• Atmosphere
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• v.29 no.5
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• pp.615-626
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• 2019

To find any effects of precipitation climate on the forecast verification methods, we processed the hourly records of precipitation over South Korea. We examined their relationship between the climate and the methods of verification. Precipitation is an intermittent process in South Korea, generally less than an hour or so. Percentile ratio of precipitation period against the entire period of the records is only 14% in the hourly amounts of precipitation. The value of the forecast verification indices heavily depends on the climate of rainfall. The direct comparison of the index values might force us to have a mistaken appraisal on the level of the forecast capability of a weather forecast center. The size of the samples for verification is not crucial as long as it is large enough to satisfy statistical stability. Our conclusion is still temporal rather than conclusive. We may need the amount of precipitation per minute for the confirmation of the present results.

• Atmosphere
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• v.33 no.5
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• pp.477-492
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• 2023

Based on the new climate normals (1991~2020), annual mean, maximum and minimum temperature is 12.5℃, 18.2℃, and 7.7℃, respectively while annual precipitation is 1,331.7 mm, the annual mean wind speed is 2.0 m s^-1, and the relative humidity is 67.8% in the Republic of Korea. Compared to 1981~2010 normal, annual mean temperature increased by 0.2℃, maximum and minimum temperatures increased by 0.3℃, while the amount of precipitation (0.7%) and relative humidity (1.1%) decreased. There was no distinct change in annual mean wind speed. The spatial range of the annual mean temperature in the new normals is large from 7.1 to 16.9℃. Annual precipitation showed a high regional variability, ranging from 787.3 to 2,030.0 mm. The annual mean relative humidity decreased at most weather stations due to the rise in temperature, and the annual mean wind speed did not show any distinct difference between the new and old normals. With the addition of a warmer decade (2011~2020), temperatures all increased consistently and in particular, the increase in the maximum temperature, which had not significantly changed in previous decades, was evident. The increasing trend of annual and summer precipitation by the 2010s has disappeared in the new normals. Among extreme climate indices, MxT30 (Daily maximum temperature ≥ 33℃ days), MnT25 (Daily minimum temperature ≥ 25℃ days), and PH30 (1 hour maximum precipitation ≥ 30 mm days) increased while MnT-10 (Daily minimum temperature < -10℃ days) and W13.9 (Daily maximum wind speed ≥ 13.9 m/s days) decreased at a statistically significant level. It is thought that a detailed study on the different trends of climate elements and extreme climate indices by region should be conducted in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• Journal of Climate Change Research
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• v.5 no.2
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• pp.165-178
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• 2014

National and local governmental adaptation plan for climate change will become mandatory in 2015. In order to establish the plan, assessment of vulnerability to climate change needs to be preceded. LCCGIS, a toolkit for vulnerability assessment, has been widely used by many local governments. However, assessment results by LCCGIS are not yet reliable because most of the vulnerability indices applied to LCCGIS　have the same value for almost all administrative units in Korea. In this study, proxy variables for hard-collectable indices were introduced, and the results were compared with those without any proxy variables. Vulnerability assessment could be conducted subjectively due to uncertainty. Thus, determination of objective indices, understanding the available data, and changes of indices in local conditions were organized. Results from this study are expected to make vulnerability assessment reliable and contribute to assessing vulnerability to climate change reflecting on local governmental characteristics.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.275-285
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• 2017

Chungnam region has established and executed the 2nd Climate Change Adaptation Initiative Execution Plan (2017~2021) based on the Framework Act on Low Carbon, Green Growth. The Execution Plan is established based on the results of climate change vulnerability assessment using the CCGIS, LCCGIS, and VESTAP analysis tools. However, the previously developed climate change vulnerability assessment tools (CCGIS, LCCGIS, VESTAP) cannot reflect the local records and the items and indices of new assessment. Therefore, this study developed a prototype of climate change vulnerability assessment analysis tool that, unlike the previous analysis tools, designs the items and indices considering the local characteristics and allows analysis of grid units. The prototype was used to simulate the vulnerability to forest fires of eight cities and seven towns in Chungcheongnam-do Province in the 2010s, 2020s, and 2050s based on the RCP (Representative Concentration Pathways) 8.5 Scenario provided by the Korea Meteorological Administration. Based on the analysis, Chungcheongnam-do Province's vulnerability to forest fires in the 2010s was highest in Seocheon-gun (0.201), followed by Gyeryong-si (0.173) and Buyeo-gun (0.173) and the future prospects in the 2050s was highest in Seocheon-gun (0.179), followed by Gyeryong-si (0.169) and Buyeo-gun (0.154). The area with highest vulnerability to forest fires in Chungcheongnam-do Province was Biin-myeon, Seocheon-gun and the area may become most vulnerable was Pangyo-myeon, Seocheon-gun. The prototype and the results of analysis may be used to establish the directions and strategies in regards to the vulnerability to wild fires to secure each local government's 2nd execution plan and attainability.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.31-44
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• 2019

The main objective of this research is to develop a hydroclimate drought index (HCDI) using the gridded climate data inputs in a Variable Infiltration Capacity (VIC) modeling platform. Typical drought indices, including, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Self-calibrated Palmer Drought Severity Index (SC-PDSI) in South Korea are also used and compared. Inverse Distance Weighting (IDW) method is applied to create the gridded climate data from 56 ground weather stations using topographic information between weather stations and the respective grid cell ($12km{\times}12km$). R statistical software packages are used to visualize HCDI in Google Earth. Skill score (SS) are computed to evaluate the drought predictability based on water information derived from the observed reservoir storage and the ground weather stations. The study indicates that the proposed HCDI with the gridded climate data input is promising in the sense that it can help us to predict potential drought extents and to mitigate its impacts in a changing climate. The longer term drought prediction (e.g., 9 and 12 month) capability, in particular, shows higher SS so that it can be used for climate-driven future droughts.

• Ocean Science Journal
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• v.43 no.1
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• pp.1-7
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• 2008

Physical and biological environmental variations in the East Sea were investigated by analysing time-series of oceanographic data and meteorological indices. From 1971 to 2000, dominant periodicity in water temperature variations had two apparent periods of 3 to 4 years and of decades, especially in the southwestern part of the East Sea affected by the influence of inflowing Tsushima warm current. Fluctuating water temperature within a certain period appears to respond to El $Ni{\tilde{n}}o$ events with a time lag. It was found that there was a strong correlation between water temperature and El $Ni{\tilde{n}}o$ events with a time lag of 1.5 and 5.5 years for periods of 3 to 6 years and of decades, respectively. Corresponding with El $Ni{\tilde{n}}o$ events, water temperature variability also showed strong correlation with shift and/or changes in biological and chemical environments of nutrient concentrations, zooplankton biomass, and fisheries. However, there also occurred a short-term periodicity of water temperature variations. Within a period of 1 to 4 years, a relatively short-term cycle of water temperature variation had strong correlation with other climate indices such as Pacific Decadal Oscillation and monsoon index. After comparing coherence and phase spectrum between water temperature and different climate indices, we found that there was a shift of coherent periods to another climate index during the years when climate regime shift was reported.

• Ocean Systems Engineering
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• v.7 no.4
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• pp.319-328
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• 2017

Higher prediction efficacy is a very challenging task in any field of engineering. Due to global warming, there is a considerable increase in the global sea level. Through this work, an attempt has been made to find the sea level variability due to climate change impact at Haldia Port, India. Different statistical downscaling techniques are available and through this paper authors are intending to compare and illustrate the performances of three regression models. The models: Wavelet Neural Network (WNN), Minimax Probability Machine Regression (MPMR), Feed-Forward Neural Network (FFNN) are used for projecting the sea level variability due to climate change at Haldia Port, India. Model performance indices like PI, RMSE, NSE, MAPE, RSR etc were evaluated to get a clear picture on the model accuracy. All the indices are pointing towards the outperformance of WNN in projecting the sea level variability. The findings suggest a strong recommendation for ensembled models especially wavelet decomposed neural network to improve projecting efficiency in any time series modeling.

• Journal of the Korean association of regional geographers
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• v.21 no.2
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• pp.394-410
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• 2015

This study aims to classify climate zones for extreme climate indices over the Republic of Korea. First, frequencies and magitudes of extreme high temperature, spatial distributions for extreme low temperature, and extreme precipitation are analysed. Frequencies of summer days in inland region show more than coastal region. In frequencies of frost days, the characteristics of altitude and longitude are appeared. Heavy precipitation days show many frequencies in the southern coastal region and Jeju island, but little in Gyeongsangbuk-do region. The classification of climate zone for extreme climate indices by principal component analysis and cluster analysis is conducted for the first half, second half of study period, and climatology period for 1981-2010. Summer days are classified according to latitude. In case of frost days, the eastern and the southern coastal region and Jeju island are classified as same region. Heavy precipitation days are classified according to longitude in south region of Gyeonggi-do and Gangwon-do. This study will help to prepare adaptation and mitigation system for climate change in wide range of fields.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.1-15
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• 2024

In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.