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Improving the Usage of the Korea Meteorological Administration`s Digital Forecasts in Agriculture: IV. Estimation of Daily Sunshine Duration and Solar Radiation Based on `Sky Condition` Product
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 Title & Authors
Improving the Usage of the Korea Meteorological Administration`s Digital Forecasts in Agriculture: IV. Estimation of Daily Sunshine Duration and Solar Radiation Based on `Sky Condition` Product
Kim, Soo-ock; Yun, Jin I.;
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 Abstract
Information on sunshine duration and solar radiation are indispensable to the understanding of crop growth and development. Yet, relevant variables are not available in the Korea Meteorological Administration`s (KMA) digital forecast. We proposed the methods of estimating sunshine duration and solar radiation based on the `sky condition` of digital forecast products and validated using the observed data. The sky condition values (1 for clear, 2 for partly cloudy, 3 for cloudy, and 4 for overcast) were collected from 22 weather stations at 3-hourly intervals from August 2013 to July 2015. According to the observed relationship, these data were converted to the corresponding amount of clouds on the 0 to 10 scale (0 for clear, 4 for partly cloudy, 7 for cloudy, and 10 for overcast). An equation for the cloud amount-sunshine duration conversion was derived from the 3-year observation data at three weather stations with the highest clear day sunshine ratio (i.e., Daegwallyeong, Bukgangneung, and Busan). Then, the estimated sunshine hour data were used to run the Angstrom-Prescott model which was parameterized with the long-term KMA observations, resulting in daily solar radiation for the three weather stations. Comparison of the estimated sunshine duration and solar radiation with the observed at those three stations showed that the root mean square error ranged from 1.5 to 1.7 hours for sunshine duration and from 2.5 to for solar radiation, respectively.
 Keywords
Sunshine duration;Solar radiation;Sky condition;Cloud amount;Digital forecast;
 Language
Korean
 Cited by
1.
Feasibility of the Lapse Rate Prediction at an Hourly Time Interval, Korean Journal of Agricultural and Forest Meteorology, 2016, 18, 1, 55  crossref(new windwow)
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