首站-论文投稿智能助手
典型文献
Refined Evaluation of Satellite Precipitation Products against Rain Gauge Observations along the Sichuan–Tibet Railway
文献摘要:
Being constructed in southwestern China, the Sichuan–Tibet Railway (STR) travels across the eastern Tibetan Plat- eau where there is the most complex terrain and changeable weather in the world. Due to sparse ground-based obser- vations over the Tibetan Plateau, precipitation products retrieved by remote sensing are more widely used; however, satellite-based precipitation products (SPPs) have not yet been strictly and systematically evaluated along the STR. This study aims to evaluate the performance of six SPPs by a series of metrics with available ground observations along the STR during 1998–2020. The six SPPs include the datasets derived from the Tropical Rainfall Measuring Mission (TRMM), Climate Prediction Center morphing technique (CMORPH), Global Precipitation Measurement (GPM), Global Satellite Mapping of Precipitation (GSMaP), Precipitation Estimation from Remotely Sensed Inform- ation Using Artificial Neural Networks (PERSIANN), and Fengyun-2 satellites precipitation estimate (FY2PRE). The results indicate that most of the SPPs can capture the precipitation characteristics on multiple timescales (monthly, daily, hourly, and diurnal cycle) as shown by the evaluated metrics. The probability density functions of the daily and hourly precipitation are also well represented by the SPPs, and 30 mm day?1 and 16 mm h?1 are identified as the daily and hourly thresholds of extreme precipitation events along the STR. The best SPP varies at different timescales: GPM and GSMaP are suitable for the monthly and daily scale, and FY2PRE and GPM are suited to the hourly scale. In general, GPM is relatively optimum on multiple timescales, and PERSIANN gives the worst performance. In addi- tion, the SPPs perform worse at higher altitudes and for more intense precipitation. Overall, the results from this study are expected to provide essential reference for using the SPPs in meteorological services and disaster preven- tion in the STR construction and its future operation.
文献关键词:
作者姓名:
Zhiqiang LIN;Xiuping YAO;Jun DU;Zhenbo ZHOU
作者机构:
Plateau Atmosphere and Environment Key Laboratory of Sichuan Province,School of Atmospheric Sciences,Chengdu University of Information Technology,Chengdu 610225;China Meteorological Administration Training Centre,China Meteorological Administration,Beijing 100081;Tibet Institute of Plateau Atmospheric and Environmental Science,Lhasa 850000
引用格式:
[1]Zhiqiang LIN;Xiuping YAO;Jun DU;Zhenbo ZHOU-.Refined Evaluation of Satellite Precipitation Products against Rain Gauge Observations along the Sichuan–Tibet Railway)[J].气象学报(英文版),2022(05):779-797
A类:
Inform,FY2PRE
B类:
Refined,Evaluation,Satellite,Precipitation,Products,against,Gauge,Observations,along,Sichuan,Railway,Being,constructed,southwestern,China,STR,travels,across,eastern,Tibetan,where,there,most,complex,terrain,changeable,weather,world,Due,sparse,ground,over,Plateau,precipitation,products,retrieved,by,remote,sensing,are,more,widely,used,however,SPPs,have,not,yet,been,strictly,systematically,evaluated,This,study,aims,performance,six,series,metrics,available,observations,during,include,datasets,derived,from,Tropical,Rainfall,Measuring,Mission,TRMM,Climate,Prediction,Center,morphing,technique,CMORPH,Global,Measurement,GPM,Mapping,GSMaP,Estimation,Remotely,Sensed,Using,Artificial,Neural,Networks,PERSIANN,Fengyun,satellites,estimate,results,indicate,that,can,capture,characteristics,multiple,timescales,monthly,daily,hourly,diurnal,cycle,shown,probability,density,functions,also,well,represented,day,identified,thresholds,extreme,events,best,varies,different,suitable,suited,general,relatively,optimum,gives,worst,addi,worse,higher,altitudes,intense,Overall,this,expected,provide,essential,reference,using,meteorological,services,disaster,preven,construction,its,future,operation
AB值:
0.54616
相似文献
Remote Sensing-based Spatiotemporal Distribution of Grassland Aboveground Biomass and Its Response to Climate Change in the Hindu Kush Himalayan Region
XU Cong;LIU Wenjun;ZHAO Dan;HAO Yanbin;XIA Anquan;YAN Nana;ZENG Yuan-State Key Laboratory of Remote Sensing Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China;School of Ecology and Environmental Sci-ences&Yunnan Key Laboratory for Plateau Mountain Ecology and Restoration of Degraded Environments,Yunnan University,Kun-ming 650091,China;College of Life Sciences,University of Chinese Academy of Sciences,Beijing 100049,China;CAS Center for Excellence in Tibetan Plateau Earth Sciences,Chinese Academy of Sciences,Beijing 100101,China;Beijing Yanshan Earth Critical Zone National Research Station,University of Chinese Academy of Sciences,Beijing 101408,China;College of Resources and Envir-onment,University of Chinese Academy of Sciences,Beijing 100049,China
Evaluating the Influence of Multisource Typhoon Precipitation Data on Multiscale Urban Pluvial Flood Modeling
Yi Lu;Jie Yin;Dandan Wang;Yuhan Yang;Hui Yu;Peiyan Chen;Shuai Zhang-Key Laboratory of Geographic Information Science(Ministry of Education),East China Normal University,Shanghai 200241,China;Shanghai Typhoon Institute,China Meteorological Administration,Shanghai 200030,China;Key Laboratory of Numerical Modeling for Tropical Cyclone of China Meteorological Administration,Shanghai 20030,China;Institute of Eco-Chongming,East China Normal University,Shanghai 202162,China;Research Center for China Administrative Division,East China Normal University,Shanghai 202162,China;National Disaster Reduction Center of China,Beijing 100124,China;State Key Laboratory of Estuarine and Coastal Research,East China Normal University,Shanghai,China
机标中图分类号,由域田数据科技根据网络公开资料自动分析生成,仅供学习研究参考。