• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.164-170
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• 2020

The weather conditions, such as temperature, precipitation, and sunshine duration, play one of the key roles in Agriculture. In particular, extreme weather events have crucial impacts on growth and yields of crops. This study estimates statistics of extreme weather events in 167 Si-gun over South Korea derived from high-resolution(30 and 270m) topo-climatology model for key three meteorological variables(temperature, precipitation and sunshine duration). It is shown that the characteristic of each extreme weather frequency in the topo-climatology model is in good agreement with observation from Korean Meteorological Administration's Automatic Surface Observing System. Moreover, it is possible to analyze the statistics of extreme weather more realistically because this data can cover the weather at not-observed regions. Hence, this data is expected to be used as baseline data for assessing vulnerability to extreme weather and politic decisions for damage reduction in agricultural sector.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.83-107
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• 2014

This study presents spatial characteristics of cloud using satellite image in the extreme heavy snowfall of the Yeongdong region. 3 extreme heavy snowfall events in the Yeongdong region during the recent 12 years (2001 ~ 2012) are selected for which the fresh snow cover exceed 50 cm/day. Spatial characteristics (minimum brightness temperature; Tmin, cloud size, center of cloud-cell) of cloud are analyzed by tracking main cloud-cell related with these events. These characteristics are compared with radar precipitation in the Yeongdong region to investigate relationship between cloud and precipitation. The results are summarized as follows, selected extreme heavy snowfall events are associated with the isolated, well-developed, and small-scale convective cloud which is developing over the Yeongdong region or moving from over East Korea Bay to the Yeongdong region. During the period of main precipitation, cloud-cell Tmin is low ($-40{\sim}-50^{\circ}C$) and cloud area is small (17,000 ~ 40,000 $km^2$). Precipitation area (${\geq}$ 0.5 mm/hr) from radar also shows small and isolated shape (4,000 ~ 8,000 $km^2$). The locations of the cloud and precipitation are similar, but in there centers are located closely to the coast of the Yeongdong region. In all events the extreme heavy snowfall occur in the period a developed cloud-cell was moving into the coastal waters of the Yeongdong. However, it was found that developing stage of cloud and precipitation are not well matched each other in one of 3 events. Water vapor image shows that cloud-cell is developed on the northern edge of the dry(dark) region. Therefore, at the result analyzed from cloud and precipitation, selected extreme heavy snowfall events are associated with small-scale secondary cyclone or vortex, not explosive polar low. Detection and tracking small-scale cloud-cell in the real-time forecasting of the Yeongdong extreme heavy snowfall is important.

• Journal of the Korean association of regional geographers
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• v.19 no.4
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• pp.600-614
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• 2013

This study aims to examine spatially-detailed changes and projection of subtropical climate zones based on the modified K$\ddot{o}$ppen-Trewartha's climate classification and extreme temperature indices using $1km{\times}1km$ high resolution RCP 4.5 and RCP 8.5 climate change scenarios based on PRIDE model over the Republic of Korea. Subtropical climate zones currently located along the southern coastal region. Future subtropical climate zones would be pushed northwards expanding to the western and the eastern coastal regions as well as some metropolitan areas. For both scenarios, the frequency of cold-related extreme temperatures projects to be reduced while the frequency of hot-related ones projects to be increased. Especially, hot days with $33^{\circ}C$ or higher temperature projects to occur more than 30 days over the most of regions except for some mountain areas with high altitudes during the period of 2070~2100. This study might provide essential information to make climate change adaptation processes be enhanced.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.161-161
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• 2003

During the last century, most scientific questions related to climate change were focused on the evidence of anthropogenic global warming (IPCC, 2001). There are robust evidences of warming and also human-induced climate change. We now understand the global, mean change a little bit better; however, the uncertainties for regional climate change still remains large. The purpose of this study is to understand the past climate change over Korea based on the observational data and to project future regional climate change over East Asia using ECHAM4/HOPE model and MM5 for downscaling. There are significant evidences on regional climate change in Korea, from several variables. The mean annual temperature over Korea has increased about 1.5∼$1.7^{\circ}C$ during the 20th century, including urbanization effect in large cities which can account for 20-30% of warming in the second half of the 20th century. Cold extreme temperature events occurred less frequently especially in the late 20th century, while hot extreme temperature events were more common than earlier in the century. The seasonal and annual precipitation was analyzed to examine long-term trend on precipitation intensity and extreme events. The number of rainy days shows a significant negative trend, which is more evident in summer and fall. Annual precipitation amount tends to increase slightly during the same period. This suggests an increase of precipitation intensity in this area. These changes may influence on growing seasons, floods and droughts, diseases and insects, marketing of seasonal products, energy consumption, and socio-economic sectors. The Korean Peninsular is located at the eastern coast of the largest continent on the earth withmeso-scale mountainous complex topography and itspopulation density is very high. And most people want to hear what will happen in their back yards. It is necessary to produce climate change scenario to fit forhigh-resolution (in meteorological sense, but low-resolution in socio-economic sense) impact assessment. We produced one hundred-year, high-resolution (∼27 km), regional climate change scenario with MM5 and recognized some obstacles to be used in application. The boundary conditions were provided from the 240-year simulation using the ECHAM4/HOPE-G model with SRES A2 scenario. Both observation and simulation data will compose past and future regional climate change scenario over Korea.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.47-54
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• 2003

Climate of Mongolia is a driven force on natural conditions as well as socio-economic development of the country. Due to the precariousness of climate conditions and traditional economic structure, natural disasters, specially disasters of meteorological and hydrological origin, have substantial effect upon the natural resources and socio-economic sectors of Mongolia. Mongolia's climate is characterized by high variability of weather parameters, and high frequency and magnitude of extreme climate and weather events. During the last few decades, climate of the country is changing significantly under the global warning. The annual mean air temperature for the whole territory of the country has increased by $1.56^{\circ}C$ during the last 60 years,. The winter temperature has increased by $1.56^{\circ}C$. These changes in temperature are spatially variable: winter warming is more pronounced in the high mountains and wide valleys between the mountains, and less so in the steppe and Gobi regions. There is a slight trend of increased precipitation during the last 60 years. The average precipitation rate is increased during 1940-1998 by 6%. This trend is not seasonally consistent: while summer precipitation increased by 11 %, spring precipitation decreased by 17. The climate change studies in Mongolia show that climate change will have a significant impact on natural resources such as water resources, natural rangeland, land use, snow cover, permafrost as well as major economic activities of arable farming, livestock, and society (i.e. human health, living standards, etc.) of Mongolia. Therefore, in new century, sustainable development of the country is defined by mitigating and adaptation policies of climate change. The objective of the presentation is to contribute one's idea in the how to reflect the changes in climate system and weather extreme events in the country's sustainable development concept.

• Journal of the Korean Geographical Society
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• v.47 no.2
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• pp.208-225
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• 2012

The spatial characteristics of changes in extreme temperature indices for 2070-2099 relative to 1971-2000 in the Republic of Korea were investigated using daily maximum (Tmax) and minimum (Tmin) temperature data from a regional climate model (HadGEM3-RA) based on the IPCC RCP4.5/8.5 at 12.5km grid spacing and observations. Six temperature-based indices were selected to consider the frequency and intensity of extreme temperature events. For validation during the reference period (1971-2000), the simulated Tmax and Tmin distributions reasonably reproduce annual and seasonal characteristics not only for the relative probability but also the variation range. In the future (2070-2099), the occurrence of summer days (SD) and tropical nights (TR) is projected to be more frequent in the entire region while the occurrence of ice days (ID) and frost days (FD) is likely to decrease. The increase of averaged Tmax above 95th percentile (TX95) and Tmin below 5th percentile (TN5) is also projected. These changes are more pronounced under RCP8.5 scenario than RCP4.5. The changes in extreme temperature indices except for FD show significant correlations with altitude, and the changes in ID, TR, and TN5 also show significant correlations with latitude. The mountainous regions are projected to be more influenced by an increase of low extreme temperature than low altitude while the southern coast is likely to be more influenced by an increase of tropical nights.

• Proceedings of the KGS Conference
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• 2003.05a
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• pp.79-82
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• 2003

인류의 활동으로 인해 전구적으로 일어나고 있는 기후 변화를 탐지하고 원인을 규명하는 것은 중요한 기후 연구 주제이다. 2001년에 발간된 IPCC 보고서는 기후에 대한 인류의 영향으로 19세기 후반 이후 지구의 평균기온이 약 0.7$^{\circ}C$ 상승했다고 결론지었다. 그러나 이러한 경향은 시공간적으로 일정하지 않을 뿐만 아니라, 평균 변화가 극한 사상의 변화를 반드시 이끌어 내는 것은 아니다. 하지만, 평균 변화는 사회나 생태계 전반에 걸쳐서 영향을 미치게 될 기후 행태를 변화시킨다. (중략)

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.179-188
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• 2022

Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.143-143
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• 2021

Climate change indicators, mainly frequent drought which has happened since the drought of 1994, 1995, and 2012 causing the devastating effect to the agricultural sector, and could be more disruptive given the context of climate change indicators by increasing the temperature and more variable and extreme precipitation. Changes in frequency, duration, and severity of droughts will have enormous impacts on agriculture production and water management. Since both the possibility of drought manifestation and substantial yield losses, we are propositioning an integrated method for evaluating past and future agriculture drought hazards that depend on models' simulations in the Hung-up watershed. to discuss the question of how climate change might influence the impact of extreme agriculture drought by assessing the potential changes in temporal trends of agriculture drought. we will calculate the temporal trends of future drought through drought indices Standardized Precipitation Evapotranspiration Index, Standardized Precipitation Index, and Palmer drought severity index by using observed data of (1991-2020) from Wonju meteorological station and projected climate change scenarios (2021-2100) of the Representative Concentration Pathways models (RCPs). expected results confirmed the frequency of extreme agricultural drought in the future projected to increase under all studied RCPs. at present 100 years drought is anticipated to happen since the result showing under RCP2.6 will occur every 24 years, RCP4.5 every 17 years, and RCPs8.5 every 7 years, and it would be double in the largest warming scenarios. On another side, the result shows unsupportable water management, could cause devastating consequences in both food production and water supply in extreme events. Because significant increases in the drought magnitude and severity like to be initiate at different time scales for each drought indicator. Based on the expected result that the evaluating the impacts of extreme agricultural droughts and recession could be used for the development of proactive drought risk management, policies for future water balance, prioritize sustainable strengthening and mitigation strategies.

• Atmosphere
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• v.29 no.4
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• pp.451-461
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• 2019

Medium-range forecast is highly dependent on ensemble forecast data. However, operational weather forecasters have not enough time to digest all of detailed features revealed in ensemble forecast data. To utilize the ensemble data effectively in medium-range forecasting, representative weather patterns in East Asia in this study are defined. The k-means clustering analysis is applied for the objectivity of weather patterns. Input data used daily Mean Sea Level Pressure (MSLP) anomaly of the ECMWF ReAnalysis-Interim (ERA-Interim) during 1981~2010 (30 years) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Using the Explained Variance (EV), the optimal study area is defined by 20~60°N, 100~150°E. The number of clusters defined by Explained Cluster Variance (ECV) is thirty (k = 30). 30 representative weather patterns with their frequencies are summarized. Weather pattern #1 occurred all seasons, but it was about 56% in summer (June~September). The relatively rare occurrence of weather pattern (#30) occurred mainly in winter. Additionally, we investigate the relationship between weather patterns and extreme weather events such as heat wave, cold wave, and heavy rainfall as well as snowfall. The weather patterns associated with heavy rainfall exceeding 110 mm day^-1 were #1, #4, and #9 with days (%) of more than 10%. Heavy snowfall events exceeding 24 cm day^-1 mainly occurred in weather pattern #28 (4%) and #29 (6%). High and low temperature events (> 34℃ and < -14℃) were associated with weather pattern #1~4 (14~18%) and #28~29 (27~29%), respectively. These results suggest that the classification of various weather patterns will be used as a reference for grouping all ensemble forecast data, which will be useful for the scenario-based medium-range ensemble forecast in the future.