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 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 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.

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

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.

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.

Impacts of high air temperature of summer in Korea.

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

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...

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

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.

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.

Oysters are a major commercial and ecological fishery resource. Recently, the oyster industry has experienced mass mortality in summer due to environmental factors. Generally, the survival of oysters in aquatic environments is mainly impacted by environmental stressors such as elevated sea temperatures and reduced salinity; however, the stressors impacting tidal flat oysters that are repeatedly exposed to air remain poorly understood. Hence, we studied the relationship between environmental factors and the survival of tidal flat pacific oysters in Incheon, South Korea, where mass mortality is common. Principal component analysis and Bayesian networks revealed that air temperature (in spring and summer) and sea temperature (in summer) are related to oyster production. In habitats of the tidal flat oysters during the summer, high temperatures of 34.7–35.4°C (maximum 47.6°C) were observed for average durations of 0.8–1.9 hours (maximum 3.6 hours). Furthermore, heat waves occurred for up to 12 consecutive days. Results from the multiple stress test showed that when exposed to 45°C (air temperature) for 4 hours per day, the survival rate of oysters was 42.5% after only 2 days and 0% after 6 days. The findings stemming from the field observations and stress tests suggest that high temperatures during emersion may contribute to mass mortality of oysters in summer, indicating a potential threat to oysters due to climate change. To understand the effects of future thermal stress on oysters more accurately, simultaneous long-term trend analyses and field-based observations are required.

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.

We present a novel quasi-Bayesian method to weight multiple dynamical models by their skill at capturing both potentially non-linear trends and first-order autocorrelated variability of the underlying process, and to make weighted probabilistic projections. We validate the method using a suite of one-at-a-time cross-validation experiments involving Atlantic meridional overturning circulation (AMOC), its temperature-based index, as well as Korean summer mean maximum temperature. In these experiments the method tends to exhibit superior skill over a trend-only Bayesian model averaging weighting method in terms of weight assignment and probabilistic forecasts. Specifically, mean credible interval width, and mean absolute error of the projections tend to improve. We apply the method to a problem of projecting summer mean maximum temperature change over Korea by the end of the 21st century using a multi-model ensemble. Compared to the trend-only method, the new method appreciably sharpens the probability distribution function (pdf) and increases future most likely, median, and mean warming in Korea. The method is flexible, with a potential to improve forecasts in geosciences and other fields.

Spring mean temperatures were calculated by averaging daily temperatures from March to May, summer mean temperature from June to August, fall mean temperature from September to November, and winter mean temperature from December to February.23 climate variables: 19 bioclimate and 4 seasonal mean temperature variables considered in this study.

Algific talus slopes are characterized by locally detected unique micrometeorological phenomena such as cold air blowing or water getting frozen during summer and warm wind blowing during winter in a hole or crack on the rock. It is thus known that rare plants and plants that are uncommon in the environments at close proximity to humans are widely distributed on the algific talus slopes. Notably, as the habitats of polar and alpine plants that naturally grow in low temperature regions are being continuously reduced due to global warming or climate change, the micrometeorological phenomena on algific talus slopes, where low temperature is maintained even in summer, are critical for providing a refuge for plants sensitive to high temperatures and for the conservation of rare and endangered species. This study was conducted to rediscover the phytogeographic values of algific talus slopes by investigating the distribution of five plant types across 25 algific talus slopes as the specific areas of forest biodiversity. Vascular plants were investigated in each season during April 2016 to November 2021. We share the data of the sample collected here.