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Drought seriously endangers the development of agro‐pastoral ecotone in arid and semi‐arid regions. However, drought evolution characteristics of semi‐arid sandy grassland and its drivers are not well understood in the complex climate change context. Thus, in this paper, the revised standardized precipitation evaporation indices on one‐month (SPEI‐1) and growing‐season (SPEI‐6) scale, flash drought and dry spells (DS) were calculated as drought indicators, and the temporal variabilities and meteorological drivers of drought in Horqin Sandy Land during the growing period (April–September) from 2007 to 2021 were studied. The results showed that SPEI‐1 and SPEI‐6 exhibited negative trends and periodic change. This drought aggravation was manifested in increased grades and numbers of drought months. Flash droughts can occur every month during the growing season. And its occurrence was not only positively correlated with all drought events in frequency but also synchronized in time. The increased number of DS showed an asymmetrical shift towards 7‐day‐and‐longer DS. SPEI sensitivity to precipitation (P) was noticeably higher than to atmospheric evapotranspiration demand (AED) at both monthly and growing season scales. SPEI sensitivity to AED was modulated by P amounts, which was higher during low P period. Apart from the amounts of P and AED, their temporal variability also strongly determined how they affect the drought severity. P was also the main driver for flash drought and long DS, but AED with larger amount and higher variability is the reason for their aggravation. Our results demonstrate the complexity of drought intensification in semi‐arid sandy grasslands and highlight the important role of AED anomalies in it. [ABSTRACT FROM AUTHOR]

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 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]

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]

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]

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]

The spatial–temporal characteristics of changes in lengths and onsets of the four seasons in China during 1961–2020 are investigated using daily temperature observations from weather stations. The relationship between changes in season lengths and climate change is also explored based on annual temperature variation, the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). The results show that lengths of spring and autumn are shorter in the plateau region but longer in the southwest compared with other regions. In the past 60 years, the onset was generally advanced for spring and summer, whereas it was delayed for autumn and winter. Lengths of summer (winter) showed an overall increase (decrease) as 10.78 days (11.74 days) from the 1960s to the 2010s, which is positively (negatively) correlated with the temperature variation. Comparatively, changes in lengths of spring and autumn are much smaller and weakly correlated with the temperature variation. However, lengths of spring and autumn significantly increased in the plateau region and parts of the southwest and decreased in the south, which is positively and negatively correlated with the temperature trend, respectively. Changes in season lengths in China are also related to the AMO and modulated by the PDO phases. At the ~55‐year scale, summer lengths and winter lengths are simultaneously affected by the AMO and the PDO. The impact of the AMO on changes in lengths of spring and autumn is mainly due to its effect on the nonlinear trend associated with long‐term climate change. [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]

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 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]

Long‐term homogenized haze data are important to understand long‐term changes in air quality. However, there is uncertainty with regard to the trend of haze days due to frequent changes in weather phenomena and visibility observation methods used in China, thereby impairing the understanding of how air quality has varied over time due to global warming. In this study, we analysed historical data on haze days collected by surface weather stations across China and identified several issues in the raw data, including the incorrect identification of floating dust as haze, zero annual records of haze days due to a lack of visibility observations, and incorrect identification of haze as smoke. To correct the affected data, inhomogeneities in the raw annual haze‐day data series since 1980 were resolved by removing floating dust observations from the haze data. Then, automated visibility measurements recorded since 2014 were calibrated according to the percentage of visibility measurements using <10 km as a reference. Finally, based on the corrected and quality‐controlled visibility, relative humidity, and weather data, haze identification was performed to reconstruct daily haze‐day data for China between 1961 and 2020. During this process, automated observation data were homogeneously standardized with former manual observation data. The mean annual haze‐day trends of each region in China showed that the national average number of haze days gradually increased at a rate of 4.27 days per decade between 1961 and 2014, after which it decreased at −1.9 days per year. This trend was verified with the variations in PM2.5 concentrations. Overall, this study presents a novel method for determining the variation and spatial distribution of haze days over the last 60 years in China. The study findings will facilitate future analyses of the spatiotemporal trends of haze days, as well as atmospheric, environmental, and climatic changes over China. [ABSTRACT FROM AUTHOR]

Water resources systems in arid regions are sensitive to climate change, which critically impacts the water cycle. In this study, we applied historical hydrometeorological data, CMIP5 data, and a large‐scale hydrological model (Community Land Model–Distributed Time‐Variant Gain Model [CLM–DTVGM]) to study the impact of climate change on the hydrological cycle (i.e., runoff, actual evapotranspiration (ETa), and terrestrial water storage [TWS]) under different scenarios at the Aksu River basin (ARB) located in the arid region of northwest China. The primary findings of this study: (a) As the determination coefficient (R2) and Nash–Sutcliffe efficiency coefficient (NSE) reached desirable levels (R2 ≥ 0.583, NSE ≥ 0.371, and root‐mean‐square error ≤ 155.727), the CLM–DTVGM achieved a better simulation of runoff in the ARB; under climate change, the runoff depth in the irrigation area became shallower and followed a decreasing trend, with a minimum depth of 0.5 mm and a significant decreasing trend of −8 mm·a−1. (b) Along with changes in the precipitation and temperature of the baseline period (i.e., 1980–2010), runoff, ETa, and TWS were predicted to change significantly in future scenarios. (c) Climate change significantly impacted the historical runoff from the Shaliguilanke and Xiehela hydrological stations, with correlation coefficients larger than 0.9; however, the runoff from the Alaer hydrological station was not affected. However, runoff, ETa, and TWS in the ARB were very closely correlated with climate change in the future scenarios, with correlation coefficients exceeding 0.9. Related research in the future would be important for guiding the sustainable development of the ARB. [ABSTRACT FROM AUTHOR]

The three provinces of northeast China (NEPs) were one of the major grain producing areas in China and has undergone significant climate warming during past decades. However, nowadays researches on climate warming mostly focused on variations of mean temperature or temperature extremes, which missed much information in the other parts of temperature. Therefore, taken NEPs as study area, variations of maximum temperature (Tmax), minimum temperature (Tmin) and diurnal temperature range (DTR) at every 10% percentile from 1961 to 2019 in NEPs were analysed at seasonal scale. The abrupt changes and decadal shifts of Tmax, Tmin and DTR at different percentiles were further highlighted. Results show that (a) for either regional average or station cases, fluctuations of daily Tmax and daily Tmin both decreased in spring and winter, but increased in autumn. In summer, fluctuations of daily Tmin decreased while those of daily Tmax increased. (b) Spatially, Tmax heated up more in south of NEPs at lower percentiles, and in northwest of NEPs at higher percentiles in spring, summer and winter. Tmin and DTR overall showed consistent spatial differences that changes in north and northwest of NEPs were with greater magnitudes. (c) In spring and winter, the higher Tmax/Tmin had earlier abrupt changes than lower Tmax/Tmin, while in summer and autumn, the abrupt changes occurred earlier for lower Tmax/Tmin. (d) In winter, overwhelming positive shifts were significant before 2000, but turned negative after 2000. In summer, Tmax heated up quickly since 1990s and Tmin since 1980s. Shifts in spring and autumn varied during different periods and generally presented alternative warming at higher and lower percentiles. The research can help better depict the warming patterns and figure out the detailed warming procedures in NEPs, which is a strong supplement for current climate change research. [ABSTRACT FROM AUTHOR]

ABSTRACT High-resolution tree-ring records covering past centuries in the western Sichuan Plateau of China are scarce, yet essential for developing a complete understanding of the regional patterns of climate change for the Tibetan plateau. This paper presents a temperature reconstruction for the Wolong Natural Reserve of the western Sichuan Plateau based on a tree-ring width chronology of a cypress species ( Sabina saltuaria) endemic to the Tibetan plateau. The annual (prior October to current September) temperature reconstruction, which spans from 1840 to 2011, was developed using a linear regression model. The reconstruction explains 54.1% of the actual temperature variance during the calibration period from 1956 to 2010. The noteworthy warming periods of the reconstruction occurred between 1864-1882 and 1927-1960, while the most pronounced cold episodes were found between 1886-1926, 1788-1822, and 1961-1996. Spectral analysis revealed the existence of multi-decadal, decadal, and annual cycles that might correspond to the related cycles of Atlantic Multidecadal Oscillation, solar activity, and ENSO-type variability, respectively. [ABSTRACT FROM AUTHOR]

Pan evaporation (Epan) analysis in the Qinghai‐Tibet Plateau (QTP) is important for improving the understanding of the climatic and environmental changes in the QTP and China. However, uneven station coverage, sparse and inconsistent observations hamper the in‐depth understanding of the spatiotemporal Epan patterns throughout the QTP over long time periods. Based on the PenPan model driven by the monthly gridded China meteorological forcing dataset, this study attempted to estimate monthly and annual grid pan evaporation (EPenPan) for the pan with a depth of 10 cm and a diameter of 20 cm at 0.1° resolution throughout the QTP and its surrounding areas during 1979–2017, then the spatiotemporal variations in EPenPan as well as the potential causative climatic variables were thoroughly examined. Results showed that the spatiotemporal patterns of EPenPan were in reasonably good agreement with the observations. The high values of mean annual EPenPan tended to distribute in the areas with water limitation or strong solar radiation like the southwest QTP. The wide decreases in annual EPenPan have reversed in the study area in around 1993, with some exceptions such as the continuous increase in the southwest QTP and monotonous decrease in the areas to the west and east of the Qaidam Basin. Comparatively, the trends in annual EPenPan in the QTP were less than the surrounding areas in the different periods, and overall accelerating annual EPenPan appeared in the both areas after 1993. With the Budyko curve, it was expected that drought severity would increase in the south of the surrounding areas in future, but the warming and wetting in the other areas would be kept. The wind speed (WS) was the primary contributor to decreasing annual EPenPan in the study area before 1993. Nevertheless, the most dominant factor for increasing EPenPan was vapour pressure deficit in the QTP and WS in the surrounding areas during 1994–2017. [ABSTRACT FROM AUTHOR]

Late spring frost stress is one of the major environmental limiting factors for apricot in the warm zone in China. Investigation of frost exposure of apricot is of particular interest for estimating the frost risk, thus representing the potential damage for apricot production. In this study, daily minimum temperature (Tmin), disaster and phenological data of apricot from 1981 to 2020 in the warm zone were integrated to explore the temperature threshold on apricot at young fruit, facilitating the assessment of apricot frost exposure (E) under the background of climate warming. The daily Tmin was firstly extracted according to the historical disaster records, to identify the per‐ and ongoing weather conditions of the low‐temperature events. The overall accuracy and Receiver Operating Characteristics curve (ROC) were combined to identify the trigger threshold of apricot frost. 1.9°C was identified as the apricot frost trigger threshold in regional assessment, with relatively higher correct rate for disaster (90.2%) and lower incorrect rate for none‐disaster (23.4%). An area under the ROC curve (AUC) of 0.88 was obtained, demonstrating a good performance of Tmin as the trigger factor in discriminating between apricot frost and no frost. High frequency of days suffered from apricot and frost exposure at young fruit were mainly found in the northwestern and middle parts of the region, with frequencies of more than 2 days and E more than 3. Regional days suffered from apricot frost and E were found to have a negative trend with slope −0.0317 and −0.789, respectively, whereas the northwest and middle part of the study region were found to have an increasing trend. The results can provide technical and theoretical support for targeted apricot frost detection and risk assessment, and measures for apricot frost prevention and mitigation can be implemented according to the threshold‐based results. [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]

Volcanic eruptions are an important driver for climate changes. However, the response of climate to volcanic eruptions sometimes varies from region to region. Although some studies reported that volcanic eruptions induced drought in Eastern China, the others argued that there is a possibility of wetter condition after volcanic eruptions in Eastern China. Until now, the response of dryness/wetness changes in this region to volcanic eruptions is controversial. Based on the dryness/wetness indexes from 100 sites in Central and Eastern China (CEC) over the past 500 years (1470–1999), the effects of volcanic eruptions occurred in the northern mid‐high latitudes (17 events) and the tropics (19 events) on dryness/wetness changes in CEC were analysed. Our results show that the significant response of dryness/wetness changes in CEC to volcanic eruptions occurred in the third or fourth year after the eruptions. Moreover, there is a significant north–south heterogeneity of the response of dryness/wetness changes in CEC to volcanic eruptions. Specifically, the response of dryness/wetness changes in northern CEC to volcanic eruptions is generally more sensitive than that in southern CEC. A persistent drying during the first to the fourth years post the volcanic events occurred in the northern mid‐high latitudes was found in north CEC, but not in south CEC. After the tropical volcanic events, there is a generally wetting in CEC, but it is stronger in north CEC than in south CEC. These results imply that, to some extent, volcanic eruptions occurred in the northern mid‐high latitudes may amplify dryness in north CEC, but may mitigate wetness in south CEC, while tropical volcanic eruptions may mitigate dryness in north CEC and amplify wetness in south CEC. [ABSTRACT FROM AUTHOR]

Technological advances have the potential to balance climate change mitigation and economic development. However, it remains unclear how much technological advances alone can mitigate climate change and the associated economic losses in the future. Through designing a suite of technological advances scenarios and using an earth system model with an integrated assessment model, we illustrate that rapid technological progress without production control might achieve the 2°C global warming target in the 2100s. Relative to a world of stagnant technology, the frequency (intensity) of extreme warm events at the end of the 21st century (2081–2100) would be reduced by ∼21% (5.5°C) via rapid technological advances, with a reduction in extreme precipitation (droughts) by ∼41% (10 times). Furthermore, fast technological advances may reduce the global economic losses linked with climate change at 2081–2100 by ∼21% and those in China related to floods (droughts) by 86% (67%). Our results highlight the potential of technological advances to fill the emission gap between the Paris Agreement and unconditional Nationally Determined Contributions and hence to efficiently mitigate global warming. [ABSTRACT FROM AUTHOR]

The global mean surface temperature does not increase monotonously over the past decades, with accelerated warming from the late 1970s to 1998 and followed by the warming slowdown during 1998–2013 (the so‐called warming hiatus). This study assessed and compared the temporal evolutions of sea surface temperature (SST) trends in the East China Seas (ECS, including Bohai, Yellow and East China Sea) and other key ocean regions. The results revealed an amplified response of ECS SST to both global warming acceleration and hiatus. This amplification was manifested as remarkably enhanced winter warming rates in the ECS of over 1.1 and 0.8°C⋅decade–1 for the 1980–1989 and 1990–1999, respectively, and as an obvious cooling trend of nearly −0.5°C⋅decade‑1 during 1998–2013. The enhanced response can be explained well by the combined effects of the Kuroshio Current (KC) and East Asian Winter Monsoon (EAWM). The weakened EAWM during the 1980s, accompanied by lower wind speeds and higher air temperatures, impeded the releases of latent and sensible heat fluxes from the ocean to the atmosphere, resulting in rapid ECS warming. During 1998–2013, the strengthened EAWM led to the enhanced cooling trend in the ECS. In addition, the volume transport of the KC east of Taiwan strengthened (weakened) during the 1990s (2000s), which might also have contributed to the enhanced warming (cooling) in the ECS. Our research suggests their sensitivity makes the ECS potentially vulnerable to the effects of global climate change, which has important implications regarding regional impact assessments. [ABSTRACT FROM AUTHOR]

The impacts and corresponding mechanisms of land use/cover change (LUCC), mainly crops and pasture, on the spatial patterns of summer precipitation over eastern China at the decadal timescale during the last millennium are investigated, using a set of land use/cover sensitivity experiments from the Community Earth System Model (CESM) Last Millennium Ensemble (LME) archive. Two leading modes of summer precipitation over eastern China at decadal scale before (with slight LUCC) and after (with drastic LUCC) 1750 AD are compared. The results show that the LUCC plays an important role in modulating the spatial patterns of summer precipitation over eastern China at decadal scale. Before 1750 AD, the first leading mode exhibits a meridional dipole pattern, while the second leading mode exhibits a meridional tripole pattern. After 1750 AD, the order of the spatial patterns switches, that is, the tripole pattern as the first leading mode and the dipole pattern as the second leading mode. During both periods, the "dry north‐wet south" dipole pattern is associated with an anomalous "A‐C" (anticyclone‐cyclone) low‐level circulation pattern and the related water vapour divergence‐convergence pattern from north to south over the eastern part of East Asia, whereas the tripole pattern corresponds to an anomalous "A‐C‐A" (anticyclone‐cyclone‐anticyclone) circulation pattern along with the corresponding tripole pattern of water vapour divergence/convergence. The regressions of sea surface temperature (SST) during boreal winter resemble obvious Pacific decadal oscillation (PDO) or Atlantic multi‐decadal oscillation (AMO) modes. In addition, the AMO index displays a decreasing trend during the last millennium under the LUCC forcing, while the PDO index does not show an obvious changing trend. The possibility of coupled PDO‐AMO anti‐phase (in‐phase) increases (decreases) after 1750 AD, leading to the increased (decreased) possibility of the tripole (dipole) pattern in eastern China. Our findings confirm the necessity of including LUCC as an important forcing factor in predictions of future climate changes, especially at the regional scale and also at longer timescales. [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]

Heat waves (HWs) are expected to increase in many parts of the world under climate warming. However, most existing studies examined the changes in HWs that are derived from air temperature only, possible different changes in humid HWs that consider the combined effects of relative humidity (RH) are much less understood. This study investigates the spatial and temporal changes in two different HW types, namely, dry and humid HWs, in China from 1961 to 2014. Analysis results show that, on average, humid HWs in China occur 20% more frequently than dry HWs. Dry HWs are more commonly located in northern China, while humid events mainly appear in monsoonal southern and eastern regions. It is also found that all measures of both dry and humid HWs across China have been increasing during the past decades, and humid HWs exhibit a more prominent intensifying trend than dry ones. In particular, the national mean frequency, participating days, magnitude, and duration of dry (humid) HWs increased by 0.061 (0.069) events decade−1, 0.32 (0.39) days decade−1, 0.53 (0.62) °C decade−1, and 0.19 (0.21) days decade−1, respectively. These trends vary in different parts of China. The largest increment of dry HW frequency appears in the arid region of northwest China, while the fastest increase of the humid HW frequency is observed in southeastern China. Given the additional stress induced by high humidity to extreme high temperature, we suggest that future climate change mitigation and adaption should consider the change and impacts of humid heat events. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ETo) is one of the most important factors influencing hydrologic and climatic quantities, and increases in ETo are often considered as a primary cause for drying under global warming scenarios. Based on bias‐corrected data from the Half a degree Additional Warming, Prognosis and Projected Impacts (HAPPI) experiment, we investigated changes in ETo and drying across the Yellow River Basin (YRB) for 1.5°C and 2°C stabilized warming, relative to the current decade (2006–2015). We used changes in the climatic water deficit (WD: defined as precipitation (P) minus (ETo) to determine drying and wetting trends. Results projected that mean annual ETo would increase significantly over the whole YRB, under 1.5°C and 2°C warming scenarios, with an increase of 4.54% (1.57–7.59% full uncertainty range) and 7.66% (4.49–10.61%), at 1.5°C and 2°C, respectively, averaged over the YRB for the multi‐model mean. It is unclear whether the YRB source region (the NE region of the Tibet Plateau) would be drier or wetter under 1.5°C and 2°C of warming, although it is likely that the N regions of the YRB, and the whole YRB except for the source region will be drier under 1.5°C and 2°C warming scenarios, respectively. With an additional 0.5°C warming, further intensification of drying is projected in the whole YRB, resulting from a more pronounced increase in ETo, and lesser increase/decrease in P. The increased ETo projected under a 0.5°C additional warming was mainly attributed to rising maximum temperatures (tasmax). These results highlight the importance of ETo, in terms of potential future YRB drying, and our study suggests that limiting future warming to 1.5°C would impact regional drying the least. [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]

Maize production on the North China Plain (NCP) is critical to food security in China; however, currently, it is affected by climate change. Understanding the spatiotemporal distribution of the climate suitability for maize on the NCP in the present and future may help sustainably use climate‐related resources to ensure food security in China. In this study, 30 general circulation models from the Coupled Model Intercomparison Project Phase 5 and a statistical downscaling model (NWAI‐WG) were used to project meteorological data in 2021–2100 under representative concentration pathway 4.5 (RCP4.5) and RCP8.5 for 23 national climatic stations on the NCP. Based on agricultural climate suitability theory and the fuzzy mathematics method, the suitability of temperature, precipitation, and solar radiation on summer maize were analysed. The results showed that temperature suitability is decreasing for 2021–2100, especially during the stages from jointing to maturity; temperature suitability is the lowest in the southwest and increases to the northeast under both scenarios. Compared to 1996–2015, the precipitation suitability in 2021–2100 increases greatly under both scenarios, especially in the central part under RCP4.5 and in the north part under RCP8.5. Solar radiation suitability shows a decreasing trend for 1996–2015, however, an increasing trend for 2021–2100 under both scenarios. At spatial scale, the solar suitability increases from southwest to northeast. The integrated climate suitability under RCP4.5 in 2021–2100 is averaged approximately 0.8 and varies slightly, indicating climate change may do small effect on maize growth, though the high values shifting from the central part in 2021–2040 to the northern part in 2081–2100; however, under RCP8.5, the integrated climate suitability shows a downward trend, indicating that climate change will make many regions less suitable for maize growth. These results could provide basic information for agriculture to adapt to climate change and ensure food security for China. [ABSTRACT FROM AUTHOR]

Long‐term changes in daily high‐temperature extremes in the summers since the late 19th century in Shanghai and their relationships with decadal or multi‐decadal climatic oscillations have been investigated via non‐stationary statistical modelling based on parametric and nonparametric frameworks. Compared to stationary modelling with the assumption of an unchanging climate, time‐varying non‐stationary models based on the generalized extreme value (GEV) result in much more reasonable estimations of the temperature extremes for the present climate in terms of their return levels and return periods. However, nonparametric modelling with cubic spline smoothing reproduced even better multi‐decadal variability for different periods. The nonparametric method also reduces the biases of estimation, especially in the heavy tail of temperature extremes in parametric GEV models. Additionally, non‐stationary models with large‐scale climate indices indicate clear influences of the large‐scale climate indices, especially the last winter's strong signals from the tropical Pacific Ocean and Indian Ocean. The significant influences of multi‐decadal variabilities from the northern Atlantic in the parametric GEV model are probably also explained by spline terms in the nonparametric method. Further application to other areas in China indicates that the developed nonparametric model can fit their extremes correctly but notable biases also remain in the estimation of distributions and heavy tails. [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]

The selection of general circulation models (GCMs) with high capability to represent the past and likely future climate for a specific geographical location is a crucial step to assess impacts of climate change on different sectors. This study included pool of 105 and 78 GCMs for representative concentration pathways (RCPs) 4.5 and 8.5, respectively, from Coupled Model Intercomparison Project—Phase 5, applied an advanced envelope‐based selection approach to select representative GCMs for the Koshi river basin in China and Nepal at short‐term (2016–2045), mid‐century (2036–2065) and end‐of‐century (2071–2100) periods, and developed range of possible future precipitation and temperature scenarios with high resolution downscaled data (10 × 10 km2), which is the novelty contribution of the study. Considering RCP4.5, average annual precipitation is expected to increase by 0–16%, 4–23% and 4–24% in the short‐term, mid‐century and end‐of‐century periods, respectively. Using RCP8.5, equivalent predictions are 6–20%, 6–36% and 13–49% in the short‐term, mid‐century and end‐of‐century periods, respectively. Average annual temperature is expected to increase, but with higher increases during winter than in the monsoon period. Considering RCP4.5, average annual temperature is expected to increase by 1–1.4°C, 1.3–1.9°C and 1.6–2.8°C in the short‐term, mid‐century and end‐of‐century periods, respectively. Similarly, using RCP8.5, equivalent predictions are 1–1.6°C, 1.8–2.9°C and 3.1–5.6°C in the short‐term, mid‐century and end‐of‐century periods, respectively. The ensemble mean of absolute change in average precipitation and temperature projects that High Himalaya and Tibet regions are more sensitive to climate change considering precipitation and temperature, respectively. The results also suggest that GCMs selection for a catchment varies with climate scenarios and specific future time periods. [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]

The spatiotemporal pattern of precipitation is significantly changing with global climate change. Snowfall is a solid phase of precipitation and an important water resource. With two gridded data sets of APHRO (Asia Precipitation‐Highly‐Resolved Observational Data Integration Towards Evaluation of Water Resources) and CN05.1, this study analyses the changes in the spatiotemporal pattern of snowfall in a snow‐dominant region of China from 1961 to 2015. The results indicate the significant increasing trend of winter snowfall in horizontal and altitude dimension in snow‐dominant regions, but the winter snowing season length shortened. For the frequency of snowfall intensity level, light, and heavy snowfall and snowstorms increased, but moderate snowfall showed no change. However, the intensity of extreme snowfall in once‐in‐a‐century was decreasing in all of the snow‐dominant regions. In the altitude dimension, the increasing trend in snow‐dominant conditions was not uniform, which may be related to change in air temperature and water vapour through the vertical atmospheric levels. The upwards trend in snowfall may be caused by the increase of atmospheric water content rather than the change of snowy weather conditions. In addition, the change values of climate indices can also contribute to snowfall increasing in snow‐dominant regions. [ABSTRACT FROM AUTHOR]

Intense anthropogenic climate changes are expected to increase atmospheric aridity in the 21st century. The aridity index (AI), defined as the ratio of annual precipitation (Pre) to atmospheric evaporation (potential evapotranspiration [PET]), represents an efficient indicator of climatic changes. However, the variations and underlying drivers of AI values have not been comprehensively compared in different climatic regions. Using the AI calculated on the basis of bias‐corrected precipitation and optimized PET over the period of 1999–2017 and two climate model projections for the coming century, we investigated the response of the AI to climate change and quantified the contributions of climatic factors to AI variations in eight climatic regions in China, that is, the northwest (NW), north‐centre (NC), northeast (NE), North China Plain (NCP), east (E), southeast (SE), southwest (SW) and Tibet Plateau (TP). The results indicated that the AI values in seven of the eight climate regions exhibited negative trends from 1999 to 2017, with mean values ranging from −0.0008 in SW to −0.0414 in NC, while the AI values in the TP region showed a significant positive trend, with a value of 0.0124. Pre was the dominant factor for the variations in AI values in all climate regions, with contribution rates from 65 to 308%, followed by decreasing solar radiation in the NW, NC, E, SE and SW regions; deceasing wind speed in NE and NCP; and deceasing actual vapour pressure in the TP. The effect of increasing temperature on the AI trend was offset by other climate factors. By the end of the 21st century, under the Representative Concentration Pathway 8.5 emission scenario, the AI will significantly increase in five of the eight regions to values approximately 16.5% higher than those during 1999–2017, and this increase in the AI will be dominated by increasing PET. Overall, the shift in the dominant AI factor from Pre in recent years to PET in the future indicates that more attention should be given to the response of the AI to global warming. Furthermore, regional differences in climate change and AI values during 2018–2,100 will inevitably influence water availability and urgently require the development of adaptation strategies for different climatic regions. [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]

This study examines potential benefits of performance‐based multi‐model ensembles (MMEs) in projecting the impacts of climate change on extreme precipitation indices over East Asia (EA) using the data from 19 GCMs in the coupled model intercomparison project 5 (CMIP5). The Taylor skill score is adopted as the measure of the model skills in simulating the spatial and interannual variability of the selected extreme precipitation indices over four EA regions. The overall rank based on the total skill score (TSC) is used to construct two skill‐based MMEs, MME of high‐skill, MMH (MME of low‐skill, MML) that include the top (bottom) seven models, in addition to the simple ensemble of all 19 GCMs (ENS). Inter‐GCM consistency is measured using the signal‐to‐noise ratio (SNR). In the present‐day period, MMH yields higher skill scores than MML and ENS for almost all extreme precipitation indices as well as regions. Regional variations in biases, inter‐model consistency, and TSC are large. The inter‐model consistency is highest for Northern China and Manchuria and is lowest for Southern China. The most notable differences in the key properties of climate change signals from the three MMEs among the three ensembles are that the climate change signals from MMH and ENS exceed the 90% significance level in much larger areas than those from MML. However, the differences in the climate change signals between MMH and MML are generally below the 90% significance level. The SNR of the projected climate change signals shows that MMH yields more consistent climate change signals than ENS/MML. Both the SNR differences and the area in which statistical significance exceed the 90% level suggest that constructing climate change signals from a group of higher‐skill models may yield more reliable projections than constructing MMEs from the entire models or a group of lower‐skilled models. The domains used in the study (SOUTH: 110°–140°E, 20°–30°N, MIDDLE: 110°–140°E, 30°–40°N), NORTH: 110°–140°E, 40°–50°N, EA: 110°–140°E, 20°–50°N) [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]

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]

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 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]

ABSTRACT Daily precipitation data from 34 weather stations in Northeast China from 1960 to 2008 are used to examine trends in the occurrence of dry days and prolonged dry episodes. Trends in the mean length and frequency of prolonged dry episodes, as well as the number of dry days within prolonged dry episodes ( DDPDE), are computed regionally and for individual stations at the threshold levels of 1 and 2 mm day−1. Regionally, the number of dry days is increasing in the summer half-year and decreasing in the winter half-year. DDPDE is significantly increasing in the summer half-year; the increased frequency of dry spells has the greatest effect. The mean length of prolonged dry episodes in the winter half-year has decreased significantly. Our results indicate that neither the frequency nor the mean length of prolonged dry episodes, alone, can adequately describe the short-term dry conditions of an area. Multiple characteristics of dry spells, including frequency, length, and the number of DDPDE should be considered. DDPDE is a function of both the frequency and length of dry episodes, but may be more influenced by one or the other characteristics of dry spells, depending on the season or region. [ABSTRACT FROM AUTHOR]