Spatial Resolution Enhancement of SSM/I Microwave Brightness Temperatures and Its Impact on Rainfall Retrieval Algorithms

Abstract

In this study the impact of spatial resolution enhancement is tested on estimates of typhoon rainfall using microwave measurements from the Special Sensor Microwave/Imager (SSM/I). Passive microwave estimates of rainfall are susceptible to errors from non-complete beam filling. The SSM/I ground footprints for the 19, 22, and 37 GHz channels have considerable overlap and thus deconvolution techniques can be applied to enhance spatial resolution. A backus-Gilbert matrix transform approach is utilized to accomplish the deconvolution so as to minimize noise amplification as suggested by Stogryn (1978). Various validation procedures are performed to demonstrate the effectiveness of the method. The deconvolution scheme is evaluated in terms of its impact on integrated rainfall throughout the life cycle of a number of tropical storms which occurred during the 1987 hurricane and typhoon season. This evaluation was performed for a single frequency emission algorithm, a single frequency scattering algorithm, and three multiple frequency algorithms, each with different properties and scientific approaches. While rainfall patterns detected by all algorithms were qualitatively enhanced, quantitative responses were different for each algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1991
Accession Number
ADA254382

Entities

People

  • Michael R. Farrar

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artificial Satellites
  • Cross Polarization
  • Cyclones
  • Data Sets
  • High Resolution
  • Measuring Instruments
  • Meteorological Satellites
  • Meteorology
  • Microwave Frequency
  • Oceans
  • Radiative Transfer
  • Remote Sensing
  • Temperature Gradients
  • Tropical Cyclones
  • Universities

Fields of Study

  • Environmental science

Readers

  • Approximation Theory.
  • Atmospheric Remote Sensing.
  • Atmospheric Science/Meteorology