In 2024, the average summer temperature in Germany was 18.5 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 11.5 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 19.7 degrees Celsius. This made Berlin the warmest federal state in the period in question, followed by Brandenburg and Baden-Württemberg.

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.

In 2023/2024, the average winter temperature in Germany was 4.1 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 17.3 days with a temperature of at least 30 degrees Celcius, which was more than three times the increase compared to 2021.

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.

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`.

Quality controlled and gap-filled continuous air temperature data from the urban rooftop weather station at Freiburg-Chemiehochhaus (FRCHEM, 7.8486ºE, 48.0011ºN, 323.5 m) using an actively ventillated and shielded psychrometer operated 2m above roof level.

• Quality controlled air temperature data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2023.
• Average, minimum and maximum 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 `FRCHEM_2023_AirTemperature_MetaData.txt`.

Version 1.1.0 contains additionally air temperature data aggregated at 10min and 30min.

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 303 liters per square meter, a decrease compared to 315 liters per square meter in summer 2023

Test Reference Years (TRY) for 15 typical regions in germany with special regards on realisitc radiation data on a 1min timescale

Summary:

The data set contains the updated test reference years (TRY) of the German Weather Service (DWD). By subdividing into 15 TRY regions, each postcode area can be assigned a representative weather data set. It should be emphasized that in addition to a mean, current test reference year for a region, there is also a year with extreme summer and extreme winter weather. To take climate change into account, there is then a time series for the year 2045 for each test reference year based on the IPCC climate models. This means that a total of 90 weather data sets are available with a one-hour time resolution.

In order to use the data in simulations with a temporal resolution of 1min or 15min, the data set was extended by linear interpolation. While this approach is justifiable for air pressure and temperature, for example, it does not depict high fluctuations in solar radiation. Therefore, based on the one-minute open data measurement data set of the Baseline Surface Radiation Network, with an algorithm by Hofmann et. al. the time series of global radiation are newly generated for all test reference years. Another algorithm by Hofmann et. al. was used to calculate the corresponding diffuse radiation times series.

Sources:

• Raw data from DWD: https://kunden.dwd.de/obt/ -> 1_raw-data
• Synthetic 1min radiation data: http://pvmodelling.org/ -> 2_synthetic-radiation

How to use or recreate the final dataset:

1. clone/download this repository
2. unzip the files from the data.zip file
   1. https://github.com/RE-Lab-Projects/TRY_DE_2015_2045/releases/download/v1.4.0/data.zip
3. Use or recreate the final dataset
   1. use: Final datasets are then located in -> 3_processed-data
   2. recreate: run the process-data.py

Test reference stations / regions

No. | lon | lat | station | region

1 | 53.5591 | 8.5872 | Bremerhaven | Nordseeküste

2 | 54.0878 | 12.1088 | Rostock | Ostseeküste

3 | 53.5299 | 10.0078 | Hamburg | Nordwestdeutsches Tiefland

4 | 52.3938 | 13.0651 | Potsdam | Nordostdeutsches Tiefland

5 | 51.4562 | 7.0568 | Essen | Niederrheinisch-westfälische Bucht und Emsland

6 | 550.6461 | 7.9426 | Bad Marienburg | Nördliche und westliche Mittelgebirge, Randgebiete

7 | 51.3334 | 9.4725 | Kassel | Nördliche und westliche Mittelgebirge, zentrale Bereiche

8 | 51.7239 | 10.6069 | Braunlage | Oberharz und Schwarzwald (mittlere Lagen)

9 | 50.8233 | 12.9181 | Chemnitz | Thüringer Becken und Sächsisches Hügelland

10 | 50.3226 | 11.9124 | Hof | Südöstliche Mittelgebirge bis 1000 m

11 | 50.4312 | 12.9522 | Fichtelberg | Erzgebirge, Böhmer- und Schwarzwald oberhalb 1000 m

12 | 49.4902 | 8.4637 | Mannheim | Oberrheingraben und unteres Neckartal

13 | 48.2432 | 12.5286 | Mühldorf | Schwäbisch-fränkisches Stufenland und Alpenvorland

14 | 48.6536 | 9.8666 | Stötten | Schwäbische Alb und Baar

15 | 47.4945 | 11.1046 | Garmisch Partenkirchen | Alpenrand und -täler

Content

• files: 90 test reference years (TRY)

15 test reference regions
x 3 reference conditions (average year, extreme summer, extreme winter)
x 2 reference projections (year 2015 and year 2045)

• columns per file:

datetime [yyyy-MM-dd hh:mm:ss+01:00/02:00]
temperature [degC]
pressure [hPa]
wind direction [deg]
wind speed [m/s]
cloud coverage [1/8]
humidity [%]
direct irradiance [W/m^2]
diffuse irradiance [W/m^2]
synthetic global irradiance [W/m^2]
synthetic diffuse irradiance [W/m^2]
clear sky irradiance [W/m^2]

• length: 1 year
• time increment: 60s / 900s / 3600s

Important hints:

• all files in 3_processed-data were calculated with the skript process-data.py
• A value with, for example, a timestamp 12:00:00 represents the mean value from this timestamp until the following timestamp.
• datetime column is in CET / CEST

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 22.4 degrees Celsius. On average, January has been the coldest month.

The difference between water supply and potential evapotranspiration during the main vegetation period (May-August) results in the effective water balance. The water supply is composed of precipitation during this period, the amounts of water present in the soil and drainable amounts of water (described by the usable field capacity in the effective root space) and, if necessary, a capillary ascent. Capillary Ascension is the result of the ascension rate per day and the culture-dependent duration of the ascent. The ascent rate is significantly dependent on the soil type and the distance of the lower boundary of the effective root space to the groundwater body or the reservoir. The utilisation-differentiated soil overview map 1:1,000,000 (BÜK1000N) was used as a ground study basis. Data from CORINE Land Cover (CLC2006) were used for land cover and land use. The climate scenario data (https://www.dwd.de/ref-ensemble) was provided by the German Weather Service (DWD) in a resolution of 5 x 5 km. This is an ensemble of 16 bias-corrected area datasets (combination of global and regional climate models) that describe the scenario RCP8.5 (RCP’s Representative Concentration Pathways) and assume an additional radiant propulsion of 8.5 W/m². The nine raster records with a resolution of 5 x 5 km each represent the middle, the 15th and 85. Percentile of the effective water balance in the main vegetation period in Germany for the climate periods 1971-2000, 2031-2060 and 2071-2099.

Pollen-based temperature and precipitation reconstructions were carried out using the probability density function "pdf" method (Kühl et al., 2002, doi:10.1006/qres.2002.2380). The “pdf method” has been previously applied to other Middle Pleistocene pollen archives, i.e., Hetendorf, Munster-Breloh and Gröbern-Schmerz (Kühl and Litt, 2007, doi:10.1016/S1571-0866(07)80041-8) and Bilshausen (Kühl and Gobet, 2010, doi:10.1016/j.quascirev.2010.08.006), which are located in a close distance to Dethlingen. The method estimates taxon-climate relations by probability density functions. Because it uses climate dependencies of many taxa and combines individually estimated plant climate relationships rather than relating complete pollen assemblages to climate, the method is relatively robust to scenarios when a taxon has shifted its climatic requirements with time (see Kühl et al., 2002, for a detailed description). The temperature reconstructions (Fig. S2) clearly show the continuous warming trend and the late climatic optimum that is characteristic for the Holsteinian interglacial (Kühl and Litt, 2007). In particular, a gradual increase in mean January temperatures, and to a lesser extent also in mean July temperatures, is observed during pollen zone (PZ) IX. Maximum temperatures are reached during the upper PZ XII and PZ XIII. During the OHO, the mean January temperatures decline by ~5 °C, whereas summer temperatures remain rather stable.

Average Summer (Jul-Sep) Temperature (2045-2060) 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.

Average Summer (Jul-Sep) 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.itRegCNETmodel.html), and the ICTP RegCM publications web site (http:users.ictp.it~pubregcmRegCM3pubs.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.govipccmodel_documentationipcc_model_documentation.php.

The data herein presents a new chironomid record and associated chironomid-based temperature reconstruction covering the time interval ca. 98–46 ka from the palaeolake Füramoos, Southern Germany. These data also include non-chironomid invertebrate remains, including Ceratopogonidae, Daphnia and Ephemeroptera as well as Characean oospores.

Methods Sample processing: Sediment samples between depths 9.6-6.0 m required no chemical treatment. Samples betweend depths of 13-9.6 m were heated in 10% KOH for 15 minutes at 85°C due to the dificulty of processing those samples. Sediment samples were then sieved through 100 and 200 micrometer sieves. Chironomids were picked from those samples using a Bogorov tray under a stereomicroscope (30 – 50 x magnification). Samples were dried and then mounted on microscope slides using Euparal and identified under at 40 – 100 x magnification with a compound microscope. Next to chironomids the remains of Sialidae, Ceratopogonidae, Daphnia, Ephemeroptera, oribatid mites, Trichoptera, Plecoptera, Sciaridae and Tipulidae as well as Characeae oogonia and Plumatella statoblasts were mounted and identified. The chironmoid based temperature reconstruciton was produced using a two-component weighted averaging partial least squares model.

For post identification data processing and temperature reconstruction analysis please see the associated publication in Quaternary Science Reviews where the results are discussed in detail. The manuscript is fully open access: https://doi.org/10.1016/j.quascirev.2021.107008.

The annual average spring temperature in Germany was 8.9 degrees Celsius during the 1991-2020. Figures increased during each decade displayed, in each season.

Die meteorologischen Daten zu den Temperatur-, Feuchte- und Windfeldern wurden während vier Messkampagnen in Stuttgart im Sommer 2017, Winter 2017, Sommer 2018 und Winter 2018 erhoben. Doppler Lidarsysteme und ein Mikrowellenradiometer wurden zur Erfassung und zur Analyse der horizontalen Struktur des innerstädtischen Windfeldes und der vertikalen Struktur der urbanen Grenzschicht eingesetzt. Die Messungen wurden im Rahmen des Verbundprojekts „Dreidimensionale Observierung atmosphärischer Prozesse in Städten (3DO)“ durchgeführt. 3DO gehört zu einem der drei Module der BMBF-Fördermaßnahme Stadtklima im Wandel (UC2). Mehr Information über Ziele der UC2 Fördermaßnahme ist auf http://www.uc2-program.org/ und in den aufgelisteten Übersichtspublikationen zu finden. Dieter Scherer, Felix Ament, Stefan Emeis, Ute Fehrenbach, Bernd Leitl, Katharina Scherber, Christoph Schneider, and Ulrich Vogt (2019): Three-Dimensional Observation of Atmospheric Processes in Cities. Meteorologische Zeitschrift 2, 2019. doi: 10.1127/metz/2019/0909. Dieter Scherer, Florian Antretter, Steffen Bender, Jörg Cortekar, Stefan Emeis, Ute Fehrenbach, Günter Gross, Guido Halbig, Jens Hasse, Björn Maronga, Siegfried Raasch, und Katharina Scherber (2019): Urban Climate Under Change [UC]2 – A National Research Programme for Developing a Building-Resolving Atmospheric Model for Entire City Regions. Meteorologische Zeitschrift 2, 2019. doi:10.1127/metz/2019/0913. This dataset of meteorological observations (temperature, humidity, wind) was collected during four field campaigns in Stuttgart, Germany, in summer 2017, winter 2017, summer 2018, and winter 2018. Doppler lidars and a microwave radiometer were deployed to investigate horizontal structures of intra-urban horizontal wind field patterns and vertical structures of the urban boundary layer. The measurements were conducted within the project ‘Three-dimensional Observation of Atmospheric Processes in Cities’ (3DO). 3DO is one of three modules of the programme ‘Urban Climate Under Change’, [UC]2, funded by the German Federal Ministry of Education and Research (BMBF). More information on the goals of the UC]2 programme can be found on http://www.uc2-program.org/ and in the overview papers listed below. Dieter Scherer, Felix Ament, Stefan Emeis, Ute Fehrenbach, Bernd Leitl, Katharina Scherber, Christoph Schneider, and Ulrich Vogt (2019): Three-Dimensional Observation of Atmospheric Processes in Cities. Meteorologische Zeitschrift 2, 2019. doi: 10.1127/metz/2019/0909. Dieter Scherer, Florian Antretter, Steffen Bender, Jörg Cortekar, Stefan Emeis, Ute Fehrenbach, Günter Gross, Guido Halbig, Jens Hasse, Björn Maronga, Siegfried Raasch, und Katharina Scherber (2019): Urban Climate Under Change [UC]2 – A National Research Programme for Developing a Building-Resolving Atmospheric Model for Entire City Regions. Meteorologische Zeitschrift 2, 2019. doi:10.1127/metz/2019/0913. DATA SET DESCRIPTION 1. Spatial coverage The measuring data were collected during intensive observation periods (IOP) in Stuttgart, Germany, under the BMBF Programme ‘Urban Climate Under Change’ [UC]2.

To gain insights into the mechanisms of abrupt climate change within interglacials, we have examined the characteristics and spatial extent of a prominent, climatically induced vegetation setback during the Holsteinian interglacial (Marine Isotope Stage 11c). Based on analyses of pollen and varves of lake sediments from Dethlingen (northern Germany), this climatic oscillation, here termed the "Older Holsteinian Oscillation" (OHO), lasted 220 years. It can be subdivided into a 90-year-long decline of temperate tree taxa associated with an expansion of Pinus and herbs, and a 130-year-long recovery phase marked by the expansion of Betula and Alnus, and the subsequent recovery of temperate trees. The climate-induced nature of the OHO is corroborated by changes in diatom assemblages and d18O measured on biogenic silica indicating an impact on the aquatic ecosystem of the Dethlingen paleolake. The OHO is widely documented in pollen records from Europe north of 50° latitude and is characterized by boreal climate conditions with cold winters from the British Isles to Poland, with a gradient of decreasing temperature and moisture availability, and increased continentality towards eastern Europe. This pattern points to a weakened influence of the westerlies and/or a stronger influence of the Siberian High. A comparison of the OHO with the 8.2 ka event of the Holocene reveals close similarities regarding the imprint on terrestrial ecosystems and the interglacial boundary conditions. Hence, in analogy to the 8.2 ka event, a transient, meltwater-induced slowdown of the North Atlantic Deep Water formation appears as a plausible trigger mechanism for the OHO. If correct, meltwater release into the North Atlantic may be a more common agent of abrupt climate change during interglacials than previously thought. We conclude that meltwater-induced climate setbacks during interglacials preferentially occurred when low rates of summer insolation increase during the preceding terminations facilitated the persistence of large-scale continental ice-sheets well into the interglacials.

This dataset of meteorological observations (temperature, humidity, wind) was collected during four field campaigns in Stuttgart, Germany, in summer 2017, winter 2017, summer 2018, and winter 2018. Doppler lidars and a microwave radiometer were deployed to investigate horizontal structures of intra-urban horizontal wind field patterns and vertical structures of the urban boundary layer. The measurements were conducted within the project ‘Three-dimensional Observation of Atmospheric Processes in Cities’ (3DO). 3DO is one of three modules of the programme ‘Urban Climate Under Change’, [UC]2, funded by the German Federal Ministry of Education and Research (BMBF). More information on the goals of the UC]2 programme can be found on http://www.uc2-program.org/ and in the overview papers listed below. Dieter Scherer, Felix Ament, Stefan Emeis, Ute Fehrenbach, Bernd Leitl, Katharina Scherber, Christoph Schneider, and Ulrich Vogt (2019): Three-Dimensional Observation of Atmospheric Processes in Cities. Meteorologische Zeitschrift 2, 2019. doi: 10.1127/metz/2019/0909. Dieter Scherer, Florian Antretter, Steffen Bender, Jörg Cortekar, Stefan Emeis, Ute Fehrenbach, Günter Gross, Guido Halbig, Jens Hasse, Björn Maronga, Siegfried Raasch, und Katharina Scherber (2019): Urban Climate Under Change [UC]2 – A National Research Programme for Developing a Building-Resolving Atmospheric Model for Entire City Regions. Meteorologische Zeitschrift 2, 2019. doi:10.1127/metz/2019/0913.