基于CLDAS土壤相对湿度的云南农业干旱监测

选取2016-2020年云南37个土壤水分观测站逐日0-10cm土层相对湿度观测数据和逐日降水、气温观测资料,采用线性插值法,将CLDAS格点数据插值到观测站点上,用于与站点观测数据对比分析。利用回归订正法对插值后的CLDAS土壤相对湿度产品进行订正。采用相对误差、平均偏差、相关系数、标准差和均方根误差统计指标,定量评估CLDAS土壤相对湿度在云南的适用性。结果表明:云南土壤水分观测站相对湿度数据观测有效率不高,选用陆面融合数据开展农业干旱监测十分必要;云南地区近80%的CLDAS土壤相对湿度与土壤水分观测站观测值的相对误差绝对值<30%,数据可信度高;在干旱发生频率高的云南中部地区,CLDAS土壤相对湿度与土壤水分观测站观测值的相关系数均在0.8以上,平均偏差小于10%。从农业干旱监测效果来看,基于CLDAS土壤相对湿度的干旱监测指标能很好地描述由气温和降水异常导致的土壤墒情变化,当日降水量接近或超过5.0mm时,能快速响应轻旱站点数的减少;当连续有效降水发生后,监测指标可反映中等及以上等级农业干旱的缓解。综合来看,CLDAS土壤相对湿度在云南农业干旱监测的适用性好。

CLDAS降水产品的适用性分析及机器学习订正应用

为获得中国气象局陆面数据同化系统(CLDAS)多源降水融合实况分析产品在甘肃省的精细化评估结论并提高该产品的精度,采用甘肃省2215个地面站的降水数据作为检验源,评估CLDAS快速融合和实时融合降水产品的适用性,并基于评估结论采用机器学习方法及优化策略,订正CLDAS降水产品。结果表明:CLDAS降水产品能较好地反映甘肃省降水时空分布,日值的精度整体不如小时值;XGBoost算法较其他模型有显著优势,且在降水量大时订正效果更显著;通过提升训练数据集质量、特征工程和精细调参优化后的XGBoost模型使3级以上降水量的均方根误差减少近50%,1~2级的误判降水得到明显改善,该模型和算法能推广应用于具有相同气候特征的领域。

CLDAS V2.0逐时气温实况产品在宝鸡市的检验评估

基于宝鸡市所有国家级自动站和区域站观测数据,通过准确率、平均误差、平均绝对误差、均方根误差,对2019-2022年中国气象局第二代陆面数据同化系统(CLDAS V2.0)在宝鸡市的逐时气温网格数据(网格实况)进行检验评估。结果表明:网格实况在国家级自动站的准确率指标高于区域站,平均误差、平均绝对误差、均方根误差指标低于区域站;在国家级自动站中,网格实况对渭滨站、陈仓站、千阳站、麟游站、凤翔站的质量较高;网格实况在9、10月份质量最高,1、2月份质量最低;网格实况在宝鸡市大部分范围平均误差均在-2~2℃,其在第四季度质量最高。

基于MODIS和CLDAS的综合干旱监测模型研究

传统的干旱监测指数主要考虑单一影响因子,往往无法全面综合反映干旱状况.基于MODIS数据和CLDAS数据,选取多个影响因子和能够直接反映干旱程度的干旱指数作为自变量,以综合气象干旱指数(CI)为因变量,通过梯度提升机(GBM)机器学习算法建立日尺度综合干旱监测模型,并以2015—2018年华北地区干旱为例进行了研究.结果表明模型监测结果与站点CI计算值具有显著的相关性,训练集和测试集决定系数分别达到0.945和0.655,均方根误差(RMSE)分别为0.033和0.082,综合干旱监测模型具有较高的精度.且模型监测与CI监测各月等级一致率均在65%以上,并与标准化降水蒸散指数(SPEI)和土壤相对湿度(RSM)相关系数分别为0.68和0.60,能较好地反映气象干旱和农业干旱状况.典型干旱情况监测表明,综合干旱监测模型综合考虑多种干旱影响因素,能较准确地识别出干旱的发生,表征综合干旱发生状况.

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.

Thermodynamic re-assessment of the Mg-Gd-Y ternary system coupling with the driving forces for phase precipitations during aging process

Based on the available experimental phase equilibrium relations and aging precipitation sequences,the Mg–Gd–Y ternary system has been thermodynamically re-assessed by means of CALPHAD technique.To simulate the experimentally reported aging precipitation sequence,α(Mg)_(SS)(supersaturated)→GP zones(D019-type,metastable)→β’-Mg_(7)Gd(c-bco,metastable)→β_(1)-Mg_(3)Gd(fcc,metastable)→β-Mg_(5)Gd(fcc,stable)near the Mg–Gd side,andα(Mg)SS(supersaturated)→β’-Mg_(7)Y(c-bco,metastable)→β-Mg_(24)Y_(5)(bcc,stable)near the Mg–Y side,the effective nucleation driving forces obtained by deducting the nucleation resistances from the thermodynamic driving forces are calculated and analyzed.Two metastable components,GP zones(D019-type)andβ’(c-bco)ordered fromα(Mg)_(SS),do not exist in the stable equilibrium phase diagram but appear in the annealing process of typical alloys.The Redlich–Kister equations are adopted to describe three solution phases,Liquid,HCP_A3 and BCC_A2.The intermediate compounds Mg_(2)Y,Mg_(24)Y_(5),Mg_(2)Gd,Mg_(3)Gd and Mg_(5)Gd are expressed by the formulas of(Mg,Y)_(2/3)(Gd,Mg,Y)_(1/3),Mg_(24/29)(Gd,Mg,Y)_(4/29)Y1/29,(Gd,Mg)_(2/3)(Gd,Mg,Y)_(1/3),(Gd,Mg)_(3/4)(Gd,Mg,Y)_(1/4)and Mg_(5/6)(Gd,Mg,Y)_(1/6),respectively.In particular,the two-sublattice models(Gd,Mg,Y)_(1/2)(Gd,Mg,Y)_(1/2),(Gd,Mg,Y)_(3/4)(Gd,Mg,Y)_(1/4)and(Gd,Mg,Y)_(7/8)(Gd,Mg,Y)_(1/8)have been respectively used to describe the stable Mg(Gd,Y)(BCC_B2)alloy compound as well as the metastable GP zones(D019-type)andβ’(c-bco)phase,in order to cope with the order-disorder transitions.A set of self-consistent thermodynamic parameters has been obtained to ensure the thermodynamic calculations well consistent with the reported experimental data,containing not only the stable equilibrium phase diagram but also the aging precipitation sequence.

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.

CLDAS地表温度产品在青藏高原多年冻土区的适用性评估与校正

青藏高原多年冻土区现有的地表温度数据主要包括点位观测的地表和浅表层地温数据,以及遥感反演、模式模拟和再分析等手段获取和制备的空间数据。中国气象局陆面数据同化系统(CLDAS)数据产品在全国大部分地区的表现较好,但受实测数据稀缺的限制以及对多年冻土特殊下垫面考量不足的影响,该数据在青藏高原多年冻土区的适用性有待进一步评估和修正。文中基于多年冻土区2008—2018年7个站点的逐日连续地表温度定点观测数据,对CLDAS地表温度数据进行评估,分析在不同时期以及不同下垫面类型下,CLDAS地表温度的适用性情况。结果表明:CLDAS在7个站点的地表温度与实测值存在较大偏差(bias=2.09℃,MAE=3.64℃,RMSE=4.67℃,R^(2)=0.83),主要表现为对地表温度的高估。其中,CLDAS在融化期的适用性相对较好,在冻融交替期、冻结期的适用性较差;在高寒荒漠、高寒荒漠草原地区的适用性较好,在高寒沼泽草甸地区的适用性较差。据此,在考虑归一化植被指数(NDVI)、归一化积雪指数(NDSI)、积雪深度、高程、坡度、坡向、土壤质地对地表温度的影响基础上,构建了多元逐步回归校正模型。校正模型考虑了研究区下垫面情况的差异,提高了CLDAS的模拟精度。结果显示,区分冻结期、融化期、交替期构建模型校正的结果优于不考虑冻融期构建的校正模型。区分冻融期分别构建多元逐步回归模型进行校正后,CLDAS地表温度的精度得到了明显提升(bias=-0.11℃,MAE=2.42℃,RMSE=3.23℃,R2=0.89)。

基于准对称混合滑动训练法对CLDAS气温的订正检验

基于准对称混合滑动训练期方法,对近两年来中国气象局陆面同化分析系统(CMA Land Data Assimilation System,CLDAS)输出的日最高气温、日最低气温网格实况分析产品进行订正,以期提高该产品在重庆地区的适用性。结果表明:订正前,2021年CLDAS日最高气温产品的平均误差为0.63℃,平均绝对误差为1.14℃,订正后平均误差减小至-0.03℃,平均绝对误差减小至0.64℃,误差小于或等于1℃的准确率由约64%提高到约90%,明显改善了该产品在重庆西部和东南部地区的适用性;订正前,2021年CLDAS日最低气温的平均误差为-0.22℃,平均绝对误差为0.75℃,订正后平均误差减小至-0.03℃,平均绝对误差减小至0.55℃,误差小于或等于1℃的准确率由约91%提高到约93%,改善了该产品在重庆中部地区的适用性。

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.