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Increasing variability of precipitation induced by climate change raises uncertainties for ecosystem services and agricultural production in the Poyang Lake Basin (PLB), China. Reanalysis precipitation datasets (RPDs) are attractive alternatives for monitoring the hydro‐climate cycles. However, their applicability in China has mainly been evaluated at the national scale, while less attention has been paid to the PLB or southeastern China. Here, we apply various metrics to evaluate the magnitude and spatial similarity of annual, monthly, different intensities and the spatial structure of precipitation from four reanalysis—the fifth global atmospheric analysis dataset of the European Center for Medium‐Range Weather Forecasts (ECMWF) (ERA5), Interim ECMWF Reanalysis (ERA‐Interim), Japanese 55‐year Reanalysis project (JRA55) and Modern‐Era Retrospective analysis for Research and Applications, Version 2 (MERRA‐2), against the rain‐gauges over the PLB during 1980–2018. The results showed that the detection capacity of ERA5 and MERRA2 shifted around 2002, whereas that of ERA‐Interim and JRA55 did not substantially change. Before 2002, ERA‐Interim had the lowest biases for the magnitude of annual, monthly and different intensities of precipitation (except for heavy rain), while ERA5 and MERRA2 had strengths in capturing spatial correlation. Notably, ERA5 and MERRA2 had region‐wide wet and dry biases, respectively, before 2002, which can be attributed mainly to the estimation of flood season precipitation (from April to June) and heavy rain. In contrast, the fractional contribution of light–moderate rain was underestimated and overestimated by ERA5 and MERRA2, respectively. However, after 2002, because of the improved reproducibility of flood season precipitation and heavy rain magnitude, the systematic biases of ERA5 and MERRA2 significantly decreased, especially for ERA5, which outperformed other RPDs on all aspects of precipitation. The conclusions of this paper suggest that the variation of applicability over time should be seriously tested before the utilization of RPDs in hydro‐climate analyses. [ABSTRACT FROM AUTHOR]

A good understanding of spatiotemporal characteristics of historical droughts is important for managing and tackling drought hazards. This paper aims to investigate spatiotemporal variations of drought in mainland China over 1961–2016 based on the standardized precipitation evapotranspiration index (SPEI) at the 1‐ and 12‐month timescales. The trend significance and magnitude of 12‐month SPEI were analysed using the modified Mann–Kendall (MMK) method and Sen's slope values. The empirical orthogonal function (EOF) and ensemble empirical mode decomposition (EEMD) were applied to analyse the spatial patterns and periods in 1‐month SPEI series. The results showed that the temporal fluctuations of SPEI were weaker as the timescale increased. The droughts in 1960s were the severest than in other decades. The sites with SPEI < −5 (denoting the extreme droughts) mainly located in the northwestern and southwestern China. An overall wetter trend was detected in most regions of China, except the belt from northeastern to middle and southwestern China. The 1‐month SPEI had shorter than 1.20‐year of mean periods for the seven sub‐regions and China, while had 0.22–2.95 years of mean periods at different sites. Residuals (decomposed from 1‐month SPEI) showed increasing trends in most of the sub‐regions except sub‐region 3. In northern and northwestern China, longer periods of SPEI were detected. The highest values of EOF1 and EOF2 illustrated the eastern and northeastern China were drought‐sensitive areas. From the correlations between 1‐month SPEI and the atmospheric circulations, the AO was the main physical factor that influenced drought occurrence in mainland China. The identified spatiotemporal characteristics of SPEI could offer references for drought prevention and management in China. [ABSTRACT FROM AUTHOR]

The roles of moisture sources and transport in intraseasonal precipitation variabilities during the preflood season over South China are complex and different. In this paper, ERA‐Interim reanalysis data that were collected four times daily from 1979 to 2017 are used to analyse the variation and influence of moisture transport in intraseasonal precipitation during the preflood season over South China. Using the Hybrid Single‐Particle Lagrangian Integrated Trajectory model, fixed atmospheric moisture sources are defined: land area source (LD source), Indian Ocean source (IO source), Pacific Ocean source (PO source), South China Sea source (SCS source), and South China source (SC source). Sea source moisture transport accounts for more than 75% of the total precipitation during the preflood season, which is the most important moisture source in South China. For April, southeasterly moisture transport, which includes PO source and SCS source moisture transports, is the major moisture transport over South China. Then, the IO source and SCS source precipitation increased significantly during May. During June, the IO source precipitation accounted for 43.75% of the total precipitation, thus dominating precipitation over South China. In addition, there is a significant difference in the interdecadal variation in the preflood season precipitation before and after the Indian summer monsoon onset. Before the Indian summer monsoon onset, the land‐sea thermal contrast decreased, which led to a significant interdecadal reduction in the IO source, PO source, and SCS source moisture transports. After the Indian summer monsoon onset, the increase in IO source moisture transport is the primary cause of the interdecadal increase in precipitation over South China. [ABSTRACT FROM AUTHOR]

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