PRISM을 이용한 30 m 해상도의 상세 일별 기온 추정
Estimation of Fine-Scale Daily Temperature with 30 m-Resolution Using PRISM
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참고문헌
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초록
This study estimates and evaluates the daily January temperature from 2003 to2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regressionon Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjustedto 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in termsof bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then comparedwith that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimatingthe temperature over Jeju island, K-PRISM has the lowest bias (−0.85) and RMSE(1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation ofobservation, but tends to underestimate due to a high-discrepancy in mean altitudes betweenthe observation stations and grid points of the 30 m topography. The temperature over SouthKorea derived from K-PRISM represents a detailed spatial pattern of the observed temperature,but generally tends to underestimate with a mean bias of −0.45. In bias terms, the estimationability of K-PRISM differs between grid points, implying that care should be taken whendealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate30 m-resolution temperature over South Korea, and reflect topographically diverse signalswith detailed structure features.
Abstract
This study estimates and evaluates the daily January temperature from 2003 to2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regressionon Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjustedto 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in termsof bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then comparedwith that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimatingthe temperature over Jeju island, K-PRISM has the lowest bias (−0.85) and RMSE(1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation ofobservation, but tends to underestimate due to a high-discrepancy in mean altitudes betweenthe observation stations and grid points of the 30 m topography. The temperature over SouthKorea derived from K-PRISM represents a detailed spatial pattern of the observed temperature,but generally tends to underestimate with a mean bias of −0.45. In bias terms, the estimationability of K-PRISM differs between grid points, implying that care should be taken whendealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate30 m-resolution temperature over South Korea, and reflect topographically diverse signalswith detailed structure features.
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