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contributor authorWen, Yixin
contributor authorKirstetter, Pierre
contributor authorGourley, J. J.
contributor authorHong, Yang
contributor authorBehrangi, Ali
contributor authorFlamig, Zachary
date accessioned2017-06-09T17:17:28Z
date available2017-06-09T17:17:28Z
date issued2017
identifier issn1525-755X
identifier otherams-82499.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4225619
description abstractnow is important to water resources and is of critical importance to our society. Ground weather radar-based snowfall observations have been highly desirable for large-scale weather monitoring and water resources applications. This study conducts an evaluation of the Multi-Radar Multi-Sensor (MRMS) quantitative estimates of snow rate using the Snow Telemetry (SNOTEL) daily snow water equivalent (SWE) datasets. A detectability evaluation shows that MRMS is limited in detecting very light snow (daily snow accumulation < 5 mm) because of the quality control module in MRMS filtering out weak signals (<5 dBZ). For daily snow accumulation greater than 10 mm, MRMS has good detectability. The quantitative comparisons reveal a bias of -77.37 % between MRMS and SNOTEL. A majority of the underestimation bias occurs in relatively warm conditions with surface temperatures in the range of -10 to 0°C. A constant reflectivity-to-SWE intensity relationship does not capture the snow mass flux increase associated with denser snow particles at these relatively warm temperatures. There is no clear dependence of the bias on radar beam height. The findings in this study indicate that further improvement in radar snowfall products might occur by deriving appropriate reflectivity-to-SWE relationships considering the degree of riming and snowflake size.
publisherAmerican Meteorological Society
titleEvaluation of MRMS snowfall products over the western United States
typeJournal Paper
journal volume018
journal issue006
journal titleJournal of Hydrometeorology
identifier doi10.1175/JHM-D-16-0266.1
journal fristpage1707
journal lastpage1713
treeJournal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 006
contenttypeFulltext


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