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Moisture sources and transport processes play a critical part in hydrological cycle and determine regional precipitation. This paper utilizes the Water Accounting Model‐2layers (WAM‐2layers) and the ERA5 reanalysis data to track the sources of precipitation over the Pearl River Basin (PRB). The contribution of external moisture and the role of local recycling are investigated. The results show that during the period from 1980 to 2020, oceanic sources including the western North Pacific and Indian Oceans serve as the primary moisture sources of precipitation over the PRB. The contributions to total seasonal precipitation are respectively 62.57% in MAM, 54.79% in JJA, 43.70% in SON and 60.88% in DJF. By contrast, the contribution of local recycling is generally below 5.50%. In the dry years of 1994, 1997 and 2001, the contribution of terrestrial sources is about 19.22%; in the wet years of 1989, 2009 and 2011, the contribution is about 16.31%. The summer precipitation anomalies are mainly attributable to moisture anomalies from the Equatorial Indian Ocean in the wet years and from Southeast Asia in the dry years. Furthermore, vertically integrated moisture flux anomalies over the boundaries of the PRB are generally the result of anomalous wind rather than anomalous moisture. In the wet years, low‐pressure systems induce strong cyclonic moisture transports, increasing the PRB precipitation. In the dry years, high‐pressure anomalies over the PRB block the moisture transports from the Indian Ocean and western North Pacific. [ABSTRACT FROM AUTHOR]

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]

Understanding and exploring hydrological (H) or soil moisture (SM) drought due to meteorological (M) drought under changing climate is crucial for drought early warning. Previously, different methods were used to calculate drought propagation from one state (M to another [H or SM]). However, each method has its pros and cons and thus cannot describe appropriate propagation attributes. In this study, a time series analysis is carried out to explore the propagation process in the Yellow River Basin (YRB) and Hai River Basin (HRB) of China. Standardized Streamflow Index (SSI), Standardized SM Index (SSMI), and Standardized Precipitation Index (SPI) 1‐month time series were calculated using streamflow, satellite‐based SM, and precipitation from 1979 to 2016. The time series framework identifies the average drought propagation as 3.4–8.3 months (M–H) and 2.3–5 months (M–SM) in YRB, while 2.8–7.7 months (M–H) and 2.3–8.5 months (M–SM) in HRB. Cross‐wavelet analysis indicated that periodic characteristics of M drought are responsible for these droughts. Overall, the findings of this study may help to minimize the drought hazards posed by M droughts. [ABSTRACT FROM AUTHOR]

Many studies found that land use change (LUC) had great impacts on regional precipitation, due to thermodynamic and dynamic responses. However, the relative contributions of these two factors to changes in precipitation due to LUC are rarely investigated. This study quantifies the relative contributions of thermodynamic and dynamic to the changes of mean and extreme precipitation due to LUC based on simulations of the Weather Research and Forecasting (WRF) model. The Yangtze River Basin (YRB) is used as a case study, as it has experienced great LUC during the past decades. Four land use scenarios (two factual cases and two hypothetical reforestation scenarios) were used to test the sensitivity of precipitation changes to LUC. Changes in mean and extreme precipitation over the YRB for all seasons are attributed to thermodynamic and dynamic changes using 500‐hPa geopotential height and precipitation data derived from the simulations of WRF. The results show that the factual process of LUC results in a decrease in summer mean daily precipitation and precipitation extremes in most areas of the YRB (except for the middle reaches of the YRB), while the hypothetical reforestation contributes to an increase in summer mean and extreme precipitation, and the impacts of reforestation on increasing precipitation are limited. The thermodynamic change contributes to an increase in seasonal mean daily precipitation, extreme precipitation totals and occurrence frequency of precipitation extremes with contributions ranging from 94 to 102%, which is the main contributor of changes in precipitation due to LUC. The dynamic change only makes a small contribution to the change of precipitation. Because the contributions of thermodynamic can be offset by dynamic changes to changes in precipitation, it could result in minimal changes in precipitation and occurrences of precipitation extremes. [ABSTRACT FROM AUTHOR]

As one of the most influential oceanic and atmospheric oscillations in the Earth system, El Niño‐Southern Oscillation (ENSO) has modulated numerous geophysical processes. This is particularly true for the Yangtze River Basin (YRB), which is vulnerable to Asian Monsoon and faces serious hydrological hazards. In this study, the co‐variability between lag–lead precipitation and sea surface temperature anomalies was evaluated utilizing singular value decomposition (SVD) method. Moreover, certain teleconnections between ENSO and streamflow were identified by wavelet methods. In addition, the contribution of related atmospheric variables was revealed by composite analysis. Results indicate that there are strong associations in lag–lead seasons between the wet condition (dry condition) and September–November (December–February) mature ENSO phase. Significant common power and coherence signals between the ENSO indices and the streamflow occur in the 4–8, 8–16 and 16–32 seasonal scales. Meanwhile, the activity cycle of the ENSO indices ahead of streamflow increases from the mid‐lower reaches to the source region. In addition, the Western Pacific Subtropical High is strengthened during the mature ENSO phase. Anomalous sinking motions and divergent water vapour flux occupy the YRB, reducing the precipitation and leading to the dry condition in the source region until the following March–May. On the other hand, ascending movements and abundant water vapour flux coming from northern Pacific, equatorial western Pacific and the Bay of Bengal result in the wet condition in the mid‐lower reaches. [ABSTRACT FROM AUTHOR]