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作 者:YUE Handong DOU Tingfeng LI Shutong LI Chuanjin DING Minghu XIAO Cunde
机构地区:[1]College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China [2]State Key Laboratory of Cryospheric Science,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China [3]State Key Laboratory of Severe Weather and Institute of Tibetan Plateau&Polar Meteorology,Chinese Academy of Meteorological Sciences,Beijing 100081,China [4]State Key Laboratory of Earth Surface Processes and Resource Ecology,Beijing Normal University,Beijing 100875,China
出 处:《Advances in Polar Science》2021年第4期327-340,共14页极地科学进展(英文版)
基 金:This study is funded by the National Key Research and Development Program of China(Grant no.2018YFC1406103);the National Nature Science Foundation of China(Grant no.NSFC 41971084).
摘 要:The effects of various precipitation types,such as snow,rain,sleet,hail and freezing rain,on regional hydrology,ecology,snow and ice surfaces differ significantly.Due to limited observations,however,few studies into precipitation types have been conducted in the Arctic.Based on the high-resolution precipitation records from an OTT Parsivel^(2) disdrometer in Utqiaġvik,Alaska,this study analysed variations in precipitation types in the Alaskan Arctic from 15 May to 16 October,2019.Results show that rain and snow were the dominant precipitation types during the measurement period,accounting for 92%of the total precipitation.In addition,freezing rain,sleet,and hail were also observed(2,4 and 11 times,respectively),accounting for the rest part of the total precipitation.The records from a neighbouring U.S.Climate Reference Network(USCRN)station equipped with T-200B rain gauges support the results of disdrometer.Further analysis revealed that Global Precipitation Measurement(GPM)satellite data could well characterise the observed precipitation changes in Utqiaġvik.Combined with satellite data and station observations,the spatiotemporal variations in precipitation were verified in various reanalysis datasets,and the results indicated that ECMWF Reanalysis v5(ERA5)could better describe the observed precipitation time series in Utqiaġvik and the spatial distribution of data in the Alaskan Arctic.Modern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2)overestimated the amount and frequency of precipitation.Japanese 55-year Reanalysis(JRA-55)could better simulate heavy precipitation events and the spatial distribution of the precipitation phase,but it overestimated summer snowfall.
关 键 词:DISDROMETER precipitation types reanalysis datasets data comparison
分 类 号:P412[天文地球—大气科学及气象学] P426.6
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