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Soil and water conservation and protection are of great importance to China, as the source of the Pearl and Xiang Rivers, and the main rare earth mining area, the ecology of Dongjiang River Basin, is very fragile. In this paper, the Chinese soil loss equation and the Geodetector method are used to analyze the spatial and temporal patterns and the impact factors of soil erosion in this area from 2016 to 2020. The results show that (1) Soil erosion intensity in the Dongjiang River Basin from 2016 to 2020 is mainly mild, with the soil erosion intensity in the Dongjiang River Basin in 2016 being the largest in five years. (2) The erosion modulus shows an increasing trend with the increase of slope. In terms of vegetation, when the vegetation cover is <30%, the soil erosion modulus is the largest, which is easy to induce soil erosion. When the vegetation cover is >60%, the soil erosion modulus is the smallest, which effectively slows down the occurrence of soil erosion. Rainfall is proportional to the soil erosion modulus and soil erosion. (3) The results of Geodetector indicate that the single factor sizes are land use > vegetation > slope > precipitation, and interaction factors all show a nonlinear enhancement. (4) The proper allocation of land use types, the prohibition of steep slopes for cultivation, and the restoration of forestry can effectively prevent and control soil erosion in the area. Core Ideas: Chinese soil loss equation enabled us to quantify soil erosion patterns.Geodetector unravels the underlying mechanisms responsible for spatial heterogeneity.The investigation highlighted the significant impact of intense rainfall events on steep slopes.Our analysis illustrates the shifting landscape of soil erosion within the Dongjiang River Basin.Our research sheds light on the key drivers behind this phenomenon. [ABSTRACT FROM AUTHOR]

A calamitous landslide happened at 22:00 on September 1, 2014 in the Yunyang area of Chongqing City, southwest China, enforcing the evacuation of 508 people and damaging 23 buildings. The landslide volume comprised 1.44 million m3 of material in the source area and 0.4 million m3 of shoveled material. The debris flow runout extended 400 m vertically and 1600 m horizontally. The Xianchi reservoir landslide event has been investigated as follows: (1) samples collected from the main body of landslide were carried out using GCTS ring shear apparatus; (2) the parameters of shear and pore water pressure have been measured; and (3) the post‐failure characteristics of landslide have been analyzed using the numerical simulation method. The excess pore‐water pressure and erosion in the motion path are considered to be the key reasons for the long‐runout motion and the scale‐up of landslides, such as that at Xianchi, were caused by the heavy rainfall. The aim of this paper is to acquired numerical parameters and the basic resistance model, which is beneficial to improve simulation accuracy for hazard assessment for similar to potentially dangerous hillslopes in China and elsewhere. [ABSTRACT FROM AUTHOR]

Currently, the opportunistic method to estimate rainfall using commercial microwave links (CMLs) has been shown as an efficient way to complement traditional instruments in terms of spatial‐temporal resolution and coverage. In this paper, we collected data from 26 CMLs in Jiangyin City, Jiangsu Province, and conducted experiments on rainfall field reconstruction and nowcasting. First, the raw CML data were processed to invert the path‐averaged rainfall intensity. Second, the algorithms of inverse distance weighting (IDW) and ordinary kriging (OK) interpolation were employed to reconstruct the rainfall field. Then a 10‐min prediction of the rainfall field was achieved using a nowcasting model based on the long short‐term memory neural network and a setup window was introduced to improve the prediction performance of the first few minutes. The reconstruction results show that the average correlation coefficient (ACC) and the average root mean square error (ARMSE) between the IDW‐based results and daily cumulative rainfall from rain gauges (RGs) are 0.89 and 8.69 mm, respectively, while the ACC and ARMSE between the OK‐based results and RG data are 0.89 and 9.13 mm, respectively. The nowcasting results show that the ACC between the prediction results with a 5‐min setup window and the IDW‐retrieved rainfall fields can reach 0.91 at the first minute and gradually decrease to 0.20 within 10 min. Furthermore, the model has better nowcasting performance for stratiform precipitation and mixed precipitation compared to convective precipitation. Plain Language Summary: Accurate and real‐time rainfall monitoring and forecasting are of great significance for disaster prevention and control, agriculture, meteorological research, and related fields. However, traditional rainfall measurement methods are insufficient for meeting the demands of comprehensive precipitation observations because of poor spatial‐temporal resolution and limited coverage. Currently, measuring rainfall using additional microwave attenuation caused by raindrops has been shown as an efficient way to complement traditional instruments. Based on commercial microwave link (CML) rainfall measurement technology, this paper carries out rainfall field reconstruction and nowcasting experiments in Jiangyin City, China. The results show the CML network enables accurate rainfall field reconstruction and nowcasting. Key Points: Based on the commercial microwave link (CML) rainfall monitoring network in Jiangyin, China, accurate rainfall inversion by CMLs is achievedThe two‐dimensional rainfall fields are accurately reconstructed using the inverse distance weighting and ordinary kriging interpolation algorithmsA long short‐term memory‐based rainfall field nowcasting model is proposed to achieve 10‐min continuous predictions of rainfall fields [ABSTRACT FROM AUTHOR]

A model‐circulation increment‐based dynamic statistical technique (MIDST) is proposed in this paper to improve the prediction of summer rainfall over southern China (SC) where quite low prediction skills have been found in the Beijing Climate Center Climate System Model version 1.1 with a moderate resolution (BCC_CSM1.1m). The results show that BCC_CSM1.1m can hardly represent the variability of the summer rainfall anomaly and its year‐to‐year increment over SC, and the skillful predictions are mostly confined over the middle reaches of the Yangtze River. Using the dynamic model output and statistical method, the MIDST is established to capture the coupled modes between the year‐to‐year increments of the summer rainfall anomaly and the associated simultaneous three‐dimensional coupled air‐sea circulation predictors. The cross‐validation indicates that the prediction skills of the MIDST are evidently improved for both the summer rainfall increment prediction and summer rainfall anomaly prediction compared with the direct BCC_CSM1.1m prediction. The skillful prediction can persist for long forecast leads over most regions except southwestern China. As the major predictability source of seasonal prediction, the intense response to changes in the circulation related to the El Niño‐Southern Oscillation (ENSO) is well captured, and thus, the performance improvement of the MIDST is primarily due to its more realistic representation of the incremental circulation related to the ENSO. [ABSTRACT FROM AUTHOR]

Both long‐term but small number of national stations and short‐term but large number of regional stations have been frequently used to study the extreme hourly precipitation (EXHP) in China. However, few studies focus on the differences of the two for revealing the features of EXHP. In this study, the characteristics of EXHP in Zhejiang Province are investigated using three rainfall data sets at three threshold criteria. The comparison between different data sets shows that increasing the station density can better reflect the climatic spatial distribution of EXHP thresholds if long‐term data is absent. The majority of EXHP can be classified into four weather types: the southwesterly wind type (30.7%–48.5%), the trough type (12.2%–23.6%), the tropical cyclone (TC) type (11.4%–17.5%) and the easterly wind type (4.9%–17.9%). The selection of stations is more sensitive to the proportions of the four weather types than the statistical years and threshold criteria. The monthly and diurnal variations of EXHP, as well as their differences revealed by the three data sets, are varied by weather type. Only using national stations cannot distinguish the spatial differences between the TC type and the easterly wind type, and there is an underestimation for southwesterly wind type and trough type in the mountainous area of southwest Zhejiang. The statistical year and station height are the main reasons for the differences in the duration of EXHP events calculated by different data sets, with the TC type having the largest effect and the southwesterly wind type the smallest. Plain Language Summary: Station data is the most common and reliable data for studying the characteristics of precipitation in China. There are two sources of station data available, that is, national station data with long time series but sparse and regional stations with short time series but numerous. However, few studies have compared the differences between these two sources of data for revealing the characteristics of extreme hourly precipitation (EXHP). In this study, the possible impact of different data sets for revealing the characteristics of EXHP under four weather types are investigated in Zhejiang Province. Zhejiang is located on the southeast coast of China with a long coastline and many mountains. Results suggest that increasing the station density can better reflect the spatial distribution of the EXHP thresholds if long‐term data is absent. EXHP events with strong synoptic‐scale forcing are more sensitive to the results obtained by different data sets. As the national stations are mostly located in the plains, the high frequency centers of EXHP are biased in each weather type if only using national stations, especially in southwest Zhejiang and near the coast. In summary, this paper provides additional perspectives for understanding the characteristics of regional EXHP by using the most common observations. Key Points: The selection of stations is sensitive to the proportions of the four main weather types in Zhejiang where extreme hourly rainfall occursExtreme hourly precipitation events with strong synoptic‐scale forcing are more sensitive to results obtained using different data setsThe sparse national stations located on the plains could hardly reflect the spatial distribution of extreme rainfall in mountainous Zhejiang [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]

This paper analyses the different relationships between the two types of South Asian highs (SAH)—the southern mode of the SAH (SSAH) and the traditional SAH in its entirety (ESAH)—with respect to the variations in summer rainfall over East Asia. The ESAH is closely related to summer rainfall over northeastern China, whereas the SSAH is closely linked to summer rainfall over the Yangtze River valley, northern China, and Japan. Above‐normal rainfall tends to occur over northeastern China in strong ESAH years, whereas strong SSAH years tend to yield above‐normal rainfall over the Yangtze River valley and Japan together with below‐normal rainfall over northern China. The westerly jet and the western Pacific subtropical high (WPSH) shifts northward associated with a strengthened ESAH. The related anomalous southwesterly winds to the northwestern side of the WPSH transports abundant water vapour to northeastern China and leads to above‐normal rainfall there. In contrast, the westerly jet shifts southward and WPSH shifts southwestward to the South China Sea associated with a strengthened and southeastward‐shifted SSAH. Accordingly, a cyclonic anomaly appears over Northeast Asia and mid‐latitude western northern Pacific and an anticyclonic anomaly occurs over subtropical western North Pacific. The associated southwesterly wind anomalies over the Yangtze River valley and Japan contributes to above‐normal rainfall over these regions via transporting sufficient amount of water vapour. In addition, the anomalous northerly winds to the western flank of the cyclonic anomaly results in below‐normal rainfall over northern China via carrying drier air southward. Furthermore, the preceding winter ENSO events may play a more important role in the SSAH variation via modulating India Ocean SST. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate a 48‐member multiphysics ensemble using the Weather Research and Forecasting (WRF) model for the JJA extreme precipitation and temperature in 2003 over the CORDEX‐EA‐II domain. The simulated precipitation and temperature are reasonable in the subregions controlled by a large‐scale circulation, yet the biases for both precipitation and temperature are evident over the subregions where the effects of mesoscale processes are important. The performance of various combinations of WRF physical schemes for simulating the JJA precipitation is dependent on the region. Meanwhile, the cumulus and microphysical schemes have substantial influences on the simulation of precipitation, and the land surface models and cumulus schemes play crucial roles in the surface temperature. Our analysis shows that the combination of Noah for the land surface process, Lin for the microphysics, G3D for the cumulus parameterization, and CAM for the radiation scheme can provide the most reliable reproduction of both precipitation and temperature extremes over China. Ensemble analysis shows that the simulated climate extremes are usually accompanied by a large ensemble spread, implying sensitivities to the model physical processes in some subregions. The simulated wind fields at low‐to‐middle atmospheric levels display responses to the options of the land surface models and cumulus schemes. The essential impact of the land–atmospheric interaction on simulating the extremes can be largely attributed to the active convective processes. WRF has difficulties in reproducing the observed temporal evolution of the rainfall process, which consists of continuous large rainfall episodes in the observation data set during the simulation period. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper focuses on testing appropriate methods to produce gridded rainfall surfaces based on the daily rainfall observed at 43 meteorological stations in the Sichuan Province during rainy seasons of 2008-2013. Rainfall is extremely variable in both spatial and temporal distribution. Therefore, three methods, namely Ordinary Kriging ( OK), Inverse Distance Weighting ( IDW) and ordinary CoKriging ( CK), have been selected and examined. First, we choose a suitable model by adjusting relevant parameters including the power exponent, the Neighbours to Include and the Include at Least. Then, cross-validation is used to verify the prediction performance of the three methods. The results for spatial interpolation of daily rainfall show that: (1) both OK and CK methods recorded smaller mean absolute error and the root-mean-square error than IDW method. (2) A preferable combination of assigning 2 to power exponent, 15 to Neighbours to Include and 5 to Include at Least is identified for IDW method. As for the best combination of OK and CK methods, Neighbours to Include is assigned with 15 while Include at Least almost has no effect on their performance. (3) CK is the optimal method for spatial interpolation of the daily rainfall in the rainy season of Sichuan. [ABSTRACT FROM AUTHOR]

ABSTRACT Heavy rain events or rainstorms of various scales often occur in Hong Kong from April to September. In extremes cases, they lead to serious landslides and flash floods resulting in loss of life, and damage to property and infrastructure. With climate change, extreme rain events are projected to be more frequent and more intense in this region. A system to gauge and label the severity of rainstorms would be useful for identifying and communicating extreme conditions in warning and disaster prevention operations. In parallel, a better understanding of the characteristics of rainstorms would also be important for impact assessments and engineering design purposes. This paper formulates a practical framework to index the magnitude and severity of rainstorms in Hong Kong. An index termed as the Severity Index combining the magnitude of different rainstorm attributes is devised for quantifying the overall severity of rainstorms. This index is flexible to allow tuning for specific applications. [ABSTRACT FROM AUTHOR]