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Rainfall and wind speed are two important meteorological variables that have a significant impact on agriculture, human health, and socioeconomic development. While individual rainfall or wind events have been widely studied, little attention has been devoted to studying the lead-lag relationship between rainfall and wind speed, particularly in coastal regions where strong dependence between rainfall and wind speed is expected. Taking China's coastline as the case study, this paper aims to explore the variation trends of wind speed and rainfall and reveal the relationships between rainfall events and wind speeds on days before and after rainfall occurrence, by using meteorological station data from 1960 to 2018. The results show that wind speed tended to decrease while rainfall showed a slight increase for most stations. The daily wind speed increased 2 days before rainfall occurrence and decreased after then, with the highest wind speed observed during rainfall onset regardless of rainfall amount. Moreover, heavier rainfall events are more likely to occur with higher wind speeds. The findings of this study potentially improve the understanding of the dependence of rainfall and wind speed, which could help rainfall or wind-related disaster mitigation. [ABSTRACT FROM AUTHOR]

Quantitatively evaluation of satellite precipitation and potential evapotranspiration products with the high resolution, wide coverage and dynamic continuity is an important foundation for drought monitoring over mainland China. This paper examined the accuracy of products and the utility of drought monitoring using the newly released long-term (more than 30 years) satellite precipitation products (climate hazards group infrared precipitation with station, CHIRPS) data version 2.0 and potential evapotranspiration products (global land-surface evaporation: the Amsterdam methodology, GLEAM) dataset. We selected standardized precipitation evapotranspiration index (SPEI) and six statistical and classification measures indexes to evaluate accuracy and the utility of CHIRPS and GLEAM-Ep (potential evapotranspiration derived from GLEAM), with China Gauge-based Precipitation Daily Analysis dataset (CGDPA) and potential evapotranspiration calculated by Penman-Monteith (PM-Ep) as evaluation reference data sets. The results showed that CHIRPS and GLEAM-Ep performed well in eastern and southwest of China. However, their performance in western China was uncertain due to the sparsity of meteorological stations. SPEIs (SPEI value calculated by the CHIRPS and GLEAM-Ep) had a good performance on drought monitoring in eastern and southwestern China. Values of correlation coefficient (CC) between SPEIs and SPEIm (SPEI value calculated by the CGDPA and PM-Ep) were more than 0.6 in southeastern China, southwestern China, the middle and lower reaches of the Yangtze River region and northern China, especially in relatively humid areas, which the correlation coefficient values were more than 0.7 and the root mean-squared error (RMSE) values were less than 0.8. In order to further evaluate the performance of SPEIs in drought monitoring at spatial and temporal scales, the SPEIs3 (SPEIs at three-month scale) and SPEIm3 (SPEIm at three-month scale) in southeastern China, southwestern China, the middle and lower reaches of the Yangtze River region and northern China were compared. SPEIs3 had a better simulation effect on the evolution process of the ratio of drought area in those regions during1981-2016. And the success ratio of simulating drought duration was about 0.93, 0.57, 0.71 and 0.81, respectively. Moreover, SPEIs3 displayed a high accuracy over the four regions in capturing drought, which was the spatial distribution of typical drought events on specific month. In conclusion, SPEI based on long-term CHIRPS and GLEAM-Ep could be applied to monitor and evaluate drought in eastern and southwestern China. This paper can provide reliable reference for monitoring and warning of drought events and water resources management in those regions. [ABSTRACT FROM AUTHOR]

Biological soil crusts are fundamental components and surface landscape in arid regions, and biogeochemical process also depends on them. However, biological soil crusts stoichiometry remains largely unknown in the desert region of Northern China. The influences of precipitation on biological soil crusts stoichiometry is also lacking in desert steppe. This paper aims to investigate the effects of precipitation on the stoichiometry of biological soil crusts in desert steppe. This field study was conducted at Dashuikeng Grassland Research Station, Yanchi County (106°58′E, 37°24′N, average elevation, 1 560 m), Ningxia Hui Autonomous Region, China. This region covers a large ecosystem of desert steppe that characterized by low rainfall and uneven precipitation, along the southwest edge of the Mu Us Sandy Land. In the study desert steppe area on the southeastern margin of the Tengger Desert, the average annual precipitation was only 298.3 mm during the 60 years from 1959 to 2019. The precipitation was regulated by the measurement of artificial rain using rainwater shed and sprinkler irrigation technologies, in order to evaluate precipitation effects on the biological soil crusts in desert steppe compared with natural precipitation. 28 precipitation treatments (6 m×6 m) were set up at the test station in early March 2018, where 3 m wide buffer zone was designed between each time. Control conditions of precipitation were designed via the shelter and sprinkler irrigation system, including 7 precipitation treatments, natural precipitation (CK), drought (1/2 reduction in precipitation, DW1/2 treatment, 1/3 reduction in natural precipitation, DW1/3 treatment, 1/4 reduction in precipitation, DW1/4 treatment), and increasing precipitation (1/2 increase in natural precipitation, IW1/2 treatment, 1/3 increase in natural precipitation, IW1/3 treatment, 1/4 increase in natural precipitation, IW1/4 treatment). Each treatment has 4 spares for the reproductivity. In the same period, small weather stations were set up in the test area. TRIME-PICO TDR Portable Soil Moisture Meter (made in Germany) was used for the data collection of precipitation in the soil water depth of 10 cm. Carbon (C), nitrogen (N) and phosphorus (P) contents of biological soil crusts were measured to examine the C: N: P stoichiometry and its driving factors. Three findings can be achieved: 1) Water-reducing treatment was beneficial to the enrichment of C, N and P in the crust. DW1/4 treatment and natural precipitation treatment posed significant effects on the C content in the crust layer and underlying soil. The water-reducing treatment can reduce the N level of the crust, while increase the N level of the underlying surface. The content of P in the crust layer was the lowest under DW 1/3 treatment, whereas the content of P in the underlying surface reached the peak under DW 1/2 treatment; 2) Natural rainfall and increased precipitation can significantly improve the underlying surface C: N and C: P. There was a reduction of N: P in the crust layer and its underlying surface; 3) Suitable soil moisture conditions promoted the accumulation of SMBC (Soil Microbial Biomass Carbon) and SMBN (Soil Microbial Biomass Nitrogen) on the crust layer and underlying surface, while excessive rainfall caused the loss of soil nutrients, which was not conducive to the accumulation of SMBC and SMBN. The relatively dry soil environment was conducive to the enrichment of soil carbon and nitrogen in the crust layer, provided more nutrients for soil microbial respiration, and was conducive to the accumulation of SMBC and SMBN. In short, the C: N: P stoichiometry of biological soil crusts and underlying surfaces had different responses to precipitation in the desertification areas of northern China. [ABSTRACT FROM AUTHOR]

Precipitation is considered a crucial component in the hydrological cycle and changes in its spatial pattern directly influence the water resources. We compare different interpolation techniques in predicting the spatial distribution pattern of precipitation in Chongqing. Six interpolation methods, i.e., Inverse Distance Weighting (IDW), Radial Basis Function (RBF), Diffusion Interpolation with Barrier (DIB), Kernel Interpolation with Barrier (KIB), Ordinary Kriging (OK) and Empirical Bayesian Kriging (EBK), were applied to estimate different rainfall patterns. Annual mean, rainy season and dry-season precipitation was calculated from the daily precipitation time series of 34 meteorological stations with a time span of 1991 to 2019, based on Leave-One-Out Cross-Validation (LOOCV), Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Symmetric Mean Absolute Percentage Error (SMAPE) and Nash–Sutcliffe Efficiency coefficient (NSE) as validation indexes of the applied models for calculating the error degree and accuracy. Correlation test and Spearman coefficient was performed on the estimated and observed values. A method combining Entropy Weight and Technique for Order Preference by Similarity to Ideal Solution (Entropy-Weighted TOPSIS) was introduced to rank the performance of six interpolation methods. The results indicate that interpolation technique performs better in estimating during periods of low precipitation (i.e., dry season, relative to rainy season and mean annual). The performance priorities of the six methods under the combined multiple precipitation distribution patterns are KIB > EBK > OK > RBF > DIB > IDW. Among them, KIB method has the highest accuracy which maps more accurate precipitation surfaces, with the disadvantage that estimation error is prone to outliers. EBK method is the second highest, and IDW method has the lowest accuracy with a high degree of error. This paper provides information for the application of interpolation methods in estimating rainfall spatial pattern and for water resource management of concerned regions. [ABSTRACT FROM AUTHOR]

In this paper, the diurnal variations of various clouds are analyzed using hourly cloud observations at weather stations in China from 1985 to 2011. In combination with merged hourly precipitation data, the relationship between the diurnal variations of clouds and precipitation in the summers from 2008 to 2011 are studied. The results show that the occurrence frequencies of total cloud and various cloud types exhibit significant diurnal variations. The diurnal variations of the occurrence frequencies of altocumulus and stratocumulus show a bimodal pattern, with peaks appearing in the early morning and late afternoon. The early morning peaks of altocumulus and stratocumulus appear earlier in the summer than in the other seasons, while the late afternoon maxima show an opposite trend. The occurrence frequency of nimbostratus peaks in the morning between 07 and 12 LST (local solar time), and the peak value lags 2 to 3 h from west to east along the Yangtze River valley; meanwhile, the diurnal variation shows no clear differences caused by changes in the latitude or seasons. Cumulus shows an afternoon (14 LST) maximum, while cumulonimbus peaks in the late afternoon during 16–20 LST, and both of them present a great diurnal range. Cirrus usually reaches its peak at 17–18 LST, and it differs by 1 to 2 h with a change in the latitude. The results of the study first show that the diurnal variations of precipitation among different regions are dominated by different clouds. The upper reaches of the Yangtze River valley present a midnight precipitation maximum that is mainly dominated by cumulonimbus. For the middle reaches of the Yangtze River valley impacted by nimbostratus, the precipitation peaks in the early morning. In South and Northeast China, the precipitation peaks in the afternoon and is determined by the diurnal variations of convective clouds. In the region between the Yangtze River valley and Yellow River valley, the precipitation peaks in the early morning and afternoon; the early morning peak is mainly determined by stratiform clouds, while the afternoon peak is closely related to convective clouds. [ABSTRACT FROM AUTHOR]