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Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Changes in patterns of meteorological parameters, like precipitations, temperature, wind, etc., are causing significant increases in various extreme events. And these extreme events, i.e., floods, heatwaves, hurricanes, droughts, etc., lead to a shortage of water resources, crop failures, wildfires, and economic losses. However, Global Circulation Models (GCMs) are considered the most important tools for quantifying climate change. Therefore, we selected 20 different GCMs of precipitation in our research, as the frequency of extreme events, like drought and flood, is highly related to changes in precipitation patterns. However, this research introduced a new weighting scheme — MCFSAWS-Ensemble: Monte Carlo Feature Selection Adaptive Weighting Scheme to Ensemble multiple GCMs, whereas, Monte Carlo Feature Selection (MCFS) is one of the most popular algorithms for discovering important variables. However, the proposed weighting scheme (MCFSAWS-Ensemble) is mainly based on two sources. Initially, it evaluates the prior performance of each GCM model to define their relative importance using MCFS. Then, it computes value by value difference between the observed and simulated model. In addition, the application of this paper is based on the monthly time series data of precipitation in the Tibet Plateau region of China. In addition, we used twenty GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to analyze the implications of the MCFSAWS-Ensemble. Further, we compared the performance of the MCFSAWS-Ensemble scheme with Simple Model Averaging (SMA) through Mean Average Error (MAE) and correlation statistics. The results of this research indicate that the proposed weighting scheme (MCFSAWS-Ensemble) is more accurate than the SMA approach. Consequently, we recommend the use of advanced machine learning algorithms such as MCFS for making accurate multi-model ensembles. [ABSTRACT FROM AUTHOR]

In recent years, the frequent occurrence of extreme climate disasters has seriously affected agriculture in Northeast China. Based on precipitation data derived from 83 geographical stations in the study area for 60 years (1960–2019), we chose the reliable statistical methods of the Mann–Kendall test, Sen's slope, and the Standardized Precipitation Index, and regarded drought and flood as a whole in this paper, to identify the temporal and spatial variation characteristics of precipitation and extreme climate events in Northeast China. The results show that an increasing trend of disasters was detected at the 95% confidence level (Z = 2.3). According to the timescale analysis, abrupt climate changes started in 2006. Temporal and spatial distribution of extreme climate disasters, mainly drought and flood disasters, showed a significant upward trend from 2006 to 2019. According to the spatial analysis, the precipitation in Northeast China decreased from south to north and fluctuated less from east to west. Moreover, stations with extreme climate trends (trend of climatic anomaly with confidence level > 90%) followed the same spatial pattern as those with a high frequency of extreme climate disasters (more than 17.87 times/decade). The severity and frequency of extreme climate have increasingly threatened Northeast China in the past decade. In particular, the Northeast Plain experienced the most severe and extreme climate events that seriously threatened the study area in 2007, 2009, 2010, and 2019. Our results highlight the urgent need for the development of monitoring and early warning of droughts and flood disasters to reduce economic losses. [ABSTRACT FROM AUTHOR]

Numerous circulation indices have been applied in practical climate services focused on regional precipitation. It is beneficial to identify the most influential or decisive indices, but this is difficult with conventional correlation analyses because of the underlying nonlinear mechanisms for precipitation. This paper demonstrates a set of the most influential indices for July–August precipitation in North China, based on the recursive random forest (RRF) method. These decisive circulation indices include the Polar–Eurasia teleconnection, North African subtropical high ridge position, India–Burma trough, Antarctic Oscillation, Northern Hemisphere polar vortex central latitude, North Atlantic Oscillation, and western Pacific subtropical high northern boundary position. Some of these factors have been recognized as directly influential to the regional precipitation, for example, those of the northwestern Pacific subtropical high; however, some are not easily understood. Decision tree (DT) models using these indices were developed to facilitate composite analyses to explain the RRF results. Taking one of the most interesting DT rules as an example, when the North African subtropical high ridge position is sufficiently far south, an anomalous anticyclone occurs in the upstream and an anomalous cyclone in the downstream of North China. This is unfavorable for northward moisture transport in eastern China and hence causes less precipitation in North China than climatology. The present results are not only helpful for improving diagnostic models of regional precipitation, but also enlightening for exploring how global climate change could impact a region by modulating large-scale circulation patterns. [ABSTRACT FROM AUTHOR]

Global climate change is considered one of the greatest environmental threats in the world. It is expected to significantly change the global hydrological cycle. The two main water cycle components, potential evapotranspiration (PET) and precipitation (P), are closely related to vegetation dynamics. In this study, the partial correlation analysis method was used to analyzed the relationship between Normalized Difference Vegetation Index (NDVI) and climate factors (PET and P) based on grid cells. PET was calculated by FAO-56 Penman-Monteith method. Moreover, we also investigated the NDVI and climate factors in different vegetation cover types. The results showed that grassland, forest and cropland in China were positively correlated with PET and P. The time scales of the maximum partial correlation coefficients between NDVI and PET of grassland vegetation were mostly longer than 5-6 months. These time scales were longer than the time scales related to P. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China, whereas the spatial distribution of related time scales was the opposite. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China. However, the spatial distribution of related time scales was the opposite. The correlations between NDVI and PET, P of cropland vegetation and the time scales related to PET had clear spatial heterogeneity. The time scale of the correlation between NDVI and P for cropland in the northern China was about 2 months. P had a strong influence on the growth of various types of vegetation in the study area, and grassland vegetation was affected by P over the shortest time scale. We compare and analyze the results of this study with other related studies. These results provide a reference for exploring the dynamic changes in different vegetation types and factors impacting them. [ABSTRACT FROM AUTHOR]

Understanding runoff dynamics is vital for effective water management in climate-affected areas. This study focuses on the Dayekou basin in China's Qilian Mountains, known for their high climate variability. Using 25 years of data (1994–2018) on river runoff, precipitation, and temperature, statistical methods were applied to explore the annual variations and climate change impacts on these parameters. Results reveal a significant variability in the river runoff (132.27 to 225.03 mm), precipitation (340.19 to 433.29 mm), and average temperature (1.38 to 2.08 °C) over the period. Decadal rising rates average 17 mm for runoff, 17 mm for precipitation, and 0.25 °C for temperature, with the peak precipitation and runoff occurring in 1998–2000, 2008, and 2016. The annual runoff distribution also exhibited a unimodal pattern, peaking at 39.68 mm in July. The cumulative runoff during low periods constituted only 13.84% of the annual total, concentrated in the second half of the year, particularly during the June-October flood season. The correlation analysis underscored a strong relationship between river runoff and precipitation (correlation coefficient > 0.80), while the temperature correlation was weaker (correlation coefficient < 0.80). This 25-year analysis provides valuable insights into runoff variation, elucidating the interconnected effects of temperature and precipitation in the Dayekou basin, with substantial implications for sustainable development amid climate challenges. [ABSTRACT FROM AUTHOR]

Middle and eastern routes of the South-North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°-42°N and 110°-122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50-100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness-wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160-170- and 70-80-yr oscillations in the north, and 100-150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997-2003 in the north, and the operation and management of the project in the future will also be influenced by climate change-in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP. [ABSTRACT FROM AUTHOR]

This paper matched the data for all non-financial listed firms in China from 1990 to 2017 with weather data and used temperature and precipitation to represent climate change. Using daily temperature and daily precipitation data, we constructed temperature bins and precipitation bins. This study presents a potential first empirical analysis that applies the risk perception theory to comprehensively examine the impacts of daily temperature and daily precipitation on firms' debt financing costs. Compared to a day with a suitable temperature, a day with temperatures above 30 °C increases firms' debt financing costs by 0.2411%. Compared to a sunny day, a day with torrential rain increases firms' financing costs by 0.2697%. Approximately $122.13 million and $20.49 million in extra costs were incurred across all firms in 2017. We conducted a series of heterogeneity tests. We found that the negative impacts of climate change on debt financing costs are greater for firms that investor considers more vulnerable. Finally, we found two possible mechanisms. First, from the firm's subjective initiative perspective, firms that respond proactively during seasons of high temperatures and heavy rains can reduce the negative impacts. Second, adverse weather caused by climate change may also increase firms' debt financing costs by blocking travel. These results enrich the literature on firms' debt financing costs and contribute to the understanding of climate change's impact on firms. [Display omitted] • An extra high-temperature day increases firms' debt financing cost by 0.2411%. • An extra heavy-rain day increases firms' debt financing costs by 0.2697%. • The negative impacts will be greater for those firms that investor considers more vulnerable. • Firms' response proactively can reduce the negative impacts. • Climate change also may increase firms' debt financing costs by blocking travel. [ABSTRACT FROM AUTHOR]

Copyright of Revista Chapingo Serie Ciencias Forestales is the property of Universidad Autonoma Chapingo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Vegetation around the Daihai Lake, northern China, is very sensitive to climate changes. In this paper, pollen-based quantitative climate reconstructions using three methods [weighted averaging partial least squares method (WAPLS), modern analog technique (MAT), and pollen response surface method (PRS)] were conducted to obtain robust reconstructions of Holocene climate changes in the Daihai Lake area. The result obtained by the three methods all consistently show the annual precipitation to have been 50–100 mm lower in the early Holocene, 100–200 mm higher in the Mid-Holocene, and 50–100 mm lower again in the late Holocene than at present. The WAPLS and the MAT methods also show quasi-synchronous oscillations of the mean annual temperature (Ta); 1°–2°C lower in the Early Holocene and 1°–3°C higher in the Mid-Holocene than today. The time period from 6200 to 5100 cal yr BP was the wettest and the warmest interval, with an annual precipitation (Pa) greater than 550 mm and mean annual temperature Ta higher than 6.5°C. Several cold and dry events can be identified to occur about 8200, 6000, and 4400 cal yr BP, with an annual precipitation less than 400 mm and a mean annual temperature colder than 4.5°C, respectively. The mean temperature of the warmest month (Tw) as reconstructed using both WAPLS and MAT methods was relatively stable during the Holocene, fluctuating about ±2°C relative to the present level, but the PRS method suggests more varied Tw values in both amplitude and frequency. After 1500 cal yr BP, no consistent pattern can be observed from these three different analyses, probably because of the impact of intensified human disturbances on the natural vegetation. The fluctuations of annual precipitation (Pa) correspond to that observed in Dongge Cave in southern China. The differences might be linked to Indian monsoon and East Asia monsoon climates or caused by the different degree of dating precision, different temporal resolution, and different sensitive response of climate proxies to the climate variations. [ABSTRACT FROM AUTHOR]

Aim: Significant changes in species elevational ranges in mountains have been repeatedly documented, yet the direction, magnitude and drivers of these shifts remain controversial. Presently, there is still lacking evidence about the general nature of species elevational range shifts in eastern Eurasia in response to anthropogenic climate change. By using historical specimen records and recent field observations for 735 seed plant species across 29 China's mountains, we assessed changes in species' elevational centroids and their drivers. Location: China. Time Period: 1950–2018. Major Taxa Studied: Seed plant species. Methods: The elevation records of all sampled occurrences in each mountain during the two time periods were estimated, and the null models were developed to test the sampling bias. Ecological niche models (ENMs) were used to evaluate the relative importance of climate factors in constraining each species distribution. Generalized linear models (GLMs) to test the relationships between the centroid elevational range shifts of species and different divers. Results: We found that 54% of the species shifting upward and 46% downhill. However, species' elevational shifts significantly differed among species and mountains. Herbaceous and lowland species moved upward faster than woody and high‐elevation species. Species in temperate mountains and in mountains with taller elevational gradients moved upward, while species in subtropical mountains and in mountains with shorter elevational gradients moved downward. Precipitation changes experienced by species, species' climatic adaptations, several species' functional traits and mountain size all contributed to explain the magnitude of species' centroid elevational range shifts. Main Conclusions: Our results highlight complex biodiversity redistribution of seed plants across Chinese mountains, not necessarily conforming to the trend of species upward shifts in elevation. Changes in precipitation regimes may blur the simplistic assumption of isotherm tracking. This study fills an important geographic shortfall for our understanding of biodiversity redistribution under anthropogenic climate change. [ABSTRACT FROM AUTHOR]

Locally evaporated water vapor is an important source of precipitation in China. The spatiotemporal variation characteristics of the precipitation recycling ratio (ρ) in the Yangtze River Basin (YRB) in 1979–2020 were calculated and analyzed, and the contribution of internal and external cycling precipitation changes to the total precipitation changes in YRB under climate change was studied. The results show that the annual average ρ in YRB is approximately 10.3%, with the highest value of 21.8% in summer, lower than 10% in spring and autumn, and the lowest in winter, with only approximately 3.5%. Over the past 40 years, the annual average ρ in YRB has shown an increasing trend, with an increased rate of 0.4%/10a, especially in summer, with an increasing rate of 1.2%/10a. In terms of spatial distribution, ρ in YRB shows an obvious difference between the eastern and western regions, with that in the upstream western region being significantly higher than that in the downstream eastern region. The annual average ρ in the upstream region was 15–35% and can reach 20–50% in summer. The annual average ρ in the downstream region is below 10%. In general, precipitation formed by advection moisture accounts for the majority of the total precipitation in YRB. From 1979 to 2020, the annual precipitation in YRB showed an increasing trend. The cumulative increase is about 47.4 mm, of which 68.9% was contributed by local evaporation, and 31.1% was contributed by external moisture. [ABSTRACT FROM AUTHOR]

The change in natural runoff is highly relevant to total river flow dispatch and water resource utilization in the Yellow River Basin (YRB). Based on the annual mean temperature and total precipitation records from 70 meteorological stations from 1961–2020, the impact of climate change on the natural runoff of the YRB is investigated using the Mann-Kendall (M-K) test and Bivariate Wavelet analysis methods. Results show that the annual mean temperature over the YRB increased by 0.33 °C decade−1 during 1961–2020, with a warming rate of more than 0.40 °C decade−1 observed in its northern part. The annual total precipitation increases by 10–20 mm decade−1 in the northwest YRB, while it decreases by 20–30 mm decade−1 in the southeast YRB. The result of the M-K test shows abrupt variations in temperature and natural runoff, especially in the 1980s and 1990s. The decrease in natural runoff is closely tied to the increase (decrease) in temperature (precipitation), especially for the period 1993–2020. The bivariate wavelet coherence analysis further suggests that the decrease in the natural runoff, which has persisted over the past 60 years, is primarily driven by precipitation reduction rather than regional warming. In the stage of rapid warming, the inter-decadal influence of precipitation on natural runoff gradually changes to the influence of inter-annual fluctuation. The finding contributes to providing an important scientific basis for evaluating the optimal allocation of water resources in arid and semi-arid areas against the background of climate change. [ABSTRACT FROM AUTHOR]

Better understanding of the spatiotemporal characteristics of precipitation is essential in developing the best management practices for ecological restoration and soil erosion control on China's Loess Plateau, an arid and semiarid region with severe soil erosion. This study aimed to explore the spatiotemporal trends of precipitation using long-term precipitation data from 1957 to 2018 from the 100 national standard meteorological stations across the Loess Plateau. The nonparametric Mann–Kendall statistical test and geospatial interpolation were used to detect the trends and to analyze spatial patterns of annual and seasonal precipitation. Wavelet analysis was applied to examine periodical variation across the plateau. The results reveal that regional annual precipitation over the Loess Plateau decreased during the 62 years of the study at a mean rate of −1.05 mm/10 years (p > 0.1). The changes in annual precipitation showed a periodical fluctuation with an increasing trend from 1957 to 1969, a decreasing trend from 1970 to 1999, and an increasing trend again in the first 18 years of the 21st century. The annual precipitation decreased in all eight sub-annual periods except for winter. Spatially, a decreasing trend occurred in the southern and eastern parts of the Loess Plateau, whereas a slight increase existed in the northwest in all periods. The decrease in six stations was statistically significant (p < 0.05), and a significant increase occurred in four stations (p < 0.1). These changes can be explained by an evident southward shift of the precipitation isohyets especially for 350 mm, 450 mm and 550 mm from the 1960s to the 1990s, and a clearly northward shift after the 1990s. Findings from this study facilitate an understanding of the spatial temporal trends of precipitation so appropriate countermeasures can be developed for effective vegetation restoration and soil erosion control across the Loess Plateau. [ABSTRACT FROM AUTHOR]

With global warming, previous studies have found nonuniformity responses of precipitation because of regional differences. However, climate change affects the mean, extreme, and data structure of precipitation. Quantile regression, which can reflect every part of the trends of data, was used to detect responses of each part of precipitation in China. The V2.0 dataset of daily precipitation grid data (0.5° × 0.5°) from 1961 to 2020 in China was used as practical observation data. Daily precipitation in 2015–2100 from the China Model BCC-CSM2-MR of scenarios SSP2-4.5 and SSP5-8.5 were chosen as future climate changes with moderate and high radiative forcing, respectively. On the basis of the sign consistency of the slope coefficients with quantile regression, the results of quantiles q = 0.3, 0.5, 0.7 and 0.9 were selected to represent low, median, high and flood precipitation, respectively. Precipitation in four seasons was separately analyzed to observe seasonal characteristics in China. For the observation data, precipitation had obviously different responses in the low and high percentiles and was present in mainly spring and summer. In spring, in the middle and lower Yangtze Plains, the low and median precipitation increased, whereas the high and flood precipitation significantly decreased. In summer, Heilongjiang Province and northern Inner Mongolia showed decreasing trends in the low quantile and increasing trends in the high quantile, indicating a completely opposite trend adjustment. These regions deserve more attention. However, obviously different responses in low and high percentiles were not so evident in future climate changes. Self-consistency in model data may weaken the heteroscedastic characteristics of precipitation. [ABSTRACT FROM AUTHOR]

Water use efficiency (WUE) is a key physiological trait in studying plant carbon and water relations. However, the determinants of WUE across a large geographical scale are not always clear, limiting our capacity to predict WUE in response to future global climate change. We propose that tree WUE is influenced by calcium (Ca) availability and precipitation. In addition, although it is well-known that transpiration is the major driving force for passive nutrient uptake, the linkage between these two processes has not been well-established. Because Ca uptake is an apoplastic and passive process that purely relies on transpiration, and there is no translocation once assimilated, we further developed a theoretical model to quantify the relationship between tree Ca accumulation and WUE using soil-to-plant calcium ratio (S Ca/ B Ca) and tree WUE derived from δ13C. We tested our theoretical model and predicted relationships using three common tree species across their native habitats in Northern China, spanning 2300 km and a controlled greenhouse experiment with soil Ca concentrations manipulated. We found that tree WUE was negatively related to precipitation of the growing season (GSP) and positively with soil Ca. A multiple regression model and a path analysis suggested a higher contribution of soil Ca to WUE than GSP. As predicted by our theoretical model, we found a positive relationship between WUE and S Ca/ B Ca across their distribution ranges in all three tree species and in the controlled experiment for one selected species. This relationship suggests a tight coupling between water and Ca uptake and the potential use of S Ca/ B Ca to indicate WUE. A negative relationship between S Ca/ B Ca and GSP also suggests a possible decrease in tree Ca accumulation efficiency in a drier future in Northern China. [ABSTRACT FROM AUTHOR]

The overall goal of this study was to examine the impacts of climate change on the mean and variance of rice yields in China by using historical climate and crop data. An econometric model was established to estimate Just–Pope stochastic production functions and identify the potential impacts of climate change on the mean and variance of rice yields by type, keeping other factors constant. Based on the estimated production functions, the contribution rate of climatic factors to rice yield was then assessed by conducting the growth accounting of yields over the past 30 years. The results showed that both the mean rice yield and the yield variability were influenced by changes in the mean climate conditions and climatic variance. In the future, the impacts of climate change on rice yields will depend on local regions' present climatic conditions. The results have implications for improving the adaptation capacity of rice production. [ABSTRACT FROM AUTHOR]

Under the intensification of global warming, the characteristics of the Three Rivers source region (TRSR; i.e., headwaters of the Yellow River, the Yangtze River, and the Lancang River) in China were diagnosed in the summer season from 1979 to 2015 using observations and reanalysis data. The diagnoses indicate that summer precipitation decreased from 1979 to 2002 [by 9.01 mm day−1 (10 yr)−1; p < 0.05 by Student's t test] and increased significantly after 2002 [by 5.52 mm day−1 (10 yr)−1]. This abrupt change year (2002) was further confirmed by the cumulative anomaly method, the moving t-test method, and the Yamamoto method. By compositing the thermodynamics before and after the abrupt change year (2002), the results reveal that increased water vapor and more substantial lower-level convergence were present over the TRSR during 2003–15. This marked interdecadal variability in the TRSR summer precipitation responded to the interdecadal position and intensity of the large-scale forcing East Asian westerly jet (EAWJ), which is significantly modulated by the low-frequency variability associated with Southern Oscillation index. The connection between the interannual TRSR precipitation and the location and intensity of EAWJ was also explored. The position index of the EAWJ is negatively (with correlation coefficient R of −0.446; p < 0.05 by Student's t test) correlated with the precipitation over the TRSR, implying that southward and northward years of EAWJ are respectively associated with intensifying and weakening the TRSR summer precipitation, whereas the intensity of EAWJ is insignificantly correlated with the TRSR summer precipitation. [ABSTRACT FROM AUTHOR]

Soil moisture (SM), an important variable in water conversion between the atmosphere and terrestrial ecosystems, plays a crucial role in ecological processes and the evolution of terrestrial ecosystems. Analyzing and exploring SM's processes and influencing factors in different permafrost regions of the Qinghai-Tibet Plateau (QTP) can better serve the regional ecological security, disaster warning, water management, etc. However, the changes and future trends of SM on the QTP in recent decades are uncertain, and the main factors affecting SM are not fully understood. The study used SM observations, the Global Land Evapotranspiration Amsterdam Model (GLEAM) SM products, meteorological and vegetation data, Mann–Kendall test, Theil–Sen estimation, Ensemble Empirical Mode Decomposition (EEMD), and correlation methods to analyze and explore the characteristics and influencing factors of SM change in different permafrost regions of the QTP. The results show that: (1) At the pixel scale, GLEAM SM products can better reflect SM changes in the QTP in the warm season. The seasonal permafrost region is closer to the real SM than the permanent region, with a median correlation coefficient (R) of 0.738, median bias of 0.043 m3 m−3, and median unbiased root mean square errors (ubRMSE) of 0.031 m3 m−3. (2) The average SM in the QTP warm season increased at a rate of 0.573 × 10−3 m3 m−3 yr−1 over the recent 40 years, and the trend accelerated from 2005–2020. In 64.31% of the region, the soil was significantly wetted, mainly distributed in the permafrost region, which showed that the wetting rate in the dry region was faster than in the wet region. However, the wetting trend does not have a long-term continuity and has a pattern of "wetting–drying-wetting" on interannual and decadal levels, especially in the seasonal permafrost region. (3) More than 65% of the SM wetting trend on the QTP is caused by temperature, precipitation, and vegetation. However, there is apparent spatial heterogeneity in the different permafrost regions and vegetation cover conditions, and the three factors have a more substantial explanatory power for SM changes in the seasonal permafrost region. With the global climate change, the synergistic SM–Climate–Vegetation effect on the QTP tends to be more evident in the seasonal permafrost region. [ABSTRACT FROM AUTHOR]

A significant greening trend has been reported globally in recent decades. The greening indicates the improvement in net primary production (NPP) in vegetation. Adopting statistics-based regression models, we investigated the dynamics of NPP and its climatic drivers in main ecosystems (forest land, grass land, and unused land) over China during the period 2000–2021. The results confirmed an increasing NPP covering approximately 86% area in the main ecosystems. NPP exhibited an increase rate of 6.11 g C m−2 yr−1 in forest land, 4.77 g C m−2 yr−1 in grass land, and 1.25 g C m−2 yr−1 in unused land, respectively. Over the same period, warm–wet climate trend was observed covering approximately 90% of the main ecosystems. The warm–wet climate has had a positive effect rather than negative effect on NPP in the main ecosystems, judging by their significant positive correlation. Our results suggested that the increase in annual precipitation exerted much more important effect on the increasing NPP. The warm–wet climate trend contributes to the upward trend in NPP, even if variability in NPP might involve the influence of solar radiation, atmospheric aerosols, CO2 fertilization, nitrogen deposition, human intervention, etc. [ABSTRACT FROM AUTHOR]

Historical records truthfully document human life and environment associated with climate changes. We quantify official historical records of China dating back last 2000 years to examine the disasters due to anomalous temperatures of cold or hot, irregular precipitations of wet or dry, and floods in inland/coastal or Northern/Southern areas in four seasons that possibly linked to solar activities during 1-1825 CE (Common Era). It is found that the proportion of disaster years is positively associated with the time periods, and therefore, both the cases with high and low solar activity (HSA and LSA) leading are under study. Statistical results show that extreme cold weather occurs particularly in the Winter and Spring during LSA periods. Irregularities precipitations, including heavy rain/hail/snow and severe drought are significantly frequent during LSA periods, while floods on inland and coastal river basins tend to occur more frequently in LSA and HSA periods, respectively. The disasters owing to irregularities precipitations and floods frequently happen in Summer and Autumn, which suggests that the irregular precipitations could cause the floods. All the disasters occur significantly in the Northern China, which suggests the climate boundary of the Qinling–Huaihe Line along at about 33°N being essential. In total, all the disasters due to the anomalously cold temperatures, irregular precipitations, and floods tend to occur during the LSA periods. [ABSTRACT FROM AUTHOR]

This paper explored the projected changes in precipitation, maximum temperature (T max), and minimum temperature (T min) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) T max (T min) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, T max (T min) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections. • Projected changes were explored by 23 CMIP6 GCMs under the three SSP-RCP scenarios. • Biases in the GCMs were corrected by Empirical Quantile Mapping (EQM) method. • Multi-model ensemble (MME) was used to reduce the uncertainties. [ABSTRACT FROM AUTHOR]

Future climate may profoundly impact the functioning of terrestrial ecosystems. However, we do not know well how the functioning of different types of grassland ecosystems is associated with variation in temperature and precipitation. Here, we used long‐term field measurements to examine how climatic changes between the 1980s and the 2010s (i.e., growing season temperature, precipitation, habitat moisture index, solar radiation, and sunshine duration) have affected aboveground net primary productivity (ANPP) for all major grassland types in northern China. We found that ANPP consistently declined over the 30‐year period across all types of grassland, on average by about 6.1%. Warming, associated with increased solar radiation and, hence, soil temperature, was the primary factor driving the decrease of ANPP. We further show that ANPP was more sensitive to climate change in alpine and lowland grasslands than in temperate grasslands. Together, our findings indicate that climate warming consistently reduces plant productivity of different types of grassland ecosystems, and emphasize the importance of soil temperature in driving the decline in grassland productivity under climate change. Plain Language Summary: Future climate may profoundly impact the functioning of terrestrial ecosystems. However, we do not know well how the functioning of different types of grassland ecosystems is associated with variation in temperature and precipitation. Here, we used long‐term field measurements to examine how climatic changes between the 1980s and the 2010s (i.e., growing season temperature, precipitation, habitat moisture index, solar radiation, and sunshine duration) have affected aboveground net primary productivity (ANPP) for all major grassland types in northern China. We found that ANPP consistently declined over the 30‐year period across all types of grassland, on average by about 6.1%. Warming, associated with increased solar radiation and, hence, soil temperature, was the primary factor driving the decrease of ANPP. We further show that ANPP was more sensitive to climate change in alpine and lowland grasslands than in temperate grasslands. Together, our findings indicate that climate warming consistently reduces plant productivity of different types of grassland ecosystems, and emphasize the importance of soil temperature in driving the decline in grassland productivity under climate change. Key Points: There is a universal decrease in aboveground net primary productivity (ANPP) over 30 years across different grassland types, and the magnitude of ANPP decline differed between typesThe air temperature and soil temperature rather than precipitation were the primary drivers of ANPP decline to climate changeThe increased air temperature and soil temperature from increased total solar radiation were the main drivers for ANPP decline [ABSTRACT FROM AUTHOR]

An extensive urban agglomeration has occurred over the Yangtze River delta (YRD) region of East China as a result of rapid urbanization since the middle 1990s. In this study, a 44-yr (i.e., 1975–2018) climatology of the summertime extreme hourly precipitation (EXHP; greater than the 90th percentile) over the YRD is analyzed, using historical land-use data, surface temperature, and hourly rain gauge observations, and then the relationship between rapid urbanization and EXHP changes is examined. Results show significant EXHP contrasts in diurnal variation and storm type roughly before and after middle July. That is, tropical cyclones (TCs) account for 16.4% of the total EXHP hours, 80.5% of which occur during the late summer, whereas non-TC EXHP accounts for 94.7% and 66.2% during the early and late summer, respectively. Increasing trends in occurrence frequency and amount of the non-TC and TC-induced EXHP are detected over the urban agglomeration. Statistically significant larger increasing trends in both the EXHP and surface temperature are observed at urban stations than those at the nearby rural stations. An analysis of 113 locally developed non-TC extreme rainfall events during 2011–18 summers also suggests the contribution of the urban heat island effects to the more occurrences of EXHP, especially over a band-shaped urban region where several major cities are distributed. This study reveals a significant correlation between rapid urbanization and increased EXHP during the past two decades over the YRD region. The results have important implications for understanding the impact of urbanization on EXHP changes in a warming climate. [ABSTRACT FROM AUTHOR]

Stationarity is an assumption that permeates training and practice in water-resource engineering. However, with global change, the validity of stationarity as well as uncertainty of nonstationarity in water-resource planning are being questioned; thus, it is critical to evaluate the stationarity of climate variables, especially precipitation. Based on the continuous observation data of precipitation from 1427 stations across China, 593 efficient grid cells (1° × 1°) are constructed, and the annual precipitation stationarities from 1959 to 2018 are analyzed. The evaluated autocorrelation stationarity indicates that 92.24%–96.12% of the grid cells for an autocorrelation coefficient of lag 1–8 years of precipitation are indistinguishable from 0 [90% confidence level (CL)]. The mean stationarity indicates that 97.47% of the grid cells have a stable mean for 30 years (90% CL); beyond the confidence limits, they are mainly located in the northwest of China, where annual precipitation is less, and the average exceeding range is ±3.78 mm. The long-term observation of annual precipitation in Beijing (1819–2018) and Shanghai (1879–2018) also yields autocorrelation and mean stationarities. There is no significant difference in the annual precipitations between the past 20 years (1999–2018) and the past 60 years (1959–2018) over China. Therefore, the annual precipitation in China exhibits a weak stationary behavior that is indistinguishable from the stationary stochastic process. The average variation in precipitation is ±9.55% between 30 successive years and 16.53% between 10 successive years. Therefore, it is valuable and feasible to utilize the historical data of annual precipitation as the basis of water-resources application. [ABSTRACT FROM AUTHOR]

Daytime (0800-2000 Beijing time) and nighttime (2000-0800 Beijing time) precipitation at approximately 2100 stations in China from 1979 to 2014 was used to evaluate eight current reanalyses. Daytime, nighttime, and nighttime-daytime contrast of precipitation were examined in aspects of climatology, seasonal cycle, interannual variability, and trends. The results show that the ECMWF interim reanalysis (ERA-Interim), ERA-Interim/Land, Japanese 55-year Reanalysis (JRA-55), and NCEP Climate Forecast System Reanalysis (CFSR) can reproduce the observed spatial pattern of nighttime-daytime contrast in precipitation amount, exhibiting a positive center over the eastern Tibetan Plateau and a negative center over southeastern China. All of the reanalyses roughly reproduce seasonal variations of nighttime and daytime precipitation, but not always nighttime-daytime contrast. The reanalyses overestimate drizzle and light precipitation frequencies by greater than 31.5% and underestimate heavy precipitation frequencies by less than −30.8%. The reanalyses successfully reproduce interannual synchronizations of daytime and nighttime precipitation frequencies and amounts with an averaged correlation coefficient r of 0.66 against the observed data but overestimate their year-to-year amplitudes by approximately 64%. The trends in nighttime, daytime, and nighttime-daytime contrast of the observed precipitation amounts are mainly dominated by their frequencies ( r = 0.85). Less than moderate precipitation frequency has exhibited a significant downward trend (−2.5% decade−1 during nighttime and −1.7% decade−1 during daytime) since 1979, which is roughly captured by the reanalyses. However, only JRA-55 captures the observed trend of nighttime precipitation intensity (2.4% decade−1), while the remaining reanalyses show negative trends. Overall, JRA-55 and CFSR provide the best reproductions of the observed nighttime-daytime contrast in precipitation intensity, although they have considerable room for improvement. [ABSTRACT FROM AUTHOR]

Due to the lack of available long-term climatic records, data related to past autumn precipitation variability throughout Northwest China, especially high-frequency variation, remains limited. In this study, it was found that inter-annual changes in Qinghai spruce radial growth were significantly and negatively (p < 0.05) correlated to inter-annual differences in precipitation during the late growing season (September-October) at all sampling sites in the upper reaches of the Heihe River. Based on the growth-climate relationship, a reconstruction of the inter-annual variation in September-October precipitation from 1839 was developed. With the help of this reconstruction, we successfully captured increased inter-annual variations in September-October precipitation during 1855-1861, 1892-1902, and 1969-1986. Furthermore, we found that increased precipitation variation might be related to variation in the westerlies and instability in the relationship between the regional westerly and precipitation. Moreover, our reconstructed data significantly correlated to the drought index (i.e., October SPEI_01) and moisture-related parameters (i.e., September-October cloud fraction), suggesting that our reconstructed data could be used as an indicator of the drought condition in the Heihe River Basin during the late growing season. [ABSTRACT FROM AUTHOR]

Aim The long-term cyclical patterns of China's geopolitical shifts are of great interest to scholars and the public, but to date there has been no satisfactory explanation for the alternating occupancy patterns of the country's pastoral and agrarian polities. We fill this gap by differentiating the agroecological settings of these polities over time and quantitatively analysing the relationships between climate change and historical geopolitical variations. Location China. Methods Our dataset comprised 38 palaeohydroclimate reconstructions, the historical boundaries of China's empire and the changes in its size, and 1028 wars and 2737 battle locations over the past 2300 years. China-wide precipitation during the period was reconstructed using the 'weighted composite plus scale' method. Time-series analyses were performed to identify the strength of the associations between climate change and the geopolitical variables. Granger causality analysis and wavelet analysis were performed to verify the hypothesized causal links. Wavelet analysis was also used to identify the possible interactions (i.e. frequencies, significance, consistency and synchrony) between the signal components of the climatic and geopolitical variables at different temporal scales. Results China's mean precipitation fell into three multicentennial cycles. The geopolitical variables corresponded to those cycles in the imperial era. The spatial-temporal frequencies of the boundaries and size of the agriculturalist empires and its frontiers with pastoralist empires were regulated by the long-term (low-frequency) precipitation fluctuations at the multicentennial scale. Wars of aggression were an important explanatory factor driving the land-occupancy patterns of the two ecoempires under climate change, and caused most of the territorial shifts. Short-term (high-frequency) geopolitical changes were not associated with climate change. Main conclusions Precipitation-induced ecological change was an important factor governing the macrogeopolitical cycles in imperial China. Long-term territorial expansion favoured the polity (agriculturalist or pastoralist) that was better adapted to the changing ecological conditions in the country's heartland. [ABSTRACT FROM AUTHOR]

Projection of future climate changes and their regional impact is critical for long-term planning at the national and regional levels aimed at adaptation and mitigation. This study assesses the future changes in precipitation in China and the associated atmospheric circulation patterns using the Couple Model Intercomparison Project 5 Phase (CMIP5) simulations under the RCP4.5 and RCP8.5 scenarios. The results consistently indicate that the annual precipitation in China is projected to significantly increase at the end of the 21st century compared to the present-day levels. The number of days and the intensity of medium rain, large rain and heavy rain are obviously increased, while the number of trace rain days is projected to decrease over the entire area of China. Further analysis indicates that the significant increase of annual precipitation in Northwest China is primarily due to the increase of light rain and the increases in North and Northeast China are primarily due to the increase of medium rain. In the region of southern China, the increases of large rain and heavy rain play an important role in the increase of annual precipitation, while light rain events play a negative role. Analysis of the changes in atmospheric circulation indicates that the East Asian summer monsoon circulation is projected to be considerably stronger, and the local atmospheric stratification is projected to be more unstable, all of which provide a background benefit for the increase of precipitation and extreme rainfall events in China under global warming scenarios. [ABSTRACT FROM AUTHOR]

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature (SAT) has increased at a rate ranging from 0.03°C (10 yr) to 0.12°C (10 yr). This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period (1000-1300 AD). Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas (GHG) concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events. [ABSTRACT FROM AUTHOR]

Several provinces of China experienced an intense drought episode during 2009 and 2010. The drought was particularly severe in southwestern and northern China, where the accumulated precipitation from May 2009 to April 2010 was about 25% less than normal. The decline of accumulated precipitation over northern China was mostly noticeable during the summer season of 2009 and it was comparable to recent dry episodes. The southwestern China drought resulted from a sequence of dry months from summer 2009 to winter 2010, corresponding to the driest event since at least 1951. The suppression of rainfall in summer over both regions was in agreement with a weakened broad-scale South Asian summer monsoon, possibly influenced by an El Niño developing phase, whereas the extremely negative phases of the Arctic Oscillation during the winter of 2010 may have contributed to the persistence of the drought in southwestern China. The assessment of the associated impacts indicates that water reservoirs were severely affected with a ~20% reduction in the nationwide hydroelectrical production during the drought event. Furthermore, an analysis of the normalized difference vegetation index data reveals that large cropland sectors of northern and eastern China experienced up to 8 months of persistently stressed vegetation between May 2009 and July 2010, while southwestern China was relatively less affected. Such different regional vegetative responses are interpreted in terms of the land-cover type, agriculture management, and their dependence on seasonal precipitation and water availability for irrigation. [ABSTRACT FROM AUTHOR]

Annual and seasonal trends of precipitable water (PW) and relative humidity (RH) at 850, 700, and 500 hPa are studied using the data from 106 radiosonde stations over China during the period 1979-2005. Analysis shows evidence of an increase in PW associated with the slight warming observed in the lower to midtroposphere over China. The northern part of China shows a significant upward trend of PW in summer, and drying of the atmosphere in winter is found in most regions over China. Annual and seasonal trends in RH at the 850-, 700-, and 500-hPa levels show no significant trends in most regions in China except for Xinjiang, which shows an upward trend, and central China, where there was a downward trend in RH at 500 hPa. It is found that changes in PW are coincident with the warming of the surface and the lower to midtroposphere. The RH in the lower to midtroposphere in most regions over China has remained steady during the most recent 30 years, as might be expected given the increasing of PW and the warming above the surface. The long-term trend of precipitation over China may be linked to the trends of PW and RH at the lower level and midlevel. [ABSTRACT FROM AUTHOR]

• Global climate change is generally expected to increase net primary production, resulting in increased soil carbon (C) inputs. To gain an understanding of how such increased soil C inputs would affect C cycling in the vast grasslands of northern China, we conducted a field experiment in which the responses of plant and microbial biomass and respiration were studied. • Our experiment included the below-ground addition of particulate organic matter (POM) at rates equivalent to 0, 60, 120 and 240 g C m−2, under either natural precipitation or under enhanced precipitation during the summer period (as predicted for that region in recent simulations using general circulation models). • We observed that addition of POM had a large effect on soil microbial biomass and activity and that a major part of the added C was rapidly lost from the system. This suggests that microbial activity in the vast temperate grassland ecosystems of northern China is energy-limited. Moreover, POM addition (and the associated nutrient release) affected plant growth much more than the additional water input. • Although we performed no direct fertilization experiments, the response of plant productivity to POM addition (and associated release of nutrients) leads us to believe that plant productivity in the semiarid grassland ecosystems of northern China is primarily limited by nutrients and not by water. [ABSTRACT FROM AUTHOR]

Vegetation fluctuation is sensitive to climate change, and this response exhibits a time lag. Traditionally, scholars estimated this lag effect by considering the immediate prior lag (e.g., where vegetation in the current month is impacted by the climate in a certain prior month) or the lag accumulation (e.g., where vegetation in the current month is impacted by the last several months). The essence of these two methods is that vegetation growth is impacted by climate conditions in the prior period or several consecutive previous periods, which fails to consider the different impacts coming from each of those prior periods. Therefore, this study proposed a new approach, the weighted time-lag method, in detecting the lag effect of climate conditions coming from different prior periods. Essentially, the new method is a generalized extension of the lag-accumulation method. However, the new method detects how many prior periods need to be considered and, most importantly, the differentiated climate impact on vegetation growth in each of the determined prior periods. We tested the performance of the new method in the Loess Plateau by comparing various lag detection methods by using the linear model between the climate factors and the normalized difference vegetation index (NDVI). The case study confirmed four main findings: (1) the response of vegetation growth exhibits time lag to both precipitation and temperature; (2) there are apparent differences in the time lag effect detected by various methods, but the weighted time-lag method produced the highest determination coefficient (R2) in the linear model and provided the most specific lag pattern over the determined prior periods; (3) the vegetation growth is most sensitive to climate factors in the current month and the last month in the Loess Plateau but reflects a varied of responses to other prior months; and (4) the impact of temperature on vegetation growth is higher than that of precipitation. The new method provides a much more precise detection of the lag effect of climate change on vegetation growth and makes a smart decision about soil conservation and ecological restoration after severe climate events, such as long-lasting drought or flooding. [ABSTRACT FROM AUTHOR]

Freshwater fishes are threatened by increasing environmental changes and human disturbances. The Min River, the largest river in Southeastern China, contains unique fish fauna for the Oriental realm. Due to environmental changes brought by forty years of economic growth, fish numbers have dramatically declined. The average taxonomic distinctness in the 1970s was significantly higher than that in 2015, while no significant differences were found in the variation in taxonomic distinctness between the two periods. Due to the river network and habitat diversity, fish fauna composition showed significant spatial differences but lower variation than the decadal variation. Precipitation was determined to be the most influential factor in determining the spatial pattern of fish fauna, followed by temperature. Species introduced for aquaculture have invaded the endemic fish community after escape and should be reconsidered in the trade-offs between economic development and ecological protection. [ABSTRACT FROM AUTHOR]

Since there are many destructive effects caused by extreme climate events in the Yellow River, it is of great theoretical and practical significance to explore the variations of climatic extremes in this key basin. We used a meteorological dataset from 66 stations within the Yellow River basin (YRB) for the period 1960–2017 to calculate magnitude and frequency of precipitation/temperature extremes. We also analyzed the relationships between the main large-scale atmospheric circulation patterns (ACPs) and precipitation/temperature extremes. The trends in precipitation extremes were nonsignificant, only a few stations were characterized by significantly increasing or decreasing anomalies; this indicates the precipitation intensity may have been strengthened, and the extreme rainfall duration appears to have been reduced during 1960–2017. The trends of magnitudes for "cold" extremes were larger than those for "warm" extremes, changes of trends in frost days were higher than those for summer days, and the trends in increasing warm nights were higher than those of warm days. The influence of the El Niño–Southern Oscillation (ENSO) and Arctic Oscillation (AO) on temperature extremes outweighed the influence of the North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO) for the other extreme climate indices. The YRB might be at risk of increased extreme high temperature events, and more attention should be paid to this higher risk of extreme climatic events. [ABSTRACT FROM AUTHOR]

To avoid more severe impacts from climate change, countries worldwide pledged to implement intended nationally determined contributions (INDCs) for emission reductions (as part of the Paris Agreement). However, it remains unclear what the resulting precipitation change in terms of regional extremes would be in response to the INDC scenarios. Here, we analyzed China's extreme precipitation response of the next few decades to the updated INDC scenarios within the framework of the Paris Agreement. Our results indicate increases in the intensity and frequency of extreme precipitation (compared with the current level) in most regions in China. The maximum consecutive five-day precipitation over China is projected to increase ~16%, and the number of heavy precipitation days will increase as much as ~20% in some areas. The probability distributions of extreme precipitation events become wider, resulting in the occurrence of more record-breaking heavy precipitation in the future. We further considered the impacts of precipitation-related extremes and found that the projected population exposure to heavy precipitation events will significantly increase in almost all Chinese regions. For example, for heavy precipitation events that exceed the 20 year baseline return value, the population exposure over China increases from 5.7% (5.1–6.0%) to 15.9% (14.2–16.4%) in the INDC-pledge scenario compared with the present-day level. Limiting the warming to lower levels (e.g., 1.5 °C or 2.0 °C) would reduce the population exposure to heavy precipitation, thereby avoiding impacts associated with more intense precipitation events. These results contribute to an improved understanding of the future risk of climate extremes, which is paramount for the design of mitigation and adaptation policies in China. [ABSTRACT FROM AUTHOR]

Based on 541 Landsat images between 1988 and 2016, the normalized difference vegetation indices (NDVIs) of the wetland vegetation at Xitugou (XTG) and Wowachi (WWC) inside the Dunhuang Yangguan National Nature Reserve (YNNR) in northwest China were calculated for assessing the impacts of climate change on wetland vegetation in the YNNR. It was found that the wetland vegetation at the XTG and WWC had both shown a significant increasing trend in the past 20–30 years and the increase in both the annual mean temperature and annual peak snow depth over the Altun Mountains led to the increase of the wetland vegetation. The influence of the local precipitation on the XTG wetland vegetation was greater than on the WWC wetland vegetation, which demonstrates that in extremely arid regions, the major constraint to the wetland vegetation is the availability of water in soils, which is greatly related to the surface water detention and discharge of groundwater. At both XTG and WWC, the snowmelt from the Altun Mountains is the main contributor to the groundwater discharge, while the local precipitation plays a lesser role in influencing the wetland vegetation at the WWC than at the XTG, because the wetland vegetation grows on a relatively flat terrain at the WWC, while it grows on a stream channel at the XTG. [ABSTRACT FROM AUTHOR]