Marine Boundary Layer Depth and Relative Humidity Estimates Using Multispectral Satellite Measurements

Abstract

A technique is presented to estimate surface relative humidity and boundary layer depth from multispectral satellite measurements using the AVHRR sensor on TIROS-N generation satellites. A sensitivity study quantifies the effect of a combination of input measurement errors of sea-surface temperature, optical depth and total water vapor used in the technique to produce outputs of surface relative humidity and boundary layer depth under simulated conditions and model atmospheres. Technique verification is then accomplished with satellite data compared to ship and aircraft vertical soundings and sea-surface temperature measurements. The root mean square differences between the surface relative humidity/boundary layer depth satellite-measured estimates and verified measurements are 6% and 75 m respectively. Finally, synoptic-scale mapping of the surface relative humidity and boundary layer depth fields based on the satellite derived estimates is accomplished with monochromatic and color enhanced satellite images. Horizontal variability of surface relative humidity and boundary layer depth on the order of kilometers can be visually detected from these images. Keywords: Remote sensing; MABL(Marine Boundary Layer); Marine atmospheres; Air ocean interface; Advanced very high resolution radiometers; Theses.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1988
Accession Number
ADA196525

Entities

People

  • Steven P. Smolinski

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Boundary Layer
  • Humidity
  • Lapse Rate
  • Layers
  • Measurement
  • Meteorological Phenomena
  • Meteorology
  • Remote Sensing
  • Satellite Imaging
  • Scattering
  • Sea Surface Temperature
  • Statistical Analysis
  • Surface Properties
  • Surface Temperature
  • Three Dimensional
  • Water Vapor

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Computational Modeling and Simulation

Technology Areas

  • Space