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The hydrological projections provided by the outputs of Global Climate Models (GCMs) combining hydrological models include multi‐source uncertainties, which may challenge the formulation of relevant adaption and mitigation policies. In this paper, the overall uncertainty and the relative contribution of each uncertainty component were investigated for hydrological projections over 408 watersheds in China by using 3 shared socioeconomic pathway emission scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5), 21 GCMs, 8 bias correction methods, 4 hydrological models, and 2 sets of optimized hydrological model parameters. The results show that the total uncertainty (T) is mainly contributed by uncertainty related to global climate models (G), with the mean percentage ranging from 60.4 to 64.1%, followed by the interaction uncertainties among all components, with the mean percentage ranging from 22.0 to 26.4%. The uncertainty contribution of hydrological models (H) (6.1–9.4%) ranks third, followed by emission scenarios (S) (2.9–5.9%) and bias correction methods (B) (0.2–1.1%). The uncertainty contribution of the optimized hydrological model parameters (P) (0.2–0.3%) is almost negligible. In terms of spatial variability, the relative contribution of uncertainty related to global climate models (G) is the highest in the near future for northern China (67.5–70.6%) and in the far future for southern China (66.1–66.7%). However, it was found to be lower for the Tibetan Plateau and northwestern China (45.3–57.9%) in the near and far future. The relative contribution of hydrological model uncertainty is higher for southwestern and northwestern China and the Tibetan Plateau (7.2–19.5%) and lower for northern, eastern, and southern China (2.5–6.6%). This study highlights the importance of including multiple GCMs and hydrological models in hydrological impact studies to consider their overall uncertainty. The development of global climate models and hydrological models is still the best way to reduce the uncertainty of climate change impact studies. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents an evaluation study of the Regional Climate Model version 4.3 ( RegCM4.3) over the Loess Plateau in northern China, which is a semi-arid region characterized by complex topography. During recent years, a series of reforestation programmes have been implemented across the region that might influence the local climate in complex ways. To better understand the local climate, the RegCM4.3 was applied to simulate the present-day conditions over the Loess Plateau. The simulation was carried out from 1990 to 2009 at the 50-km horizontal resolution, with lateral boundary conditions taken from the ECMWF-Interim reanalysis. A series of climate variables and processes were evaluated during the winter and summer seasons, such as 2-m air temperature, precipitation, wind circulation, surface energy balance, full moisture budget, and cloud radiative forcing (CRF). The possible origins of the simulation bias and the physical linkages with other model processes were examined. In general, RegCM4.3 is able to reproduce both the spatial and temporal features of the regional climate over the Loess Plateau. However, there are still biases in some meteorological variables including precipitation and 2-m air temperature. In particular, the model tends to produce cold biases during winter and underestimate precipitation during summer. Further analyses indicates that the cold biases in winter may have resulted from the deficiency of the downward longwave radiation fluxes, excessive ground heat fluxes, and negative temperature advection by the seasonal mean circulation. These processes are primarily triggered by deficiencies in CRF and excessive northwesterlies over the plateau. The underestimated precipitation during summer is associated with a weak southerly monsoon in the model. A full moisture budget analysis reveals that the dry bias in this region can be mainly attributed to model deficiency in moisture advection and convergence, and to a lesser extent to that in surface evaporation. [ABSTRACT FROM AUTHOR]

The frequency and magnitude of global warming events varies greatly across different regions and countries. The climatic diversity for China and future warming features are projected across 12 climatic zones based on the ensemble of the five well‐performing high‐resolution downscaled climate models for each zone. There are warming patterns for the mean near‐surface air temperature (Tm), maximum near‐surface air temperature (Tmax), minimum near‐surface air temperature (Tmin) as well as heatwave and frost events. Under RCP4.5 and RCP8.5 scenarios, the three indices (i.e., Tm, Tmax and Tmin) countrywide are likely to increase at respective rates of 0.30–0.31 and 0.64–0.67°C·decade−1. The extent of frost event (FE) are projected to decrease at a rate of −1912 and −4442 day·km−2·decade−1 while the extent of heatwave event (HE) increase at a rate of 1116 and 3557 day·km−2·decade−1 under RCP4.5 and RCP8.5 scenarios, respectively. A higher increment in temperatures, a decreasing trend in diurnal temperature range (DTR), frost days and FE are highlighted in the western and northern zones, while these trends are opposite in southern zones. The warming is likely to get faster in the current colder zones (western and northern zones) while heatwave is more intense and severe in Jianghuai, Jianghan, the south Yangzi River, South China and Xinjiang. These potential changes indicate that adaption and mitigation strategies are necessary in response to future warming. [ABSTRACT FROM AUTHOR]

Many studies have shown that the climate system has the long‐range correlation (LRC) characteristics, which provide a good test bed for evaluating the performance of climate models. In this study, the LRC characteristics of the observed surface daily temperature data in China is first analysed by detrended fluctuation analysis. It is found that the daily temperature records, including daily mean temperature (Tmean), daily maximum temperature (Tmax), and daily minimum temperature (Tmin), all exhibit LRC characteristics with scaling exponents more than 0.6 in most of China. Then, the performances of two different versions for the Beijing Climate Center Climate System Model (BCC‐CSM), namely, BCC‐CSM1.1m in CMIP5 and BCC‐CMS2‐MR in CMIP6, are quantitatively evaluated by comparing the differences of the LRC characteristics between the observations and the simulations. The results indicate that BCC‐CSM2‐MR performs better than BCC‐CSM1.1(m) in western Northwest China, most of south of the middle and lower reaches of Yangtze River, North China, central Inner Mongolia for the daily Tmean and Tmax. As far as the daily Tmin is concerned, BCC‐CSM1.1(m) performs better than BCC‐CSM2‐MR in western South China and southern Xinjiang, and the performance of BCC‐CSM2‐MR in CMIP6 has not been significant improved. Compared with BCC‐CSM1.1(m), BCC‐CSM2‐MR cannot significantly improve the simulations for the LRC characteristics of the three daily temperature variables in central and eastern Qinghai‐Tibet plateau, and the areas of between lower reaches of Yellow River and Yangtze River. [ABSTRACT FROM AUTHOR]

In this study, we focus on the features and predictability of winter 2‐m air temperature (t2m) over China under different intensities of La Niña events. The seasonal and intraseasonal prediction skills of winter t2m over China are examined by four state‐of‐art seasonal climate forecast models. The results show that the China winter t2m anomaly is sensitive to the intensity of La Niña. Strong and moderate (S/M) La Niña events are often accompanied by cold winter over China, while a positive anomaly of mean t2m over China frequently occurs in the weak La Niña events. The intensity difference of the East Asian winter monsoon (EAWM) results in this discrepancy. All models have a slightly higher anomaly correlation coefficient (ACC) for the S/M La Niña than that for the weak La Niña in leading 1 month (LT1). Both individual models and MME exhibit higher skills of anomaly sign consistency rate (ASCR) for the S/M La Niña, which implies that models predict t2m anomaly over China more accurately in the S/M La Niña events. Furthermore, the winter t2m over China presents larger intraseasonal variability for the S/M La Niña than that for the weak La Niña. Models can capture the t2m anomaly over China more accurately when the temperature varies gently with small intraseasonal variability during winter for the S/M La Niña. [ABSTRACT FROM AUTHOR]

Drought is one of the most serious natural disasters exacerbated by climate change. Changes in precipitation and temperature in the future increase the likelihood of drought in China. In this study, a stepwise cluster ensemble downscaling (SCED) model was developed to bias‐correct projections of temperature and precipitation from multiple RCM outputs, and further characterized the drought hazards. The developed SCED model was used to aggregate and correct the results of multiple regional climate models, and its performance was proved to be reliable by comparing with the observed results. The proposed SCED method has been applied for drought projections over the Fujian province, China. The results showed that the changes of precipitation and temperature in Fujian would have obvious spatial heterogeneous characteristics. The temperature in the southeast coastal areas will increase by up to 4°C and the precipitation will decrease by 3.1% in the late 21st century, while the temperature rises and precipitation increases in the southwest. Temperature in inland areas will be lower and precipitation will be less. The drought hazards were also characterized by both SPI and SPEI based on biased‐corrected projections from SCED model. According to the SPI and SPEI indices, although the number of dry months in Fujian province will not change significantly in future, the spatial and temporal heterogeneity may become more explicit. Moreover, the moderate drought (from SPI) may increase while the general drought may decrease (from both SPI and SPEI). For extreme droughts, there would not be visible changes detected by SPI, but an increasing trend characterized since the impact of temperature was included in SPEI. In addition, there would be an increasing trend on drought when increasing temperature and precipitation occurred simultaneously. [ABSTRACT FROM AUTHOR]

Daily climate data are extremely important to drive ecological models, but the outputs of climate models are often deviated from the observations. The bias correction methods mostly highlight the target statistical parameters (e.g., mean and variance) for a target period, but perturb the simulated change trend and variability. In this study, we utilize a trend‐preserving bias correction method that can simultaneously consider the frequency and intensity of climatic variables to adjust the daily maximum and minimum temperature, and precipitation (Tmax, Tmin, and Pre) from CORDEX‐EA regional climate models for the period of 2021–2050 over China. Results show that: (a) the bias correction method greatly improves the spatial patterns of simulated Tmax, Tmin, and Pre since the corrected data has higher correlation and smaller differences across the whole domain. The differences in mean Tmax, Tmin, and Pre between climate models and observations have been reduced from −4.5 ± 6.41°C, −2.06 ± 0.58°C, 177.25 ± 51.55 mm before correction to 0.01 ± 0.02°C, −0.01 ± 0.02°C, −26.22 ± 6.39 mm after correction, respectively. In addition, the simulated change trend and climate variability at all time scales are well preserved. (b) Spatially, the warming rates in the west would be higher than in the east, and they are larger under the most severe future emissions scenario (RCP8.5) relative to the low‐mid emissions scenario (RCP4.5). The Pre change would mainly occur over east China with the significant upward trend. The dataset presented in this article has been published in the Network Common Data Form (NetCDF) File Format at https://doi.org/10.5281/zenodo.5058620. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The East Asian summer monsoon (EASM) is unique among monsoon systems that it features meridional evolution of the summer monsoon. In this study, we evaluate the performances of a Variable‐Resolution Community Earth System Model (VR‐CESM) regionally refined over eastern China (14 km) in reproducing the seasonal evolution of EASM precipitation over China. Compared with reference datasets, VR‐CESM shows better performance than the corresponding globally uniform coarse‐resolution model CESM (quasi‐uniform 1°), especially over western China where complex local topography exists. The northward monsoon migration is closely related to low‐level southerly flows and vertical moisture advection, which are more reasonably simulated in VR‐CESM. The four critical timings of the EASM (monsoon onset, withdrawal, peak, and duration) are also better captured in VR‐CESM than in CESM. The corresponding spatial Pearson correlation coefficients of the four critical timings with respect to reference datasets are about 0.1 higher in VR‐CESM than those in CESM. Both models are most accurate in simulating monsoon onset and least accurate at simulating the monsoon peak. The overestimated zonal thermal contrast in CESM is responsible for the earlier monsoon onset and excessive precipitation in September over the Yangtze River valley. Finer resolution in VR‐CESM, especially over the Tibetan Plateau (TP), appears to be a main factor in simulating better zonal thermal contrast and seasonal evolution of the EASM. [ABSTRACT FROM AUTHOR]

The present study aimed to evaluate the performance of 46 global climate models (GCMs) from the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) in the historical simulation of precipitation and temperature, and select the best performing GCMs for future projection across China and three major river basins. This study uses four shared socioeconomic pathways (SSPs), namely SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 relative to the base period (1961–2014). Initially, 46 models were evaluated across China employing an improved Taylor diagram method. Based on relatively better performance, 10 best‐performing models (TBMs) were selected out of 46 models for further evaluation. The results show that historical temperature was well reproduced by CMIP6 over the study regions with a high correlation coefficient (CC). All the TBMs produced good CC ranging from 0.8 to 0.99 presenting the precipitation and temperature distribution well. Meanwhile, EC‐Earth3 and EC‐Earth3‐Veg well simulated the precipitation and temperature amounts as well as trends over selected three river basins. The multimodel ensemble mean (MME) underestimates temperature over China and selected three basins with bias values of −0.53, −0.21, −0.91, and −0.68°C, respectively. In contrast, MEM overestimated the simulated precipitation with the amount of 27.7, 32.4, 21.0, and 104.6% across China and selected three basins. During future projections, increased precipitation and temperature trends are projected over three selected river basins as well as all across China. The increasing trend of future precipitation over China under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 scenarios are 0.65, 0.86, 1.29, and 0.76 mm·a−1, whereas, the increasing trend of temperature is 0.008, 0.028, 0.050, and 0.065°C·a−1, respectively. Comparatively, the greater the radiation force, the higher projected increases in precipitation and temperature across China and three major river basins were observed. The extent of CMIP6 models over the target region and its river basins calls for further deep assessment of the attribution and possible implementation of robust methods that can accurately simulate the observed patterns for future practice. [ABSTRACT FROM AUTHOR]

Global climate change is projected to increase the probability of occurrence and severity of droughts. Increased CO2 concentration drives partial closure of plant stomata and reduces evapotranspiration. However, the impact of reduced evapotranspiration due to CO2 on future droughts characteristics in China is unclear. In this study, we have used the Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model simulations (GCMs) under historical period, and four shared socioeconomic pathway scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5) to estimate drought. We used a widely applicable drought index (i.e., the self‐calibrating Palmer Drought Severity Index [scPDSI]) to evaluate the historical and future drought conditions, using the Penman–Monteith formula with and without the CO2 concentrations. The results show that the increasing trend of scPDSI slows down when the CO2 effect is considered in all scenarios, especially in Heilongjiang, northern Xinjiang, and the Qinghai–Tibet Plateau. The divergence in the slowdown trend among the different scenarios becomes greater after 2030, with higher emission scenarios implying a greater slowdown in the increasing trend of scPDSI. After considering CO2, drought characteristics such as the drought frequency, intensity, and drought area decrease. Increased CO2 concentration on vegetation physiological processes could mitigate future drought. Therefore, the effects of CO2 on plant physiology should be considered in studies of future drought trends to develop more realistic response and adaptation policies to future drought changes. [ABSTRACT FROM AUTHOR]

The surface air temperature seasonal cycle in China has clearly changed in response to global warming, but its future projection has yet to be studied. Here, we investigate the performance and projection of the temperature seasonal cycle in China in 32 global climate models participating in the Coupled Model Intercomparison Project 6 (CMIP6). The characteristics of the temperature seasonal cycle, as represented by the amplitude and phase, are measured by the Fourier transform. The results show that the CMIP6 models can reasonably capture the observed typical temperature seasonal cycle feature with clear north–south gradients both for amplitude and phase in China. In the twenty‐first century, the models robustly project a delay in the phase across the whole country and a reduction in the amplitude in most of China relative to the reference period. Those changes are similar in the two shared socioeconomic pathway (SSP) scenarios, with overall larger magnitudes in the SSP5‐8.5 scenario than in the SSP2‐4.5 scenario. Projected amplitude changes are mainly linked to surface energy flux changes, especially latent heat flux changes. In response to future global warming, larger increases in the latent heat flux and thus stronger surface evaporative cooling lead to weaker surface warming in summer than in winter, contributing to a decrease in the amplitude of the temperature seasonal cycle in most regions of China. [ABSTRACT FROM AUTHOR]

Within the frameworks of the Coordinated Regional Downscaling Experiment‐East Asia first and second phase (CORDEX‐EA‐I and CORDEX‐EA‐II), the impact of spatial resolution, physical parameterization schemes and spectral nudging (SN) on simulating inland and offshore near‐surface wind speed over China is evaluated. By using WRF and RegCM4 models, the CORDEX‐EA simulations driven by the ERA‐Interim reanalysis data are conducted from 1989 to 2008. The regional climate models (RCMs) have the capacity to simulate the spatial patterns of surface wind, although significant overestimations exist over inland China. The WRF CORDEX‐EA‐II experiments with increasing horizontal resolution perform better in reproducing both inland and offshore wind speed than the CORDEX‐EA‐I experiments. Moreover, the experiments with SN can significantly reduce the positive biases of surface wind speed. For the temporal variation of wind speed, almost all the simulations show larger biases in winter than in summer. Particularly, the simulated wind speed in summer in the RegCM4 experiment with CLM3 land surface model (RCC‐II) is close to the observations. The extreme wind speed can be well reproduced by WRF simulations, and the SN experiments perform better than the experiments without SN (NOSN). In addition, the overestimations of surface wind speed can be partly explained by the overestimations of the wind field at 850 hPa level inherited from ERA‐Interim reanalysis and the increase of temperature gradient between the land and ocean in winter. [ABSTRACT FROM AUTHOR]

This study presents an analysis of the changes in extreme temperatures over major river basins in China under different shared socioeconomic pathway (SSP) scenarios based on a set of dynamical downscaling over CORDEX East Asia, performed with the regional climate model RegCM4 at a resolution of 25 km, driven by the global climate model FGOALS‐g3. The results indicated that the dynamical downscaling tended to reduce the warm (cold) biases of the present‐day daily maximum (TXx) and minimum temperatures (TNn) simulated by FGOALS‐g3. Under the SSP scenarios, substantial increases in TXx and TNn and the number of warm days and warm nights throughout China were projected by both models. The average increase in TXx in most of the river basins ranged from 1 to 2°C under the SSP1‐2.6 scenario, from 2 to 3°C under the SSP2‐4.5 scenario, and from 3 to 5°C under the SSP5‐8.5 scenario. Reductions in the number of cold days and cold nights were projected across China, but these reductions were smaller than the increases in the number of warm days and warm nights. The interregional variability in the increases in TXx and TNn was more pronounced in the SSP5‐8.5 scenario and the RegCM4 model than in the other SSP scenarios and the FGOALS‐g3 model, respectively. Larger percentages of the land area and population of China would be affected by greater increases in extreme high temperatures and TNn. Under the SSP2‐4.5 (SSP1‐2.6) scenario, 20–65% (50–95%) of the impacts of extreme temperatures under the SSP5‐8.5 scenario could be avoided across most regions in China. The avoided impacts of warm days and warm nights were greater than those of the other extreme temperature indices. More of the impacts of extreme temperatures could be avoided in the Huai River basin, Yellow River basin, Hai River basin, and Northwest Interior River basin than in the other river basins in China. [ABSTRACT FROM AUTHOR]

Bias‐corrected monthly precipitation and surface temperature datasets are constructed for the monsoon transitional zone (MTZ) in China during 1965–2100 based on 21 coupled climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) using the equi‐ratio and equidistant cumulative distribution function quantile‐based mapping methods (equi‐ratio cumulative distribution function [ERCDF] and equidistant cumulative distribution function [EDCDF]), respectively. The efficiencies of the two methods are verified via cross‐validation by the jack‐knife method, and the biases are remarkably reduced compared to those of the raw model outputs. Then, the bias‐corrected model outputs are applied to future projections of precipitation, surface temperatures and drought events under the medium (SSP2‐4.5) and high (SSP5‐8.5) shared socioeconomic pathway scenarios. The obtained results present pronounced increases in both the projected annual mean precipitation and temperature fields for the model ensemble mean. In accompany, the MTZ is predicted to become drier in the three future periods; this result was attributed to the dramatic increases in semiarid events and to the decreases in humid events. The drought tension showed more rapid development under SSP585 than under the other scenario, with comparable occurrence frequencies of relatively wet and dry events in the long‐term period, posing a serious threat to regional sustainable development. [ABSTRACT FROM AUTHOR]

Hindcasts during 1991–2010 are analysed to investigate the forecast skills for summer precipitation in northeast China (NEC) and circulations in northeast Asia with a leading time of 1‐month in three operational climate models and their equally weighted mean. It is found that the precipitation prediction ability of all the models and their combinations are much low in NEC. However, both the single model and their averages can well reproduce the basic summer circulation characteristics over Northeast Asia, especially the northeast China cold vortex (NECV) that directly affects precipitation in NEC. Observed precipitation is significantly correlated with the forecasted vorticities in each model and their combinations, particularly in the ensemble mean of the models (MME). Furthermore, the interannual variability of the NECV in MME agrees well with the observations. Linear regression between the simulated NECV and the precipitation in NEC is established for each model and their averages. The root‐mean‐square errors (RMSEs) of precipitation forecast from the regression of NECV are much lower than the direct outputs in above models, while the correlation coefficients (CCs) are much higher. The CC between observation and forecasts by the regression method based on the NECV in MME is the highest (0.5), closest to the value of 0.58 in observation, and the RMSE is the smallest (0.54), decreased by 13% compared with MME direct outputs. The cross‐validation during the 20 years can provide better prediction skills with a CC of 0.37, higher than that for the single‐model outputs, the averages of random two models and the MME. Independent forecasts also provide higher prediction skills than the official forecast of China Meteorological Administration in 4 years during 2013–2018, especially the extreme flood summer of 2013. The results indicate it might be a feasible approach to improve the prediction skill of summer precipitation in NEC. [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]

Using the dynamical downscaling by the regional climate model RegCM4 from four global climate models, future changes in heat waves (HWs) over China under the RCP4.5 scenario are projected in terms of frequency and magnitude. The magnitude combines the duration and intensity together to characterize HW severity. The ensemble of RegCM4 downscaling simulations indicates a substantial increase in the frequency and magnitude of HWs over China toward the end of the 21st century relative to the current climate (1986–2005). The considerable changes occur in Southwest, South, North, and Northeast China for the frequency and in South, Southwest, East, and Central China for the magnitude. The prolonged HW duration plays a leading role in the enhancement of HW severity. In particular, an accelerated aggravation of the risk of extreme HWs is anticipated. Unusual HWs that never occurred in the current climate are expected to be usual phenomenon. For instance, by the end of the 21st century, the risks of the occurrence of extreme HWs (above the 99th percentile) in Southwest and South China are 64 and 53 times of the current, respectively, while the projected risks of the occurrence of mild HWs (below the 60th percentile) are much smaller and comparable in China. The HW frequency above the maximum of the current would appear once almost every year, and South, Central, and East China (North and Northeast China) would experience more severe HWs than the most extreme of the present every 1–2 (2–4) years. [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]

Accurate vegetation cover data are important for realistic simulation of regional climate. The default vegetation parameters from Global Land Cover 2000, currently incorporated into global climate models and used in regional climate model RegCM, are not realistic for China, which may have contributed to serious bias in surface climate simulation. In this study, a new set of vegetation parameters considering the Plant Functional Type (PFT) fractions and the corresponding monthly leaf area index (PFT_LAI), were developed based on the land cover and MODIS LAI data sets. The regional climate model RegCM4.5 coupled with the land surface model CLM4.5 were utilized to test the performance of the new vegetation parameters by comparing simulations with observations using different surface parameters. The surface energy balance was analysed to examine the effects of changed vegetation parameters on regional climate. The results showed that the new parameters were more accurate than the GLC2000 parameters when describing the distribution of crops, grassland, and forests over China. The improved vegetation parameters reduced model biases for winter air temperature and precipitation over southern China by 0.9°C and 8%, respectively, and reduced the winter temperature and summer precipitation biases over northeastern China by approximately 0.7°C and 8%, respectively. More accurate surface albedo are the main reasons for reductions in model bias. However, certain biases, such as the cold and dry bias over the Tibetan Plateau, still remained in the simulation results using our new vegetation data. [ABSTRACT FROM AUTHOR]

Adverse impacts and increasing economic losses from tropical cyclones (TCs) are a major focus in respect to the potential global warming of 1.5 °C or even 2.0 °C. Based on observed meteorological data and county‐scale loss records, loss‐inducing rainfall and wind speed thresholds are identified using the regional climate model CCLM to project future TC events in China. An established damage function is combined with future gross domestic product predictions under five shared socio‐economic pathways. At the 1.5 °C warming level, normalized TC losses will be four times higher than in the reference period (1986–2005). At the 2.0 °C warming level, a sevenfold increase is projected. Relative to the 1.5 °C warming level, TCs will become more frequent under the 2.0 °C scenario, especially along the southeast coast of China. Nearly 0.2–0.5% of the increase in gross domestic product might be offset by TC losses between the 1.5 °C and 2.0 °C warming levels, and the single highest TC loss at 2.0 °C may double that at 1.5 °C, with a larger affected area and more severe rainstorms and wind speeds. Rainfall is attributed more often to TC losses than wind speed. Limiting global warming at 1.5 °C would avoid an estimated increase in TC losses of more than 120 billion CNY annually. Based on a simple linear regression approach, normalized event‐based (a) and annual aggregated (b) TC losses in China will be four times higher at the 1.5 °C warming level than in the reference period (1986–2005). Relative to the 1.5 °C warming level, TCs will become more frequent under the 2.0 °C scenario, especially along the southeast coast of China. Limiting global warming at 1.5 °C would avoid an estimated increase in TC losses of more than 120 billion CNY annually. [ABSTRACT FROM AUTHOR]

ABSTRACT: The changes in mean and extreme climate in China during 2020–2060 are detected with both Weather Research and Forecasting and RegCM4, by downscaling the simulations from EC‐EATTH and IPSL‐CM5A under both the RCP4.5 and RCP8.5 scenarios. The climate changes under the two scenarios exhibit similar patterns, with stronger intensity under the RCP8.5 scenario. For the mean precipitation, increases are projected in most regions, with the largest relative increase in the Tarim Basin. Slight drought mainly occurs in the south‐eastern part of China. The frequency of drizzle rain is expected to decrease in all the sub‐regions, but the moderate to heavy rainfall as well as the storm would occur more frequently, especially on the Tibetan Plateau. The whole country would experience much warmer climate in the future, with the strongest warming over the Tibetan Plateau. By detecting the changes in climate extremes, it is indicated that less dry extremes would occur in the wet areas of China, while more dry events in the arid and semiarid regions. The wet extreme indices would increase in most regions, especially in the wet areas. The surface air temperature tends to become extremely warmer in the future over the whole country, with the strongest change over the Tibetan Plateau. The changes in mean and extreme climate depend strongly on the driving global climate models, with wetter and warmer climate in the downscalings over IPSL‐CM5A, and the model physics of the regional climate models also exert great impact on the projections. Finally, the possible mechanisms for the changes of extreme precipitation are discussed. The enhanced summer monsoon in the future transports more moisture to China, which could lead to more summer precipitation. As a result, the wet extremes tend to increase. [ABSTRACT FROM AUTHOR]

ABSTRACT: Western China (WC) is located in the arid and semi‐arid belt of the mid‐latitudes. Understanding the causes of the large temperature increases experienced in this region is of great importance because both the fragile ecological environment and the human societies in WC are highly vulnerable to changes in climate. We conducted a detection and attribution analysis on the annual mean temperature using an optimal fingerprinting method by comparing observations based on homogenized station data with simulations conducted using the models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The results show that the increase in the mean temperature can be attributed to human activities. The effect of anthropogenic (ANT) forcing can be detected in single‐signal detection analyses when the response to the ANT forcing is compared directly with the observations. This effect can also be separated from the influence of the natural external forcing in two‐signal analyses. The warming attributable to the ANT forcing explains most of the observed regional warming. The models appear to have underestimated the observed warming, suggesting that the projected future temperature increases based on raw output from the model simulations may have also been underestimated. [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]