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Last modified
7/28/2009 2:32:30 PM
Creation date
1/8/2008 12:16:45 PM
Metadata
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Weather Modification
Sponsor Name
USBR, Technical Service Center, River Systems 7 Meteorology Group
Project Name
Use of NEXRAD WSR-88D Radar Snow Accumulations Algorith in the GCIP LSA-NC
Title
Use of NEXRAD WSR-88D Radar Snow Accumulations Algorith in the GCIP LSA-NC
Prepared For
USBR Technical Service Center
Prepared By
Arlin B. Super
Date
1/1/1998
State
MN
Weather Modification - Doc Type
Report
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<br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br /> <br />Considerable programming and testing were needed to produce a version of the BAA <br />that could use Level III data. The Level III product is in the form of binary files <br />intended for visual display, not for use as discrete digital dBZ values. Each Level <br />III reflectivity interval had to be assigned a dBZ value. Use of midpoints was <br />shown to be too simplistic for greater reflectivities. However, the BAA can now run <br />successfully with archived Level III reflectivity files. <br /> <br />Parallel runs of the SAA, using Level II and Level III reflectivities as input, were <br />made for five major Minnesota snow storms, one with mixed rain and snow. The <br />degree of agreement was shown to be quite good, especially at ranges less than 150 <br />km where radar estimates are most reliable. Most Level III runs had area average <br />SWE accumulations within 10 percent or less of the standard Level II runs for the <br />same volume scans, at least within 150 km range. These results indicate that use <br />of archived Level III data from Minnesota snow storms provides quite reasonable <br />SWE estimates using Level II estimates as the standard. <br /> <br />The next step in this applied research will be to continue work on the VPS range <br />correction scheme so that the SAA can apply appropriate corrections for all ranges <br />between about 50 and 150 km and perhaps farther. It would, of course, be very <br />desirable to test this scheme against "ground truth" SWE observations. Accurate <br />surface measurements of snowfall, either of depth or SWE, are difficult to find. <br />However, attempts will be made to find the means to test the SAA range correction <br />scheme against some surface observations. <br /> <br />5. REFERENCES <br /> <br />Andrieu, H. and J.D. Creutin, 1995: Identification of Vertical Profiles of Radar <br />. Reflectivity for Hydrological Applications Using an Inverse Method: Part I: <br />Formulation. Journal of Applied Meteorology, 34, 225-239. <br /> <br />Crum, T.D., R. L. Alberty and D. W. Burgess, 1993: Recording, Archiving and <br />Using WSR-88D Data. Bulletin of the American Meteorological Society, 74,645- <br />653. <br /> <br />Joss, J. and R. Lee, 1995: The Application of Radar-Gauge Comparisons to <br />Operational Precipitation Profile Corrections. Journal of Applied Meteorology, <br />34, 2612-2630. <br /> <br />Joss, J. and A. Waldvogel, 1989: Precipitation Estimates and Vertical Reflectivity <br />Profile Corrections. Pre prints, 24th Conference on Radar Meteorology, American <br />Meteorological Society, Tallahassee, FL, March 27-31,682-688. <br /> <br />Joss, J. and A. Waldvogel, 1990: Precipitation Measurements and Hydrology. Radar <br />in Meteorology, D. Atlas, Ed., American Meteorological Society, 577-606. <br /> <br />23 <br />
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