The intertidal zone has both land and marine characteristics and shows complex weather environments. These characteristics are suited for studying climate change, energy balance and ecosystems, and may play an important role in coastal and marine weather prediction and analysis. This study was conducted at Odo Island, approximately 300m from the mainland in Yeosu. We built a weather observation system capable of real-time monitoring on the mud flat in the intertidal zone and measured actual weather and marine data. Weather observation was conducted from April to June 2022. The results showed changes in air temperature and water temperature with changes in the tide level during spring. Correlation analysis revealed characteristic changes in air temperature and water temperature during the day and night, and with inundation and exposure.

This study evaluates the quality of surface air temperature, relative humidity, and precipitation detection observed by 22 internet of thing (IoT)-based mini-weather stations in Seoul in 2020 summer. The automatic weather station (AWS) closest to each IoT-based station is used as reference. The IoT-based observations show surface air temperature and relative humidity are about 0.2-4.0°C higher and about -1--22% lower than the AWS observations, respectively. However, they exhibit temporal variability similar to the AWS observations on both diurnal and daily time scales, with daily correlations greater than 0.90 for temperature and 0.82 for relative humidity. Given these strong linear relationships, it show that temperature and relative humidity biases can be effectively corrected by applying a simple bias correction method. For IoT-based precipitation detection, we found that precipitation conductivity value (PCV) during precipitation events is well separated from that during non-precipitation events, providing a basis for distinguishing precipitation events from non-precipitation events. When the PCV threshold is set to 250 for precipitation detection, the highest critical success index and the bias score index close to one, suitable for operational precipitation detection, are obtained. These results demonstrate that IoT-based mini-weather stations can successfully measure surface air temperature, relative humidity, and precipitation detection with appropriate bias corrections.

We projected the temperature changes in the mid-21st century with Representative Concentration Pathway (RCP) 4.5 and RCP8.5 using the temperature data simulated by four regional climate models (RCMs: WRF, CCLM, MM5, RegCM4) in Korea. The simulation area and spatial resolution of RCMs were the CORDEXEA (COordinated Regional Climate Downscaling Experiment-East Asia) area and 25 km, respectively. We defined the temperature change as the difference (ratio) between the average annual temperature (IAV: Interannual Variation) over the projected 25 years (2026-2050) and that over the present 25 years (1981-2005). The fact that the average annual temperature bias of the four RCMs is within ±2.5°C suggests that the RCM simulation level is reasonable in Korea. Across all RCMs, scenarios, and geographic locations, we observed increased temperatures (IAV) in the mid-21st century. In RCP4.5 and RCP8.5, 1.27°C and 1.57°C will be increased by 2050, respectively. The ensemble suggests that the temperature increase is higher in winter (RCP4.5: 1.36°C, RCP8.5: 1.75°C) than summer (RCP4.5: 1.25°C, RCP8.5: 1.49°C). Central Korea exhibited a higher temperature increase than southern Korea. A slightly larger IAV is expected in the southeastern region than in the Midwest of Korea. IAV is also expected to increase significantly in RCP4.5 (summer) than in RCP8.5 (winter).

This study analyzed how the impacts of major teleconnection patterns on December mean temperature in Korea have been changed during the period before and after the regime shift of 1986 for the last 61 years from 1958 to 2018. During the period before the regime shift, the teleconnection patterns originating from the North Atlantic mainly affected the temperature variability in Korea, but its influence almost disappeared after the regime shift. On the other hand, the Arctic Oscillation (AO) and warm Arctic and cold Eurasia (WACE) patterns played a more important role in the temperature variability in Korea after the regime shift. Regression analysis showed that the AO could explain about 12% of the total temperature variability before the regime shift, but about 22% after the regime shift. WACE pattern also explained about 4% before the regime shift, but after the regime shift, the importance increased by about 4.5 times to 18%. On the other hand, East Atlantic pattern (EA) and North Atlantic Oscillation (NAO), which are east-west teleconnection patterns, explained 27% and 11%, respectively, before the regime shift, but had little influence within 3% after the regime shift. This means that the influence of east-west teleconnection patterns disappeared after the regime shift, and teleconnection patterns by the Arctic Circle became more important.

The present study aims to analyze climate change and trend of extreme temperature events occurred over the Republic of Korea. The observation data used are daily average, maximum, and minimum temperature from 6 weather stations for the period of 1912-2020. Seven extreme indices regarding frequency and extreme value of temperature are calculated in seasonal and annual time range. In addition, hot extremes and their changes by four physical terms that include information on the annual mean temperature, the amplitude of the annual cycle, the diurnal temperature range and the local temperature anomaly on the day of the extreme are analyzed. The climatology for the analysis is updated to the new normal year of 1991-2020. Consistent with the previous findings, statistically significant change was detected in the indices of annual lowest daily minimum temperature, annual extreme temperature range, frequency of daily minimum temperature below -12℃ and 10%ile(TN10p) during winter. Due to the gradual decrease of the occurrence days regarding the extreme minimum temperature during winter, the frequency calculated by the relative threshold in extreme high temperature during summer prevail since 1990s. Indices related with extreme high temperature had larger low-frequency variability than significant climate change during the analysis period. However, the assessment of hot extremes according to the terms describing mean, variability and tails during the new normal year of 1991-2020, significant increasing trend was detected not only in the annual mean and the amplitude of the seasonal cycle, but also in the daily hot extreme anomaly.

In this study, a high-resolution daily data set of surface weather were obtained from PRIDE(PRISMbased Dynamic downscaling Error correction) model for the period of 2000 to 2017 over South Korea. The simulation data of five RCM(Regional Climate Model) were also used which are forced by the CMIP6 participating model UK-ESM as the boundary condition under historical period (2000-2014) and SSP 5-8.5 period (2015- 2017). Here we compared the RCM data and the PRIDE data with MK-PRISM data in terms of ensemble mean and ensemble spread. Results show that the PRIDE model effectively eliminates systematic error in the RCM up to 63.0% for daily average temperature, 72.2% for daily maximum temperature, 68.2% for daily minimum temperature, and 28.7% for daily precipitation when evaluated from the RMSE perspective. Overall, the ensemble spread of the PRIDE model is significantly decreased from 1.46°C to 0.36°C for daily temperature and from 2.0 mm/day to 0.72 mm/day for daily precipitation compared to the RCM ensemble spread, indicating that the largest systematic error of the RCMs is effectively removed in the PRIDE model.

The purpose of this study is to examine the trends of extreme temperature events in East Asia over the past 40 years (1979-2018) and their potential relationships with recent changes in the Northern Hemisphere cryosphere. Analyses of Sen’s slope and Mann-Kendall tests are performed for time series data of extreme temperature events extracted from NCEP-DOE reanalysis II Gaussian grid daily 2-m air temperature data. As the result, it is found that extreme high temperature events exceeding the 99th percentile show more noticeable increasing trends than the magnitude of the decreasing extreme low temperature events below the 1st percentile particularly in Mongolia, Korean Peninsula and southern China due to unexpected cold events since the late 2000s. Correlation analyses based on Kendall’s tau indicate that the reduction of spring-early summer Eurasian snow cover (data from Rutgers University Global Snow Lab.) may lead to the increasing tendency of extreme high temperature events in East Asia through snow albedo feedbacks, while paradoxically the reducing autumn-early winter Arctic sea ice (data from NSIDC) due to global warming seems to cause more frequent extreme low temperature events in recent years through the amplification of Rossby waves. Thus, it is needed to continue monitoring the feedbacks between changing Arctic cryosphere and East Asian climate systems in the warmer 21st century.

The Korean Peninsula has experienced regime shift (RS) in winter temperature since the mid-1980s. After the RS, monthly mean temperature significantly increased by 1.05°C in December with 95% confidence level, 1.36°C in January with 99% confidence level, and 1.60°C in February with 99% confidence level, respectively. Interestingly there is no RS in warm winter with 95% confidence level while there is a clear RS in cold winter with 99% confidence level, especially in December and January (DJ), indicating that the RS of winter temperature is mainly due to an abrupt temperature shift in December and January after the RS. Composite analysis suggests that abrupt shift in January after the RS is related to the reduction in sea level pressure (SLP) between Siberian high and Aleutian low, leading to anomalous southerly. However, abrupt shift in December is closely related to the propagation of Rossby wave spanning from the weakening of Ural high to negative anomaly over the North Pacific via high pressure anomaly over the Korean Peninsula, leading to adiabatic heating. Wave activity flux analysis suggests that the abrupt shift of DJ and the associated high pressure anomaly over the Korean Peninsula is induced by the propagation of Rossby wave spanning from North Atlantic Ocean to the Korean Peninsula via the Arctic, especially in cold winter.

본 연구는 봄 식물계절지수와 기온지표와의 관계를 알아보기 위해 지난 9년간(2010년-2018년) 대구수목원, 팔공산, 주왕산, 가야산에 공통적으로 생육하는 소나무, 일본잎갈나무, 신갈나무, 진달래, 생강나무, 당단풍나무 6종을 대상으로 발아, 개화, 개엽의 봄 식물계절 시기의 변화 경향과 기온간의 관계를 파악하였다. 기온의 변화는 9년동안 2월 보다 3~4월의 월평균 기온이 증가하였으며, 지역별로 수목원과 팔공산의 평균기온이 높았다. 발아, 개화, 개엽은 수종별로 생강나무가 가장 빠르며 소나무가 가장 느렸고, 지역별로 수목원에서 가장 빨리 식물 계절시기가 도래하였다. 봄 식물계절시기는 –1.267~-6.151일 /9년 정도 앞당겨지고 있는 경향을 보이는데 소나무(–6.151일/9 년)가 가장 크며, 진달래(–1.267일/9년)의 변화율이 가장 낮았다. 발아, 개화, 개엽에서 모두 유의한 값을 보이는 수종은 진달래와 소나무로서 이들은 1월~3월 평균기온과 상관관계를 보였다. 봄 식물계절지수(SPI)의 시계열 변화를 확인한 결과 4개 지역의 변화율이 모두 음의 값으로 식물계절 시기가 모두 빨라지고 있었다. 그 중 수목원, 팔공산 및 가야산과 같은 내륙지역일수록 변화율이 컸으며, 다소 거리가 떨어진 주왕산의 경우 변화율이 조금 낮게 나타났다.

본 연구에서는 외기온 영하조건에서 노출시간 변화별 콘크리트의 초기동해 피해를 입는 온도이력을 확인하고, 실험연구결과 –10℃인 외기조건에서 200 mm 두께의 슬래브는 18시간까지는 외기온에 노출되어도 콘크리트의 수화열에 의해 초기동해 피해가 발생하지 않는 것을 알 수 있었다.

This study investigated the relationship between heat-related illnesses obtained from healthcare big data and daily maximum temperature observed in seven metropolitan cities in summer during 2013~2015. We found a statistically significant positive correlation (r = 0.4~0.6) between daily maximum temperature and number of the heat-related patients from Pearson's correlation analyses. A time lag effect was not observed. Relative Risk (RR) analysis using the Generalized Additive Model (GAM) showed that the RR of heat-related illness increased with increasing threshold temperature (maximum RR = 1.21). A comparison of the RRs of the seven cities, showed that the values were significantly different by geographical location of the city and had different variations for different threshold temperatures. The RRs for elderly people were clearly higher than those for the all-age group. Especially, a maximum value of 1.83 was calculated at the threshold temperature of 35℃ in Seoul. In addition, relatively higher RRs were found for inland cities (Seoul, Gwangju, Daegu, and Daejeon), which had a high frequency of heat waves. These results demonstrate the significant risk of heat-related illness associated with increasing daily maximum temperature and the difference in adaptation ability to heat wave for each city, which could help improve the heat wave advisory and warning system.

In this study, we compared the prediction performances according to the bias and dispersion of temperature using ensemble machine learning. Ensemble machine learning is meta-algorithm that combines several base learners into one prediction model in order to improve prediction. Multiple linear regression, ridge regression, LASSO (Least Absolute Shrinkage and Selection Operator; Tibshirani, 1996) and nonnegative ride and LASSO were used as base learners. Super learner (van der Lann et al ., 1997) was used to produce one optimal predictive model. The simulation and real data for temperature were used to compare the prediction skill of machine learning. The results showed that the prediction performances were different according to the characteristics of bias and dispersion and the prediction error was more improved in temperature with bias compared to dispersion. Also, ensemble machine learning method showed similar prediction performances in comparison to the base learners and showed better prediction skills than the ensemble mean.

We estimated changes in temperature-related extreme events over South Korea for the mid and late 21st Century using the 122 years (1979-2100) data simulated by RegCM4 with HadGEM2-AO data as boundary conditions. We analyzed the four extreme events (Hot day: HD, Tropical day: TD, Frost day: FD, Icing Day: ID) and five extreme values (Maximum temperature 95/5 percentile: TX95P/TX5P, Minimum temperature 95/5 percentile: TN95P/TN5P, Daily temperature range 95 percentile: DTR95P) based on the absolute and relative thresholds, respectively. Under the global warming conditions, hot extreme indices (HD, TD, TX95P, TN95P) increase, suggesting more frequent and severe extreme events, while cold extreme indices (FD, ID, TX5P, TN5P) decrease their frequency and intensities. In the late 21st Century, changes in extremes are greater in severe global warming scenario, RCP8.5 rather than RCP4.5. HD and TD (FD and ID) are expected to increase (decrease) in the mid 21st Century. The average HD is expected to increase by 14 (17) days in RCP4.5 (8.5). All the percentile indices except for DTR95P are expected to increase in both RCP4.5 and RCP8.5. In the late 21st Century, HD and TD are significantly increased in RCP8.5 compared to RCP4.5, but FD and ID are expected to be significantly reduced. HD is expected to increase mainly in the southwestern region, twice (+41 days) in RCP8.5. TD is expected to increase by 17 days in RCP8.5, which is 5 times greater than that in RCP4.5. TX95P, TN95P and TX5P are expected to increase by about 2°C and 4°C in RCP4.5 and RCP8.5, respectively. TN5P is expected to increase significantly by 4°C and 7°C in RCP4.5 and RCP8.5, respectively.

This study aims to analyze the change of onset and end dates of extreme temperature events and examine their relationships with global warming. The data used for this study are daily maximum temperature, daily minimum temperature, and global mean temperature anomaly. Results were similar to the trend of global temperature, showing that the onset date of extreme high temperature is advanced while the end date of extreme high temperature is delayed. Also, the change of onset (end) dates of extreme low temperature were clear, with coming later (earlier). There is more distinct change in extreme low temperature than extreme high temperature. The length between onset date and end date of extreme high (low) temperature is significantly longer (shorter). The onset (end) date of extreme high temperature has a negative (positive) relationship with global mean temperature. The onset (end) date of extreme low temperature has a positive (negative) relationship with global mean temperature. It might be concluded that the change of onset and end date of extreme temperature in South Korea has been affected by global warming.

This study was conducted to propose a strength correction factor to compensate the strength delay at designed age caused by the temperature drop in low temperature condition. Strength correction factors due to temperature drop T28 were provided using the constant function model.

In this study, daily precipitation data and daily average temperature data of meteorological observatories in Daegu, Busan, Daejeon, Seoul, Mokpo, and Gwangju cities inland and offshore were analyzed by using moving average method. Were compared. Overall, summarizing changes in precipitation and temperature over the 24 seasons, precipitation and temperature in all six stations increased compared to the past 1960s. In the case of precipitation, precipitation increased at the end of July and early August, whereas precipitation in April, September and early October decreased. In the case of temperature, especially in February, the temperature increased, and in Mokpo, the temperature from August to December showed a general decline. Changes in precipitation and temperature due to seasons in the 24 seasons affect agriculture and our everyday life, and further research is needed to determine how these changes will affect agricultural water supply, crop growth and daily life. The results of this study can be useful.

Background : Panax ginseng C. A. meyer is currently cultivated throughout the Korea Peninsula except for Jeju Island. We divided into 3 sectors according to latitude, north, middle, and south, and compared ginseng growth and environmental factors. Methods and Results : We surveyed 11 farms, and while temperature, plant density, sunshade material, and soil properties were varied between the farms, most north part used sunshade film and transfer-seeding, and middle-south and south part used sunshade net, and direct-seeding. From 1st to 10th of June, 2018, the temperature inside of sunshade of each farm which ranged 20.5 - 24.5℃ did not concerted with the local meteorological air temperature nor latitude. The average plant length was 66.0 ± 8.1 with a significant difference between local farms (p < 0.001). Plant length showed high correlation with stem length, stem diameter, leaf length, and leaf width, but not with chlorophyll content, thus plant length was used to compare the effects of environmental factors on plant growth. The temperature had negative correlations between plant length (r = -0.396, p = 0.056) and stem length (r = -0.420, p = 0.041), but not with others. When local farms grouped into 3 sectors, the temperature inside sunshade was lowest in south than others, and stem diameter, leaf length, and leaf width of north sector were higher than other sectors. Conclusion : The temperature of local farm might affected by micro environment such as sunshade and geometrical properties, and partially devote on the growth difference between the local farms.

The study aims to investigate the effect of air temperature on growth date(bud bursting, flowering, blooming) of Citrus Unshiu in Jeju and Seogwipo, and estimate future growth date using air temperature data and growth date of Citrus Unshiu from 1998 to 2015. The trend and relationship between growth date of Citrus Unshiu and air temperature in Jeju and Seogwipo are analysed. As a result, The trend of growth date of Citrus Unshiu is delayed during study period. The correlation between Citrus Unshiu growth date and air temperature is negative. It means that air temperature related to the growth date of Citrus Unshui is decreasing. Future growth date of Citrus Unshiu is estimated to be earlier by future climate change scenarios. Air temperature expect to rise, but it can appear the low air temperature to be able to hurt citrus tree.

This study was conducted to determine the effects of combination of air temperature and soil water content on the growth, physiological disorder rate, and yield of hot peppers. The study was carried out in a typical plastic house (open on one side and with ventilation fans on the other side), which was maintained with gradient air temperature (maximum difference in air temperature: 6°C). The deficit irrigation (DI) treatment commenced 65 days after transplanting. The height of plant and fresh and dry weights of the stem increased at high air temperature (ambient + 6°C, extreme high temperature; EHT). Furthermore, the leaf area decreased significantly with the DI treatment. There were no significant differences in the stem diameter, number of branches, and fresh and dry weights of the leaves among all the treatments. The net photosynthesis rate of the full irrigation (FI) treatment was higher than that of the DI treatment. The photosynthesis rate at ambient air temperature was 19.7 μmol CO2m-2·s-1, the highest among all the treatments; however, the photosynthesis rate of the EHT treatment decreased by 60% (12.3 μmol CO2m-2·s-1). Additionally, the formation of guard cells in the leaf was abnormal with the EHT treatment, and there was a decrease in translocation efficiency. The effects of air temperature treatment were more pronounced on the physiological disorder rate and yield. The physiological disorder rate of the EHT treatment was the highest under the DI treatment condition. The yield of the AFI (ambient air temperature with full irrigation) treatment was 3,771 kg/10a, the highest among all the treatments; however, the yield of the EHT treatment with DI and FI was 1,282 and 1,327 kg/10a, respectively. These results indicate that growth and physiological disorder rate improved with the EHT treatment; however, there was a decrease in yield. Furthermore, the formation of guard cells was abnormal and malfunctional.

In this study, the purpose of the study is to determine the depth of damage caused by early frost damage in concrete slab structures under the conditions of external temperature during winter. In other words, we intend to analyze the depth variation of the early frost damage as the thickness of the concrete slab member changes under the condition of the 3-component binder frequently used in practice. As a result, the thinner the component, the significantly reduced the overall temperature of the concrete. In addition, the thinner the component thickness, the higher the delay in increasing the brightness of the core collected from the concrete member, and the greater the effect on the depth of the early frost damage was on the thinner the component thickness.