Quantitative Precipitation Estimation Using X-band Phased Array Weather Radar

This study utilized data from an X-band phased array weather radar and ground-based rain gauge observations to conduct a quantitative precipitation estimation(QPE)analysis of a heavy rainfall event in Xiong an New Area from 20:00 on August 21 to 07:00 on August 22,2022.The analysis applied the Z-R relationship method for radar-based precipitation estimation and evaluated the QPE algorithm s performance using scatter density plots and binary classification scores.The results indicated that the QPE algorithm accurately estimates light to moderate rainfall but significantly underestimates heavy rainfall.The study identified disparities in the predictive accuracy of the QPE algorithm across various precipitation intensity ranges,offering essential insights for the further refinement of QPE techniques.

Effect of two-step solid solution on microstructure andδphase precipitation of Inconel 718 alloy

Inconel 718 is the most popular nickel-based superalloy and is extensively used in aerospace,automotive,and energy indus-tries owing to its extraordinary thermomechanical properties.The effects of different two-step solid solution treatments on microstructure andδphase precipitation of Inconel 718 alloy were studied,and the transformation mechanism fromγ″metastable phase toδphase was clarified.The precipitates were statistically analyzed by X-ray diffractometry.The results show that theδphase content firstly increased,and then decreased with the temperature of the second-step solid solution.The changes in microstructure andδphase were studied by scanning electron microscopy and transmission electron microscopy.An intragranularδphase formed in Inconel 718 alloy at the second-[100]_(δ)[011]γ step solid solution temperature of 925℃,and its orientation relationship withγmatrix was determined as//and(010)_(δ)//(111)γ.Furthermore,the Vickers hardness of different heat treatment samples was measured,and the sample treated by second-step solid solution at 1010℃ reached the maximum hardness of HV 446.84.

Effect of drying-wetting cycles on pore characteristics and mechanical properties of enzyme-induced carbonate precipitation-reinforced sea sand

Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic characteristics of EICP-treated specimens against the impact of drying-wetting(D-W)cycles is under-explored yet.This study investigates the evolution of mechanical behavior and pore charac-teristics of EICP-treated sea sand subjected to D-W cycles.The uniaxial compressive strength(UCS)tests,synchrotron radiation micro-computed tomography(micro-CT),and three-dimensional(3D)recon-struction of CT images were performed to study the multiscale evolution characteristics of EICP-reinforced sea sand under the effect of D-W cycles.The potential correlations between microstructure characteristics and macro-mechanical property deterioration were investigated using gray relational analysis(GRA).Results showed that the UCS of EICP-treated specimens decreases by 63.7% after 15 D-W cycles.The proportion of mesopores gradually decreases whereas the proportion of macropores in-creases due to the exfoliated calcium carbonate with increasing number of D-W cycles.The micro-structure in EICP-reinforced sea sand was gradually disintegrated,resulting in increasing pore size and development of pore shape from ellipsoidal to columnar and branched.The gray relational degree suggested that the weight loss rate and UCS deterioration were attributed to the development of branched pores with a size of 100-1000 m m under the action of D-W cycles.Overall,the results in this study provide a useful guidancee for the long-term stability and evolution characteristics of EICP-reinforced sea sand under D-W weathering conditions.

Spatio-Temporal Characteristics of Heavy Precipitation Forecasts from ECMWF in Eastern China

This study examines the spatio-temporal characteristics of heavy precipitation forecasts in eastern China from the European Centre for Medium-Range Weather Forecasts(ECMWF) using the time-domain version of the Method for Object-based Diagnostic Evaluation(MODE-TD). A total of 23 heavy rainfall cases occurring between 2018 and 2021 are selected for analysis. Using Typhoon “Rumbia” as a case study, the paper illustrates how the MODE-TD method assesses the overall simulation capability of models for the life history of precipitation systems. The results of multiple tests with different parameter configurations reveal that the model underestimates the number of objects’ forecasted precipitation tracks, particularly at smaller radii. Additionally, the analysis based on centroid offset and area ratio tests for different classified precipitation objects indicates that the model performs better in predicting large-area, fast-moving, and longlifespan precipitation objects. Conversely, it tends to have less accurate predictions for small-area, slow-moving, and shortlifespan precipitation objects. In terms of temporal characteristics, the model overestimates the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. In terms of temporal characteristics, the model tends to overestimate the forecasted movement speed for precipitation objects with small-area, slow movement, or both long and short lifespans while underestimating it for precipitation with fast movement. Overall, the model provides more accurate predictions for the duration and dissipation of precipitation objects with large-area or long-lifespan(such as typhoon precipitation) while having large prediction errors for precipitation objects with small-area or short-lifespan. Furthermore, the model’s simulation results regarding the generation of precipitation objects show that it performs relatively well in simulating the generation of large-area and fast-moving precipitation objects. However, there are significant differences in the forecasted generation of small-area and slow-moving precipitation objects after 9 hours.

Future changes in precipitation and water availability over the Tibetan Plateau projected by CMIP6 models constrained by climate sensitivity

Precipitation projections over the Tibetan Plateau(TP)show diversity among existing studies,partly due to model uncertainty.How to develop a reliable projection remains inconclusive.Here,based on the IPCC AR6–assessed likely range of equilibrium climate sensitivity(ECS)and the climatological precipitation performance,the authors constrain the CMIP6(phase 6 of the Coupled Model Intercomparison Project)model projection of summer precipitation and water availability over the TP.The best estimates of precipitation changes are 0.24,0.25,and 0.45 mm d^(−1)(5.9%,6.1%,and 11.2%)under the Shared Socioeconomic Pathway(SSP)scenarios of SSP1–2.6,SSP2–4.5,and SSP5–8.5 from 2050–2099 relative to 1965–2014,respectively.The corresponding constrained projections of water availability measured by precipitation minus evaporation(P–E)are 0.10,0.09,and 0.22 mm d^(−1)(5.7%,4.9%,and 13.2%),respectively.The increase of precipitation and P–E projected by the high-ECS models,whose ECS values are higher than the upper limit of the likely range,are about 1.7 times larger than those estimated by constrained projections.Spatially,there is a larger increase in precipitation and P–E over the eastern TP,while the western part shows a relatively weak difference in precipitation and a drier trend in P–E.The wetter TP projected by the high-ECS models resulted from both an approximately 1.2–1.4 times stronger hydrological sensitivity and additional warming of 0.6℃–1.2℃ under all three scenarios during 2050–2099.This study emphasizes that selecting climate models with climate sensitivity within the likely range is crucial to reducing the uncertainty in the projection of TP precipitation and water availability changes.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

Impacts of Future Changes in Heavy Precipitation and Extreme Drought on the Economy over South China and Indochina

Heavy precipitation and extreme drought have caused severe economic losses over South China and Indochina(INCSC)in recent decades.Given the areas with large gross domestic product(GDP)in the INCSC region are distributed along the coastline and greatly affected by global warming,understanding the possible economic impacts induced by future changes in the maximum consecutive 5-day precipitation(RX5day)and the maximum consecutive dry days(CDD)is critical for adaptation planning in this region.Based on the latest data released by phase 6 of the Coupled Model Intercomparison Project(CMIP6),future projections of precipitation extremes with bias correction and their impacts on GDP over the INCSC region under the fossil-fueled development Shared Socioeconomic Pathway(SSP5-8.5)are investigated.Results indicate that RX5day will intensify robustly throughout the INCSC region,while CDD will lengthen in most regions under global warming.The changes in climate consistently dominate the effect on GDP over the INCSC region,rather than the change of GDP.If only considering the effect of climate change on GDP,the changes in precipitation extremes bring a larger impact on the economy in the future to the provinces of Hunan,Jiangxi,Fujian,Guangdong,and Hainan in South China,as well as the Malay Peninsula and southern Cambodia in Indochina.Thus,timely regional adaptation strategies are urgent for these regions.Moreover,from the sub-regional average viewpoint,over two thirds of CMIP6 models agree that maintaining a lower global warming level will reduce the economic impacts from heavy precipitation over the INCSC region.

Time-lagged Effects of the Spring Atmospheric Heat Source over the Tibetan Plateau on Summer Precipitation in Northeast China during 1961–2020:Role of Soil Moisture

The spring atmospheric heat source(AHS)over the Tibetan Plateau(TP)has been suggested to affect the Asian summer monsoon and summer precipitation over South China.However,its influence on the summer precipitation in Northeast China(NEC)remains unknown.The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study.Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation,and higher soil moisture in the Yellow River Valley-North China region(YRVNC)acts as a bridge.During spring,the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC.Thus,soil moisture increases,which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat.Owing to the memory of soil moisture,the lower spring sensible heat over the YRVNC can last until mid-summer,decrease the land–sea thermal contrast,and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific.This modulates the East Asia–Pacific teleconnection pattern,which leads to a cyclonic anomaly and excessive summer precipitation over NEC.

Differences in spring precipitation over southern China associated with multiyear La Ni?a events

Composite analyses were performed in this study to reveal the difference in spring precipitation over southern China during multiyear La Ni?a events during 1901 to 2015. It was found that there is significantly below-normal precipitation during the first boreal spring, but above-normal precipitation during the second year. The difference in spring precipitation over southern China is correlative to the variation in western North Pacific anomalous cyclone(WNPC), which can in turn be attributed to the different sea surface temperature anomaly(SSTA) over the Tropical Pacific. The remote forcing of negative SSTA in the equatorial central and eastern Pacific and the local air-sea interaction in the western North Pacific are the usual causes of WNPC formation and maintenance.SSTA in the first spring is stronger than those in the second spring. As a result, the intensity of WNPC in the first year is stronger, which is more likely to reduce the moisture in southern China by changing the moisture transport, leading to prolonged precipitation deficits over southern China. However, the tropical SSTA signals in the second year are too weak to induce the formation and maintenance of WNPC and the below-normal precipitation over southern China. Thus, the variation in tropical SSTA signals between two consecutive springs during multiyear La Ni?a events leads to obvious differences in the spatial pattern of precipitation anomaly in southern China by causing the different WNPC response.

Interdecadal variability of summer precipitation in the Three River Source Region: Influences of SST and zonal shifts of the East Asian subtropical westerly jet

Summer precipitation in the Three Rivers Source Region(TRSR)of China is vital for the headwaters of the Yellow,Yangtze,and Lancang rivers and exhibits significant interdecadal variability.This study investigates the influence of the East Asian westerly jet(EAWJ)on TRSR rainfall.A strong correlation is found between TRSR summer precipitation and the Jet Zonal Position Index(JZPI)of the EAWJ from 1961 to 2019(R=0.619,p<0.01).During periods when a positive JZPI indicates a westward shift in the EAWJ,enhanced water vapor anomalies,warmer air,and low-level convergence anomalies contribute to increased TRSR summer precipitation.Using empirical orthogonal function and regression analyses,this research identifies the influence of large-scale circulation anomalies associated with the Atlantic–Eurasian teleconnection(AEA)from the North Atlantic(NA).The interdecadal variability between the NA and central tropical Pacific(CTP)significantly affects TRSR precipitation.This influence is mediated through the AEA via a Rossby wave train extending eastward along the EAWJ,and another south of 45°N.Moreover,the NA–CTP Opposite Phase Index(OPI),which quantifies the difference between the summer mean sea surface temperatures of the NA and the CTP,is identified as a critical factor in modulating the strength of this teleconnection and influencing the zonal position of the EAWJ.

Coupled multiphysical model for investigation of influence factors in the application of microbially induced calcite precipitation

The study presents a comprehensive coupled thermo-bio-chemo-hydraulic(T-BCH)modeling framework for stabilizing soils using microbially induced calcite precipitation(MICP).The numerical model considers relevant multiphysics involved in MICP,such as bacterial ureolytic activities,biochemical reactions,multiphase and multicomponent transport,and alteration of the porosity and permeability.The model incorporates multiphysical coupling effects through well-established constitutive relations that connect parameters and variables from different physical fields.It was implemented in the open-source finite element code OpenGeoSys(OGS),and a semi-staggered solution strategy was designed to solve the couplings,allowing for flexible model settings.Therefore,the developed model can be easily adapted to simulate MICP applications in different scenarios.The numerical model was employed to analyze the effect of various factors,including temperature,injection strategies,and application scales.Besides,a TBCH modeling study was conducted on the laboratory-scale domain to analyze the effects of temperature on urease activity and precipitated calcium carbonate.To understand the scale dependency of MICP treatment,a large-scale heterogeneous domain was subjected to variable biochemical injection strategies.The simulations conducted at the field-scale guided the selection of an injection strategy to achieve the desired type and amount of precipitation.Additionally,the study emphasized the potential of numerical models as reliable tools for optimizing future developments in field-scale MICP treatment.The present study demonstrates the potential of this numerical framework for designing and optimizing the MICP applications in laboratory-,prototype-,and field-scale scenarios.

Variable precipitation behaviors of Laves phases in an ultralight Mg-Li-Zn alloy

Precipitation habits plays a decisive role in strengthening materials,especially for Mg alloys the non-basal plane precipitation is necessary but very limited.Generally,the precipitates would nucleate and grow up in a specific habit plane owing to the constraint of free-energy minimization of the system.Herein,in an aged ultralight Mg-Li-Zn alloy,we confirmed that the precipitates dominated by C15 Laves structure could form in a variety of habit planes,to generate three forms of strengthening-phases,i.e.,precipitate-rod,precipitate-lath,and precipitate-plate.Among which,the precipitate-plates are on basal plane as usually but precipitate-rods/laths are on non-basal plane,and such non-basal precipitates would transform into the basal(Mg,Li)Zn_(2)Laves structure with prolonged aging.These findings are interesting to understand the precipitation behaviors of multi-domain Laves structures in hexagonal close-packed crystals,and expected to provide a guidance for designing ultralight high-strength Mg-Li based alloys via precipitation hardening on the non-basal planes.

The GNSS PWV retrieval using non-observation meteorological parameters based on ERA5 and its relation with precipitation

The pressure and temperature significantly influence precipitable water vapor(PWV) retrieval. Global Navigation Satellite System(GNSS) PWV retrieval is limited because the GNSS stations lack meteorological sensors. First, this article evaluated the accuracy of pressure and temperature in 68 radiosonde stations in China based on ERA5 Reanalysis data from 2015 to 2019 and compared them with GPT3model. Then, the accuracy of pressure and temperature calculated by ERA5 were estimated in 5 representative IGS stations in China. And the PWV calculated by these meteorological parameters from ERA5(ERA5-PWV) were analyzed. Finally, the relation between ERA5-PWV and precipitation was deeply explored using wavelet coherence analysis in IGS stations. These results indicate that the accuracy of pressure and temperature of ERA5 is better than the GPT3 model. In radiosonde stations, the mean BIAS and MAE of pressure and temperature in ERA5 are-0.41/1.15 hpa and-0.97/2.12 K. And the mean RMSEs are 1.35 hpa and 2.87 K, which improve 74.77% and 40.58% compared with GPT3 model. The errors of pressure and temperature of ERA5 are smaller than the GPT3 model in bjfs, hksl and wuh2, and the accuracy of ERA5-PWV is improved by 18.77% compared with the GPT3 model. In addition, there is a significant positive correlation between ERA5-PWV and precipitation. And precipitation is always associated with the sharp rise of ERA5-PWV, which provides important references for rainfall prediction.

A New Algorithm of Rain Type Classification for GPM Dual-Frequency Precipitation Radar in Summer Tibetan Plateau

In this study, a new rain type classification algorithm for the Dual-Frequency Precipitation Radar(DPR) suitable over the Tibetan Plateau(TP) was proposed by analyzing Global Precipitation Measurement(GPM) DPR Level-2 data in summer from 2014 to 2020. It was found that the DPR rain type classification algorithm(simply called DPR algorithm) has mis-identification problems in two aspects in summer TP. In the new algorithm of rain type classification in summer TP,four rain types are classified by using new thresholds, such as the maximum reflectivity factor, the difference between the maximum reflectivity factor and the background maximum reflectivity factor, and the echo top height. In the threshold of the maximum reflectivity factors, 30 d BZ and 18 d BZ are both thresholds to separate strong convective precipitation, weak convective precipitation and weak precipitation. The results illustrate obvious differences of radar reflectivity factor and vertical velocity among the three rain types in summer TP, such as the reflectivity factor of most strong convective precipitation distributes from 15 d BZ to near 35 d BZ from 4 km to 13 km, and increases almost linearly with the decrease in height. For most weak convective precipitation, the reflectivity factor distributes from 15 d BZ to 28 d BZ with the height from 4 km to 9 km. For weak precipitation, the reflectivity factor mainly distributes in range of 15–25 d BZ with height within 4–10 km. It is also shows that weak precipitation is the dominant rain type in summer TP, accounting for 40%–80%,followed by weak convective precipitation(25%–40%), and strong convective precipitation has the least proportion(less than 30%).

The Influence of Airflow Transport Pathways on Precipitation during the Rainy Season in the Liupan Mountains of Northwest China

This study investigates the influence of airflow transport pathways on seasonal rainfall in the mountainous region of the Liupan Mountains(LM) during the rainy seasons from 2020 to 2022, utilizing observational data from seven ground gradient stations located on the eastern slopes, western slopes, and mountaintops combined with backward trajectory cluster analysis. The results indicate 1) that the LM's rainy season, characterized by overcast and rainy days, is mainly influenced by cold and moist airflows(CMAs) from the westerly direction and warm and moist airflows(WMAs) from a slightly southern direction. The precipitation amounts under four airflow transport paths are ranked from largest to smallest as follows: WMAs, CMAs, warm dry airflows(WDAs), and cold dry airflows(CDAs). 2) WMAs contribute significantly more to the intensity of regional precipitation than the other three types of airflows. During localized precipitation events,warm airflows have higher precipitation intensities at night than cold airflows, while the opposite is true during the afternoon. 3) During regional precipitation events, water vapor content is the primary influencing factor. Precipitation characteristics under humid airflows are mainly affected by high water vapor content, whereas during dry airflow precipitation, dynamic and thermodynamic factors have a more pronounced impact. 4) During localized precipitation events, the influence of dynamic and thermodynamic factors is more complex than during regional precipitation, with the precipitation characteristics of the four airflows closely related to their water vapor content, air temperature and humidity attributes, and orographic lifting. 5) Compared to regional precipitation, the influence of topography is more prominent in localized precipitation processes.

Improving the accuracy of precipitation estimates in a typical inland arid area of China using a dynamic Bayesian model averaging approach

Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region,which can even improve the performance of hydrological modelling.This study evaluated the applicability of widely used five satellite-based precipitation products(Climate Hazards Group InfraRed Precipitation with Station(CHIRPS),China Meteorological Forcing Dataset(CMFD),Climate Prediction Center morphing method(CMORPH),Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record(PERSIANN-CDR),and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA))and a reanalysis precipitation dataset(ECMWF Reanalysis v5-Land Dataset(ERA5-Land))in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations.Based on this assessment,we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging(DBMA)approach,the expectation-maximization method,and the ordinary Kriging interpolation method.The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability,with an outstanding performance,as indicated by low root mean square error(RMSE=1.40 mm/d)and high Person's correlation coefficient(CC=0.67).Compared with the traditional simple model averaging(SMA)and individual product data,although the DBMA-fused precipitation data were slightly lower than the best precipitation product(CMFD),the overall performance of DBMA was more robust.The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final(IMERG-F)precipitation product,as well as hydrological simulations in the Ebinur Lake Basin,further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region.The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas,and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions.

Characteristics and Preliminary Causes of Tropical Cyclone Remote Precipitation over China

In this study,the characteristics and preliminary causes of tropical cyclone remote precipitation(TRP)over China during the period from 1979 to 2020 are investigated.Results indicated that approximately 72.42%of tropical cyclones(TCs)in the Western Pacific produce TRP over China.The peak months for TRP are July and August.The four key regions of TRP are the adjacent areas between the Sichuan and Shaanxi Provinces,the northern coast of the Bohai Sea,the coast of the Yellow Sea,and the southern coast area.The typical distance between the station with TRP and the TC center ranges from 1500 to 2500 km.Most of these stations are situated north to 60°west of north of the TC.The south–west water vapor transportation on the west side of the TC is crucial to TRP.TRP has a decreasing trend because of the decrease in the number of TCs that generate TRP.From the perspective of large-scale environmental conditions,a decrease in the integrated horizontal water vapor transport in China' Mainland,the weakening of upward motion at approximately 25°–35°N,which is inconducive to convection,and an increase in low-level vertical wind shear,which is unfavorable for the development of TC in areas with high frequencies of TRP-related TCs,are the factors that result in the decreasing trend of TRP.

Cloud-Type-Dependent 1DVAR Algorithm for Retrieving Hydrometeors and Precipitation in Tropical Cyclone Nanmadol from GMI Data

Understanding the structure of tropical cyclone(TC)hydrometeors is crucial for detecting the changes in the distribution and intensity of precipitation.In this study,the GMI brightness temperature and cloud-dependent 1DVAR algorithm were used to retrieve the hydrometeor profiles and surface rain rate of TC Nanmadol(2022).The Advanced Radiative Transfer Modeling System(ARMS)was used to calculate the Jacobian and degrees of freedom(△DOF)of cloud water,rainwater,and graupel for different channels of GMI in convective conditions.The retrieval results were compared with the Dual-frequency Precipitation Radar(DPR),GMI 2A,and IMERG products.It is shown that from all channels of GMI,rain water has the highest△DOF,at 1.72.According to the radiance Jacobian to atmospheric state variables,cloud water emission dominates its scattering.For rain water,the emission of channels 1–4 dominates scattering.Compared with the GMI 2A precipitation product,the 1DVAR precipitation rate has a higher correlation coefficient(0.713)with the IMERG product and can better reflect the location of TC precipitation.Near the TC eyewall,the highest radar echo top indicates strong convection.Near the melting layer where Ka-band attenuation is strong,the double frequency difference of DPR data reflects the location of the melting.The DPR drop size distribution(DSD)product shows that there is a significant increase in particle size below the melting layer in the spiral rain band.Thus,the particle size may be one of the main reasons for the smaller rain water below the melting layer retrieved from 1DVAR.

A New Merged Product Reveals Precipitation Features over Drylands in China

Due to the considerable uncertainties inherent in the datasets describing the spatiotemporal distributions of precipitation in the drylands of China,this study presents a new merged monthly precipitation product with a spatial resolution of approximately 0.2°×0.2°during 1980–2019.The newly developed precipitation product was validated at different temporal scales(e.g.,monthly,seasonally,and annually).The results show that the new product consistently aligns with the spatiotemporal distributions reported by the Chinese Meteorological Administration Land Data Assimilation System(CLDAS)product and Multi-Source Weighted Ensemble Precipitation(MSWEP).The merged product exhibits exceptional quality in describing the drylands of China,with a bias of–2.19 mm month^(–1)relative to MSWEP.In addition,the annual trend of the merged product(0.09 mm month^(–1)yr^(−1))also closely aligns with that of the MSWEP(0.11 mm month^(–1)yr^(−1))during 1980–2019.The increasing trend indicates that the water cycle and wetting process intensified in the drylands of China during this period.In particular,there was an increase in wetting during the period from 2001–2019.Generally,the merged product exhibits potential value for improving our understanding of the climate and water cycle in the drylands of China.

Precipitation and anthropogenic activities regulate the changes of NDVI in Zhegucuo Valley on the southern Tibetan Plateau

Whether climate change or anthropogenic activities play a more pivotal role in regulating vegetation growth on the Tibetan Plateau is still controversial.A better understanding on grassland changes at a fine scale may provide important guidance for local government policy and grassland management.Using two of the most reliable satellite NDVI products(MODIS NDVI and SPOT NDVI),we evaluated the dynamic of grasslands in the Zhegucuo valley on the southern Tibetan Plateau from 2000 to 2020,and analyzed its driving factors and relative influences of climate change and anthropogenic activities.Here,the key indicators of climate change were assumed to be precipitation and temperature.The main results were:(1)the grassland NDVI in Zhegucuo valley did not reflect a significant temporal change during the last 21 years.The variation of precipitation during the early growing season(GSP)resembled that of NDVI,and the GSP was positively correlated with NDVI.At the pixel level,the partial correlation analysis showed that 37.79%of the pixels depicted a positive relationship between GSP and NDVI,while 11.32%of the pixels showed a negative relationship between temperature during the early growing season(GST)and NDVI.(2)In view of the spatial distribution,the areas mainly controlled by GSP were generally distributed in the southern part,while those affected by GST stood in the eastern part,mainly around the Zhegucuo lake where most population in Cuomei County settled down.(3)Decreasing NDVI trends were mainly occurred in alpine steppe at lower elevations rather than alpine meadow at higher elevations.(4)The residual trend(RESTREND)analysis further indicated that the anthropogenic activities played a more pivotal role in regulating the annual changes of NDVI rather than climate factors in this area.Future studies should pay more attention on climate extremes rather than the simple temporal trends.Also,the influence of human activities on alpine grassland needs to be accessed and fully considered in future sustainable management.