• Title/Summary/Keyword: Forest meteorology

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Estimation and Evaluation of Reanalysis Air Temperature based on Mountain Meteorological Observation (산악기상정보 융합 기반 재분석 기온 데이터의 추정 및 검증)

  • Sunghyun, Min;Sukhee, Yoon;Myongsoo, Won;Junghwa, Chun;Keunchang, Jang
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.4
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    • pp.244-255
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    • 2022

  • This study estimated and evaluated the high resolution (1km) gridded mountain meteorology data of daily mean, maximum and minimum temperature based on ASOS (Automated Surface Observing System), AWS (Automatic Weather Stations) and AMOS (Automatic Mountain Meteorology Observation System) in South Korea. The ASOS, AWS, and AMOS meteorology data which were located above 200m was classified as mountainous area. And the ASOS, AWS, and AMOS meteorology data which were located under 200m was classified as non-mountainous area. The bias-correction method was used for correct air temperature over complex mountainous area and the performance of enhanced daily coefficients based on the AMOS and mountainous area observing meteorology data was evaluated using the observed daily mean, maximum and minimum temperature. As a result, the evaluation results show that RMSE (Root Mean Square Error) of air temperature using the enhanced coefficients based on the mountainous area observed meteorology data is smaller as 30% (mean), 50% (minimum), and 37% (maximum) than that of using non-mountainous area observed meteorology data. It indicates that the enhanced weather coefficients based on the AMOS and mountain ASOS can estimate mean, maximum, and minimum temperature data reasonably and the temperature results can provide useful input data on several climatological and forest disaster prediction studies.

  • https://doi.org/10.5532/KJAFM.2022.24.4.244 인용 PDF KSCI