Water Vapor Profile Retrievals at 183 GHz: Land vs. Ocean and Clear vs. Cloudy,

Abstract

This report summarizes the results of an initial study to investigate the retrieval of water vapor profiles over land from several combinations of millimeter wave frequency channels, to compare the results obtained over land to performance expected over the ocean, and to assess the feasibility of obtaining cloud information from 183 GHz measurements. Brightness temperatures were simulated for four hypothetical millimeter wave moisture sounders using a recently developed sensor simulation model. Channel frequency selecton was investigated by comparing results from individual instrumental channel sets. In performing these simulations atmospheric data sets consisting of 400 radiosonde temperature and moisture profiles obtained over both land and ocean were used. The effect of beam-filling cloud on brightness temperatures was evaluated by incorporating physical cloud submodles. For representative cloud types within the simulation algorithm. Retrievals of vertical moisture profiles were accomplished by implementing a general statistical regression method which minimizes the mean square of interest. Retrieval statistics evaluated from a dependent subset of channel brightness temperatures and vertical water vapor profiles were applied subsequently to infer water vapor profiles from an independent set of brightness temperatures.

Document Details

Document Type
Technical Report
Publication Date
May 01, 1985
Accession Number
ADA170033

Entities

People

  • G. Deblonde
  • R. G. Isaacs

Organizations

  • Atmospheric and Environmental Research, Inc

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Brightness
  • Data Sets
  • Frequency
  • Measurement
  • Millimeter Waves
  • Moisture
  • Radiosondes
  • Simulations
  • Statistics
  • Vapors
  • Water Vapor

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Computational Modeling and Simulation

Technology Areas

  • 5G
  • 5G - Internet of Things
  • AI & ML
  • AI & ML - Bayesian Inference