Application of genetic algorithm in atmospheric carbon dioxide concentration retrieval

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper introduces the basic theory and method of carbon dioxide (CO2) retrieval. The key step is to search for the optimal solution and the random search algorithm Genetic Algorithm (GA) which can effectively avoid the local optimization. We first investigate the basic principles of GA in CO2 retrieval and then design the corresponding encoding and decoding methods as well as the fitness function. This newly-developed GA is further applied to retrieve the atmospheric CO2 concentration using Atmospheric Infrared Sounder (AIRS) observations from January 2006 to December 2008 centered at 20°N, 144°E. Compared to the aircraft measurements, the GA retrieval yields the small root mean square error of 1.13 ppmv and reproduces good results with the observed seasonal cycle.

Original languageEnglish
Title of host publicationRemote Sensing and Modeling of Ecosystems for Sustainability X
PublisherSPIE
ISBN (Print)9780819497192
DOIs
StatePublished - 2013
EventRemote Sensing and Modeling of Ecosystems for Sustainability X - San Diego, CA, United States
Duration: 26 Aug 201329 Aug 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8869
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceRemote Sensing and Modeling of Ecosystems for Sustainability X
Country/TerritoryUnited States
CitySan Diego, CA
Period26/08/1329/08/13

Keywords

  • Genetic Algorithm
  • carbon dioxide
  • retrieval

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