tropical cyclone precipitation estimation technique using geostationary satellite data
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tropical cyclone precipitation estimation technique using geostationary satellite data by LeRoy E. Spayd

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Published by U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service in Washington, D.C .
Written in English


  • Precipitation forecasting.,
  • Cyclones.,
  • Meteorological satellites.

Book details:

Edition Notes

StatementLeRoy E. Spayd, Jr., Roderick A. Scofield.
SeriesNOAA technical memorandum NESDIS -- 5.
ContributionsScofield, Roderick A., United States. National Environmental Satellite, Data, and Information Service.
The Physical Object
Paginationiii, 36 p. :
Number of Pages36
ID Numbers
Open LibraryOL15315568M

Download tropical cyclone precipitation estimation technique using geostationary satellite data


The objective of this study is therefore to analyze the performance of rainfall estimation from TRMM 3BV7 (henceforth TRMM) using rain gauge data in Malaysia, specifically from the Pahang river. In November the TRMM (Tropical Rainfall Measuring Mission) satellite was launched (3). This satellite carries all the above (passive microwave, infrared, and visible), plus an active radar. This combination provides a far superior estimate of rainfall within 35° from the equator.. The Figure on the right shows a 3D slice through tropical cyclone Susan east of Fiji (the green specks on.   The Advanced Dvorak Technique: Continued Development of an Objective Scheme to Estimate Tropical Cyclone Intensity Using Geostationary Infrared Satellite Imagery Weather and Forecasting, 22 (), pp. Cited by: 1. the Tropical Rainfall Measuring Mission satellite algorithm 3B42, version 6 (3B42), Climate Prediction Center morphed (CMORPH) product, and one based on the Geostationary Meteorological Satellite.

A relatively simple method to estimate tropical cyclone wind radii from routinely available information including storm information (location, motion, and intensity) and an estimate of the tangential wind at km (i.e., V) that is a proxy for TC size (i.e., R5) has been described. The algorithm is derived using geostationary IR data from cases from 87 tropical systems in the Atlantic and east Pacific Ocean basins during the – hurricane seasons that had corresponding aircraft data available. The algorithm is tested on 50 cases from seven tropical storms and hurricanes during the season. This blended geostationary-microwave technique is oriented towards rapid-update operational usage in quantitative precipitation forecasting, numerical weather prediction models, and to estimate.   In addition to the Dvorak-type techniques, researchers have explored other tropical cyclone intensity estimation techniques based on geostationary satellite data. For example, Kossin et al. () estimated the maximum wind speed radius and critical wind radius using linear regression techniques based on infrared satellite image data.

THE DVORAK TROPICAL CYCLONE INTENSITY ESTIMATION TECHNIQUE A Satellite-Based Method that Has Endured for over 30 Years This insight, which expresses itself by what is called Imagination, is a very high sort of seeing, which does not come by study, but by the intellect being where and what it sees, by sharing the path, or circuit of things through.   The technique presented here for measuring the wind radii is objective and, because it uses the Geostationary Operational Environment Satellite imagery as its primary predictor, wind radii estimates can be made every half hour although it is likely that smoothing the data to a 3- or 6-h interval will be of the most use operationally. The Dvorak technique is a method using enhanced Infrared and/or visible satellite imagery to quantitatively estimate the intensity of a tropical system. Cloud patterns in satellite imagery normally show an indication of cyclogenesis before the storm reaches tropical storm intensity. Indications of.   This chapter provides a review on satellite remote sensing of tropical cyclones (TCs). Applications of satellite remote sensing from geostationary (GEO) and low earth orbital (LEO) platforms, especially from passive microwave (PMW) sensors, are focused on TC detection, structure, and intensity analysis as well as precipitation patterns. The impacts of satellite remote sensing on .