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Environmental Engineering Research 2009;14(2): 88-94. DOI: https://doi.org/10.4491/eer.2009.14.2.088
An Attempt of Estimation of Annual Fog Frequency over Gyeongsangbuk-do of Korea Using Weather Generator MM5
Do-Yong Kim1, Jai-Ho Oh2, Jin-Young Kim2, Purnendranath Sen2, and Tae-Kook Kim3
1Center for Atmospheric Sciences & Earthquake Research, Korea Meteorological Administration, Busan, Korea
2Department of Environmental Atmospheric Sciences, Pukyong National University, Busan, Korea
3Water Resources Operations Center, Korea Water Resources Corporation, Daejeon, Korea
Corresponding Author: Do-Yong Kim ,Tel: +82-51-629-7311, Fax: +82-51-629-7315, Email: dykim@cater.re.kr
Received: September 6, 2008;  Accepted: March 7, 2009.
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In this study an attempt has been made to predict the annual foggy days over Gyeongsangbuk-do of Korea, using the regional mesoscale model (MM5). The annual meteorological conditions are simulated, and the annual and seasonal foggy days are predicted from the simulated results based on the seasonal and spatial information of the observed meteorological characteristics for fog occurrence such as wind speed, relative humidity, and temperature. Most of observed inland fog over Gyeongsangbuk-do occurs in autumn under the meteorological conditions such as a calm, a high temperature range (above 10°C), and a high relative humidity (above 85%). The predicted results show the various foggy days, about 10~60 days, depending on the season and the site locations. The predicted annual foggy days at inland sites are about 30~60 days, but at coastal sites, about 10~ 20 days. Also, a higher frequency of fog occurrence at inland sites is shown in autumn (about 60% of the annual foggy days). Otherwise, a higher frequency of fog occurrence at coastal sites is shown in summer (about 60% of the annual foggy days), unlike the inland. These annual foggy days and their seasonal variations agree reasonably well with the observed values. It can be concluded that it is possible to predict the occurrence of annual or seasonal foggy days by MM5.
Keywords: Annual and seasonal foggy days | Meteorological characteristics | Numerical prediction | MM5
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