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The uneven changes in potential evapotranspiration (PET) in response to temperature rise are called the 'evapotranspiration paradox' phenomenon, which is expected to intensify further under a warming climate. In this paper, we explored the spatial–temporal changes in the future 'evapotranspiration paradox' phenomenon over China and its 10 major river sub‐regions under different climate change scenarios. Thus, this paper uses four global climate model outputs under seven shared socioeconomic pathway‐based scenarios (SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, SSP4‐3.4, SSP4‐6.0 and SSP5‐8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Considering the latest IPCC's 6th Assessment Report (AR6), this research emphasizes the 2021–2040 (near‐term), 2041–2060 (mid‐term) and 2081–2100 (long‐term) periods to anticipate the 'evapotranspiration paradox' phenomenon. In this study, PET is estimated based on the modified Penman–Monteith (P‐M) method (considering CO2). Furthermore, the paradox phenomenon in this study is defined considering two pivotal conditions: the surface temperature increases but the evaporation decreases (Type I), and the temperature decreases but the evaporation still tends to increase (Type II). The results show that there were only Type I 'evapotranspiration paradoxes' that existed in the historical period, which were dominant especially before the 1990s. Nearly 50% of the areas experienced the Type I 'evapotranspiration paradox' phenomenon that occurred during 1975–1994 and 1995–2014. Spatially, it covered 100% of the area of the Southeast River (SER) and the Liaohe River (LR) during 1975–1994 and the area of the SER, the HAR, the HHR and the LR during 1995–2014. In the future, the interdecadal growth rate of PET in China is projected to be the highest under the SSP5‐8.5 and the lowest under the SSP3‐7.0 with spatial variation. Importantly, the largest areas of approximately 36% and 45% with the Type I phenomenon are inclined to occur under the SSP1‐1.9 and SSP4‐6.0, respectively, over the long‐term period (2081–2100). The area with the Type I phenomenon will be less than 20% in the near‐term, and it is less than 12% in the mid‐term period. For the Type II evapotranspiration paradox, the uppermost 45% of the area is expected to experience the Type II phenomenon under SSP1‐1.9 during the mid‐term period, while it is 30% under SSP1‐2.6 during the long‐term period. However, this study's findings provide the scientific basis for formulating adaptation and mitigation strategies to combat 'evapotranspiration paradox'‐related extremes at regional scales. [ABSTRACT FROM AUTHOR]

This paper describes the construction of a 0.25° × 0.25° daily soil temperature (TS) data set at six soil depths (i.e., 0, 5, 10, 15, 20, and 40 cm) based on a homogenized TS at more than 2,000 meteorological stations across mainland of China for 1960–2017. First, at each station, the observed TS is split into a daily climatology of 1981–2010 and a daily anomaly for 1960–2017. Then, they are respectively interpolated to 0.25° × 0.25° horizontal resolution by using the thin‐plain spline and the angular distance weight interpolation methods. Finally, a gridded multilayer TS data set is constructed from the sum of the above two gridded products. Latitude, longitude, and high‐resolution digital elevation models are explicitly incorporated into the interpolation processes. Selectivity tests indicate that the optimal interpolation distance for the TS anomaly field is 500 km, where the gridded data set may have maximum coverage of the entire Chinese mainland. The results show that the gridded TS climatology is slightly lower than the station observations. The differences between gridded and the station‐based TS varies ±3°C, with relatively large in SW and TIBET. For the gridded anomaly fields, the cross‐validation shows that the mean absolute errors between gridded and station‐based TS are generally less than 0.6°C in the YZ, SW, and SC, but they are above 1.0°C in the NW and TIBET due to the sparse station distribution and large topographic relief. From 1961 to 2016, the seasonal variability of the gridded TS is generally consistent with that of the surface air temperature. The gridded TS over the majority of land displays significantly positive trends in both summer and winter (p > 95%), indicating an overall warming land surface in China. The long‐term gridded TS data not only preserves the spatial features represented in the station observations, but also provides a spatio‐temporal continuous long‐term product of mainland China. Thus, it may be used in future studies, for example, evaluation of land surface model simulations, validation of satellite retrievals, land‐atmosphere interactions, and climate change. [ABSTRACT FROM AUTHOR]

The cold surge (CS) is an extreme climate event that frequently affects China. By using a 0.25° × 0.25° gridded observation dataset provided by the China Meteorological Administration (CN05.1), this paper investigates the spatial–temporal characteristics of various CSs in China during 1962–2018. According to the duration and coverage area (CA), CSs are classified into the short‐lived cold surges (SLCSs), the persistent cold surges (PCSs) and the extensive and persistent cold surges (EPCSs). They are also divided into the weak cold surges (WCSs), the strong cold surges (SCSs) and the super strong cold surges (SSCSs) based on the temperature drop (ΔT). The extreme cold surges (ECSs) are also defined and occur 38 times over 57 years. The total CSs and various CSs all display patterns of higher frequencies in the northeast and lower frequencies in the southwest. Northeast China and Inner Mongolia are frequently hit by various CSs, but the frequencies show overall downward trends in the regions during 1962–2018. The ΔT of the total CSs and ECSs both show significant decreasing trends in the whole of China from 1962 to 2018. From 1962 to 2018, the annual frequency and the ΔT of the total CSs both show decreasing trends. SLCSs and WCSs frequencies show overall increasing trends, but other kinds of CSs show overall decreasing trends. The annual frequencies of the total CSs and various CSs all have trend abrupt changes around 2000. The ΔT of ECSs shows a sharply increasing trend during 1962–2018. The total CSs and all kinds of CSs frequencies have a significant periodic oscillation. ECSs occur most in February. The total CSs and other kinds of CSs occur most in January. There are obvious differences between the multiyear average ECSs frequencies before 2000 and after 2000. [ABSTRACT FROM AUTHOR]

Drought occurs more frequently in the context of climate change and threatens water security worldwide. An appropriate fitting distribution is crucial for accurately identifying drought using drought indices. Here, seven two‐parameter distributions (Gamma, Gumbel, Logistic, Log–Logistic, Log‐normal, Normal, and Weibull) and four distributions (general logistic, generalized extreme value, Normal, and Pearson Type III) are applied to calculate the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), respectively, to choose the most appropriate fit for the 541 stations in China. The results show that, in most cases, Gamma and general logistic were the best distributions for SPI and SPEI, respectively. Nevertheless, we noted that Pearson Type III and generalized extreme value also fit the SPEI series well, indicating the importance of distribution fitting assessment for various regions. The annual and seasonal drought evolutions across China were clarified, with drought decreasing significantly in western Northwest China (annually and each season), northern North China (spring and winter), the Tibetan Plateau (spring), and the lower reaches of the Yangtze River (winter) and increasing mainly in South China (spring) and western South China (summer and autumn). The intensity, duration and severity of light, moderate, and severe drought were also detected; the results suggest that drought in China is mainly concentrated around the changes in light and moderate drought. Additionally, we assessed the sensitivity of drought evolution to various meteorological variables. The most sensitive variable in South China, North China and the Tibetan Plateau is precipitation, followed by wind speed, temperature, relative humidity, and sunshine duration; in Northwest China, the order is wind speed, precipitation, temperature, relative humidity, and sunshine duration. Furthermore, the correlation results also indicate that the drought evolution is affected by the multivariate ENSO index, while the influencing characteristics are different in various seasons and regions. The results in this paper contribute to drought mitigation and the effective utilization of water resources in China. [ABSTRACT FROM AUTHOR]

ABSTRACT The biases in the Global Circulation Models ( GCMs) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from the assumption that model bias is stationary. This paper provides a non-stationary bias correction model, termed residual-based bagging tree ( RBT) model, to reduce simulation biases and to quantify the contributions of single models. Specifically, the proposed model estimates the residuals between individual models and observations, and takes the differences between observations and the ensemble mean into consideration during the model training process. A case study is conducted for 10 major river basins in Mainland China during different seasons. Results show that the proposed model is capable of providing accurate and stable predictions while including the non-stationarities into the modelling framework. Significant reductions in both bias and root mean squared error are achieved with the proposed RBT model, especially for the central and western parts of China. The proposed RBT model has consistently better performance in reducing biases when compared with the raw ensemble mean, the ensemble mean with simple additive bias correction, and the single best model for different seasons. Furthermore, the contribution of each single GCM in reducing the overall bias is quantified. The single model importance varies between 3.1% and 7.2%. For different future scenarios ( RCP 2.6, RCP 4.5, and RCP 8.5), the results from RBT model suggest temperature increases of 1.44, 2.59, and 4.71 °C by the end of the century, respectively, when compared with the average temperature during 1970-1999. [ABSTRACT FROM AUTHOR]

There is an increasing focus on the usefulness of climate model--based seasonal precipitation forecasts as inputs for hydrological applications. This study reveals that most models from the North American Multi-Model Ensemble (NMME) have potential to forecast seasonal precipitation over 17 hydroclimatic regions in continental China. In this paper, we evaluated the NMME precipitation forecast against observations. The evaluation indices included the correlation coefficient (R), relative root-mean-square error (RRMSE), rank histogram (RH), and continuous ranked probability skill score (CRPSS).We presented the RRMSE-R diagram to distinguish differences between the performances of individual models. We find that the predictive skill is seasonally and regionally dependent, exhibiting higher values in autumn and spring and lower values in summer. Higher predictive skill is observed over most regions except the southeastern monsoon regions, which may be attributable to local climatology and variability. Among the 11 NMME models, CFS, especially CFSv2, exhibits the best predictive skill. The GFDL and NASA models, which are followed by CMC, perform worse than CFS. The performances of IRI and CCSM3 are relatively worse than that of the other models. The forecast skills are significantly improved in multi-model mean forecasts based on simple model averaging (SMA). The improvement is more obvious for Bayesian model averaging (BMA), which is employed to further improve the forecast skill and address model uncertainty using multiple model outputs, than individual model and SMA. [ABSTRACT FROM AUTHOR]

Understanding future dry and wet changes under global climate change is of great regional significance in China. Based on six Global Climate Models (GCM) from the Coupled Model Intercomparison Project phase 6 (CMIP6), we project the changes of dry‐wet climate regions in China in the 21st century under the three SSP‐RCP (shared socioeconomic pathway‐representative concentration pathway) scenarios (SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5), and further identify the key climatic factors that lead to the transition of dry‐wet climate regions. The results show the area of humid and subhumid regions in China will show an upward trend in the future, while the area of semiarid and arid regions will show a downward trend. Especially under the SSP5‐8.5 scenario, the area of the subhumid region has the largest increase trend (0.042% per year), and the area of the arid region has the largest decline trend (−0.048% per year). The three main transfer directions of dry‐wet climate regions are from arid to semiarid regions, from semiarid to subhumid regions, and from subhumid to humid regions in the future. Due to the future extensive wetting trend in the north, the future dry‐wet climate regions will shift to wetter types in Tibet, North China, the Qinling‐Huaihe regions and the northeast. In addition, the key climatic factors for the transition of dry‐wet climate regions are mainly precipitation, maximum temperature and solar radiation. The increase of precipitation plays a dominant role for areas projected to change to wetter types, and the increase of potential evapotranspiration (PET) plays a dominant role for areas projected to change to drier types. The PET changes in changed areas of dry‐wet climate regions are mainly dominated by maximum temperature and solar radiation. Our research has important implications for future water resource management and reconsideration of climate mitigation and adaptation policies. [ABSTRACT FROM AUTHOR]

Consecutive extreme wet days (CEWDs) typically affect the likelihood of flooding and landslides and have negative effects on both natural and artificial ecosystems; however, the spatiotemporal changes in their features are still unclear at the national scale. Investigating changes in the frequency and intensity of such events is essential for climate risk management. Here, this study thoroughly analysed CEWD features in China from 1980 to 2020 using the daily observation dataset. We also evaluated and compared the ability of two widely used precipitation products, the European Centre for Medium‐Range Weather Forecasts Reanalysis 5th Generation (ERA5) and the Multi‐Source Weighted‐Ensemble Precipitation version 2 (MSWEP), to detect CEWD features. According to the observation data, the frequency and intensity of CEWD events are related to local climate and present "high eastern and low western" spatial patterns across China. Since 1980, more than half of China's mainland has experienced increases in both the frequency and intensity of CEWDs. Some stations detected decreasing trends in CEWD frequency and amounts, which are primarily located in the eastern coastal regions and southwest of warm temperate humid/subhumid regions. The ERA5 precipitation product generally outperforms MSWEP data in detecting CEWD events, and the latter significantly underestimates the annual frequency and amounts of CEWDs. These findings provide basic and valuable information regarding CEWD features across China and where such studies can be conducted based on precipitation datasets. Furthermore, these findings will also aid policymakers in managing extreme precipitation‐related natural hazards. [ABSTRACT FROM AUTHOR]

Various climatic factors and their interactions affect China's snow depth alterations. However, a measure of the relative importance of climatic factors regarding the variance in snow depth is lacking. Here, we use a heretofore largest dataset, quality‐controlled daily observations from 1,665 meteorological stations, and statistical analyses to identify proxy drivers and their contributions regarding regional variability and trends in China's snow depth and snow depth‐climate relationships from 1951 to 2019. Results show that seasonal snow depth alterations are substantial in China and caused by various climatic drivers. In winter, observed positive trends in the northwest and northeast of China mainly respond to augmentation in solid precipitation and snow accumulation in fall. For the Tibetan Plateau, the negative snow depth anomaly seems to respond to the rising air temperature below the freezing point along with some secular changes in solid precipitation and shallower fall snowpacks. All these trends in winter snow depth over the northwest, northeast, and Tibetan Plateau of China account approximately for 30% of the total interannual variance in spring snow depth in these regions. In the milder central north and south of China, snow accumulation is not evident. Besides solid precipitation and rising air temperature below the freezing point, atmospheric humidity is also notable for its effect on the interannual variance in winter snow depth in these regions. In spring and fall, however, the negative effect of warming climate on snow depth becomes remarkably more important. It seems that about 13–33% (12–50%) of the total interannual variance in the widespread decrease (insignificant perturbation), except for some weak increases in the northeast region (decreases in the Tibetan Plateau), of China's spring (fall) snow depth are caused by the rising air temperature below the freezing point. [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]

Climate warming is steadily increasing drought risk in many regions of the world. However, the contribution of warming over the past few decades to drought evolution in China remains unclear. This study used the self‐calibrating Palmer drought severity index (sc‐PDSI) and a detrending experiment to quantify the contribution of warming to severe drought (sc‐PDSI < −3.0) characteristics (intensity, frequency, and duration) over China from 1980 to 2019. Differences in drought characteristics calculated from original and detrended temperature data were attributed to warming effects. The results showed that 93.8% of areas in China have experienced a significant (p <.05) warming trend from 1980 to 2019. Warming remarkably intensified severe drought characteristics across China. Without warming, the extent, frequency, and duration of severe droughts in China would reduce by 2.04%, 2.0%, and 0.82 months. In addition, there are apparent regional differences in the response of severe drought characteristics to warming. Severe drought characteristics in high elevations and high latitudes are more sensitive to warming than in other regions. [ABSTRACT FROM AUTHOR]

China's surface air temperature is increasing due to global warming, so it is interesting that how low temperatures would be changed during the growth period of winter wheat in future. We focused on the low temperatures of winter wheat from 2021 to 2050, using temperatures under the high emission scenario Representative Concentration Pathway 8.5 (RCP8.5) projected by the RegCM4.4 regional climate model. The results showed that the annual mean temperature was projected to increase by 0.42°C⋅decade−1 in the northern and by 0.35°C⋅decade−1 in the southern winter wheat region. Furthermore, the temperature was expected to increase rapidly in spring, which could advance the dates of flowering and the start of the grain‐filling period. Using the genetic parameters determined by the calibration and validation of WOFOST and bias‐corrected projected meteorological data, simulations of winter wheat growth were performed over the winter wheat region for 2021–2050. The simulated number of days to the flowering period of winter wheat for 2041–2050 was on average 6.5 days less than in 2021–2030, due to the spring warming. Because of the earlier start of the growing season, winter wheat could face negative effects by being subjected to low temperatures. Indeed, the number of low‐temperature days was projected to increase by 110% from 2041 to 2050 compared to 2021–2030, and the number of killing degree days (KDDs) is projected to increase by 120% at the same time. If the number of days to flowering did not change, the number of low‐temperature days and KDDs only changed slightly, showing that the negative influence of low temperature was mainly caused by the advancement of the flowering date. The effect of low temperature on growth was underestimated when the response of winter wheat growth to global warming was not considered. [ABSTRACT FROM AUTHOR]

Knowledge of the difference between soil and air temperatures (ΔT) is helpful to improve our understanding on the land‐atmosphere thermal interactions and temperature‐dependent soil processes. Based on 272 stations across China, this study investigated the spatiotemporal variations of the annual and seasonal ΔT (difference between soil temperature at a depth of 0.4 m and air temperature) from 1981 to 2014, and quantified the relative contributions of multiple environmental variables (snow cover, precipitation, vegetation, soil moisture, and solar radiation) to ΔT variation for the first time. Air temperature primarily controls soil temperature dynamics, but the asynchronous trends of soil and air temperatures may lead to the complexity of the land‐atmosphere relationship. Almost no apparent trends in ΔT were detected for the entire China (except in summer), but the spatial heterogeneity of trends was evident. Snow cover conditions greatly dominated the ΔT dynamics both annually and seasonally (except in summer). The relative contribution of snow cover duration to ΔT variation was significantly greater than that of mean snow depth for the entire China, but the regional differences in the contributions of the two variables were noticeable at different seasons. The greening of vegetation closely associated with the ΔT variation in annual, autumn and winter, and soil moisture exerted a great influence on summer ΔT, associated with sunshine duration (a proxy for surface solar radiation). The amount of precipitation made a slight impact on ΔT at either seasonal or annual scales. [ABSTRACT FROM AUTHOR]

A heavy rainfall trajectory (HRT) is defined as the trajectory formed by the movement of the rainstorm centre of a heavy rainfall event over time. Based on this definition, the dispersion degree (DD) of HRTs is applied based on the Euclidean distance and an empirical orthogonal function (EOF) to quantify the spatiotemporal distribution and evolution characteristics of HRTs in China. The results show that (a) the spatial distribution and length of HRTs in China have distinct geographical and seasonal characteristics, which are strongly influenced by the East Asian summer monsoon. (b) From southeast China to northwest China, the DDs increased to 8 and the length of HRTs decreased by 53,925 m. (c) According to EOF analysis, the direction angle change of northeast‐oriented HRTs shows a significant negative trend across the country, while those of southeast‐, southwest‐ and northwest‐oriented HRTs show a significant positive trend. From 2008 to 2019, HRTs flattened in the northeast and southwest directions, while HRTs steepened in the southeast and northwest directions. This research provides certain scientific guidance for the prevention and mitigation of regional disasters and provides necessary theoretical support for the changing patterns of the climate system under the impact of climate change. [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]

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]

The evolution of the frequency of dry/wet spells is a hot topic in global climate change research. The synergistic effects of dry/wet spells make their consequences far more significant than a single disaster, having considerable impacts on hydrology, ecology, and economies, especially in the context of global warming. In this study, the standardized precipitation evapotranspiration index (SPEI)‐based identification of dry/wet spells was used to explore the evolution of the frequency of dry/wet abrupt alternation (DWAA) events in the past four decades in China, makes up for the lack of research on the evolution of such compound disasters. China has been affected by dry/wet spells in many areas for a long time. Studies found that high‐frequency DWAA areas are concentrated in densely populated areas, China's essential food bases and core areas for economic development. Dry‐to‐wet (D–W) events and wet‐to‐dry (W–D) events basically increased or decreased at the same pace in this period. We innovatively find DWAA events (D–W events and W–D events) are projected to occur increasingly in a wider region of China. The frequency of D–W events across China has increased from 2.35 in the 1980s to 3.56 in the last decade, a 50% increase. On the other hand, W–D events increased from 2.6 to 3.23, increasing 24%. The three regions with the most remarkable changes in the past four decades are Inner Mongolia, northwest China, and north China, where D–W events increased by 121, 61, and 58%, respectively, and W–D events increased by 71, 57, and 61%, respectively. Hereby, it is vital to implement effective prevention against DWAA events in the area which has been neglected in the past decades because of lower frequency. These results may help policymakers develop suitable disaster mitigation plans for reducing the potential risks of extreme compound natural events. [ABSTRACT FROM AUTHOR]

The last millennium (LM, 1000–1850 AD) is crucial for studying historical climate change on decadal to multidecadal timescales. The summer surface air temperature (SAT) evolutions on regional scales (e.g. over China) are more uncertain than the globe/Northern Hemisphere, especially in response to external forcing factors and internal climate variability. Here, we provide one‐signal (full‐forcing) fingerprints of summer SAT in China derived from three large ensemble model archives with a multi‐proxy reconstruction during the LM, Little Ice Age (LIA, 1451–1850 AD), and Medieval Climate Anomaly (MCA, 1000–1250 AD), respectively. Our results show that (a) SATs in the northeast, southeast, northwest, and Tibetan Plateau (TP) regions of China show evident decreasing trends during the LM. External forcing response from all model archives agrees with the regional SAT reconstruction but underestimates variability in northwest China at the multidecadal timescale. (b) During the LIA, the summer regional SAT exhibits a cold condition in the reconstruction and simulations, especially in the northeast and northwest regions of China. External forcing responses in most model archives are the dominant factor on multidecadal SAT evolutions in the southeast, northeast, and TP regions of China and decadal SAT evolutions in northwest China. (c) During the MCA, detection and attribution of SAT shows that internal climate variability dominates in southeast, northeast, and TP regions of China, but external forcing dominates in northwest China at decadal to multidecadal timescales. These results contribute to a better understanding of the causes and mechanisms of regional climate change. [ABSTRACT FROM AUTHOR]

The effects of aridity on ecosystems and water cycles are pronounced and have received considerable attention. However, aridity changes due to future warming and its regional variability over China remain uncertain. This paper aims to identify the spatiotemporal variations in aridity and its key influencing factors over China in the mid-21st century based on five general circulationmodels (GCMs) and four representative concentration pathway (RCP) scenarios. An aridity index (AI), defined as the ratio of reference evapotranspiration (ETo) to precipitation (P), was calculated. We show that the GCMensemble means are able to reproduce the variation of aridity during the baseline period. Generally, ETo anomalies are consistently positive. Other than for the RCP2.6 low-emission scenario, precipitation and aridity are both projected to increase. There are pronounced regional differences in aridity changes; i.e. wetter across most of western China and drier across most of eastern China in the mid-21st century. Negative AI anomalies in western China can be attributed mainly to the projected increase in precipitation. In eastern China, the AI was higher despite positive precipitation anomalies, due mainly to the greater effect of climate change on increasing atmospheric moisture demand. This suggests that evapotranspiration demand should be incorporated into aridity changes under future warming. [ABSTRACT FROM AUTHOR]

Compared to individual dry or hot events, compound dry and hot events (CDHEs) usually pose more severe economic and societal impacts. A growing body of literature investigates the role of anthropogenic forcing on variations of individual dry and hot events at different spatial scales. However, the attribution of CDHEs in China using model simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) has received little attention. This study investigates the anthropogenic influence on CDHEs during summer in China and projects their future occurrences using CMIP6 simulations with data from the Climatic Research Unit (CRU) as observations. The results show that large regions of China experienced a significantly increased frequency of CDHEs during 1971–2010 relative to 1931–1970, which is overall captured by the CMIP6 simulations. Anthropogenic forcing is shown to contribute to the high likelihood of CDHEs in recent decades over most parts of China, with remarkable contributions in southwestern regions. Under future socioeconomic development scenarios, these CDHEs are projected to become more frequent in 2021–2100, which will increase by approximately 51.56–55.00% on average compared to that in 1931–2010. This study could aid the development of mitigation strategies of CDHEs across China under global warming. [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]

Performance of six models in the Coupled Model Intercomparison Project phase 5 (CMIP5) and their new versions in CMIP phase 6 (CMIP6) in representing the climatological (1976–2005) precipitation extremes over China were evaluated based on five precipitation indices. Improvements are found in CMIP6 models in simulating the climatology of all five indices, in which GFDL‐CM4 and GFDL‐ESM4 show significant improvement. Dry biases over South China (SC) are reduced in five CMIP6 models (BCC‐CSM, CanESM, GFDL‐CM, GFDL‐ESM, and IPSL‐CM), with the largest decreased root‐mean‐square error (RMSE) of 59.2% in GFDL‐CM. The reduced dry biases in CMIP6 can be attributed to more moisture transported into SC from the southern boundary and dynamic processes of the atmosphere except in BCC‐CSM, where the increased evaporation dominates. Additionally, increased heavy precipitation events (>20 mm·day−1) are produced over SC in CMIP6 models. Wet biases over West China (WC) are also reduced. with the largest reduced RMSE of 46.8% in GFDL‐CM, which are related to the reduced precipitation frequency (more than 40%) and weakened precipitation intensity. In addition, the CMIP6 models show a higher skill in simulating the frequency distribution of daily precipitation intensity. More heavy precipitation over SC and Northeast China, and fewer weak precipitation (<20 mm·day−1) over WC can be reasonably reproduced. Although the CMIP6 models have obviously improved in simulating total precipitation on wet days, wet days (WD), simple daily intensity index (SDII), and extreme precipitation amount (R95T), the bias still exists in simulating consecutive dry days (CDD). [ABSTRACT FROM AUTHOR]

The yearly tornado occurrence in China is approximately 5–10% of that in the United States, and the peak month of tornado occurrence in China is July, while that in the United States is May. However, the two countries have nearly the same land area and similar latitudinal location. This study attempts to disclose the differences in the key tornadic environments that are most possibly responsible for the large discrepancy of tornado occurrences observed between the two countries. The region with the highest tornado density in China (JS) is compared with three similarly sized regions in the United States, including two tornado‐prone regions (UC and USE1) and one region similar to JS (USE2). The results show that JS has a much lower tornado frequency than UC and USE1, mainly due to JS's much lower likelihood of multiple tornadoes occurring in a short period during its tornado season. Compared with UC and USE1, JS features relatively low mean values of the significant tornado parameter (STP) during their respective tornado seasons. The STP, incorporating several tornado‐related variables, was found to show a monotonic relationship with the total tornado count at a seasonal scale and perform well to explain monthly variations in tornado frequencies. Compared with the target regions in the United States, JS has a similar magnitude and decreasing trend of the 0–6‐km vertical wind shear from spring to summer, but a later increase in instability. Resulting from a balance between the decreasing vertical shear and the increasing thermodynamic instability, JS features a delayed monthly peak of STP and thus a delayed tornado season, which makes JS having a worse kinematic environment for tornadogenesis with far lower low‐level vertical wind shear during its tornado season than that of the United States. [ABSTRACT FROM AUTHOR]

The mechanism of the abrupt temperature change‐climate warming hiatus is not clear, and understanding the response relationships between it and the influencing factors is significant to the study the mechanism. Based on the annual average temperature (Tave), annual average minimum temperature (Tmin), and annual average maximum temperature (Tmax) of 622 meteorological stations in China from 1951 to 2018, the response relationships between the three temperatures and the influencing factors were analyzed. The results showed that In the periods before, during, and after an abrupt temperature change, For the abrupt changes in the three temperatures, the regions significantly influenced by the solar radiation (SR), AMO, multivariate El Niño southern oscillation (ENSO) index (MEI), and Pacific Decadal Oscillation (PDO) accounted for more than 80% of China, and for the abrupt changes in Tmin, the regions with significant influences covered the whole of China. The regions significantly influenced by the AO accounted for more than 60% of China, and the regions significantly influenced by the remaining factors accounted for more than 30% of China. The AO mainly influenced the abrupt temperature change in the northern regions, the AGG and CO2 mainly influenced all the regions except for Northeast China, and the influencing scopes of the atmospheric pressure (AP) were relatively small and not concentrated. In summary, when some conditions continued for a period and a tendency rate or value was reached, abrupt temperature change occurred, and the conditions were as follows: the AGG continued to increase, the PDO was in a positive phase, the AMO and SR continued to rise, the MEI changed abruptly, and the AP in each zone continued to decline/increase and experienced the subsequent trend change. In the periods before, during, and after the climate warming hiatus, few influencing factors had a significant correlation with the temperatures. The MEI and PDO influenced more than 80% of the regions that experienced the climate warming hiatus, and other factors influenced less than 60% of these regions. In the 1990s, especially after 1998, the increase in the AGG slowed, the PDO declined or was in a negative phase, the MEI and SR decreased, and the AP in each zone continued to decline/increase and experienced the subsequent trend change; when those conditions continued for a period and a tendency rate or value was reached, the climate warming hiatus occurred. The abrupt temperature change‐climate warming hiatus was the result of the joint action of multiple influencing factors. [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]

To contribute a more ambitious target of Paris Agreement, that is, limiting global warming to 1.5°C instead of 2.0°C above preindustrial levels, it is essential to quantitatively reveal regional impacts of an additional 0.5°C warming to inform climate policymaking. Based on bias‐corrected simulations of four models from the half a degree additional warming, prognosis and projected impacts (HAPPI), we examine how dry–wet condition may change in China at 1.5 and 2.0°C warming levels, focusing on the projected changes in the area of drylands. Results showed that China is projected to be dominated by a decrease Surface Wetness Index (SWI), due to a larger increase in potential evapotranspiration (PET) than precipitation, implying a drying signal, in both 1.5 and 2.0°C warming levels against a present‐day scenario. Correspondingly, an expansion of drylands is expected, the larger expansion with the higher warming level, with changes approximately 0.77 ± 2.02% in 1.5°C level, and 2.29 ± 2.69% in 2.0°C level, although there exists considerable intermodel variability. For an additional warming of 0.5°C, there is high confidence of the projected decrease of SWI and expansion of drylands, approximately 1.52 ± 0.77%. That is to say, limiting global warming to 1.5°C is suggested to robustly reduce the likelihood of emerging aridification compared to 2°C, and China might obtain considerable benefits in term of socio‐economic impacts related to the reduction of aridification. Thus, it is necessary for continued efforts to limit global warming to 1.5°C. [ABSTRACT FROM AUTHOR]

China is drastically influenced by the Asian monsoon. Based on the relationship (r = −.636, N = 62, p <.001) between tree‐ring δ18O values from nine cores of Pinus tabulaeformis Carr. from Nanwutai and the Asia monsoon‐related June–August relative humidity (RHJJA), we designed a transfer function reconstructing the RHJJA variation from 1760 to 2018 CE. Our RHJJA reconstruction captured some extreme climatic events that occurred in the past, such as the Ding‐Wu disaster (1876–1878 CE), which was the most serious drought event of northern China in the 19th century, and the severe drought event of 1925–1930 CE. The spatial correlation analysis shows that our RHJJA reconstruction has not only local but also large‐scale hydroclimate circulations. Our reconstruction compared well with other hydroclimate series from northern China, indicating the large‐scale representativeness of our reconstruction. Both the ensemble empirical mode decomposition (EEMD) and the periodicity analyses revealed that the El Niño–South Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Arctic Oscillation (AO) and the solar activity strongly affected Asian monsoon‐related RHJJA changes over Guanzhong Plain in the past. We believe this study is of great significance and provides an in‐depth understanding of climate change in the Guanzhong Plain and in northern China. [ABSTRACT FROM AUTHOR]

We conducted three pairs of 21‐year (1980–2000) experiments using the Weather Research and Forecast (WRF) model. The paired two experiment members were identical, except for the underlying land use/cover data, which were from the early 1980s and 2000 (hereafter, EXP1980 and EXP2000), respectivley. The differences in EXP1980 and EXP2000 were primarily induced by the land use/cover change (LUCC) from the early 1980s to 2000. To minimize the effects of WRF model uncertainties, the ensemble mean of three couples was applied. We found that the modifications of LUCC on summer precipitation over eastern China exhibited inter‐annual variability rather than kept fixed through 1980 to 2000. Due to the LUCC, the precipitation in eastern China may be decreased in 1981, 1984, 1986, 1988, 1989, and 1998 (hereafter, LR years) while increased in 1983, 1985, 1993, 1994, 1995, and 1999 (hereafter, MR years). Due to large discrepancy of large‐scale circulation background between MR years and LR years, there are different modifications by the LUCC on surface energy budget and therefore also on temperature, air pressure, water vapour supply and, eventually, precipitation. In the MR years, the LUCC induced increased evapotranspiration (i.e., latent heat) and decreased sensible heat over the middle and north partitions of eastern China; hence, there was a cooling effect. This cooling effect led to a decline in surface air pressure, thereby intensifying the ocean‐land pressure gradient; as a result, ocean‐to‐land movement of water vapour increased. Eventually, this led to increased precipitation. In the LR years, the LUCC induced significantly more sensible heat and slightly more latent heat over the north partition of eastern China, resulting in a warming effect. Then, the modifications to the surface air pressure and ocean‐land pressure gradient, as well as the water vapour flux, were reversed to those of the MR years, eventually leading to decreased precipitation. [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]

This study identifies a significant positive association between tropical North Atlantic (TNA) sea surface temperature (SST) during preceding spring and the frequency of intense tropical cyclones (TCs) making landfall over mainland China during autumn on interannual time scales. Observational analyses show that a warm SST anomaly in TNA during spring can induce a warm SST anomaly in the western part of the western North Pacific (WNP) in subsequent autumn, through a chain of air‐sea coupled processes such as Rossby‐wave response, wind‐evaporation‐SST feedback, and westward advection of warm surface water. The physical mechanisms are verified using a suite of coupled numerical experiments performed by the state‐of‐the‐art Community Earth System Model. The warm SST anomaly in the western part of WNP is responsible for the genesis and intensification of intense TCs in situ, and the climatologically mean southeasterly steering flow is favourable for the intense TCs to make landfall over mainland China. [ABSTRACT FROM AUTHOR]

Maize is one of China's most important crops and is profoundly sensitive to drought. Using weather and county‐level maize yield data, the drought risk for maize in China was estimated for the period 1971–2010. The results show that drought risk has increased in China over the last 40 years, and that areas experiencing moderate to high drought risk have expanded, particularly in Northeast China. The main reasons for the observed changes are increased drought hazard associated with climate change, and increased exposure of maize to drought due to an expanded production area. Drought risk over all of China increased by 55% in the 2000s compared to the 1970s. While around 93% of the increase in drought risk in the maize production regions is due to increased drought exposure, 7% is attributable to climate change. In Northeast China alone, drought risk increased by 129% from the 1970s to the 2000s, which is the sum of an 86% increase caused by greater drought exposure, associated with expansion of the production area, and a 14% increase driven by climate change. The results indicate that the drought hazard has increased by around 13%, and drought risk has increased by 110% for each 1°C rise in annual mean temperature in Northeast China over the past 40 years. Maize yield losses have increased by around 4% per 1°C increase in annual mean temperature in this region. The sensitivity of maize to drought means that climate change is likely to have significant negative impact on future maize productivity, and China's export and import of maize is likely to be affected. [ABSTRACT FROM AUTHOR]

Changes in soil temperature will exert an important influence on the management and utilization of vegetation and agricultural production, whereas the spatiotemporal variations in soil temperature under different vegetation regions across China remain largely unknown. The shallow soil temperatures (0–20 cm) during the growing season (May–September) from 1965 to 2014 across China were analysed, and the findings showed that the spatial distribution of shallow soil temperature was determined primarily by latitude in eastern China (east of 110°E), and by altitude in western China (west of 110°E) with some high (low) temperature centres. The vegetation regions with relatively low soil temperatures are mainly concentrated in high altitude and high latitude areas, which have relatively large differences in soil temperature at different depths and relatively high soil warming rates. Over the past 50 years, shallow soil temperatures increased greatly during the growing season at the site, vegetation region and nation scales, but the warming rate and its relationship with climate change varied greatly. The soil temperature variables were affected substantially by air temperature and precipitation in the subtropical forest and tropical forest regions but were affected primarily by air temperature in the other vegetation regions. This difference may be due to the spatial difference in precipitation amounts across China, which affected the soil temperature via soil moisture feedback. Further study indicated that the warming rate in shallow soil was higher in stations (vegetation regions) with less precipitation than in those with more precipitation. [ABSTRACT FROM AUTHOR]

As atmospheric moisture holding capacity is positively dependent on temperatures, a large intensification of precipitation extremes is projected under foreseeable climate warming. Flooding that is mainly attributed to extreme storms usually accounts for an ambitious target in weather‐related hazard mitigation over China. Previous works seldom focused on flooding evolution patterns under climate change at a national scale, and fewer flooding projections considered the estimation uncertainty sourced from limited samples. This study systematically projected changes in flood quantiles based on annual maximum series and seasonality and also evaluated the variations of sampling uncertainty for 151 catchments over mainland China under the emission scenario of representative concentration pathway (RCP) 8.5. In order to project future streamflow series, the bias‐corrected outputs of six global climate models (GCMs) were input into a best‐performing hydrological model, which was selected from four calibrated hydrological models based on the KGE criteria. The Pearson type‐III (P‐III) distribution and L‐moments (L‐M) method were employed to derive the flood quantiles for different return periods during historical (1961–2005) and future (2056–2100) periods, and the bootstrapping method was applied to estimate the sampling uncertainty. A regression trend method was used to track the variations of flood seasonality in the context of climate warming. Our results project earlier flood timing and larger flood quantiles for most catchments in future period than those in the historical period, despite being accompanied by substantial spatial variations. We also project that the sampling uncertainty in estimating flood quantiles is increased in a warming future. Many catchments are exposed to dramatic changes in both flood quantile and estimation uncertainty by over 50%, while only a few catchments are projected to have decreasing flood risks. These results suggest an urgent need to improve the functionality of early warning systems and increase societal resilience to warming climates over China. [ABSTRACT FROM AUTHOR]

Socioeconomic development and natural ecosystems of China are strongly affected by droughts. The socioeconomic risk of droughts in China should be quantified under climate change. This study assessed drought impacts on population and gross domestic product (GDP) under the 2.0°C‐warmer climate scenario, by implementing multiple general circulation model (GCM) simulations under the representative concentration pathway (RCP). Using the standardized precipitation evapotranspiration index (SPEI), we calculated drought frequencies in the base period (1986–2005) and 2.0°C‐warmer climate (2040–2059 in RCP4.5). Then, population and GDP exposures were evaluated by combining the drought frequency with population and GDP simulations under a shared socioeconomic pathway (SSP). Droughts were likely to occur more frequently under the 2°C‐warmer climate, especially for inland areas of northern China (i.e., Xinjiang, Xizang, Qinghai, Ningxia, Shaanxi, Gansu provinces), consisting mainly of mild and moderate droughts. Population exposure to drought was projected at 4.94 ± 0.36 × 109 person‐months, around 2% increase over the base period value. GDP exposure would increase significantly to 2.08 ± 0.15 × 1014 PPP $‐months, approximately 14‐fold over the base period. Probability analysis showed nearly 50% of the grid cells of China's entire territory undergoing more than an 11‐fold increase in GDP exposure. Our findings indicated the climate and GDP effects were primary contributors, respectively, to the changed population and GDP exposures to drought. Population and GDP exposures were distributed unequally across the country, having a large impact in the east where both population and economic activity are highly agglomerated. Our results reveal an urgent need to design and implement effective adaptation measures to overcome droughts, especially in eastern China. [ABSTRACT FROM AUTHOR]

Long‐term relative humidity change in central China has been rarely studied due to the shortness of instrumental records. In this study, we developed an annually resolved tree‐ring width chronology dating back to 1727 coefficient of efficiency (CE) with Chinese pine (Pinus tabulaeformis Carr.) samples from Mt. Shiren, central China. Relative humidity of current April–July (RHAJ) was reconstructed for the region from 1801 to 2016 CE using a linear regression model, which explains 43.9% of the variance in the instrumental records from 1960 to 2016 CE. The reconstructed RHAJ revealed that there were 33 extremely dry years, accounting for 15.28% of the past 216 years. The five driest years and the corresponding anomalies were 1835 (60.05%), 1955 (60.24%), 1929 (60.50%), 1907 (60.71%), and 1801 (60.83%). In agreement with the PDSI reconstruction for Mt. Shennong and the drought/flood series in Zhengzhou, the reconstructed RHAJ captured common droughts in 1813–1814, 1847, 1876–1880, 1900, 1923–1945, 1960–1961, and wet periods in 1863–1872, 1882–1885, 1897–1898, 1954–1956, and 1983–1984. Spatial correlation analyses showed that the reconstructed RHAJ for Mt. Shiren had significant positive correlations with vapour pressure, precipitation, and relative humidity of 850 hPa around the study area, which indicates that the reconstructed RHAJ reflects regional humidity change in central China. To sum up, these results may be provide us with a better understanding of drought variation in central China. [ABSTRACT FROM AUTHOR]

Global climate change is likely to affect reference evapotranspiration (ET0), which is important for agricultural water resources and food security. Analysis of ET0 changes is also important for understanding climate change and its impacts on hydrology. In this study, ET0 was calculated from 2020 to 2099 in nine agricultural regions and the entire country of China utilizing the Penman–Monteith method based on bias‐corrected climate data from the global climate models MIROC‐ESM‐CHEM, NorES1‐M, IPSL‐CM5A‐LR, GFDL‐ESM 2M and HadGEM2‐ES under future climate change scenarios. The spatiotemporal characteristics of seasonal and annual ET0 and climatic variables were analysed based on the Mann–Kendall test with trend‐free prewhitening (TFPW‐MK) and Sen's slope estimator. Sensitivity coefficient and multivariate regression were used to identify factors controlling the change in ET0. The results showed that seasonal and annual air temperature and precipitation both increased under all climate scenarios, and the majority of relative humidity and wind speed values showed downward trends during 2020–2099. The lowest annual ET0 values were found in the NECR and QTR, and the SCR had the maximum ET0. Both the TFPW‐MK and slope statistics showed an upward trend of seasonal ET0 during 2020–2059 under all scenarios. During 2060–2099, seasonal ET0 values showed a slight and nonsignificant downward trend under RCP 2.6, while upward trends were produced in other scenarios. Areas with high ET0 values were located in the SCR, GXR and HHHR, while low ET0 values mainly occurred in the NECR and QTR. The ET0 for the four seasons in the SCR was higher than that in the other regions, and the summer ET0 was the highest compared with that in the other seasons overall. For the attribution assessment, Tavg is the main controlling variables to ET0 trends under the interaction of multiple climatic factors though RH is the most sensitive. [ABSTRACT FROM AUTHOR]

In recent years, extreme droughts have been frequent and widespread, and understanding the spatiotemporal variations in drought events in China plays an important role in drought risk management. In this study, using monthly meteorological data at 618 stations, we computed the Standardized Precipitation Evapotranspiration Index with potential evapotranspiration based on the Penman–Monteith equation (SPEI_PM) for drought assessment. Furthermore, we analysed the trend, affected area, frequency and duration of drought in China over the period of 1960–2014 by the piecewise linear regression method (LRM) and Mann–Kendall (MK) method. The results showed that (a) the slight wetting trend reflected during 1960–2014 by the SPEI_PM (0.03/10a (p >.05). This trend was allocated to most parts of northern and southeastern China and was prone to arrive in winter. In contrast, the most significant drying trend was in the Loess Plateau and Yunnan–Kweichow Plateau. (b) The turning point (TP) year of drought trend was 1993. The SPEI_PM was increased in most parts of northern China before 1993 according to the LRM and MK method. However, it decreased after 1993, especially in the south and northwest of China; (c) Over the past 55 years, the areas affected by drought decreased at a rate of −1.23%/10a (p <.05). In detail, these areas decreased at a rate of −3.41%/10a before 1993 (p <.05) and increased at a rate of 2.71%/10a after 1993 (p >.05). (d) The drought frequency in most parts of China was between 15 and 20 during 1960–2014. Furthermore, compared with that in 1960–1977, the drought frequency was decreased in 1978–1995 and then increased in 1996–2014. These findings suggested that the long‐term trend in drought events during 1960–2014 was not significant in China. However, the severity, affected area and frequency of droughts increase after 1993. These results allowed us to understand the changes in the drought across China over the last 55 years, which is important for guiding relevant agricultural activities. [ABSTRACT FROM AUTHOR]

A large‐scale high air temperature event in China during July 2017 is examined using observational reanalysis data. Based on this case study, summer extreme hot events (EHEs) over China are classified into five types using the self‐organizing map (SOM) method. The five EHE types include those over northeast China (NEC type), northwest China (NWC type), north China (NC type), mid‐eastern China (MEC type) and south China (SC type). All types are associated with sustainable anticyclones (EHE anticyclones). Composite analysis shows that the EHE anticyclone in northern China (corresponding to the NEC, NWC and NC types) is primarily formed by downstream wave train propagation from upstream blocking, while EHE anticyclone formation in southern China (corresponding to the MEC and SC types) is driven by the joint action of downstream wave train propagation and westward movement of the western Pacific subtropical high. Moreover, the upstream blocking and downstream EHE anticyclone embedded in the wave train play important roles in maintaining the wave train. The upstream blocking acts as an energy source for downstream EHE anticyclone intensification and leads to EHE formation, with the intensified zonal wind at certain latitudes affecting the wave train propagation direction. This finding indicates that the upstream blocking with intensified zonal wind at certain latitudes may serve as an indicator for the prediction of EHE anticyclones over China. As a consequence of the persistent EHE anticyclone, the land surface is primarily warmed by enhanced shortwave radiation through reduced regional cloud cover. For the NWC and NC types, heating of the lower atmosphere takes place via the sensible heat flux; whereas, for the NEC, MEC and SC types, the main heating terms are the latent heat flux, sensible heat flux and upward longwave radiation. [ABSTRACT FROM AUTHOR]

The variation in the number of extreme low‐temperature days (NELD) during winter over China is examined. The NELD mainly has a significant decreasing trend across China. The leading NELD empirical orthogonal function (EOF) mode also shows consistent change characteristics over China, and a Mann–Kendall (MK) test of its time coefficients indicates that the NELD abruptly changed in approximately 1980. The impact of sea ice concentrations in the Arctic Ocean on the NELD is investigated. Sea ice concentration declines in the Barents Sea and the sea east of Greenland have significant negative effects on the NELD. Sea surface temperatures in these regions are negatively correlated with the NELD. The study analyses the influence mechanism by researching the composite atmosphere variable anomalies between years with below‐normal NELD and those with above‐normal NELD. [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]

Climate change and urbanization collectively influence precipitation changes. However, their separate potential contributions to precipitation changes are not well understood due to their complex interactions. Hence, a "trajectory"‐based method was used to separate their potential contributions across national, regional and local scales in China. Precipitation changes in non‐urban regions can be regarded as representing the influence of climate change and can serve as a reference for isolating precipitation changes due to urbanization in urban areas. Our results revealed that climate change was the dominant factor for precipitation trends, while urbanization exhibited a relatively weak influence, especially for extreme precipitation at the national scale. At the regional scale, the impacts of urbanization on precipitation became more significant. About 20.2 and −30.6% of positive and negative trends in total precipitation originated from urbanization. At the local scale, the potential contribution of urbanization was strongly correlated with local environmental characteristics. Although there were differences in the potential contributions of climate change and urbanization at national, regional and local scales, climate change was the dominant factor for precipitation trends and urbanization acted as a regulator to drying or wetting due to precipitation under climate change. In general, urbanization causes a greater impact on total precipitation than on precipitation extremes. Due to this, attribution approach is static and broad‐based and does not render the level of confidence that is needed for scale‐aware attribution, future studies are needed to understand the physical mechanisms of impacts of local environment changes on precipitation trends at different geographical locations over China. [ABSTRACT FROM AUTHOR]

Using 15‐year observations obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board both NASA Terra and Aqua from March 2003 to February 2018, this study investigated the spatio‐temporal variations of both macro‐ and micro‐physical cloud properties over China, including cloud fraction (CF), cloud top pressure (CTP), cloud top temperature (CTT), cloud optical thickness (COT), and effective radius (re) of both liquid water and ice clouds. Multi‐year averaged CF is around 61% over whole China region. However, CF varies with both regions and seasons. The CFs are about 6–8% larger in summer and winter (~64–65%) than in spring and autumn (~58%). By classifying China into five regimes, which are northwestern China (NW), northeastern China (NE), Tibetan Plateau (TP), northern China (N), and southern China (S), there is a clear CF regional distribution pattern. In general, there are large amount of clouds in S and southeast of TP, and small amount in NE, N, NW and most TP. Moreover, there are generally more clouds over ocean than over land, and much more clouds over S than over N. The CFs are larger (smaller) in the afternoon than in the morning over most land (ocean) regions. Furthermore, the largest CF differences between afternoon and morning occur over the TP region in China. COT demonstrates almost the same regional distribution pattern as the CF for all four seasons. Specifically, COT is higher in S than in N, which is most likely associated with the type of clouds and the availability of water vapour. Cloud re shows larger values in NW and TP than in eastern China regions in all seasons except for summer, which could be related to the heavy aerosol pollution in eastern China regions. Accompanying with the cold cloud tops over TP, a low CTP centre is often located there. Using 15‐year MODIS observations, this study statistically analyses the cloud characteristics over China along with five regions of N, S, NW, NE, and TP. It is found that multi‐year averaged CF is ~61% over China, with ~64–65% in summer and winter, and ~58% in spring and autumn; and for most seasons, CF and COT are larger in S than N, CTT and CTP are lowest over TP, cloud re is larger in NW and TP than other regions. [ABSTRACT FROM AUTHOR]

China has experienced alarming drought events during recent decades. In this study, we investigated monthly drought severity related to the eastern Pacific cooling (EPC), eastern Pacific warming (EPW), and central Pacific warming (CPW), and analysed the differential influence of canonical ENSO (c‐ENSO) and El Niño Modoki (ENSO_M) events on monthly droughts severity based on the SPEI at multiple timescales in China. The results show that (a) EPC episodes negatively affected 1‐ and 3‐month drought severity in southeast and northeast China with negative anomalies lower than −0.4 (<−0.4) during November–February the next year. EPW and CPW episodes significantly negatively affect drought severity in central north China (<−0.8) and the coastal areas of southeast China (<−0.6) during the most months, respectively. (b) La Niña negatively affected drought severity in the most parts of northeast China (<−0.2) and southeast China (<−0.4) during the most months, and La Niña Modoki caused dry conditions in the most parts of China (<−0.2) during a few months. Significant dry conditions were observed in central north China (<−0.8) in many months during El Niño, but dry conditions covered south China (<−0.4) in the most months during El Niño Modoki. (c) SST anomalies in Niño3 and ENSO_M regimes and wind anomalies might explain the spatial distribution of dry conditions across China during c‐ENSO and ENSO_M phases. The results could provide valuable information for predicting droughts associated with the c‐ENSO and ENSO Mokodi. Spatial distribution of meteorological stations in China. [ABSTRACT FROM AUTHOR]

Climate model response (M) and greenhouse gas emissions (S) uncertainties are consistently estimated as spreads of multi‐model and multi‐scenario climate change projections. There has been less agreement in estimating internal climate variability (V). In recent years, an initial condition ensemble (ICE) of a climate model has been developed to study V. ICE is simulated by running a climate model using an identical climate forcing but different initial conditions. Inter‐member differences of an ICE manifestly represent V. However, ICE has been barely used to investigate relative importance of climate change uncertainties. Accordingly, this study proposes a method of using ICEs, without assuming V as constant, for investigating the relative importance of climate change uncertainties and its temporal–spatial variation. Prior to investigating temporal–spatial variation in China, V estimated using ICE was compared to that using multi‐model individual time series at national scale. Results show that V using ICE is qualitatively similar to that using multi‐model individual time series for temperature. However, V is not constant for average and extreme precipitations. V and M dominate before 2050s especially for precipitation. S is dominant in the late 21st century especially for temperature. Mean temperature change is projected to be 30–70% greater than its uncertainty until 2050s, while uncertainty becomes 10–40% greater than the change in the late 21st century. Precipitation change uncertainty overwhelms its change by 70–150% throughout 21st century. Cold regions (e.g., northern China and Qinghai‐Tibetan Plateau) tend to have greater temperature change uncertainties. In dry regions (e.g., northwest China), all three uncertainties tend to be great for changes in average and extreme precipitations. This study emphasizes the importance of considering climate change uncertainty in impact studies, especially taking into account that V is irreducible in the future. Using ICEs without assuming V as constant is an appropriate approach to study climate change uncertainty. Using initial condition ensembles without assuming internal variability as constant is an appropriate approach to study climate change uncertainties. Changes in internal variabilities of average and extreme precipitations are significant. Temperature change is greater than its uncertainty first, then the other way round. Precipitation change is less than its uncertainty in this century. Cold regions have great temperature change uncertainties, while dry regions have great precipitation change uncertainties. [ABSTRACT FROM AUTHOR]

As the climate system is known to be warming unevenly, the open question of whether there has been a significant warming "hiatus" at global or regional scales has attracted worldwide attention. With annual mean air temperature (Tmean) setting new records subsequent to 2012, it is reasonable to reanalyse the presence of an apparent decelerated warming trend in China. We therefore examined the shifts of temperature trends in China between 1980 and 2017 using homogenized records from 798 meteorological stations via the Breaks For Additive Season and Trend (BFAST) method and Mann–Kendall and Sen's slope estimator statistical tests. The results show that Tmean at the country level exhibited monotonic increase with a positive break occurring around 1997, and the warming rate during 1980–2017 (0.36 °C/decade) was slightly higher than that during 1980–1997, which suggests that this positive break did not overwhelm the overall continuous warming trend. Spatial records show that most areas west of 108°E or south of 30°N within the country experienced a continual warming trend over the study period and that negative break that occurred around 2010 was major contributor to temporary decelerated warming trend detected in other areas, especially in Northeast China. Hence, this study highlights annual air temperature has continued to rise overall in China since 1980, while considerable regional differences have been detected within the shifts of temperature trends. Annual air temperature has continued to rise overall in China since 1980, albeit with short‐term fluctuations (a). Most areas west of 108°E or south of 30°N within the country has experienced a continual warming trend, whereas negative break that occurred around 2010 was a major contributor to the temporary decelerated warming trend detected in other areas (b). [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]

The spatiotemporal variations of seasonal precipitation extremes during 1963–2013 over China and the possible teleconnections with large‐scale ocean–atmosphere indices are investigated by using the rotated empirical orthogonal functions, cross‐correlation analysis and stepwise variable selection methods. Results show that northwest China experiences the most frequent dry events but exhibits a wetting tendency in all seasons, while in south and central China, extreme wet conditions are remarkable in seasons except for winter but a drying tendency is found in spring and autumn. Precipitation extremes in four different seasons are influenced by the different combinations of large‐scale climate indices with different time lags, and their regional responses are complex when the climate indices are at different phases, such as winter heavy precipitation (R95p) in south of Nanling Mountain generally tends to be increased by the simultaneous positive El Niño–Southern Oscillation (ENSO) and sea surface temperature anomalies (SSTs) over South China Sea and positive Arctic Oscillation (AO) with 5‐month lag, while summer R95p in the middle and lower reaches of Yangtze River Basin be decreased by the simultaneous negative SSTs over Bay of Bengal and positive AO with 9‐month lag. Besides, the dominant climate indices identified by teleconnection analysis can partly explain the temporal changes of seasonal extreme precipitation in China, which can be confirmed by very similar fluctuation in the oscillatory patterns of eight chosen couples with higher correlation coefficient, and their explanation skill is more powerful in sensitive areas highlighted in the leading spatial modes of corresponding precipitation index. Moreover, this explanation skill generally enhances as the cumulative contribution of leading four rotated modes to total variance of the target variable over whole study area increases. In addition, the precipitation indices related to precipitation amount can be better explained than those related to wet or dry spell by identified dominant climate indices. Teleconnection patterns of seasonal precipitation extremes are investigated by REOFs and stepwise regression. South of Nanling Mountain highlighted in the figure is the sensitive area, and positive NINO3_0, NINO3_1, SCS_0 and AO_5 tend to increase winter R95p there. These identified indices together explain 58% variability in RPC1 of winter R95p. Furthermore, NINO3_0 can generally catch the fluctuation in first rotated temporal signal of winter R95p. The explanation skill of identified climate indices largely depends on cumulative variance of leading modes. [ABSTRACT FROM AUTHOR]

Understanding the changes in aridity is crucial because of the substantial impacts it can have on human society. However, realistic aridity changes and their underlying climatic mechanisms demonstrate large uncertainties in China. Here we adopted the aridity index (AI) to assess the aridity changes in China, and we quantified the relative contributions of various climatic drivers (the precipitation, net radiation, wind speed, relative humidity, and air temperature) to AI changes based on the station data during 1961–2016. Our results showed that the arid/semi‐arid northwest China and Tibet Plateau experienced wetting trends, while western sub‐humid north and northeast China and western humid south China exhibited drying trends during 1961–2016. The dominant climatic drivers involved in the changing AI trends changed from arid to humid regions. In arid northwest China, increasing precipitation and decreasing wind speeds contributed the most to the wetting trends (0.024 and 0.017 in 56 years, respectively). In the semi‐arid Tibet Plateau, increasing precipitation dominated the wetting trends (0.045 in 56 years). However, in sub‐humid/humid north and northeast China and south China, decreasing wind speed and net radiation dominated the annual AI changes (0.061 and 0.092 in 56 years, respectively). In addition, AI of northwest China and the Tibet Plateau exhibited a significant abrupt change in 1987 and exhibited wetter states afterwards, which could be caused by the abrupt increase in precipitation in 1987. This study could improve current understanding of the aridity changes in China and help adapt its potential impacts. This study investigated the aridity changes and their underlying climatic mechanisms in China using station data during 1961–2016. Results showed that the "arid regions getting drier; humid regions getting wetter" is not applicable to China. The dominant climatic driver for aridity changes varies from arid to humid regions. Precipitation dominates the wetting trends in arid/semi‐arid northwest China and the Tibet Plateau, whereas wind speed and net radiation dominate aridity changes in sub‐humid/humid north and northeast China and south China. [ABSTRACT FROM AUTHOR]

In December 2015, the Paris Agreement was reached in an effort to limit global warming to below 1.5 °C. However, there is few scientific literature assessing changes in the climate with 1.5 °C of warming over China. We investigated changes in climate extremes in China that generally present high impacts on society. The results indicated that an additional warming of 0.5 °C would lead to significant increases in temperature and precipitation extremes across China. Both the temperatures on the hottest days and the frequencies of heat events across China are estimated to be lower when limiting warming to 1.5 °C compared to 2.0 °C. Events such as the record heat case in the summer of 2013 over eastern China would be approximately 28% less likely to occur if warming was limited to below 1.5 °C. Moreover, China would experience reduced precipitation extremes, although this projection is accompanied by a relatively lower confidence level than for changes in temperature extremes. High‐impact heavy rain events similar to that in the summer of 2012 over northern China (Beijing) that led to severe urban waterlogging and loss of life would be less likely if there is no more than 0.5 °C of warming. Similarly, the odds of wide‐ranging severe droughts, as witnessed in the summer of 2014 over north China, are projected to decrease clearly. The positive effects of limiting warming on changes in climate extremes are thus clear, and limiting warming should be encouraged regardless of the political and socio‐economic goals of a country. [ABSTRACT FROM AUTHOR]

The self‐calibrating Palmer drought severity index (scPDSI) was computed based on the four atmospheric reanalysis data sets combined with observational data over China during 1980–2015. The discrepancies of scPDSI among the four reanalysis data sets show the necessity of integrating multiple data sets. Drought characteristics, such as drought area, severity, duration, and frequency were examined based on multi‐data set mean scPDSI. The results reveal that significant drying trends are found in Qinghai‐Tibet Plateau, southwest, southeast and entire China. Drought area (drought severity) has increased (decreased) by about 1.16% (0.015%) per decade over entire China. Trends in drought duration, temporally averaged severity and frequency also indicate that droughts become more serious in each region during the past 36 years. The identification of drought events in each month by the clustering algorithm shows that droughts over China are more and more frequent. In addition, 65 separate drought events with the duration longer than 3 months were identified under the area threshold of 150,000 km2. Through severity‐area‐duration analysis, the 2005–2015 drought is found to be the prominent event. [ABSTRACT FROM AUTHOR]