Regional forecast of the UV index with optimized total ozone prediction using satellite observations over East Asia

Yun Gon Lee, Jhoon Kim, Hi Ku Cho, Chul H. Song

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3 Citations (Scopus)


A regional forecast model of the ultraviolet (UV) index has been developed by using a radiative transfer model and a multiple linear regression model to forecast total ozone over East Asia. This is a difficult and challenging task because of frequent cloud cover and atmospheric aerosols. The new, improved total ozone forecast model was constructed over each grid point in East Asia based on extensive investigation of the correlation between the total ozone and predictors related to the variation in total ozone. Root mean square errors (RMSEs) in the UV index between the forecast and satellite observations from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) for clear sky conditions range from 0.27 to 1.50 with an average of 0.79 in monthly statistics. Although the patterns of the corrected UV index when applying the cloud modification factor (CMF) and the aerosol modification factor (AMF) compare reasonably well with those of the UV index measured with the Ozone Monitoring Instrument (OMI), the performance depends on the accuracy of forecast for cloud and aerosol optical depth (AOD). Additional consideration of surface albedo and cloud optical depth are required to further refine and improve the accuracy of the prediction.

Original languageEnglish
Pages (from-to)6035-6051
Number of pages17
JournalInternational Journal of Remote Sensing
Issue number22
Publication statusPublished - 2009

Bibliographical note

Funding Information:
This work was funded by the Korean Meteorological Administration Research and Development Programme under Grant CATER 2006–3203. We thank the Korean Meteorological Administration (KMA) and National Institute of Meteorological Research (NIMR) for providing data. This research was partially supported by the Brain Korea 21 (BK21) programme (to Jhoon Kim and Yun Gon Lee).

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)


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