The climate at a given location on Earth is determined by the totality of meteorological influences. This means that it is not only about the average temperature or average precipitation, but also about all other relevant meteorological factors. However, the commonly known climate categories usually consider only a few meteorological parameters, particularly those relevant for the prevailing plant and animal life. Typical variations, such as seasonal and diurnal cycles, are also part of the climate definition, as is the occurrence of certain extreme values in the various parameters.
To reliably estimate the climate at a location, measurements covering a sufficiently long period are required. The World Meteorological Organization (WMO) has established that certain “climate normal periods” should be considered for this purpose. These periods span 30 years, with defined boundaries. The years 1961–1990 and 1991–2020 are examples of such normal periods.
The Earth’s climate has undergone significant changes over geological timescales. This is due, for example, to variations in the Earth’s orbit around the Sun or to the shifting of continents, which can also lead to the relocation of equatorial regions into polar climate zones. Considerable climate fluctuations can also be observed in historical times. For instance, the frequency of certain plant species can be inferred from pollen preserved in newly deposited sediment layers at lake margins, and tree growth can be analyzed through tree rings. These fluctuations have had impacts on human societies, which can be reconstructed using historical records and archaeological evidence.
Klimaprojektionen zeigen, dass die Region Berlin-Brandenburg, im Vergleich zu anderen Regionen in Deutschland, stärker vom Klimawandel betroffen ist. Die obere Abbildung zeigt, wie sich die klimatische Wasserbilanz (in mm) in Deutschland für die Zukunft entwickeln wird. Laut Prognose für 2041–2050 wird sich insbesondere in Berlin-Brandenburg diese weiter in den negativen Bereich bewegen.
Es werden verschiedene Modellszenarien für Temperatur und Niederschlag für Brandenburg diskutiert. Verschiedene Entwicklungspfade zeigen zum Bespiel an, wie sich unterschiedlicher Klimaschutz auswirken könnte.
Climate in SpreeWasser:N
Forecasts of drought and heavy rainfall probabilities
Short-term weather forecasts over several days are already very accurate today. Nevertheless, in the case of events such as local heavy rainfall, it is not yet possible today to accurately predict the affected locations and the amount of precipitation for this period.
This is even more true for longer-term forecasts over a period of several weeks to several years, and of course also for climate scenarios, which mostly extend to the end of the current century. Here, it can only be a matter of estimating probabilities. Whether and to what extent a dry period or a heavy rain event is relevant depends not only on its duration and intensity, but also, for example, on the season of occurrence.
Circulation patterns as a key to analyzing drought periods
In Work Package 2, “Climatic and Hydrological Extremes,” the Free University of Berlin analyzed large-scale atmospheric circulation patterns to better understand their relationship with drought periods. A classification based on the Lamb Weather Types (Jones et al., 1993), derived from surface pressure data and adapted to the study region, was employed. This classification distinguishes between 27 and 54 weather types and is suitable for describing typical conditions during droughts.
Daily ERA5 reanalysis data (1940–2024) were evaluated. In collaboration with the Leibniz Centre for Agricultural Landscape Research (ZALF), the focus was on agriculturally relevant drought periods between May and August, with particular attention to the water demand of winter wheat.
Composites of anomalies in sea level pressure (SLP; contour lines) and precipitable water in the atmosphere (PRW; colored) for the Lamb weather types that exhibit significant positive anomalies during precipitation-based drought periods (year-round analysis), based on ERA5 data.
Drought periods were identified using two approaches:
Precipitation-based: ≥ 14 consecutive days with < 1 mm of rainfall.
SPEI-based: Using the Standardized Precipitation Evapotranspiration Index, which combines precipitation and evapotranspiration.
Eight weather types occurred significantly more frequently during droughts, mostly under high-pressure conditions. A simple forecasting model based on these weather types achieved a 40 % higher hit rate than a random prediction.
Overall, the analysis demonstrates that certain atmospheric circulation patterns are closely associated with the occurrence of droughts. By combining weather type classifications, reanalysis data, and standardized drought indicators, robust relationships can be derived, enabling improved assessment of drought risks—both retrospectively and with respect to future developments.
author: Clara Hauke, FU Berlin
All displayed measurement data are the property of the Free University of Berlin and are protected by copyright. They may, upon request to the SpreeWasser:N coordination team, be made available for further use.
