipitation days (R20) in the Southwest region, max 5-day precipitation (RX5D) in North China and Southwest region, and SDII in the Northeast region and Yunnan. Under SSP5-8.5 scenario, significant impacts include increased TXx in Northwest China, more heatwave days in Southwest China, and more T35 in South China. Extreme precipitation will become more frequent in South and East China, with the greatest intensity increases in Southwest China (SWC1). North China will see fewest consecutive dry days (CDD) indices, while consecutive wet days (CWD) will prominently rise in SWC1.
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