Comparison of snowfall estimates from the NASA CloudSat Cloud Profiling Radar and NOAA/NSSL Multi-Radar Multi-Sensor System

被引:43
作者
Chen, Sheng [1 ,2 ,3 ,4 ]
Hong, Yang [3 ,4 ,5 ]
Kulie, Mark [6 ,7 ]
Behrangi, Ali [8 ]
Stepanian, Phillip M. [9 ]
Cao, Qing [10 ]
You, Yalei [11 ]
Zhang, Jian [12 ]
Hu, Junjun [13 ]
Zhang, Xinhua [14 ]
机构
[1] Sun Yat Sen Univ, Sch Atmospher Sci, 135 West Xingang Rd, Guangzhou 510275, Guangdong, Peoples R China
[2] Sun Yat Sen Univ, Guangdong Prov Key Lab Climate Change & Nat Disas, Guangzhou 510275, Guangdong, Peoples R China
[3] Univ Oklahoma, Adv Radar Res Ctr, 120 David L Boren Blvd,Suite 4610, Norman, OK 73072 USA
[4] Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73019 USA
[5] Tsinghua Univ, Dept Hydraul Engn, Beijing, Peoples R China
[6] Univ Wisconsin, Dept Atmospher & Ocean Sci, Madison, WI USA
[7] Univ Wisconsin, Space Sci & Engn Ctr, Madison, WI USA
[8] CALTECH, Jet Prop Lab, Pasadena, CA USA
[9] Univ Oklahoma, Sch Meteorol, Norman, OK 73019 USA
[10] Enterprise Elect Corp, Res & Innovat Div, Norman, OK 73072 USA
[11] CMNS Earth Syst Sci Interdisciplinary Ctr, M Sq Res Pk, MD USA
[12] NOAA, Natl Severe Storms Lab, Norman, OK 73069 USA
[13] Univ Oklahoma, Sch Comp Sci, Norman, OK 73072 USA
[14] Sichuan Univ, State Key Lab Hydraul & Mt River Engn, Chengdu 610065, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
CloudSat; NEXRAD; Radar; Snowfall; CONTINENTAL UNITED-STATES; REAL-TIME ALGORITHM; QPE ERRORS; PRECIPITATION; PRODUCT;
D O I
10.1016/j.jhydrol.2016.07.047
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The latest global snowfall product derived from the CloudSat Cloud Profiling Radar (2C-SNOW-PROFILE) is compared with NOAA/National Severe Storms Laboratory's Multi-Radar Multi-Sensor (MRMS/Q3) system precipitation products from 2009 through 2010. The results show that: (1) Compared to Q3, CloudSat tends to observe more extremely light snowfall events (<0.2 mm/h) and snowfall rate (SR) between 0.6 to 1 mm/h, and detects less snowfall events with SR between 0.2-0.5 mm/h. (2) CloudSat identifies 69.40% of snowfall events detected by Q3 as certain snow and 10% as certain mixed. When possible snow, possible mixed, and certain mixed precipitation categories are assumed to be snowfall events, CloudSat has a high snowfall POD (86.10%). (3) CloudSat shows less certain snow precipitation than Q3 by 26.13% with a low correlation coefficient (0.41) with Q3 and a high RMSE (0.6 mm/h). (4) With Q3 as reference, CloudSat underestimates (overestimates) certain snowfall when the bin height of detected snowfall events are below (above) 3 km, and generally overestimates light snowfall (<1 mm/h) by 7.53%, and underestimates moderate snowfall (1-2.5 mm/h) by 42.33% and heavy snowfall (>= 2.5 mm/h) by 68.73%. (5) The bin heights of most (99.41%) CloudSat surface snowfall events are >1 km high above the surface, whereas 76.41% of corresponding Q3 observations are low below 1 km to the near ground surface. This analysis will provide helpful reference for CloudSat snowfall estimation algorithm developers and the Global Precipitation Measurement (GPM) snowfall product developers to understand and quantify the strengths and weaknesses of remote sensing techniques and precipitation estimation products. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:862 / 872
页数:11
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