TY - JOUR
T1 - Comparison of snowfall estimates from the NASA CloudSat Cloud Profiling Radar and NOAA/NSSL Multi-Radar Multi-Sensor System
AU - Chen, Sheng
AU - Hong, Yang
AU - Kulie, Mark
AU - Behrangi, Ali
AU - Stepanian, Phillip M.
AU - Cao, Qing
AU - You, Yalei
AU - Zhang, Jian
AU - Hu, Junjun
AU - Zhang, Xinhua
N1 - Funding Information:
This work was supported in part by the Hydrometeorology and Remote Sensing (HyDROS) Laboratory at The University of Oklahoma, in part by the National Natural Science Foundation of China (No. 41361022 and No. 41171020 ), the Open Fund from State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University (No. SKHL1310 and No. SKHL1501 ). Part of the research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. A.B. was supported by NASA New Investigator Program (NIP) and Energy and Water Cycle Study (NEWS) awards. Thanks are given to Youcun Qi from NOAA/NSSL for his great help in VPR analysis during revision process, to Dr. Benjamin Johnson from Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center for his constructive advice for this paper in early version, and to Mr. Nicholas Carr from The University of Oklahoma for assistant proofreading early versions of this manuscript.
Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2016/10/1
Y1 - 2016/10/1
N2 - 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.
AB - 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.
KW - CloudSat
KW - NEXRAD
KW - Radar
KW - Snowfall
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U2 - 10.1016/j.jhydrol.2016.07.047
DO - 10.1016/j.jhydrol.2016.07.047
M3 - Article
AN - SCOPUS:84992445173
SN - 0022-1694
VL - 541
SP - 862
EP - 872
JO - Journal of Hydrology
JF - Journal of Hydrology
ER -