Objective tropical cyclone intensity estimation using analogs of spatial features in satellite data

Gholamreza Fetanat, Abdollah Homaifar, Kenneth R. Knapp

Research output: Contribution to journalArticlepeer-review

Abstract

An objective method for estimating tropical cyclone (TC) intensity using historical hurricane satellite data (HURSAT) is developed and tested. This new method, referred to as feature analogs in satellite imagery (FASI), requires a TC's center location to extract azimuthal brightness temperature (BT) profiles from current imagery as well as BT profiles from imagery 6, 12, and 24 h prior. Instead of using regression techniques, the estimated TC intensity is determined from the 10 closest analogs to this TC based on the BT profiles using a k-nearest-neighbor algorithm. The FASI technique was trained and validated using intensity data from aircraft reconnaissance in the North Atlantic Ocean, where the data were restricted to include storms that are over water and south of 458N. This subset comprised 2016 observations from 165 storms during 1988-2006. Several tests were implemented to statistically justify the FASI algorithm using n-fold cross validation. The resulting average mean absolute intensity error was 10.9 kt (50% of estimates are within 10 kt, 1kt 5 0.51ms21) or 8.4mb (50% of estimates are within 8 mb); its accuracy is on par with other objective techniques. This approach has the potential to provide global TC intensity estimates that could augment intensity estimates made by other objective techniques.

Original languageEnglish
Pages (from-to)1446-1459
Number of pages14
JournalWeather and Forecasting
Volume28
Issue number6
DOIs
StatePublished - Dec 2013

Keywords

  • Algorithms
  • Data mining
  • Data processing
  • Remote sensing
  • Satellite observations
  • Tropical cyclones

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