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Regional precipitation patterns may change in a warmer climate, thereby increasing flood and drought risks. In this paper, annual, annual maximum, intense, heavy, moderate, light, and trace precipitation are employed as indicators to assess changes in precipitation patterns under two scenarios in which the global mean temperature increases by 1.5 °C and 2.0 °C relative to pre-industrial levels using the regional climate model COSMO-CLM (CCLM). The results show that annual precipitation in China will be approximately 2.5% higher under 1.5 °C warming relative to the present-day baseline (1980–2009), although it will decrease by approximately 4.0% under an additional 0.5 °C increase in global mean temperature. This trend is spatially consistent for regions with annual precipitation of 400–800 mm, which has experienced a drying trend during the past half century; thus, limiting global warming to 1.5 °C may mitigate these drying conditions. The annual maximum precipitation continues to increase from present day levels to the 2.0 °C warming scenario. Relative to the baseline period, the frequency of trace and light precipitation days exhibits a negative trend, while that of moderate, heavy, and intense precipitation days has a positive trend under the 1.5 °C warming scenario. For the 2.0 °C warming world, the frequency of days is projected to decrease for all precipitation categories, although the intensity of intense precipitation increases. Spatially, a decrease in the number of precipitation days is expected to continue in central and northern China, where a drying trend has persisted over the past half century. Southeastern China, which already suffers greatly from flooding, is expected to face more heavy and intense precipitation with an additional 0.5 °C increase in global mean temperature. Meanwhile, the intensity of intense precipitation is expected to increase in northern China, and the contribution of light and moderate precipitation to the annual precipitation is expected to decrease in southeastern China. Therefore, flood risk in northern China and drought risk in southern China should draw more attention for a global air temperature increase from 1.5 °C to 2.0 °C. [ABSTRACT FROM AUTHOR]

In recent years, climate extreme events have caused increasing direct economic and social losses in the arid region of northwestern China. Based on daily temperature and precipitation data from 1960 to 2010, this paper discussed the linear trend and abrupt changes of climate indices. The general evolution was obtained by the empirical orthogonal function (EOF), the Mann-Kendall test, and the distribution-free cumulative sum chart (CUSUM) test. The results are as follows: (1) climate showed a warming trend at annual and seasonal scale, with all temperature indices exhibiting statistically significant changes. The warm indices have increased, with 1.37%days/decade of warm days (TX90p), 0.17 °C/decade of warmest days (TXx) and 1.97 days/decade of warm spell duration indicator (WSDI), respectively. The cold indices have decreased, with − 1.89%days/decade, 0.65 °C/decade and − 0.66 days/decade for cold nights (TN10p), coldest nights (TNn) and cold spell duration indicator (CSDI), respectively. The precipitation indices have also increased significantly, coupled with the changes of magnitude (max 1-day precipitation amount (RX1day)), frequency (rain day (R0.1)), and duration (consecutive dry days (CDD)). (2) Abrupt changes of the annual regional precipitation indices and the minimum temperature indices were observed around 1986, and that of the maximum temperature indices were observed in 1996. (3) The EOF1 indicated the overall coherent distribution for the whole study area, and its principal component (PC1) was also observed, showing a significant linear trend with an abrupt change, which were in accordance with the regional observation results. EOF2 and EOF3 show contrasts between the southern and northern study areas, and between the eastern and western study areas, respectively, whereas no significant tendency was observed for their PCs. Hence, the climate indices have changed significantly, with linear trends and abrupt changes noted for all climate indices, which will have serious impacts on water resources and ecological environment in the arid region of China. [ABSTRACT FROM AUTHOR]

Understanding future climate change is crucial for securing and managing water supplies necessary for agricultural activities in China, particularly in rainfed agriculture regions. This paper evaluates the projected climate change for nine major agricultural zones in China, using ensembles of regional climate models (RCMs) simulated under the Coordinated Regional Downscaling Experiment-East Asia second phase (CORDEX-EA-II) framework. The simulations were conducted for two climate scenarios (RCP2.6 and RCP8.5) at a 25 km grid spacing, with three RCMs (RegCM4, REMO, and WRF) driven by multiple CMIP5 global climate models (GCMs). The study compares the RCM simulations to the driving CMIP5 and the recent CMIP6 ensembles, focusing on surface temperature, precipitation, and surface relative humidity for the present day (1981–2010), mid-future (2036–2065), and far future (2070–2099) periods. The model evaluations indicate that the GCM and RCM simulations are consistent with observations, with RCMs showing better performance than the driving GCMs. The results show that both GCMs and RCMs project increased temperature and precipitation in most agricultural zones of China in the future, with the CMIP6 ensembles projecting the largest temperature increase and the CORDEX-EA-II ensemble showing the finest spatial details. Relative humidity is projected to decrease over major rice-producing areas of South China in the CORDEX-EA-II, CMIP5, and CMIP6 ensembles. This study provides valuable information to support climate change adaptation and mitigation efforts in China, particularly in the agricultural sectors. • CORDEX-EA-II simulations demonstrate better model performance over China. • Temperature and precipitation are projected to increase in the future. • Relative humidity is projected to decrease over South China. [ABSTRACT FROM AUTHOR]

In this paper, the HYSPLIT model, driven with reanalysis meteorological data from 1978 to 2013, was used to understand the potential transport characteristics of dust and salt dust emanating from the playa of Ebinur Lake in arid northwest China. Daily air parcel trajectories were computed forward for 8 days from an origin centered over Ebinur Lake at 100 m above ground level. Air parcel trajectory density plots were mapped for seven levels: 0–100 m agl., 100–500 m agl., 500–1000 m agl., 1000–1500 m agl., 1500–2000 m agl., 2000–3000 m agl., and 3000–5000 m agl. These show that potential dust transport pathways have clear seasonal differentiation. The potential transport distance of dust and salt dust is greatest in spring and summer. In autumn and winter, the potential transport of the high-density air trajectory is below 1000 m traveling a shorter distance. Potential dust transport pathways showed notifying directivity in different seasons and heights. Southeast in spring and summer, and north to northeast in autumn and winter are the two main potential transport channels of dust and salt dust. Accordingly, dust and salt dust from the playa of Ebinur Lake may influence the atmospheric processes and biogeochemical cycles of a vast region. The main area of influence of dust and salt dust is close to the source area, and will significantly accelerate the melting of snow and ice in the Tianshan Mountains. This highlights the urgent need to combine remote sensing, isotope and other methods to further research the transport characteristics of dust and salt dust from the playa of the Ebinur Lake. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the variability of daily temperature in the Yangtze River Delta (YRD) for the period 1958–2007 was investigated by selecting three typical temperature variables (daily minimum, mean and maximum temperatures) and the diurnal temperature range (DTR). Three variability patterns of daily mean temperature and two variability patterns of daily minimum and maximum temperatures were first classed, and then statistical properties of three temperature variables in 1958–1985 and 1986–2007 were analyzed. After that, temporal trends of three temperature variables and DTR were detected. Finally, the impacts of urbanization on the variability of daily temperature were investigated. Results indicate that: (1) daily mean temperature shows more complex variability than daily minimum and maximum temperatures; (2) in 1986–2007 three temperature variables have bigger mean values but smaller C v (coefficient of variance) values, and are more close to normal probability distribution; (3) three temperature variables show positive trends in 1986–2007, and the increase of daily mean temperature is more due to the increase of daily minimum temperature in the northern YRD but due to daily maximum temperature in the mid and southern YRD; (4) in the mid and southern YRD, daily maximum temperature has bigger increasing magnitude than daily minimum temperature in 1986–2007, causing positive trend of DTR; and (5) rapid urbanization causes normal distribution of three temperature variables, and notably increasing magnitude of daily temperature and DTR in 1986–2007 at the lower reaches of the Yangtze River and the Hangzhou Bay. [Copyright &y& Elsevier]

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]

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

The objective of this paper is to investigate the projected regional responses of univariate and bivariate behaviors of extreme precipitation to climate change over the upper-middle Huaihe River Basin. Based on twelve GCM outputs under historical, RCP4.5 and the observations at 32 rainfall stations, the equidistant cumulative distribution function matching method (EDCDFm) was utilized to bias correct daily precipitation during the historical (1961–2005) and future (2021–2080) periods. Four precipitation indices combinations were introduced based on eight precipitation indices to characterize the regional-scale changes of precipitation events, which designate the duration, intensity and amount of heavy and weak precipitation in a year. Their dependence structures were captured by Copulas. Kendall return period (KRP) were applied to discuss hazard scenarios and we quantified the spatial variability of KRPs under different marginal values. The results indicated that projected precipitation characteristics including the average intensity, the amount of annual precipitation, the intensity and amount of extreme precipitation together with annual extremes displayed increasing trends, while the changes of consecutive wet and dry days did not present pronounced trends. Decreased KRPs in the vast majority of the territory manifested that the frequency of simultaneous floods and droughts in a year as well as that of extreme heavy precipitation events would augment. Obvious spatial heterogeneity of the changes of KRP was partly attributed to the topography difference, especially the coastal areas along the main stream of the Huaihe River. Consequently, there will be a higher risk of water resources-related issues in this region for upcoming decades. • Significant decreases will occur in the intensity and amount of heavy precipitation for upcoming decades. • Change rates of precipitation indices combinations illustrate obvious spatial heterogeneity. • The frequency of simultaneous floods and droughts in a year and that of extreme heavy precipitation events will augment. [ABSTRACT FROM AUTHOR]

Trend detection in hydro-climatological time series is a prime task under the context of climate changes. Rainfall is a key component of the water cycle and its variability can profoundly influence agriculture, ecosystems and water resource management. In this paper, an innovative trend analysis (ITA) method with a significant test is used for rainfall trend detection at 14 stations in the Yangtze River Delta (YRD) during 1961–2016. The trends are separately evaluated for low (<10th percentile), medium (10th–90th percentile) and high (>90th percentile) rainfall at the annual and seasonal scales. The slope and significance of the rainfall trends derived from the ITA method are compared with those from the classical trend analysis methods Theil-Sen approach and Mann-Kendall test, respectively. The ITA shows significant increasing trends at the 99% confidence level in annual rainfall at all stations. While the same significant increasing trends are identified for summer and winter, decreasing trends dominate in spring and autumn. Contrasting trends are found for extreme rainfall with strong increasing trends in high rainfall in summer and winter and decreasing trends in low rainfall in spring and autumn. The results of the ITA confirmed by the classical trend analysis methods call for more attention to the risk management of flood in extreme seasons and drought in transitional seasons across the YRD region. • Trends analysis of rainfall across the Yangtze River Delta is performed by the innovative trend analysis (ITA) method. • Separate trends in low, medium and high rainfall are quantitatively calculated based on the ITA method. • Some advantages of the ITA method to classical trend methods (Mann-Kendall test and Theil-Sen approach) are presented. • High rainfall in summer showed significant increase while low rainfall in spring and autumn exhibited decrease. [ABSTRACT FROM AUTHOR]