Satellite Sounding Applications at the Synoptic Scale and as Input to Global Numerical Models.

Abstract

This Final Report is a summary which describes previously reported research done for AFGL under this contract. It also includes a report of the latest research results. The new results include a new statistical procedure for retrieving water vapor profiles from satellite radiances. The statistical tools fo empirical orthogonal function (EOF) analysis and clustering were used to define types of vertical distributions of water vapor. The profile types are used as a basis for classifying soundings, and each class is shown to be characteristic of certain types of weather features. Multiple regression is used to retrieve approximate precipitable water using satellite-derived brightness temperatures simulated for the DMSP SSH-2 infrared sounder. Discriminant analysis is used to retrieve the type of vertical distribution in the water vapor profile. Channel selection is used for optimizing both the regression and the discrimination. It is shown that stratification of soundings by total water content improves discrimination skill. The potential for using the retrieval scheme in numerical modeling and in subjective forecasting is discussed. In addition a new computer program for executing water vapor profile retrievals is presented. The handling of sounding zenith angle variations and cloud contamination are dealt with specifically. A program listing is provided. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1983
Accession Number
ADA148012

Entities

People

  • A. E. Lipton
  • D. W. Hillger
  • T. H. Vonder Haar

Organizations

  • Colorado State University

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Artificial Satellites
  • Brightness
  • Clustering
  • Computer Programs
  • Computers
  • Contamination
  • Contracts
  • Delphi Method
  • Discriminant Analysis
  • Discrimination
  • Radiance
  • Stratification
  • Vapors
  • Water Vapor

Fields of Study

  • Environmental science

Readers

  • Computer Science.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Spectroscopy.

Technology Areas

  • Space