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Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive SensorsThere is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.
Document ID
20170011598
Document Type
Reprint (Version printed in journal)
Authors
Skofronick-Jackson, Gail M. (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Johnson, Benjamin T. (Maryland Univ. Baltimore County Baltimore, MD, United States)
Munchak, S. Joseph (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
December 7, 2017
Publication Date
February 1, 2013
Publication Information
Publication: IEEE Transactions on Geoscience and Remote Sensing
Volume: 51
Issue: 7
ISSN: 0196-2892
Subject Category
Meteorology and Climatology
Earth Resources and Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN26814
Distribution Limits
Public
Copyright
Other
Keywords
remote sensing
water resources
clouds
earth