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

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.

South Korea Climate Change: Tax Revenue: USD: Transport data was reported at 8.558 USD bn in 2021. This records an increase from the previous number of 7.804 USD bn for 2020. South Korea Climate Change: Tax Revenue: USD: Transport data is updated yearly, averaging 5.896 USD bn from Dec 1994 (Median) to 2021, with 28 observations. The data reached an all-time high of 13.006 USD bn in 2014 and a record low of 2.859 USD bn in 1998. South Korea Climate Change: Tax Revenue: USD: Transport data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Cross Cutting Domains: OECD Member: Annual.

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.

South Korea Climate Change: Tax Revenue: % of GDP: Transport data was reported at 0.471 % in 2021. This records a decrease from the previous number of 0.475 % for 2020. South Korea Climate Change: Tax Revenue: % of GDP: Transport data is updated yearly, averaging 0.599 % from Dec 1994 (Median) to 2021, with 28 observations. The data reached an all-time high of 0.985 % in 1996 and a record low of 0.458 % in 2019. South Korea Climate Change: Tax Revenue: % of GDP: Transport data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Cross Cutting Domains: OECD Member: Annual.

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, Private Sector, Public Sector, Science and Technology, Social Development, Urban Development, Gender, Climate Change, External Debt, Trade.

South Korea Climate Change: Tax Revenue: % of Total Environmental Related Tax Revenue: Energy data was reported at 60.299 % in 2014. This records a decrease from the previous number of 62.378 % for 2013. South Korea Climate Change: Tax Revenue: % of Total Environmental Related Tax Revenue: Energy data is updated yearly, averaging 71.778 % from Dec 1994 (Median) to 2014, with 21 observations. The data reached an all-time high of 79.596 % in 2004 and a record low of 43.886 % in 1994. South Korea Climate Change: Tax Revenue: % of Total Environmental Related Tax Revenue: Energy data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Cross Cutting Domains: OECD Member: Annual.

this work provides the Korean weather dataset

South Korea Climate Change: Tax Revenue: % of GDP: Resources data was reported at 0.000 % in 2021. This stayed constant from the previous number of 0.000 % for 2020. South Korea Climate Change: Tax Revenue: % of GDP: Resources data is updated yearly, averaging 0.000 % from Dec 1994 (Median) to 2021, with 28 observations. The data reached an all-time high of 0.000 % in 2021 and a record low of 0.000 % in 2021. South Korea Climate Change: Tax Revenue: % of GDP: Resources data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Cross Cutting Domains: OECD Member: Annual.

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 set contains the Coordinated Energy and Water Cycle Observation Project (CEOP) Enhanced Observing Period 3 (EOP-3) CEOP Asia-Australia Monsoon Project (CAMP) Korean Haenam Hourly Soil Data Set. This data set contains data at a half-hour resolution from one station in the CAMP reference site for the CEOP EOP-3 time period, which is the Korean Haenam station. This dataset only contains the entire EOP-3 time period (i.e., 1 October 2002 through 30 September 2003). This data set contains both ASCII data and netCDF data. The ASCII data file covers the entire time period for all stations. The netCDF data file covers the entire time period with one netCDF file for each station.

Species distribution modeling is widely used for evaluating invasion risk, and for prioritizing areas for the control and management of invasive species. However, selecting a modeling tool that accurately predicts species invasion risk requires a systematic approach. In this study, five species distribution models (SDMs), namely, artificial neural network (ANN), generalized linear model (GLM), multivariate adaptive regression splines (MARS), maximum entropy (MaxEnt), and random forest (RF), were performed and evaluated their model performance using the mean value of area under the curve (AUC), true skill statistics (TSS), and Kappa scores of 12 ecosystem disturbing alien plant species (EDAPS). The mean evaluation metric scores were highest in RF (AUC = 0.924 ± 0.058, TSS = 0.789 ± 0.109, Kappa = 0.671 ± 0.096, n = 12) and lowest in ANN. The ANOVA of AUC, TSS, and Kappa metrics revealed the RF model was significantly different from other SDMs and was therefore selected as the relatively best model. The potential distribution area and invasion risk for each EDAPS were quantified. Under the current climate conditions of South Korea, the average potential distribution area of EDAPS was estimated to be 13,062 km2. However, in future climate change scenarios, the average percentage change of EDAPS distribution relative to the current climate was predicted to be increased over 219.93%. Furthermore, under the current climate, 0.16% of the area of the country was estimated to be under a very high risk of invasion, but this would increase to 60.43% by 2070. Invasion risk under the current climate conditions was highest in the northwestern, southern, and southeastern regions, and in densely populated cities, such as Seoul, Busan, and Daegu. By 2070, invasion risk was predicted to expand across the whole country except in the northeastern region. These results suggested that climate change induced the risk of EDAPS invasiveness, and SDMs could be valuable tools for alien and invasive plant species risk assessment.

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 describes the weather data of 64 cities in Korea for each day and the weather anomaly scores for each day from 2010 to 2020. The dataset includes city name, dates, temperature, humidity, vapor pressure, dew point temperature, sea level pressure, ground pressure, ground temperature, LOF anomaly score, IF anomaly score, COPOD anomaly score, ABOD anomaly score, HBOS anomaly score, SOD anomaly score and ROD anomaly score. In the dataset, the weather data and the weather anomaly score of each day for 64 Korean cities from 2010 to 2020 are stored into 64 csv files. Each csv file in the dataset represents each city. The 64 cities include Seoul, the capital of Korea, and the 6 metropolitan cities of Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. In addition, the weather data and weather anomaly scores for 19 coastal cities and 4 islands in Korea are included in the dataset.

Comprehensive dataset of 44 Weather forecast services in South Korea as of August, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

South Korea Official Development Assistance: % of Total ODA: Climate Change Adaptation data was reported at 40.580 % in 2022. This records an increase from the previous number of 37.580 % for 2021. South Korea Official Development Assistance: % of Total ODA: Climate Change Adaptation data is updated yearly, averaging 10.850 % from Dec 2010 (Median) to 2022, with 13 observations. The data reached an all-time high of 40.580 % in 2022 and a record low of 2.140 % in 2011. South Korea Official Development Assistance: % of Total ODA: Climate Change Adaptation data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.GGI: Environmental: Environmental Policy, Taxes and Transfers: OECD Member: Annual.

Please refer to the 'Readme' file.

South Korea Climate Change: Tax Revenue: % of GDP: Pollution data was reported at 0.000 % in 2021. This stayed constant from the previous number of 0.000 % for 2020. South Korea Climate Change: Tax Revenue: % of GDP: Pollution data is updated yearly, averaging 0.000 % from Dec 1994 (Median) to 2021, with 28 observations. The data reached an all-time high of 0.000 % in 2021 and a record low of 0.000 % in 2021. South Korea Climate Change: Tax Revenue: % of GDP: Pollution data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Korea – Table KR.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Cross Cutting Domains: OECD Member: Annual.