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Development of Snowfall Retrieval Algorithm by Combining Measurements from CloudSat, AQUA and NOAA Satellites for the Korean Peninsula

  • Kim, Young-Seup (Department of Spatial Information Engineering, Pukyong National University) ;
  • Kim, Na-Ri (Department of Spatial Information Engineering, Pukyong National University) ;
  • Park, Kyung-Won (Department of Spatial Information Engineering, Pukyong National University)
  • Received : 2011.05.26
  • Accepted : 2011.06.24
  • Published : 2011.06.30

Abstract

Cloudsat satellite data is sensitive to snowfall and collected during each month beginning with Dec 2007 and ending Feb 2008. In this study, we attempt to develop a snowfall retrieval algorithm using a combination of radiometer and cloud radar data. We trained data from the relation between brightness temperature measurements from NOAA's Advanced Microwave Sounder Unit-B(AMSU-B) and the radar reflectivity of the 2B-GEOPROF product from W-band(94 GHz) cloud radar onboard Cloudsat and applied it to the Korea peninsula. We use a principal components analysis to quantify the variations that are the result of the radiometric signatures of snowfall from those of the surface. Finally, we quantify the correlation between the higher principal component (orthogonal to surface variability) of the microwave radiances and the precipitation-sensitive CloudSat radar reflectivities. This work summarizes the results of applying this approach to observations over the East Sea during Feb. 2008. The retrieved data show reasonable estimation for snowfall rate compared with Cloudsat vertical image.

Keywords

Acknowledgement

Supported by : NRF

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