In 2024, the average summer temperature in Germany was **** degrees Celsius. This was basically unchanged compared to the year before. While figures fluctuated during the given timeline, there were regular peaks, and in general, temperatures had grown noticeably since the 1960s. Not beating the heat German summers are getting hotter, and as desired as warm weather may be after months of winter (which, incidentally, also warms up year after year), this is another confirmation of global warming. Higher summer temperatures have various negative effects on both nature and humans. Recent years in Germany have seen a growing number of hot days with a temperature of at least 30 degrees, with **** recorded in 2023. However, this was a decrease compared to the year before. The number of deaths due to heat and sunlight had peaked in 2015. Rain or shine All the German states saw less sunshine hours in 2023 compared to the previous year. The sunniest states were Baden-Württemberg, Bavaria and Saarland. Meanwhile, summer precipitation in Germany varied greatly during the same timeline as presented in this graph, but 2022 was one of the dryest years yet.

Based on current monthly figures, on average, German climate has gotten a bit warmer. The average temperature for January 2025 was recorded at around 2 degrees Celsius, compared to 1.5 degrees a year before. In the broader context of climate change, average monthly temperatures are indicative of where the national climate is headed and whether attempts to control global warming are successful. Summer and winter Average summer temperature in Germany fluctuated in recent years, generally between 18 to 19 degrees Celsius. The season remains generally warm, and while there may not be as many hot and sunny days as in other parts of Europe, heat waves have occurred. In fact, 2023 saw 11.5 days with a temperature of at least 30 degrees, though this was a decrease compared to the year before. Meanwhile, average winter temperatures also fluctuated, but were higher in recent years, rising over four degrees on average in 2024. Figures remained in the above zero range since 2011. Numbers therefore suggest that German winters are becoming warmer, even if individual regions experiencing colder sub-zero snaps or even more snowfall may disagree. Rain, rain, go away Average monthly precipitation varied depending on the season, though sometimes figures from different times of the year were comparable. In 2024, the average monthly precipitation was highest in May and September, although rainfalls might increase in October and November with the beginning of the cold season. In the past, torrential rains have led to catastrophic flooding in Germany, with one of the most devastating being the flood of July 2021. Germany is not immune to the weather changing between two extremes, e.g. very warm spring months mostly without rain, when rain might be wished for, and then increased precipitation in other months where dry weather might be better, for example during planting and harvest seasons. Climate change remains on the agenda in all its far-reaching ways.

This statistic shows the average temperature in Germany in the summers of 2023 and 2024, by federal state. In summer 2024, the average temperature in Berlin was **** degrees Celsius. This made Berlin the warmest federal state in the period in question, followed by Brandenburg and Baden-Württemberg.

Temperature in Germany increased to 10.88 celsius in 2023 from 10.78 celsius in 2022. This dataset includes a chart with historical data for Germany Average Temperature.

In 2023/2024, the average winter temperature in Germany was *** degrees Celsius. That winter was part of a growing list of warmer winters in the country. Figures had increased noticeably compared to the 1960s. Warmer in the winter Everyone has a different perception of what actually makes a cold or warm winter, but the fact is that winter temperatures are, indeed, changing in Germany, and its 16 federal states are feeling it. Also in 2022/2023, Bremen and Hamburg in the north recorded the highest average figures at around 4 degrees each. The least warm states that year, so to speak, were Thuringia, Saxony, and Bavaria. The German National Meteorological Service (Deutscher Wetterdienst or DWD), a federal office, monitors the weather in Germany. Global warming Rising temperatures are a global concern, with climate change making itself known. While these developments may be influenced by natural events, human industrial activity has been another significant contributor for centuries now. Greenhouse gas emissions play a leading part in global warming. This leads to warmer seasons year-round and summer heat waves, as greenhouse gas emissions cause solar heat to remain in the Earth’s atmosphere. In fact, as of 2022, Germany recorded **** days with a temperature of at least 30 degrees Celcius, which was more than three times the increase compared to 2021.

This dataset contains outputs from two runs of a coupled atmosphere-ocean model at DKRZ in Hamburg. The runs were made in 1990 and they include a control run and an IPCC Scenario A run. We received 100 years of monthly 10-year climatologies of 2m temperature, precipitation, net surface solar radiation, and reflected surface solar radiation in GRIB0 format. We also received outputs from 100-year transient runs (control, IPCC Scenario A, and IPCC Scenario D). These included monthly means of 59 parameters at the surface and 15 isobaric levels. We were notified in May 1993 that there was a problem with the vertical interpolation in those runs, so the data are no longer in our public distribution, but they remain in our archive.

Overview

These are two multi-annual raster products from the german weather service, that got refined from a 1km grid to a 25m grid, by using a local regression model.

The base rasters from DWD are:

• HYRAS precipitation
• REGNIE precipitation
• DWD-grid (precipitation, potential evapotranspiration and temperature 2m above ground)

To refine the grids the Copernicus DEM with a resolution of 25m got used. For every cell a linear regression model got created, by selecting the multi-annual rasters value and the elevation, from the original digital elevation model that was used by the DWD to create the raster, in a certain window around the cell. This window was at least 2 cells around the considered cell, so 5x5=25 cells. If the standard deviation of the elevation in this window was less than 4m, more neighbooring cells are considered until a maximum of 13x13=169 cells are considered. This widening of the window was necessary for flat regions to get a reasonable regression model.

Out of these combinations of elevation and climate parameter a linear regression model was build. These regression models are then applied to the finer digital elevation model with its 25m resolution from Copernicus.

The following image illustrates the generation of the refined rasters on a small example window:

Data sets of current German weather stations updated hourly or every twelve hours. Data sets, in German, include: * Daily mean values ??of temperature, updated hourly. Daily archive since 29.1.2008 * Daily maximum and minimum temperature, updated every 12 hours. Daily archive since 21.7.2008 * Monthly mean values ??of temperature and deviation, updated daily . * Rainfall in the last 12 hours and monthly total, updated every 12 hours . * Monthly totals of precipitation and relative to langj. means in%, updated every 12 hours. Monthly Archive since Feb. 2008 * Air pressure and pressure tendency, updated hourly.

Average temperature since 1881 in Germany, time series for areal means for federal states and combinations of federal states.

This statistic shows the average precipitation amount in summer in Germany from 1960 to 2024. In 2024, summer precipitation in Germany amounted to 240 liters per square meter. This was a decrease compared to the previous year. Figures have fluctuated over the timeline under review.

Quality controlled and gap-filled continuous air temperature data from the urban weather station at Freiburg-Werthmannstrasse (FRWRTM, 7.8447ºE, 47.9928, 277 m) using a passively ventilated and shielded temperature and humidity probe (Campbell Scientific Inc., CS 215) operated in a Stevenson Screen 2m above ground level in the vegetated backyard of Werthmannstrasse 10, 79098 Freiburg im Breisgau, Germany.

• Quality controlled in-canopy air temperature data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2024.
• Average, minimum and maximum in-canopy air temperatures are provided on hourly, daily, monthly and annual scales.
• Characteristic hours and days are reported on daily, monthly and annual scales (e.g. summer days with T_max > 25ºC, hot days with T_max > 30º, desert days with T_max > 35ºC, tropical nights with T_min > 20°, frost days with T_min < 0ºC and ice days with T_max < 0ºC, all based on 00:00 - 24:00 UTC).
• Detailed information on gap-filled data is provided.
• Note: All times are provided in UTC, not local time.

For more details read `FRWRTM_2024_AirTemperature_MetaData.txt`.

Regular monitoring

🇩🇪 독일

Context

This dataset contains weather details of five most important countries including Germany and Italy which was affected greatly with Covid_19 spread.

Content

It is believed that climate conditions might be one of the major reasons for the spread of covid_19. This Dataset contains climate changes occured from 19th February to 17th April 2020. This contains the climate changes recorded for every 10 mins on the aforementioned countries.

File Description

The file contains below columns:

Temperature - Actual Temperature Recorded in degree celsius Wind_speed - Wind Speed Description - Description of the current weather Weather - Categorical value depicts the types of weather name - Depicts the country name temp_min - Minimum temperature recorded temp_max - Maximum temperature recorded

Other variables are pretty much self explanatory.

Acknowledgements

As part of my thesis project, this dataset was being prepared with a help of web scraper which will trigger an open source REST API end point for every 10 minutes. It was hosted in an EC2 instance which will update a CSV file periodically. Thought that this could contribute for the analysis of Covid_19 spread, hence shared the same.

Hope this could be useful!

Inspiration

As mentioned earlier, Climate could be one of the significant factors which spreads covid_19. Need to analyse further on the same. Italy could be considered for the research as we have the climate data for that country. Alongside, this country was affected largely.

This statistic shows the amount of precipitation in summer in Germany 2024, by federal state. In 2024, the precipitation in summer in Bavaria amounted to *** liters per square meter, a decrease compared to *** liters per square meter in summer 2023

Abstract: Climate time series for Germany derived from observations of the German Meteorological Service (Deutscher Wetterdienst / DWD) provided in daily resolution at a grid width of 250 meters for the period from 1961 to 2020 (current status February 2023). The following variables were processed: Daily total global radiation, separately for a horizontal and an inclined plane; daily total precipitation; daily mean, minimum and maximum 2m-air temperature; daily mean water vapor saturation deficit; daily mean wind speed. The temperature data sets are available in two different versions: V5 including a residual correction and V6 without.

TableOfContents: Daily total global radiation at horizontal plane (grhds); daily total global radiation at inclined plane (grids); daily total precipitation (rrds); daily mean water vapor saturation deficit (sddm); daily mean 2m-air temperature (tadm); daily minimum 2m-air temperature (tadn); daily maximum 2m-air temperature; daily mean wind speed (wsdm)

TechnicalInfo: dimension: 2578 columns x 3476 rows; temporalExtent_startDate: 1961-01-01 00:00:00; temporalExtent_endDate: 2020-12-31 23:59:59; temporalDuration: 60; temporalDurationUnit: a; temporalResolution: 1; temporalResolutionUnit: d; spatialResolution: 250; spatialResolutionUnit: m; horizontalResolutionXdirection: 250; horizontalResolutionXdirectionUnit: m; horizontalResolutionYdirection: 250; horizontalResolutionYdirectionUnit: m; verticalResolution: none; verticalResolutionUnit: none

Methods: Spatialization of gridded climate fields is performed, merging Model Output Statistics (MOS) downscaling with surface parameterization techniques (Böhner and Antonic, 2009; Böhner and Bechtel, 2018) to account for terrain-forced fine-scale topoclimatic variations. For a comprehensive description of the methods, see Wehberg and Böhner (2023).

A description of the methods used can be found in:

Dietrich, H.; Wolf, T.; Kawohl, T.; Wehberg, J.; Kändler, G.; Mette, T.; & Röder, A. & Böhner, J. (2019). Temporal and Spatial High-Resolution Climate Data from 1961 to 2100 for the German National Forest Inventory (NFI). Annals of Forest Science 76, 6. https://doi.org/10.1007/s13595-018-0788-5

Kawohl, T.; Dietrich, H.; Wehberg, J.; Böhner, J.; Wolf, T. & Röder, A. (2017). Das Klima in 80 Jahren – Wein- statt Waldbau? – AFZ-Der Wald 15: 32-35.

For GIS-based Terrain-parameterization methods and their application in statistical-dynamical downscaling see, e.g.:

Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fischer, E., Gerlitz, L., Wehberg, J., Wichmann, V., & Böhner, J. (2015). System for Automated Geoscientific Analyses (SAGA) v. 2.1.4, Geosci. Model Dev., 8, 1991–2007, https://doi.org/10.5194/gmd-8-1991-2015.

Böhner, J. & Bechtel, B. (2018): GIS in Climatology and Meteorology. – In: Huang, B. [Ed.]: Comprehensive Geographic Information Systems. – Vol. 2, pp. 196–235. Oxford: Elsevier. http://dx.doi.org/10.1016/B978-0-12-409548-9.09633-0.

Quality: --

Units: MJ/m2; MJ/m2; mm; hPa; degC; degC; degC; m/s

GeoLocation: westBoundCoordinate: 278750; westBoundCoordinateUnit: m; eastBoundCoordinate: 923000; eastBoundCoordinateUnit: m; southBoundCoordinate: 5234000; southBoundCoordinateUnit: m; northBoundCoordinate: 6102750; northBoundCoordinateUnit: m; ProjectCoordinateSystem: Transverse_Mercator; ProjectionCoordinateSystemParameters: [+proj=utm +datum=WGS84 +zone=32 +no_defs]. geoLocationPlace:Germany; UTMZone: 32

Size: Files are first packed into zip-archives and then further grouped together into one tar-archive per variable and 10-year period. The original file size is between about 4 and 7.5 GB per year and variable. The file size of the tar archives ranges between 3 GB and 70 GB.

Format: SAGA-Grid (.sgrd), https://saga-gis.sourceforge.io/en/index.html

DataSources: DWD Climate Data Center (CDC): Historical daily station observations (temperature, pressure, precipitation,sunshine duration, etc.) for Germany, version v21.3, 2021. Dataset-ID: urn:x-wmo:md:de.dwd.cdc::obsgermany-climate-daily-kl-historical and DWD Climate Data Center (CDC): Historical daily precipitation observations for Germany, version v21.3,2021. Dataset-ID: urn:x-wmo:md:de.dwd.cdc::obsgermany-climate-daily-more_precip-historical. http://opendata.dwd.de/climate_environment/CDC/observations_germany/climate/daily/

Contact: Prof. Dr. Jürgen Böhner, Universität Hamburg, Center for Earth System Research and Sustainability, Institute of Geography, Bundesstraße 55, 20146 Hamburg, juergen.boehner (at) uni-hamburg.de; https://www.geo.uni-hamburg.de/en/geographie/mitarbeiterverzeichnis/boehner.html

Webpage: https://www.waldklimafonds.de/ and https://www.lwf.bayern.de/boden-klima/wasserhaushalt/223446/index.php

🇩🇪 독일 English This data set includes historical weather data for the station of the DWD (Station number: 02712) at Silvanerweg 6 in Constance over a longer period of time. On July 25, 2017, an amendment to the German Weather Service Act ("DWD Act") came into force. The DWD is legally mandated to provide its weather and climate information largely free of charge. Currently, many geodata such as model predictions, radar data, current measurement and observation data as well as a large number of climate data are available on the Open Data Server https://opendata.dwd.de . The climate data is provided under https://opendata.dwd.de/climate_environment/CDC. The freely accessible data may continue to be used without restrictions in accordance with the "Ordinance on the Determination of the Terms of Use for the Provision of Federal Geodata (GeoNutzV)" with the addition of a source note (https://gdz.bkg.bund.de). With regard to the design of the source notes, the German Meteorological Service (DWD) (pursuant to § 7 DWD Act, § 3 GeoNutzV) requests the following information: The obligation to include provided source notes applies to the unchanged use of spatial data and other services of the DWD. References must also be included when extracts are created or the data format is changed. An illustration of the DWD logo is sufficient as a source reference within the meaning of the GeoNutzV. For further changes, edits, new designs or other modifications, the DWD expects at least one mention of the DWD in central source directories or in the imprint. Indications of change according to GeoNutzV can be, for example: "Data base: German Weather Service, raster data graphically reproduced", "Data base: German weather service, individual values averaged" or "Data base: German weather service, own elements added". In the case of a use that does not meet the intended purpose of the performance of the DWD, enclosed source notes must be deleted. This applies in particular to weather warnings if it is not ensured that they are made available to all users at all times completely and immediately. Source: German Weather Service (DWD)

DE: Annual Surface Temperature: Change Since 1951 1980 data was reported at 1.304 Number in 2021. This records a decrease from the previous number of 2.499 Number for 2020. DE: Annual Surface Temperature: Change Since 1951 1980 data is updated yearly, averaging 1.302 Number from Dec 1990 (Median) to 2021, with 32 observations. The data reached an all-time high of 2.506 Number in 2014 and a record low of -0.706 Number in 1996. DE: Annual Surface Temperature: Change Since 1951 1980 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 Germany – Table DE.OECD.GGI: Environmental: Climate Risk: OECD Member: Annual.

GTS data from Germany for 2007,
data are extracted from the original WMO bulletins for a subset of WMO FM12 code,
data have been collected and processed at the Department of Meteorology and Geophysics,
no data quality control at the Department of Meteorology and Geophysics, University of Vienna at all,
for further details see file: jdc_data_description.pdf in entry "jdc_obsdata_info_1".

GTS data from Germany for 2007,
data are extracted from the original WMO bulletins for a subset of WMO FM12 code,
data have been collected and processed at the Department of Meteorology and Geophysics,
no data quality control at the Department of Meteorology and Geophysics, University of Vienna at all,
3h-accumulation performed at the University of Hohenheim and University of Vienna,
for further details see file: jdc_data_description.pdf in entry "jdc_obsdata_info_1".