• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.135-143
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• 2020

Shortwave radiation and sunshine hours (SHOUR) are important variables having many applications, including crop growth. However, observational data for these variables have low horizontal resolution, rendering its application to related research and decision making on f arming practices challenging. In the present study, hourly solar radiation data were physically generated using the Land-Atmosphere Modeling Package (LAMP) at the National Center f or Agro-Meteorology, and then daily SHOUR fields were calculated through statistical downscaling. After data quality evaluation, including case studies, the SHOUR data were added to the existing publically accessible LAMP daily database. The LAMP daily dataset, newly updated with SHOUR, has been provided operationally as input data to the "Gyeonggi-do Agricultural Drought Prediction System," which predicts agricultural weather disasters and field crop growth status.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2018.06a
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• pp.121-121
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• 2018

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2018.06a
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• pp.120-120
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• 2018

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2017.11a
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• pp.71-71
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• 2017

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2017.11a
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• pp.72-72
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• 2017

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.118-119
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• 2019

• Atmosphere
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• v.22 no.1
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• pp.129-135
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• 2012

This study restores rainfall measurements taken with the Chugugi (rain gauge) at Wonju, Hamheung, and Haeju from the Deungnok (government records from the Joseon Dynasty). We restored rainfall data corresponding to a total of 9, 13, and 18 years for Wonju, Hamheung, and Haeju, respectively. Based on the restored data, we reconstructed monthly rainfall data. Restoration was most successful for the rainy season months of June, July and August. The restored rainfall data were compared with the summer rainfall data for Seoul as recorded by the Seungjeongwon (Royal Secretariat). In June, the variation in the restored rainfall data was similar to that of the Seungjeongwon data for Seoul. In July and August, however, the variations in the reconstructed data were markedly different from those in the Seoul data (Seungjeongwon). In the case of the worst drought in the summer of 1888, a substantial shortage of rainfall was found in both the Seungjeongwon data for Seoul and the restored data for the three regional locations.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.290-291
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• 2019

• Atmosphere
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• v.14 no.1
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• pp.4-23
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• 2004

To monitor the world's oceans and understand the role of the oceans for climate change, an Array for Real-time Geostrophic Oceanography (ARGO) program has been carried out since year 2000. Autonomous profiling floats of about 820 are reporting the vertical temperature, salinity, and pressure profiles of the upper 2000 m underwater at regular time intervals. Meteorological Research Institute (METRI) of Korea Meteorological Administration (KMA) launched 45 floats at the East Sea and the western Pacific to understand characteristics of water properties and develop the global ocean observation system as a part of international cooperation project. In this study, we introduce ARGO program, METRI-ARGO and the features of APEX float itself and their data formats. We also describe the significant points to be considered for using ARGO data.