Water shortages, floods or crop failures: worldwide, as a result of climate change, pronounced dry and rainy phases are occurring more frequently and more intensively, causing human suffering and great economic damage. The more precise seasonal forecasts are for the coming months, the more effectively these consequences can be mitigated. A research team from the Karlsruhe Institute of Technology (KIT) has now been able to improve global forecasts with statistical methods so that they can be used regionally. They describe the new approach and the economic benefits of seasonal forecasts in the journals Earth System Science Data and Scientific Reports .
One consequence of global warming are increased and more intense phases of drought or precipitation, which meanwhile cause major problems worldwide – for example in the supply of food, energy and drinking water. Improved seasonal meteorological forecasts can help: “If we predict precipitation amounts and temperatures for weeks and months more precisely, decision-makers on site can, for example, control and plan reservoirs or the selection of seeds for the planting season more proactively. In this way they can reduce damage and losses, ”says Professor Harald Kunstmann from the Institute for Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU), the KIT Campus Alpin in Garmisch-Partenkirchen, and from the University of Augsburg. Using statistical methods, he and his team have now been able to derive local forecasts from global climate models that are significantly more precise than the seasonal forecasts available to date. The researchers developed the method within the international project “Seasonal Water Resource Management in Dry Regions” (SaWaM for short), which is funded by the Federal Ministry of Education and Research (BMBF) and has now been completed.
Regionalized global forecasts with local relevance
So far, only global climate models are usually available for regional forecasts over an average period of weeks and months. “These models in their raw form are actually not suitable for high-resolution seasonal forecasts,” explains Dr. Christof Lorenz from the KIT Campus Alpin, who helped develop the new method. The reasons for this are, among other things, inconsistencies between predictions of different starting times and deviations from climatological reference data caused by model errors. “Thanks to the statistical correction and regionalization procedures we have developed, we can now derive seasonal forecasts that are many times more precise,” says Lorenz. In the study regions in Sudan, Ethiopia, Iran, Northeast Brazil, Ecuador,
The new methods for preparing seasonal forecasts are so precise that they can now be put to good use in practice. “In particular, the early warning of periods of above-average wet or dry periods means that the improved forecast makes it possible to initiate measures on site in good time to minimize damage,” explains Tanja Portele, climate researcher involved at the KIT Campus Alpin and at the University of Augsburg. The researchers were able to demonstrate how economically relevant their approach is based on climate data from several decades. “We have shown that seasonal drought forecasts can save up to 70 percent of the costs that would have been possible with a mathematically optimal approach.” For the Upper Atbara Dam, a large dam in Sudan, the scientists quantified the exact savings potential for a drought year by way of example. It amounts to $ 16 million.
Methods from KIT in use worldwide
The new methods for more precise seasonal forecasts are of particular importance in the context of semi-arid regions in which the rainy season is limited to a few months of the year. “Here the water usually has to be stored in reservoirs,” says Kunstmann. “When using it, there can then be conflicting goals between agriculture, the energy industry and drinking water supply.” Weather services and official institutions from Sudan and Iran are already using the new statistical methods from KIT in order to be able to act on the basis of knowledge. But even for regions that were originally rarely affected, more precise seasonal forecasts are becoming more and more relevant due to climate change. “This is why the method is to be used for drought forecasts in Germany in the future,” said the climate researcher.
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