In 2023, the average summer temperature in South Korea was around **** degrees Celsius, up from **** degrees Celsius in the previous year. The highest temperature since 2000 was **** degrees Celsius in 2018, while the lowest temperature was **** degrees Celsius in 2003.

In 2018, South Korea recorded its hottest summer since 1973, with 31 heat-wave days. Heatwaves with maximum temperatures above 33 degrees Celsius usually occur after the rainy season in summer. In recent years, not only has the frequency of heatwaves increased, but also their intensity. Summer in South Korea Summer in South Korea (from June to August) is usually hot and humid with a lot of rainfall during the rainy season of the East Asian monsoon (Changma). About 60 percent of precipitation falls during this season. The average temperature in summer was around 24.7 degrees Celsius in 2023. The amount of precipitation in summer that year stood at over 1,000 millimeters, more than four times higher than in winter. Climate change South Korea is known for its four distinct seasons, yet weather patterns have increasingly changed in recent decades, resulting in longer summers and shorter winters. This shows that South Korea is not excluded from the effects of climate change. Changing climate patterns in recent decades have also led to an intensification of precipitation and more heat waves in South Korea. Meanwhile, climate change is taken very seriously by South Koreans: about 48 percent of respondents to a 2019 survey said that global warming or climate change is the most important environmental issue for South Korea.

In June 2025, the average temperature in South Korea was **** degrees Celsius. August 2024 was the hottest month in the past five years, with a mean of around **** degrees Celsius. In the same period, December 2022 was the coldest month, with an average temperature of minus *** degrees Celsius.

In May 2025, the average temperature in Incheon, South Korea was 16.5 degrees Celsius. August 2024 was the city's hottest month in the past six years, while December 2022 was the coldest, with an average temperature of minus 2.6 degrees Celsius.

In May 2025, the average temperature in Jeju, South Korea, was 17.5 degrees Celsius. The island's hottest month was August 2024, while February 2022 was the coldest, with an average temperature of 5.2 degrees Celsius.

In May 2025, the average temperature in Busan, South Korea was 17.4 degrees Celsius. August 2024 was the city's hottest month in the past five years, while February 2025 was the coldest, with an average temperature of 2.9 degrees Celsius.

In May 2025, the average temperature in Seoul, South Korea was **** degrees Celsius. August 2024 was the hottest month in the city in the past six years, while December 2022 was the coldest, with an average temperature of minus *** degrees Celsius.

In May 2025, the average temperature in Gwangju, South Korea was 18.2 degrees Celsius. August 2024 was the city's hottest month in the past six years, while December 2022 and February 2025 were the coldest, with an average temperature of 1.1 degrees Celsius.

Summary of Korean summer mean maximum temperature change probabilistic projections from 1973–2005 to 2081–2100 under the RCP8.5 emissions scenario from the “trend” and “trend+var” methods.

For extreme temperature, we used climate extreme indices provided by CLIVAR (Climate and Ocean-Variability, Predictability, and Change) ETCCDI (Expert Team on Climate Change Detection and Indices). ETCCDI has provided 27 climate extreme indices not only with global reanalysis datasets but with CMIP5 simulations. The indices data are available on-line and the results with CMIP5 simulations were summarized by Sillmann et al. [2013]. For our analysis, we downloaded a monthly minimum of daily minimum surface air temperature (TNn) and a monthly maximum of daily maximum temperature (TXx). Among the CMIP5, 27 model results available on their website, we used 23 model results containing both of the TNn and TXx for all of the historical, RCP 4.5 and 8.5 experiments.

Since our focus is on boreal-winter extreme temperature, we selected the lowest TNn and highest TXx among the three months of December-January-February every year from 1861 to 2005 for the historical simulation and from 2006 to 2099 for the RCP 4.5 and RCP 8.5 scenario. Before the spatial averaging over the analysis domain (34°N-43°N in latitude and 124°E-131°E in longitude including the Korean Peninsula), we had remapped all of the simulation data onto a 1.5° x 1.5° horizontal resolution.

The time of unprecedented climate (TUC) for extreme temperature is defined in this study as the beginning year when the extreme temperature projected for the future climate scenarios exceed a critical value in all subsequent years during the RCP scenario runs.

In this study, the critical value for extreme temperatures is specified as a 50-year return level which is rather arbitrary but refers to a rough estimate for the social lifetime of a man. One may find the return level empirically from historical data, but this study estimates it using a Generalized Extreme Value distribution function as suggested by Kharin et al. [2007]. Based on the CMIP5 historical simulation data using R, we obtained three parameters determining a GEV distribution for each model, respectively for TNn and TXx. The GEV distribution for each model and variable has been verified using a Q-Q (quantile-quantile) plot if it adequately describes the CMIP5 historical data. All of the models showed the Q-Q plot within the 95% confidence range (Figure 1a for GFDL-ESM2G TXx for an instance). Then, we estimated the return level from the distribution and TUC from the RCP scenario runs for the wintertime TNn and TXx averaged over Korea.

Distribution of weather and death descriptions in the past and in recent times of summer.

In 2024, precipitation in Jeju in South Korea was the highest nationwide, with about 1928.9 millimeters. Gyeongnam followed with around 1713.6 millimeters.

Contains data from the World Bank's data portal covering the following topics which also exist as individual datasets on HDX: Agriculture and Rural Development, Aid Effectiveness, Economy and Growth, Education, Energy and Mining, Environment, Financial Sector, Health, Infrastructure, Social Protection and Labor, Poverty, Private Sector, Public Sector, Science and Technology, Social Development, Urban Development, Gender, Millenium development goals, Climate Change, External Debt, Trade.

Impacts of high air temperature of summer in Korea.

Yearly citation counts for the publication titled "Sensitivity of summer precipitation over the Korean Peninsula to temperature gradients".

In 2023, the average temperature for summer in South Korea was **** degrees Celsius. South Korea has four distinct seasons, which can be seen in the different average temperatures for each season.

This dataset provides comprehensive hydrometeorological data from South Korea, sourced through the WAMIS Open API. It includes hourly, daily, and monthly records of precipitation, water levels, meteorological conditions, river flow rates, and suspended sediment loads. The data is collected from various stations across South Korea and is regularly updated to support environmental monitoring, research, and water resource management. Users can access real-time and historical data, making this dataset valuable for climate studies, hydrological modeling, and infrastructure planning.

This catalog includes the following data resources:

Hourly Precipitation Data: Precipitation levels recorded every hour over the last 3 days.

Daily Precipitation Data: Daily precipitation measurements covering the last 3 months.

Monthly Precipitation Data: Monthly precipitation data spanning the last 3 years.

Hourly Water Level Data: Water level data recorded hourly for various rivers, updated every 3 hours.

Daily Water Level Data: Daily water level records from the last 3 months for multiple stations.

Hourly Meteorological Data: Hourly meteorological data including temperature, humidity, wind speed, and solar radiation.

Daily Meteorological Data: Daily meteorological summaries, ideal for longer-term climate analysis.

Daily River Flow Rate Data: Daily records of river flow rates for the current year.

Suspended Sediment Load Data: Information on sediment load concentrations and flow rates over the last 3 years.

This data provides data on heated effluent discharge and temperature difference for each of Korea Western Power's plants (Taean, Pyeongtaek, Gunsan, and Seoincheon). These data are key indicators for assessing the environmental impact of cooling water discharged from power plants back into the water system. The monthly average temperature difference, calculated by comparing the water temperatures at the inlet and outlet, reflects seasonal variations. The temperature difference increases in summer due to increased cooling load and decreases in winter due to the increased temperature difference. Analysis of this monthly average data allows for a quantitative understanding of the thermal impact of power plant operations on aquatic ecosystems. This data serves as the basis for assessing compliance with environmental standards and developing efficient water resource management strategies.

Understanding climatic effect on wildlife is essential to prediction and management of climate change’s impact on the ecosystem. The climatic effect can interact with other environmental factors. This study aimed to determine effects of climate and altitude on Siberian roe deer (Capreolus pygargus) activity in temperate forests of South Korea. We conducted camera trapping to investigate roe deer’s activity level from spring to fall. Logistic regressions were used to determine effects of diel period, temperature, rain, and altitude on the activity level. A negative relationship was noted between temperature and the activity level due to thermoregulatory costs. Roe deer activity exhibited nocturnal and crepuscular patterns during summer and the other seasons, respectively, possibly due to heat stress in summer. In addition, the effect of temperature differed between high- and low-altitude areas. In low-altitude areas, temperature affected negatively the activity level throughout the study..., The camera trapping method was used to observe temporal variations in roe deer capture (sampling days: September to October 2021 and April to August 2022). In the study area, a 5 × 6 grid design (interval = 600 m) was established, and one trail camera (Spec Ops Elite HP4; Browning Co., USA) was deployed corresponding to each cell of the grid. The study period was divided into five seasons, and further analyses were performed for each season: spring (15 April to 15 May, 960 trap-days), early summer (16 May to 30 June, 1380 trap-days), summer (1 July to 31 August, 1860 trap-days), early fall (September, 900 trap-days) and fall (October, 810 trap-days). The camera-plot altitudes were categorised into four classes: 600 (600–800 m asl, n = 3), 800 (800–1,000 m asl, n = 10), 1,000 (1,000–1,200 m asl, n = 11) and 1,200 (1,200–1,400 m asl, n = 6). We created a roedeer variable as presence/absence of observation per 2-h in each altitude class. In order to account for sampling effort depending on..., , This README file was generated on 2023-09-22 by Tae-Kyung Eom.

GENERAL INFORMATION

1. Title of Dataset: Adaptive response of Siberian roe deer (Capreolus pygargus) to climate and altitude in the temperate forests of South Korea

2. Author Information A. Principal Investigator Contact Information Name: Tae-Kyung Eom Institution: Chung-Ang University Address: Ansung, South Korea Email: xorud147@naver.com

   B. Associate or Co-investigator Contact Information Name: Jae-Kang Lee Institution: Chung-Ang University Address: Ansung, South Korea

   Name: Dong-Ho Lee Institution: Chung-Ang University Address: Ansung, South Korea

   Name: Hyeongyu Ko Institution: Chung-Ang University Address: Ansung, South Korea

   Name: Shin-Jae Rhim Institution: Chung-Ang University Address: Ansung, South Korea

3. Date of data collection (single date, range, approximate date): 2021-2022

4. Geographic location of data collection: Mt. Gariwang, Pyeo...

A service that provides weather forecasts (ultra-short-term forecasts/1-hour intervals, short-term forecasts/3-hour intervals) for beaches nationwide, tide information, wave height information (data from the closest marine observation equipment point to the beach), sunrise and sunset information (based on the point where the beach is located, using data from the Korea Astronomy and Space Science Institute), water temperature information, and high and low tides (based on the closest tide station to the beach, using data from the National Oceanographic Research Institute). To support safe leisure activities for the public during the summer, a weather service is provided for major beaches nationwide, and the target locations are Eulwang-ri, Wangsan, Hanagae, Minmeoru, Janggyeong-ri, Ongam, Sugi, Dongmak, Seopo-ri, Siplipo, Gureop, Ttepuru, Batjireum, Handeul, Keunpulan, Janggol, and Beolan, approximately 330 locations.