DocumentCode
1503162
Title
Satellite Retrievals of Arctic and Equatorial Rain and Snowfall Rates Using Millimeter Wavelengths
Author
Surussavadee, Chinnawat ; Staelin, David H.
Author_Institution
Res. Lab. of Electron., Massachusetts Inst. of Technol., Cambridge, MA, USA
Volume
47
Issue
11
fYear
2009
Firstpage
3697
Lastpage
3707
Abstract
A new global precipitation retrieval algorithm for the millimeter-wave Advanced Microwave Sounding Unit is presented that also retrieves Arctic precipitation rates over surface snow and ice. This algorithm improves upon its predecessor by excluding some surface-sensitive channels and by reducing the number of principal components (PCs) used to represent those that remain. The training sets were also modified to better represent cold regions. The algorithm still incorporates conversion of brightness temperatures to nadir, spatial filtering to better detect pixels scattering near 54 GHz, PC filtering of surface effects, and use of separate neural networks trained with the fifth-generation National Center for Atmospheric Research/Penn State Mesoscale Model (MM5) for land and sea, where warm and cold ocean are now treated differently. The validity of the snowfall detections is supported by nearly coincident CloudSat radar observations, and the physics of the model is largely validated by the reasonable agreement in annual precipitation obtained for 231 globally distributed rain gauges, including many at latitudes where snowfall dominates. Observed annual global precipitation statistics are also presented to permit comparisons with other algorithms and sensors.
Keywords
atmospheric techniques; geophysical signal processing; hydrological techniques; neural nets; principal component analysis; rain; remote sensing; snow; Advanced Microwave Sounding Unit; Arctic precipitation rates; Arctic snowfall rate; CloudSat radar observations; MM5; National Center for Atmospheric Research; Penn State Mesoscale Model; brightness temperature conversion; equatorial rain rate; fifth generation NCAR-PSU Mesoscale Model; global precipitation retrieval algorithm; millimeter wave AMSU; millimeter wavelengths; principal component filtering; satellite based precipitation rate retrievals; spatial filtering; surface ice; surface snow; trained neural networks; Advanced Microwave Sounding Unit (AMSU); Arctic; microwave precipitation estimation; precipitation; remote sensing; satellite; snow;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/TGRS.2009.2029093
Filename
5290107
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