In 2024, the average air temperature in Japan's capital reached around **** degrees Celsius. Tokyo's annual mean air temperature increased by **** degrees Celsius since 1900, showing the progress of global warming. Weather in Tokyo Tokyo lies in the humid subtropical climate zone. It is affected by the monsoon circulation and has mild, sunny winters and hot, humid, and rainy summers. In most of Japan, the rainy season lasts from early June to mid-July. Furthermore, heavy rainfall is often caused by typhoons, which develop over the Pacific Ocean and regularly approach the archipelago between July and October. In recent years, the Kanto region, including Tokyo Prefecture, was approached by at least two typhoons each year. Since the winters are rather mild in Tokyo, the capital city does not often see snowfall and the snow rarely remains on the ground for more than a few days. Effects of global warming in Japan The increasing air temperature is one of the main consequences of global warming. Other effects are increased flooding frequency and a rise in sea levels due to melting ice caps. Global warming has already influenced Japan's climate in recent years, resulting in more frequent heat waves as well as increased annual rainfall. These weather changes can intensify natural disasters such as typhoons and inhibit the growth of crops. To counter global warming, Japan aims to reduce its greenhouse gas emissions by increasing its renewable and nuclear energy share.

Temperature in Japan increased to 13.11 celsius in 2024 from 13 celsius in 2023. This dataset includes a chart with historical data for Japan Average Temperature.

In 2024, the highest average monthly air temperature in Japan's capital Tokyo was recorded in August, reaching about ** degrees Celsius. With an average of *** degrees Celsius, January represented the month with the lowest temperature.  Weather in Japan Due to its wide range of latitude, Japan hosts contrasting climate regions, ranging from a humid continental climate in the north to a humid subtropical climate in the south. The island nation has four distinct seasons, but the weather conditions differ between the Pacific side and the Sea of Japan side. In Japan, the majority of rain falls during the rainy season, which usually lasts from early June to mid-July. Furthermore, heavy rain is often caused by typhoons, which regularly approach the archipelago between July and October.  Climate change and extreme weather Global warming has already influenced Japan's climate in recent years, resulting in increased average annual rainfall as well as an increase in the average annual temperature in Tokyo. These weather changes can intensify extreme weather situations and natural disasters such as heavy rain, typhoons, and heatwaves. In recent years, the higher frequency of heat waves with temperatures above ** degrees caused health problems for citizens, as shown in the increase in the number of patients taken to the hospital with heat strokes.

In 2023, the weather observing station in Naha, which is situated in the southernmost Japanese prefecture Okinawa, measured the highest annual average temperature of **** degrees Celsius. With around ** degrees Celsius, the lowest annual average temperature was measured in Sapporo, Hokkaido.

Context

It's just the average monthly temperature data ...

Content

Monthly average temperature around Aomori City, Aomori Prefecture, Japan from January 1882 to December 2019.

Acknowledgements

Thanks for the data provided by the Japan Meteorological Agency.

Inspiration

The average annual temperature is on the rise, but the trend seems to be different depending on the season and month. What does this mean?

The Historical Gridded Meteorological Dataset in Japan (HGMD-Japan) is a grided high-resolution (1km x 1km, approximately) daily (and in some cases hourly or yearly) meteorological datasets, intended for use in agricultural climate change analysis, created from 1978 to the latest year continuously. The daily data were created by overlaying the spatially interpolated differences between observed and climate normal at the meteorological observation stations onto the 1km resolution gridded climate data. In this process, in order to maintain time-series homogeneity in each variable, possible source of time-series heterogeneities unrelated to climate change, such as changes in statistical methods and instrument types, were corrected as much as possible.

The details of this dataset are described as follows.

■ Common items Projection: Geographic Geodetic system: Tokyo Datum

◆ Daily data Directory structure: HGMDJ_NARO(YYYY)daily[file] File name: (YYYY)_d_(element).bin Element name (element): Mean temperatures (tmp) [0.1 °C]
Maximum temperatures (hourly) (tmx) [0.1 °C] Minimum temperatures (hourly) (tmn) [0.1 °C] Precipitation (pre) [0.1 mm] Solar radiation (srd) [0.1 MJ/m2/d] Sunshine duration (sdr) [0.1 hour] Relative humidity (rhu) [0.1 %] Wind speed at 2.5m height (wsd) [0.1 m/s] Downward long wave radiation (lrd) [0.1 MJ/ m2/d] Potential evapotranspiration (pet) [0.1 mm] FAO reference evapotranspiration (eto) [0.1 mm] Paddy water temperature (LAI=0) (tw0) [0.1 °C] Paddy water temperature (LAI=∞) (twi) [0.1 °C] Error value: -999 Record format: Data format: Binary format (little endian) Data size: 278,237,440 bytes Record length: 736 bytes (4+366*2: see below) Number of rows (meshes): 378040 Structure: 1) 3rd mesh code (4 byte long), data (2 byte short) x 366 days 2) 3rd mesh code (4 byte long), data (2 byte short) x 366 days ・・・ 378040) 3rd mesh code (4 byte long), data (2 byte short) x 366 days * Dummy (-999) for the 366th day in no-leap years

◆ Hourly data Directory structure: HGMDJ_NARO(YYYY)hourly[element][file] File name: (YYYYMMDD)_h_(element).bin Element name (element): Rice panicle temperatures (tp) [0.1 °C] Air temperatures (ta) [0.1 °C] Error value: -999 Record format: Data format: Binary format (little endian) Data size: 19,658,080 bytes Record length: 52 bytes (4+24*2: see below) Number of rows (meshes): 378040 Structure: 1) 3rd mesh code (4 byte long), data (2 byte short) x 24 hours 2) 3rd mesh code (4 byte long), data (2 byte short) x 24 hours ・・・ 378040) 3rd mesh code (4 byte long), data (2 byte short) x 24 hours

◆ Yearly data Directory structure: HGMDJ_NARO(YYYY)yearly[file] File name: (YYYY)_y_(element).bin Element name (element): Heat-dose of daily maximum temperature above 35 ℃ (HD_x35) (hdx35) [0.1 °C day] Heat-dose of daily minimum temperature above 25 ℃ (HD_n25) (hdn25) [0.1 °C day] Heat-dose of daily mean temperature above 26 ℃ (HD_m26) (hdm26) [0.1 °C day] Mean air temperature during 20 days after heading date (hed20atm) [0.1 °C] HD_m26 during 20 days after heading date (hed20hdm26) [0.1 °C day] Mean panicle temperature during daytime within 5 days around heading date (ptm5dc) [0.1 °C] Mean panicle temperature during daytime within 7 days around heading date (ptm7dc) [0.1 °C] Error value: -999 Record format: Data format: Binary format (little endian) Data size: 2,268,240 bytes Record length: 6 bytes (4+2: see below) Number of rows (meshes): 378040 Structure: 1) 3rd mesh code (4 byte long), data (2 byte short) 2) 3rd mesh code (4 byte long), data (2 byte short) ・・・ 378040) 3rd mesh code (4 byte long), data (2 byte short)

Context It's just the average monthly temperature data …

Content Monthly average temperature around Hiroshima City, Hiroshima Prefecture, Japan from January 1900 to November　2023.

In 2022, the annual mean air temperature in Kagoshima, Japan amounted to around **** degrees Celsius. Figures increased compared to about **** degrees Celsius in 2013. Kagoshima Prefecture is located in the southern tip of the main island Kyushu.

Content

This data was downloaded via a POST request to Japanese Meteorological Agency's page on historical data. The site numbers were retrieved from the agency's site master index.

All temperatures are in Celsius.

Data Files

The main file, Japanese_City_Temps.csv has all of the cities from the master index combined into a single CSV.

The individual cities are in their own CSVs under the individual_cities directory. A couple of column notes. I left kanji in the Average Temperature column in case there were any discrepancies I missed in my initial download. The other columns are marked with a tn to indicated a translator note. Those were my attempts at translating what those columns were intended for in the original files.

Context This dataset provides weather data for Tokyo, covering the period from June 26, 2018, to June 26, 2024. The data is sourced from the Japan Meteorological Agency (JMA). According to their usage terms, numerical figures are not subject to copyright and can be freely used.

Content The dataset includes daily weather data for Tokyo with the following columns:

• Date: The date of the recorded data.
• Average Temperature (°C): The average temperature for the day.
• Highest Temperature (°C): The highest temperature recorded for the day.
• Highest Temperature (°C) Datetime: The date and time when the highest temperature was recorded.
• Lowest Temperature (°C): The lowest temperature recorded for the day.
• Lowest Temperature (°C) Datetime: The date and time when the lowest temperature was recorded.
• Total Precipitation (mm): The total precipitation for the day.
• Sunshine Duration (hours): The total duration of sunshine for the day.
• Maximum Snow Depth (cm): The maximum snow depth recorded for the day.
• Maximum Snow Depth (cm) Datetime: The date and time when the maximum snow depth was recorded.
• Total Snowfall (cm): The total snowfall for the day.
• Average Wind Speed (m/s): The average wind speed for the day.
• Maximum Wind Speed (m/s): The maximum wind speed recorded for the day. Maximum wind speed refers to the highest 10-minute average wind speed observed within a specific time period.
• Maximum Wind Speed (m/s) Datetime: The date and time when the maximum wind speed was recorded.
• Maximum Wind Speed (m/s) Direction: The direction of the maximum wind speed recorded.
• Maximum Gust Speed (m/s): The maximum gust speed recorded for the day. Maximum gust speed refers to the highest instantaneous wind speed observed, typically measured over a 3-second period.
• Maximum Gust Speed (m/s) Datetime: The date and time when the maximum gust speed was recorded.
• Maximum Gust Speed (m/s) Direction: The direction of the maximum gust speed recorded.
• Most Frequent Wind Direction (16-point compass): The most frequent wind direction recorded using a 16-point compass.
• Average Vapor Pressure (hPa): The average vapor pressure for the day.
• Average Humidity (%): The average humidity for the day.
• Minimum Relative Humidity (%): The minimum relative humidity for the day.
• Minimum Relative Humidity (%) Datetime: The date and time when the minimum relative humidity was recorded.

Inspiration 1. Climate Change Analysis Analyze Tokyo's weather data to identify climate change impacts and trends over the past four years, aiding in the development of accurate climate models and policies. Note that certain usage restrictions apply under specific laws such as the Meteorological Service Act; see ML-17 and ML-23 for details.

1. Renewable Energy Optimization Optimize solar and wind energy deployment in Tokyo by assessing sunshine and wind data, improving renewable energy efficiency and supporting sustainability goals.

2. Urban Planning and Public Health Use Tokyo's weather data to enhance urban planning and public health initiatives, mitigating heat islands, reducing flood risks, and improving residents' quality of life.

Acknowledgements Special thanks to the Japan Meteorological Agency for providing this valuable data. When using this data, please attribute it as follows:

出典：気象庁ホームページ　https://www.jma.go.jp/jma/kishou/info/coment.html

From 2016 to 2021, a national survey of birds has been conducted as "Japan Breeding Bird Atlas" We conducted two complete survey courses within each cell of a 20km square mesh (total 2344 courses) placed as a graticule over the map of Japan. Using this data, we determined the average temperature of breeding birds in Japan. The mean temperatures of the distribution areas of various bird species (species temperature index: STI) weighted with number of individuals were calculated. Species recorded at over 30 sites were indicated.

Disclaimer

I have prepared the data for RV_Forecasting EDA and I do have no claim on data's usage rights. All data belongs to JMA. Please use it at your own risk. I hope you could find this dataset useful as well and share your experiences with me.

Description

Since JMA does not do all the possible calculations in many weather stations, I have focused on prefecture-centres which nearly all calculations are made in the expense of accuracy in the geographic tagging. It is assumed that all the districts within a prefecture should have similar weather conditions in a given day.

Content

date calendar date in classic Y-M-D format.

air_district1 could be harvested from air_area_name column via str_split_fixed(air_area_name, " ", n = 3)[,1] code utilizing stringr package in R

avg_temp Average Temperature Data

rain_amount Amount of Precipitation in centimetres

sunshine_hours Daylight in hours

wind_speed Wind_Speed in kilometres-per-hour

snowfall Total snowfall during day in centimetres

In 2024, the average air temperature in Naha amounted to around **** degrees Celsius. Figures increased throughout the past decade, compared to around ** degrees Celsius in 2013. Naha is the capital city of Okinawa Prefecture, the southernmost island of Japan.

Japan Heating Degree Days data was reported at 4,740.880 Degrees Celsius in 2020. This records a decrease from the previous number of 4,764.450 Degrees Celsius for 2019. Japan Heating Degree Days data is updated yearly, averaging 5,237.220 Degrees Celsius from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 6,013.210 Degrees Celsius in 1984 and a record low of 4,672.320 Degrees Celsius in 2015. Japan Heating Degree Days data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Environmental: Climate Risk. A heating degree day (HDD) is a measurement designed to track energy use. It is the number of degrees that a day's average temperature is below 18°C (65°F). Daily degree days are accumulated to obtain annual values.;World Bank, Climate Change Knowledge Portal. https://climateknowledgeportal.worldbank.org;;

Dataset

This dataset was created by Tetsuya Sasaki

Released under CC BY-NC-SA 4.0

Contents

In this study, the price elasticity of water demand was estimated using disaggregated data of approximately 30,000 households recorded over five years: two years before and three years after a tariff revision. From the results of the latent class analysis, the mean price elasticity was − -0.1. The households were divided into three groups: 35%–55% of the households did not respond to the tariff revision, and households with high water demand prior to the revision had higher elasticity. In addition, no statistically significant difference was observed in elasticity between the first and third years after revision. This dataset includes household water demand, price, and average temperature by month in Hadano City, Kanagawa, Japan.Â

In 2024, areas across Japan measured **** days on average with a temperature of ** degrees Celsius and above, the highest number of days within this range in the country's recorded weather history.Most areas on the main island Honshu have a humid subtropical climate that is characterized by warm and rainy summers and fairly mild winters. The source stated that the average number of days with ** degrees and above increased significantly from **** days in 1910.

Japan Cooling Degree Days data was reported at 998.270 Degrees Celsius in 2020. This records an increase from the previous number of 992.380 Degrees Celsius for 2019. Japan Cooling Degree Days data is updated yearly, averaging 823.280 Degrees Celsius from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 1,096.980 Degrees Celsius in 2010 and a record low of 537.130 Degrees Celsius in 1993. Japan Cooling Degree Days data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Environmental: Climate Risk. A cooling degree day (CDD) is a measurement designed to track energy use. It is the number of degrees that a day's average temperature is above 18°C (65°F). Daily degree days are accumulated to obtain annual values.;World Bank, Climate Change Knowledge Portal. https://climateknowledgeportal.worldbank.org;;

Urban Tokyo Temperature Dataset

This dataset contains daily weather observations for the 23 special wards of Tokyo, Japan (2010–2020).

  Columns

date: Date of observation temp_c: Mean temperature (°C) dew_c: Dew point (°C) humidity: Relative humidity (%) wind_kph: Wind speed (km/h) pressure_hg: Atmospheric pressure (inHg) precip_mm: Precipitation (mm) district: Tokyo ward (23 classes) year: Year month: Month (string)

  Size

Rows: 92,414 File size: 6.23 MB… See the full description on the dataset page: https://huggingface.co/datasets/torodriguezt/Urban_Tokyo_Temperature.

BackgroundIn metropolitan Tokyo in 2014, Japan experienced its first domestic dengue outbreak since 1945. The objective of the present study was to quantitatively assess the future risk of dengue in Japan using climate change scenarios in a high-resolution geospatial environment by building on a solid theory as a baseline in consideration of future adaptation strategies.MethodsUsing climate change scenarios of the Model for Interdisciplinary Research on Climate version 6 (MIROC6), representative concentration pathway (RCP) 2.6, 4.5, and 8.5, we computed the daily average temperature and embedded this in the effective reproduction number of dengue, R(T), to calculate the extinction probability and interepidemic period across Japan.ResultsIn June and October, the R(T) with daily average temperature T, was 1 during these months under RCP8.5. The time period with a risk of dengue transmission gradually extended to late spring (April–May) and autumn (October–November). Under the RCP8.5 scenario in 2100, the possibility of no dengue-free months was revealed in part of southernmost Okinawa Prefecture, and the epidemic risk extended to the entire part of northernmost Hokkaido Prefecture.ConclusionEach locality in Japan must formulate action plans in response to the presented scenarios. Our geographic analysis can help local governments to develop adaptation policies that include mosquito breeding site elimination, distribution of adulticides and larvicides, and elevated situation awareness to prevent transmission via bites from Aedes vectors.