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.

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.

In June 2025, the average temperature in Berlin was **** degrees Celsius. This was an increase compared to the June a year ago.

Temperature in Germany increased to 11.19 celsius in 2024 from 10.89 celsius in 2023. This dataset includes a chart with historical data for Germany Average Temperature.

In 2024, Germany recorded a mean temperature of **** degrees Celsius. This was practically unchanged compared to the year before. Figures fluctuated during the timeline presented, but have grown compared to the 1960s and 70s.

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 statistic displays the average maximum monthly temperature in Germany over the past 20 years. It shows that over the past twenty years the month with the highest average maximum temperature has been July, with an average temperature of **** degrees Celsius. On average, January has been the coldest month.

This data shows the average temperature in Germany 2024, by federal state. That year, the average temperature in the city-state Berlin was **** degrees Celsius.

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.

The grids were derived from data from the DWD stations and qualitatively equivalent partner network stations in Germany, taking into account the altitude dependencies. pdf

In July 2025, the average precipitation amounted to 114 liters per square meter, a drastic increase compared to the previous month. The rainiest state in Germany was Saarland.

Heating Degree Days data was reported at 5,362.530 Degrees Celsius in 2020. This records a decrease from the previous number of 5,499.780 Degrees Celsius for 2019. Heating Degree Days data is updated yearly, averaging 6,221.490 Degrees Celsius from Dec 1970 (Median) to 2020, with 51 observations. The data reached an all-time high of 7,395.710 Degrees Celsius in 1996 and a record low of 5,320.830 Degrees Celsius in 2014. Heating Degree Days data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.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;;

Average temperatures (tvs) 1969-2019 — Saarland — for the forest vegetation period May to September divided into heat levels. Calculated on a grid of 1x1km of a digital elevation model based on the station measurement network of the DWD (Climate Data Center (CDC), grid of the monthly mean of the air temperature (2 m) for Germany, versionv1.0). Climate and weather-influencing processes (e.g. urban heat island, cold air discharge) that are not recorded directly with the station measurement network or cannot be determined by the regression method are not shown in the grid data. Data preparation by the Rhineland-Palatinate Competence Center for Climate Change Impacts, compilation by SaarForst Landesbetrieb.

In winter 2024/25, the average temperature in Bremen was *** degrees Celsius. This made it the warmest federal state during this timeline, followed by Schleswig-Holstein. The coldest at the same time was Bavaria, with an average temperature of *** degrees Celsius.

Average Annual Temperature (2015-2030) simulated by RegCM3 with ECHAM5 projections as boundary conditions. Units are degrees Celsius. These data were generated by the regional climate model RegCM3 with boundary conditions from a GCM future climate projections. The data were downscaled statistically by calculating differences (anomalies) between the RegCM3 results with GCM-driven boundary conditions for 1968-99 and those for a future period, in this case 2015-2030. The anomalies were added (temperatures) or multiplied (precipitation) to a climate baseline from PRISM (Parameter-elevation Regressions on Indepenent Slopes Model - prism.oregonstate.edu) data based on historical observations. The PRISM baseline was calculated as average monthly climate conditions for 1968-1999 reprojected the results to the BLM Albers 4km grid. PRISM data are provided in a 2.5 arc-minute lat-lon grid. RegCM3 is the third generation of the Regional Climate Model originally developed at the National Center for Atmospheric Research during the late 1980s and early 1990s. Details on current model components and applications of the model can be found in numerous publications (e.g., Giorgi et al, 2004a,b, Pal et al, 2007), the ICTP RegCNET web site (http://users.ictp.it/RegCNET/model.html), and the ICTP RegCM publications web site (http://users.ictp.it/~pubregcm/RegCM3/pubs.htm). The Western North America domain has a horizontal grid spacing of 15 km and 18 vertical levels. RegCM3 requires time-dependent lateral (wind, temperature, and humidity) and surface [surface pressure and sea surface temperature (SST)] boundary conditions that are updated every 6 hours of simulation. Lateral boundary conditions are derived from General Circulation Model (GCM) output or observations (e.g. NCEP). Additional information can be found at: http://regclim.coas.oregonstate.edu/. Global simulations from the Max Planck Institute (Germany) climate model ECHAM5 were part of a suite of model results used in the 4th Climate Model Inter-comparison Project (CMIP4) and the Intergovernmental Panel for Climate Change 4th Assessment Report. Details and documentation of the model can be found on the CMIP website: http://wwwpcmdi.llnl.gov/ipcc/model_documentation/ipcc_model_documentation.php.

The secular record of annual mean temperatures of Bremen shows that inhomogeneities - especially caused by station transfers - lead to serious problems concerning the interpretation of climatic trends or fluctuations. Especially two transfers of the meteorological observing station in Bremen within our century - 1935/36 and 1978 - caused significant inhomogeneities, well documented by parallel measurements for several years. Obviously the stagnation of the temperature level of the original data set is a result of these transfers. The homogenized record version reveals a significant warming trend of about 1 Kelvin within the last century. Supplement to: Bätjer, Diedrich; Heinemann, Hans-Joachim (1980): Eineinhalb Jahrhunderte meteorologischer Beobachtungen in Bremen. Abhandlungen des Naturwissenschaftlichen Vereins zu Bremen, 39, 185-261

The rainfall data inter-comparison dataset is a collection of precipitation statistics calculated from the hourly nationwide German radar climatology (RADKLIM) and radar online adjustment (RADOLAN) composites provided by the German Weather Service (Deutscher Wetterdienst, DWD), which were combined with rainfall statistics derived from rain gauge data for inter-comparison. Moreover, additional information on parameters that can potentially influence radar data quality, such as the height above sea level, information on wind energy plants and the distance to the next radar station, were included in the dataset.

The dataset consists of two point shapefiles which are readable with all common GIS. It constitutes a spatially highly resolved rainfall statistics geodataset for the period 2006 - 2017, which can be used for statistical rainfall analyses or for the derivation of model inputs. Furthermore, this data collection has the potential to benefit all users who intend to use precipitation data for any purpose in Germany and to identify the rainfall dataset that is best suited for their application by a straightforward comparison of three rainfall datasets without any tedious data processing and georeferencing.

• Spatial extent: Germany
• Spatial Resolution: 1 x 1 km
• Time period: 2006 - 2017
• Data Format: Two point shapefiles
• Compared precipitation datasets: RADKLIM, RADOLAN, rain gauge data
• Selection of calculated precipitation statistics:
  • Annual precipitation sum
  • Mean annual precipitation sum
  • Mean seasonal precipitation sums
  • Number of days exceeding a daily precipitation of 1 mm
  • Number of days exceeding a daily precipitation of 20 mm
  • Mean daily precipitation sum of all days exceeding a precipitation sum of 1 mm
  • Mean daily precipitation sum of all days exceeding a precipitation sum of 20 mm
  • Number of NoData entries

An Excel file with detailed information on all parameters and on original data sources is also included in the dataset.

Original data source URLs:

• RADKLIM (DWD): https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/reproc/2017_002/bin/
• RADOLAN (DWD): ftp://ftp-cdc.dwd.de/pub/CDC/grids_germany/hourly/radolan/historical/bin/
• Rain Gauge Data (DWD): https://opendata.dwd.de/climate_environment/CDC/observations_ germany/climate/1_minute/precipitation/
• Location of wind energy plants (UFZ): https://www.ufz.de/record/dmp/archive/5467/de/
• SRTM DEM (DLR): https://geoservice.dlr.de/egp/

Quality controlled and gap-filled air temperature and atmospheric humidity dataset from the street-level weather sensor network (WSN) in Freiburg i. Br., Germany for the period 2022-09-01 to 2023-08-31 as described in:

Plein M, Feigel G, Zeeman M, Dormann C, Christen A (2025): Using Gradient Boosting for gap-filling to analyze temperature and
humidity patterns in an urban weather station network in Freiburg, Germany. Urban Climate. https://doi.org/10.1016/j.uclim.2025.102496.

Hourly gap-filled values

The file "Freiburg_AWS_20220901_20230831_gap_filled_data_ta_rh_Plein_et_al.csv" contains gap-filled hourly air temperature and relative humidity time series from 41 stations of the street-level weather sensor network (WSN) in Freiburg i. Br., Germany from 1 Sep 2022 to 31 Aug 2023 with the following field descriptors:

• "datetime_UTC" the time stamp of the measured value in the format YYYY-MM-DDTHH:II:SSZ where Y = year, M = month, D = day of month, H = hour, I = minute, S = second in UTC attributing the start of the averaging interval.
• "station_id" - 6 letter code of WSN (FR for Freiburg and last 4 letters for station name, see also https://doi.org/10.5281/zenodo.12732552). The station FRTECH is not included.
• "variable" - the variable ("Ta_degC" for air temperature in ºC or "RH_percent" for relative humidity in %).
• "value" - the numeric value of the measurement.
• "data_type" - either "observed" (i.e. measured) or "imputed" (i.e. gap-filled using the Extreme Gradient Boosting method).

Annual statistics per station

The files "Freiburg_AWS_20220901_20230831_annual_statistics_per_station_Plein_et_al" (in csv and xlsx Format) contain annual summary statistics based on the gap-filled hourly air temperature and relative humidity time series of the street-level weather sensor network (WSN) in Freiburg i. Br., Germany from 1 Sep 2022 to 31 Aug 2023 and from two official DWD stations in Freiburg with the following field descriptors:

• "station_id" - 6 letter code of weather station (FR for Freiburg and last 4 letters for station name, see also https://doi.org/10.5281/zenodo.12732552). The two official DWD stations are also included (No. 01443 on the airfield and No. 13667 in the city centre).
• "station_name" - Full human-readable name of weather station.
• "latitude_degN" - Latitude of site in decimal degrees North.
• "longitude_degE" - Longitude of site in decimal degrees East.
• "elevation_masl" - Elevation of site in metres above mean sea level.
• "mean_ta_degC" - Annual average air temperature in the period 2022-09-01 to 2023-08-31 in ºC.
• "mean_rh_percent" - Annual average relative humidity in the period 2022-09-01 to 2023-08-31 in %.
• "mean_vp_kPa" - Annual average vapour pressure in the period 2022-09-01 to 2023-08-31 in kPa based on Tetens equation.
• "mean_vpd_Pa"- Annual average vapour pressure deficit in the period 2022-09-01 to 2023-08-31 in Pa based on Tetens equation.
• "sum_summer_day_per_year" - Annual number of summer days (maximum air temperature greater or equal to 25ºC) in the period 2022-09-01 to 2023-08-31 in days per year.
• "sum_hot_day_per_year" - Annual number of hot days (maximum air temperature greater or equal to 30ºC) in the period 2022-09-01 to 2023-08-31 in days per year.
• "sum_desert_day_per_year" - Annual number of desert days (maximum air temperature greater or equal to 35ºC) in the period 2022-09-01 to 2023-08-31 in days per year.
• "sum_tropical_night_per_year" - Annual number of tropical nights (minimum nocturnal air temperature greater or equal to 20ºC) in the period 2022-09-01 to 2023-08-31 in days per year.
• "sum_frost_day_per_year" - Annual number of frost days (minimum air temperature lower than 0ºC) in the period 2022-09-01 to 2023-08-31 in days per year.
• "sum_ice_day_per_year" - Annual number of ice days (maximum air temperature lower than 0ºC) in the period 2022-09-01 to 2023-08-31 in days per year.
• "sum_hottest_station_ranking_per_year" - Annual number of days this station was the station with the highest recorded air temperature in the period 2022-09-01 to 2023-08-31.
• "sum_coldest_station_ranking_per_year" - Annual number of days this station was the station with the lowest recorded air temperature in the period 2022-09-01 to 2023-08-31.

Station descriptions

Details on the stations can be found in the sensor network documentation:

• Plein M, Kersten F, Zeeman M, Christen A (2024): Street-level weather station network in Freiburg, Germany: Station documentation (1.0) Zenodo. https://doi.org/10.5281/zenodo.12732552

Code availability

The code used for the imputation of missing values is documented and available here:

• Plein M, Feigel G, Zeeman M, Dormann C, Christen A (2024): Code Supporting the Publication "Using Gradient Boosting for gap-filling to analyze temperature and humidity patterns in an urban weather station network in Freiburg, Germany." (1.0.0) Zenodo. https://doi.org/10.5281/zenodo.14536824

This is the raw data that was used as input to create the German test reference years (2017). The departmental research project "TRY advancement" was financed by the BBSR via the research initiative Future Construction

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`.