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An analysis is presented of the precipitation bias and change signal in an ensemble of regional climate model (RCM) (RegCM4) projections driven by multiple general circulation models (GCMs) over China. RegCM4 is driven by five different GCMs for the 120‐year period 1979–2099 at 25 km grid spacing, under the representative concentration pathway RCP8.5. We find that the GCMs and RegCM4 reproduce the general spatial pattern of precipitation over China in all four seasons, with RegCM4 providing greater spatial detail, especially over areas with complex terrain. The spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by an underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in northern China, most pronounced in the Northwest basins, by both the GCMs and RegCM4 in all seasons except summer, when more mixed results are found. In addition, weak correlations of the projected change patterns are found in summer between the GCMs and nested RegCM4, indicating the greater role played by the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Plain Language Summary: China is a vulnerable country to climate change due to its dense population, unbalanced social and economic development, shortage of water resources, and fragile ecosystems. How future precipitation will change over the region is of great concern for the general public and decision makers. This paper presents a first analysis of precipitation simulations from a set of five RCM (RegCM4) 21st century climate change projections, driven by coarse resolution general circulation models (GCMs) over China. We find that the spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by a precipitation underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in north China by both the GCMs and RegCM4 in all seasons except summer, when, weak correlations of the projected change patterns are found between the GCMs and nested RegCM4, indicating the greater role of the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Key Points: The spatial patterns of bias show common features between the GCMs and RegCM4RegCM4 provides greater spatial detail of present day precipitation simulation compared to the GCMs and finer structures of future changesThe change patterns across the RegCM4 projections show a high correlation, but not always between each pair of driving GCM and RegCM4 [ABSTRACT FROM AUTHOR]

This paper provides a review of paleoclimate modeling activities in China. Rather than attempt to cover all topics, we have chosen a few climatic intervals and events judged to be particularly informative to the international community. In historical climate simulations, changes in solar radiation and volcanic activity explain most parts of reconstructions over the last millennium prior to the industrial era, while atmospheric greenhouse gas concentrations play the most important role in the 20th century warming over China. There is a considerable model-data mismatch in the annual and boreal winter temperature change over China during the mid-Holocene [6000 years before present (ka BP)], while coupled models with an interactive ocean generally perform better than atmospheric models. For the Last Glacial Maximum (21 ka BP), climate models successfully reproduce the surface cooling trend over China but fail to reproduce its magnitude, with a better performance for coupled models. At that time, reconstructed vegetation and western Pacific sea surface temperatures could have significantly affected the East Asian climate, and environmental conditions on the Qinghai-Tibetan Plateau were most likely very different to the present day. During the late Marine Isotope Stage 3 (30-40 ka BP), orbital forcing and Northern Hemisphere glaciation, as well as vegetation change in China, were likely responsible for East Asian climate change. On the tectonic scale, the Qinghai-Tibetan Plateau uplift, the Tethys Sea retreat, and the South China Sea expansion played important roles in the formation of the East Asian monsoon-dominant environment pattern during the late Cenozoic. [ABSTRACT FROM AUTHOR]

In recent years, China has suffered from frequent extreme precipitation events, and predicting their future trends has become an essential part of the current research on this issue. Because of the inevitable uncertainties associated with individual models for climate prediction, this study uses a machine learning approach to integrate and fit multiple models. The results show that the use of several evaluation metrics provides better results than the traditional ensemble median method. The correlation coefficients with the actual observations were found to improve from about 0.8 to 0.9, while the correlation coefficients of the precipitation amount (PRCPTOT), very heavy precipitation days (R20mm), and extreme precipitation intensity (SDII95) reached 0.95. Based on this, the precipitation simulations of moderate forced scenario for sharing socio-economic path (SSP2-4.5) from 27 coupled models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were used to explore potential changes in future extreme precipitation events in China and to calculate the distribution and trends of the PRCPTOT, extreme precipitation amount (R95pTOT), maximum consecutive 5-day precipitation (Rx5day), precipitation intensity (SDII), SDII95, and R20mm for the early 21st century (2023–2050), mid-21st century (2051–2075), and late 21st century (2076–2100), respectively. The results showed that the most significant increase in extreme precipitation indices is expected to occur by the end of the century, with the R95pTOT, Rx5day, and SDII95 increasing by 13.73%, 9.43%, and 9.34%, respectively, from the base period. The remaining three precipitation indexes, the PRCPTOT, SDII, and R20mm, also showed increases of 8.77%, 6.84%, and 4.02%, respectively. Additionally, there were apparent differences in the spatial variation of extreme precipitation. There were significant increasing trends of extreme precipitation indexes in central China and northeast China in the three periods, among which the total annual precipitation showed an increasing trend in central and northern China and a decreasing trend in western and south China. An increasing trend of annual precipitation intensity was found to be mainly concentrated in central China and south China, and the annual precipitation frequency showed a larger increasing trend at the beginning of this century. The annual precipitation frequency showed an increasing trend in the early part of this century. In general, all the indices showed an overall increasing trend in the future period, with the PRCPTOT, Rx5day, and SDII95 showing the most significant overall increasing trends. [ABSTRACT FROM AUTHOR]

To support future solar energy deployment in China, long‐term changes in solar energy resources over China were investigated based on high‐resolution dynamical downscaling simulations under three emission scenarios. First, an evaluation of model performance was conducted through comparison with station and ERA5 data, which indicated that although consistent overestimation was found, the spatial distribution and intra‐annual variation of solar radiation were captured well by ensemble simulation, showing added value over regions with complex topography as well. Then, the trends of the solar power output from photovoltaic (PV) systems during 2020–2099 were projected, characterized by an increase in east and central China, and a consistent decrease in the solar‐energy‐abundant regions (e.g., northeast China, the Tibetan Plateau, and northwest China) under the three scenarios. Except for under the low emission scenario, the regional averaged trends of PV were projected to decrease consistently over China in all four seasons, with significant magnitude apparent in both spring and winter. In addition, a more intense magnitude of decline was found under the higher emission scenario, with more subregions with a significant trend and higher intra‐annual and inter‐annual variability. However, it seems that the emission scenarios impact the spatial pattern only remarkably in the late century, however strengthened the decreasing magnitude in all future periods. In addition, results indicate decline in the future PV potential over most of subregions of China due to reduced radiation and increased temperature, but for the decrease over Tibetan Plateau the reduced wind speed also act as an important factor. Plain Language Summary: The long‐term goal of carbon neutrality in China involves new requirements for the development and utilization of solar energy. The present study was motivated by supporting future solar energy deployment at local scales. However, due to data limitations, relatively little effort has been made to project long‐term changes in solar energy over different subregions of China. Accordingly, we investigated this based on a set of high‐resolution dynamical downscaling simulations under different climate scenarios, and found that the higher emission scenarios reinforce the magnitude of the decline in solar energy and result in higher inter‐annual variability. These findings suggest an increased need for constraining emissions for the benefit of solar energy. In addition, we found that radiation will likely be the most important factor related to future changes in solar resources over most of subregions under RCP2.6 scenario, however the effect of wind speed should not be ignored over Tibetan Plateau. Key Points: Despite some overestimation, the spatial distribution and intra‐annual variation of solar radiation were captured well, showing added valuesFuture solar power were projected to generally increase in east and central China but decrease in solar‐energy‐abundant regionsRadiation was the most robust factor for future solar energy trend over China, however wind speed can not be ignored over Tibetan Plateau [ABSTRACT FROM AUTHOR]

Understanding future drought risks plays a crucial role in developing climate change adaptation strategies and in enhancing disaster resilience. However, previous studies may lead to biased conclusions due to the neglect of two factors, including the relative performance of climate simulations and the uncertainty in drought characterization. In this study, Bayesian model averaging is used to merge five regional climate model simulations and to project future changes in hydroclimatic regimes over China under two representative emission scenarios (RCP4.5 and RCP8.5). Drought characteristics, including drought severity and duration, are extracted using the Standardized Precipitation Evapotranspiration Index (SPEI). A Bayesian copula approach is used to uncover underlying interactions of drought characteristics and associated uncertainties across 10 climate divisions of China. The regional return periods of drought characteristics are used to assess future changes in multidimensional drought risks and the probability of extreme droughts. Our findings reveal that the variations in drought characteristics are generally underestimated by the ensemble mean (AEM) simulation. The Bayesian framework improves the reliability and accuracy of hydroclimate simulations and better reproduces the drought regimes compared to the AEM simulation. The drought duration and severity are projected to substantially increase for most areas of China based on the Bayesian framework, but the AEM simulation may lead to multiple opposite behaviors, especially under RCP4.5. The estimated joint risk from drought duration and drought severity is expected to increase under both emission scenarios. The likelihood of extreme droughts is also projected to increase as the radiative forcing increases. [ABSTRACT FROM AUTHOR]

Projections of future drought conditions under climate change are an important step in formulating the long‐term climate adaptation strategies. It is therefore valuable to predict the drought conditions in China following the release of the CMIP6 (the phase six of the Coupled Model Inter‐comparison Project). Thus, based on 20 global climate model simulations from CMIP6, we project China's drought conditions and its socioeconomic impacts using the self‐calibrated Palmer Drought Severity Index (scPDSI). Four scenarios are considered in this analysis: SSP1‐2.6 (the low‐level development scenario), SSP2‐4.5 (the middle‐level development scenario), SSP3‐7.0 (the medium to high‐level development scenario) and SSP5‐8.5 (the high‐level development scenario). Under SSP1‐2.6, we observed wetting trends over large areas of China except the arid region during 2020–2099; however, under SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5, significant drying trends are detected in the humid and temperate semi‐humid region, while in other areas there are significant wetting trends. The projected drought conditions are likely to be severe with more frequent monthly occurrences and higher probability of extreme drying conditions, especially in these humid and temperate semi‐humid regions under SSP3‐7.0 and SSP5‐8.5. Consequently, the population exposure to drought in most climatic regions will increase initially up to 2040s and gradually decrease under all the scenarios except SSP3‐7.0; and the humid region will be a future hotspot where the impact of climate on population exposure to drought will be more significant. The economic exposure to drought will increase over the whole China under all four scenarios, especially in the humid and semi‐humid region. Our results have important implications for future drought projections and provide a scientific evidence for developing climate change adaptation strategies and disaster prevention. [ABSTRACT FROM AUTHOR]

In this paper, future drought characteristics (frequency, duration and intensity) over China are analysed by using four climate models from CMIP6 under the seven SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, SSP370, and SSP585) for three defined periods of 2021–2040 (near-term), 2041–2060 (mid-term) and 2081–2100 (long-term). The corresponding four climate models output from CMIP5 are also used to conduct a comparison analysis between CMIP5 and CMIP6 to address the improvements added to CMIP6 in terms of drought identification. The drought characteristics are identified by applying the standardized precipitation-evapotranspiration index (SPEI) at a 12-month timescale and run theory. The results show that CMIP6 has a robust capability to capture historical (1986–2005) drought characteristics. For the future period of 2021–2040, the decrease in precipitation and increase in potential evapotranspiration will lead to continuous dry conditions in the upper and middle Yangtze River basin and eastern Pearl River basin. Relative to the reference period, drought events will be more frequent and severe with longer durations in the Northwest River basins and middle Yangtze River basin. Furthermore, higher emissions signify a greater increase in drought frequency and intensity in the long-term period. Except for the SSP585 scenario, the lower emission scenario corresponds to the higher drought duration soon and in the mid-21st century (2021–2060). This finding is regarded as a "strange phenomenon", which cannot be detected by the previous CMIP5-based emission scenarios (RCP2.6, RCP4.5 and the unlikely pathway RCP8.5). Therefore, additional "possible future"-based scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, and SSP370) should be included in extreme climate studies, especially for the near future and mid-21st century. Notably, compared with CMIP5, the reduced biases in drought characteristics are more likely associated with improvements in the representation of physical processes in climate models from CMIP6. The results of this study could provide a basis for the development of drought adaptation measures over China. • Latest CMIP6 climate models and seven SSP-RCP scenarios are used to analyze the possible changes in droughts over China. • More robust projections will be presented by CMIP6 than CMIP5, due to the better representations in physical processes. • The higher emission signifies shorter drought duration, lower precipitation and PET in mid-21st century over China. [ABSTRACT FROM AUTHOR]

Based on hourly temperature data collected from 2,307 meteorological stations over China and two sets of climate change simulations over East Asia using the regional climate model version 4.4 (RegCM4.4) driven by the global models of HadGEM2‐ES and MPI‐ESM‐MR, future changes of heating and cooling degree‐hours (HDH and CDH) at the end of the 21st century under RCP4.5 scenario are investigated. Compared against the observation, the spatial distribution, magnitude and annual cycle of present‐day HDH and CDH at different times, as well as the diurnal cycle of them can be realistically simulated by the model. Meanwhile, some bias can also be found and it varies with the times, especially for CDH. At the end of the century, significant decrease of HDH can be found over the Tibetan Plateau, the northern part of Northeast China, and Northwest China at each times while increase of CDH are observed at all the times except some parts of the Tibetan Plateau where the CDH remains zero due to the cold climate there. But for different times, some differences are found in HDH decrease and CDH increase. For example, the changes of HDH at the fifth to the seventh times present a weaker decrease in the northwestern basins compared to other times and the CDH increase are more significant at the fifth and the sixth times. The regional mean changes of HDH and CDH over China in the 21st century (2006–2098) also diverge among different times, which indicates the degree‐hours is needed to precisely calculate the hourly heating and cooling energy demand and then the heating and cooling degree days. [ABSTRACT FROM AUTHOR]

Based on the outputs of 27 global climate models (GCMs) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5), projected changes of extreme temperature events have been analyzed over nine river basins in China by the end of the twenty-first century relative to the reference period 1961-1990. The temporal and spatial changes and their projection uncertainty are studied using the extreme temperature indices defined by the Expert Team of Climate Change Detection and Indices (ETCCDI) under two Representative Concentration Pathways (RCPs). The model simulations predict a general increasing (decreasing) trend in warm (cold) extremes over China in the twenty-first century, with more pronounced warming trend under a higher emission scenario. The projected changes in cold and warm extremes exhibit a large difference in spatial patterns. The high-latitude and high-elevation regions of China (e.g., Continental and Southwest basins) are projected to respond more strongly to changes in cold extremes, while eastern and southern China (e.g., Yangtze River and Pearl River basins) tend to be more sensitive to the increases in warm extremes. In general, projected changes in cold indices based on minimum temperature tend to be more pronounced than in warm indices based on maximum temperature. Uncertainty analysis shows a large difference among the 27 GCMs under 2 RCP scenarios, and the uncertainty ranges tend to be larger under a higher emission scenario. Overall, the uncertainties in the emission scenarios are smaller than those from the climate models in the near future period. However, for the long-term climate projections (e.g., by the end of the twenty-first century), the projected difference under various emission scenarios tends to be larger than those by different climate models and hence can be the dominant contributor to the projection uncertainty of temperature indices. [ABSTRACT FROM AUTHOR]

Climate change as a result of the increased greenhouse gas emissions may influence the availability of water resources in many regions on the globe. In the past decades, China has been facing severe shortage of water resources. This study focuses on the assessment of the impact of climate change on both blue and green water resources in ten large river basins in China. The blue and green water resources for these river basins were derived from the terrestrial hydrological fluxes in period 1960-2100, which were simulated with the Max Planck Institute Hydrological Model-MPI-HM. The forcing data for the hydrological model, the precipitation and temperature were obtained from three coupled Atmosphere-Ocean General Circulation Models (GCMs)-ECHAM5, IPSL and CNRM, under A2 and B1 greenhouse gas emission scenarios. The statistical bias correction method was applied on the output from the three GCMs. By using this climate model-hydrology model modeling chain, the impact of climate change on the blue and green water resources was analyzed over the ten Chinese river basins. Here, the projected changes in 2071-2100 are considered relative to 1971-2000. The projected change of monthly mean and annual mean of green water resources show the general increase for all ten river basins; among them, Inland river, Zhemin river and Zhujiang river have larger change signal than other basins. For blue water resources, increases of the annual mean are projected from November to March for Heilongjiang river, Liaohe river and Yellow river, Inland river in Northern China; and decreases are projected for Huaihe river, Zhemin river, Haihe river, Yangzi river, Southwest river, and Zhujiang river basins in Southern China. It is found that climate change has impact on both blue and green water resources over large river basins in China. The sustainable blue water resources management should take into account the different changes in both Northern and Southern China. The results show that a better management of green water resources is of importance for food and ecological securities in the context of global change. [ABSTRACT FROM AUTHOR]

ABSTRACT Extreme climate events over China at the end of the 21st century (2080-2099) are investigated using the regional climate model RegCM4. Model performance is validated through comparison between observations and simulations over the period 1985-2005. The results show that RegCM4 can satisfactorily reproduce the spatial distribution of extreme climate events over China. The model simulates temperature extremes more accurately than precipitation. Under the RCP8.5 (high emission) scenario, the number of frost days decreases, and both the heat wave duration index and the growing season length increase dramatically towards the end of the 21st century. Changes in extreme temperature become increasingly pronounced from South to North China, with the most significant changes occurring on the Tibetan Plateau ( TP). The proportion of heavy precipitation generally increases, except on the southern TP. The number of very heavy precipitation days increases by 25-50% in Northwest and East China. In winter, the number of consecutive dry days ( CDD) decreases in North China and increases in South China. The greatest increases in CDD are found in June, July and August ( JJA) in Southwest China. In a future that follows this scenario, drought events may be aggravated in Southwest China, and decrease in North China. In contrast, when repeating these projections under the assumption of the RCP4.5 scenario for emissions, the frequency of extreme climate events is reduced. These results suggest that reductions in greenhouse gas emissions may mitigate the effects of climate change over the coming decades. [ABSTRACT FROM AUTHOR]

Climate change in the 21st century over China is simulated using the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model version 3 (RegCM3). The model is one-way nested within the global model CCSR/NIES/FRCGC MIROC3.2_hires (Center for Climate System Research/National Institute for Environmental Studies/Frontier Research Center for Global Change/Model for Interdisciplinary Research on Climate). A 150-year (1951-2100) transient simulation is conducted at 25 km grid spacing, under the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A1B scenario. Simulations of present climate conditions in China by RegCM3 are compared against observations to assess model performance. Results show that RegCM3 reproduces the observed spatial structure of surface air temperature and precipitation well. Changes in mean temperature and precipitation in December-January-February (DJF) and June-July-August (JJA) during the middle and end of the 21st century are analyzed. Significant future warming is simulated by RegCM3. This warming becomes greater with time, and increased warming is simulated at high latitude and high altitude (Tibetan Plateau) areas. In the middle of the 21st century in DJF, a general increase of precipitation is found in most areas, except over the Tibetan Plateau. Precipitation changes in JJA show an increase over northwest China and a decrease over the Tibetan Plateau. There is a mixture of positive and negative changes in eastern China. The change pattern at the end of the century is generally consistent with that in mid century, except in some small areas, and the magnitude of change is usually larger. In addition, the simulation is compared with a previous simulation of the RegCM3 driven by a different global model, to address uncertainties of the projected climate change in China. [ABSTRACT FROM AUTHOR]

Investigating the impact of climate change at regional scales is of importance for adaption purposes. In this study, a regional climate model PRECIS is for the first time run for East China on a spatial resolution of 25 km using two global climate models (GCMs) ECHAM5 and HadCM3 as boundary data under A1B emission scenario. The baseline period is 1961-1990. An upgraded quantile mapping method is used to correct the bias of PRECIS outputs for providing reliable future climate change projections (2011-2040). The regional climate model is then coupled with a mesoscale distributed hydrology soil vegetation model (DHSVM), to investigate the impact of climate change on future water resources in the Jinhua River Basin, East China. The hydrological model is calibrated and validated on a daily basis and show reasonable performance. The results show that under both GCMs, statistically, no significant changes in future annual runoff are projected. However, large changes in seasonal and monthly runoff are projected. ECHAM5 projects large decreases in summer () and autumn () and slight increases in spring and winter whereas HadCM3 projects large decreases in autumn () and large increases in spring (28.7%) and winter (60%). The seasonal changes in precipitation in this region are the main driving force for the changes in future runoff. [ABSTRACT FROM AUTHOR]