• Atmosphere
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• v.29 no.5
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• pp.585-597
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• 2019

This study evaluates the performance of Weather Research and Forecasting (WRF) model in simulating temperature over the COordinated Regional climate Downscaling EXperiment-East Asia (CORDEX-EA) Phase 2 domain for the reference period (1981~2005), and assesses the changes in temperature and its extremes in the mid-21st century (2026~2050) under global warming based on Representative Concentration Pathway (RCP) scenarios. MPI-ESM-LR forced by two RCP scenarios (RCP2.6 and RCP8.5) is used as initial and lateral boundary conditions. Overall, WRF can capture the observed features of temperature distribution reflecting local topographic characteristic, despite some disagreement between the observed and simulated patterns. Basically, WRF shows a systematic cold bias in daily mean, minimum and maximum temperature over the entire domain. According to the future projections, summer and winter mean temperatures over East Asia will significantly increase in the mid-21st century. The mean temperature rise is expected to be greater in winter than in summer. In accordance with these results, summer (winter) is projected to begin earlier (later) in the future compared to the historical period. Furthermore, a rise in extreme temperatures shows a tendency to be greater in the future. The averages of daily minimum and maximum temperatures above 90 percentiles are likely to be intensified in the high-latitude, while hot days and hot nights tend to be more frequent in the low-latitude in the mid-21st century. Especially, East Asia would be suffered from strong increases in nocturnal temperature under future global warming.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.3
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• pp.189-197
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• 2021

Climate change effects are particularly apparent in many cool-season grasslands in South Korea. Moreover, the probability of climate extremes has intensified and is expected to increase further. In this study, we performed climate change vulnerability assessments in cool-season grasslands based on the analytic hierarchy process method to contribute toward effective decision-making to help reduce grassland damage caused by climate change and extreme weather conditions. In the analytic hierarchy process analysis, vulnerability was found to be influenced in the order of climate exposure (0.575), adaptive capacity (0.283), and sensitivity (0.141). The climate exposure rating value was low in Jeju-do Province and high in Daegu (0.36-0.39) and Incheon (0.33-0.5). The adaptive capacity index showed that grassland compatibility (0.616) is more important than other indicators. The adaptation index of Jeollanam-do Province was higher than that of other regions and relatively low in Gangwon-do Province. In terms of sensitivity, grassland area and unused grassland area were found to affect sensitivity the most with index values of 0.487 and 0.513, respectively. The grassland area rating value was low in Jeju-do and Gangwon-do Province, which had large grassland areas. In terms of vulnerability, that of Jeju-do Province was lower and of Gyeongsangbuk-do Province higher than of other regions. These results suggest that integrating the three aspects of vulnerability (climate exposure, sensitivity, and adaptive capacity) may offer comprehensive and spatially explicit adaptation plans to reduce the impacts of climate change on the cool-season grasslands of South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.1
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• pp.40-49
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• 2013

Current service system of the Korea Meteorological Administration (KMA) for blooming date forecasting in spring depends on regression equations derived from long term observations in both temperature and phenology at a given station. This regression based system does not allow a timely correction or update of forecasts that are highly sensitive to fluctuating weather conditions. Furthermore, the system cannot afford plant responses to climate extremes which were not observed before. Most of all, this method may not be applicable to locations other than that which the regression equations were derived from. This note suggests a way to replace the location restricted regression equations with a thermal time based phenology model to complement the KMA blooming forecast system. Necessary parameters such as reference temperature, chilling requirement and heating requirement were derived from phenology data for forsythia, azaleas and Japanese cherry at 29 KMA stations for the 1951-1980 period to optimize spring phenology prediction model for each species. Best fit models for each species were used to predict blooming dates and the results were compared with the observed dates to produce a correction grid across the whole nation. The models were driven by the KMA's daily temperature data at a 5km grid spacing and subsequently adjusted by the correction grid to produce the blooming date maps. Validation with the 1971-2012 period data showed the RMSE of 2-3 days for Japanese cherry, showing a feasibility of operational service; whereas higher RMSE values were observed with forsythia and azaleas.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.83-93
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• 2020

East Asia, which includes China, Japan, Korea, and Mongolia, is highly impacted by hydroclimate extremes such drought, flood, and typhoon recent year. In 2017, more than 18.5 million hectares of crops have been damaged in China, and Korea has suffered economic losses as a result of severe drought. Satellite-derived rainfall products are becoming more accurate as space and time resolution become increasingly higher, and provide an alternative means of estimating ground-based rainfall. In this study, we verified the availability of rainfall products by comparing widely used satellite images such as Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with ground stations in East Asia. Also, the satellite-based rainfall products were used to calculate the Standardized Precipitation Index (SPI). The temporal resolution is based on monthly images and compared with the past 30 years data from 1989 to 2018. The comparison between rainfall data based on each satellite image products and the data from weather station-based weather data was shown by the coefficient of determination and showed more than 0.9. Each satellite-based rainfall data was used for each grid and applied to East Asia and South Korea. As a result of SPI analysis, the RMSE values of CHIRPS were 0.57, 0.53 and 0.47, and the MAE values of 0.46, 0.43 and 0.37 were better than other satellite products. This satellite-derived rainfall estimates offers important advantages in terms of spatial coverage, timeliness and cost efficiency compared to analysis for drought assessment with ground stations.

• Atmosphere
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• v.34 no.2
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• pp.139-151
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• 2024

The Yeongdong region has suffered from severe snowstorms and the relevant damage such as traffic accidents on slippery roads, and the collapse of greenhouses and temporary buildings. While a lot of research on snowfall has been conducted, the detailed study of snow crystals' phase and habit through intensive observations and the relevant microphysical analysis is still lacking. Therefore, a snowflake camera, PARSIVEL, and intensive radiosonde soundings were utilized to investigate phase and habit changes in solid precipitation. Two remarkable episodes of phase and habit changes were selected such as 19 March 2022 and 15 February 2023. Both events occurred in the synoptic condition of the High in the north and the Low passing by the south, which was accompanied by rapid temperature cooling below 2.5 km. During the events of a short period between 3 to 6 hours, the temperature at 850 hPa decreased by about 4 to 6℃. This cooling led to a change in the main habit of snow particles from riming to aggregate, identified with both MASC and PARSIVEL. Meanwhile, the LDAPS model analyses do not successively represent the rapid cooling and short-term variations of solid precipitation, probably by virtue of overestimating low-level equivalent potential temperature during these periods. The underlying causes of these the low-level temperature variations within 6 hours, still remain unclear. It might be associated with mesoscale orographic phenomenon due to the mountains and East Sea effects, which certainly needs an intensive and comprehensive observation campaign.

• Journal of Bio-Environment Control
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• v.29 no.4
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• pp.399-405
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• 2020

Recently, it is difficult to produce uniform scions and rootstocks with high quality in a greenhouse due to weather extremes. The closed transplant production system is useful for producing scions and rootstocks with desirable morphological characteristics by environment control regardless of weather outside. In this study, we investigated transpiration rates and growth of cucumber and tomato scions and rootstocks grown under different light intensity conditions for precise irrigation control in a closed transplant production system. Hanging system to measure continuously the weight of plug tray consisting of seedlings and substrate with load-cell was installed in each growing bed. Using this system, we confirmed initial wilting point of cucumber and tomato seedlings, and conducted subirrigation when moisture content of substrate was not below 50%. The irrigation time of cucumber scions and rootstocks were 7 and 6 days after sowing, respectively. In tomato scions and rootstocks grown under PPF (photosynthetic photon flux) 300 μmol·m^-2·s^-1, the irrigation time were 5, 8, 11, and 13 days after sowing. Increasing light intensity increased transpiration rates and differences of transpiration rates by light intensity was higher in tomato seedlings. The growth of cucumber and tomato seedlings was promoted by increasing light intensity, especially, hypocotyl elongation and stem thickening was affected by light intensity. Cumulative transpiration rate of plug tray in cucumber and tomato seedlings was increased by increasing light intensity, and daily transpiration rate per seedling was regressed by 1st-order linear equation with high correlation coefficient. Estimation of transpiration rates by weighing continuously plug tray of vegetable seedlings can be useful to control more accurately irrigation schedule in a closed transplant production system.