Multispectral Passive Microwave Correlations with an Antecedent Precipitation Index Using the Nimbus 7 SMMR.

Abstract

Analysis of the passive microwave brightness temperatures from the Scanning Multichannel Microwave Radiometer (SMMR) aboard Nimbus 7 can infer soil moisture through an Antecedent Precipitation Index (API). This investigation involves correlation analysis between five passive microwave brightness temperature wavelengths (0.81, 1.36, 1.66, 2.80, and 4.54 cm) in two polarizations spanning a one year period. Data analysis was done by a temporal and areal approach, for both the normalized brightness temperatures and the differences in the polarized channels, for all five SMMR wavelengths. Three transformations of the polarized brightness temperatures were used to evaluate the ability of the microwave data to infer soil moisture through correlations with the API. These transformations included the horizontally polarized normalized brightness temperature, the difference between the polarized channels, and the normalized brightness temperature, the difference between the polarized channels, and the normalized difference between the polarized channels, and the normalized difference between the polarized channels. It was evident that all three indices had very high correlations with API, however the correlation coefficient for the normalized brightness temperature data consistently was slightly higher than the values for the other two indices. The conclusion is that polarized data can infer soil moisture through the API without the use of surface data. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1984
Accession Number
ADA145419

Entities

People

  • G. D. Wilke

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Climate Change
  • Computer Programs
  • Correlation Analysis
  • Data Analysis
  • Databases
  • Dielectric Permittivity
  • Geography
  • Information Science
  • Meteorological Satellites
  • Meteorology
  • Precipitation
  • Radiation
  • Remote Sensing
  • Statistical Analysis
  • Statistics
  • Surveys
  • United States

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  • Atmospheric Science/Meteorology
  • Spectroscopy.

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  • AI & ML