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Regional climate projections have been performed for Europe with the climate version CLM (version 3.1) of the 'Lokal-Modell' (LM) of the German Meteorological Service. CLM has been forced with output of the ECHAM5/MPIOM global climate model of the Max Planck Institute for Meteorology, which contributed to the fourth climate assessment report (AR4) of the International Panel on Climate Change (IPCC). The results of the global model for the IPCC A1B and B1 scenarios as well as the reconstruction of the last four decades of the 20th century (20C3M) for the AR4 are dynamically scaled down to the CLM grid cell size of about 18×18 km2. Climatological parameters including all model variables and additional quantities characterising the climate are available from the World Data Centre for Climate database run by the German climate service group Model and Data. They can be accessed by the general public at no costs with the help of M and D. In particular, the 'Service Group Adaptation' (SGA) has been established at M and D to assist adaptation projects funded by the German Federal Ministry of Education and Research (BMBF) giving advice on the interpretation of the CLM model results.
Der 2. Hochschultag vor Ort der Nationalen Stadtentwicklungspolitik
„Provinzstädte - Neu definiert“ lud am 23. und 24. Mai 2017 ein, im lokalen Kontext der Region Cottbus über die räumliche Entwicklung von Städten zwischen Metropole und Dorf zu diskutieren.
Die dabei entstandenen Ideen für Praxis, Wissenschaft und Lehre sind in dieser Broschüre dokumentiert.
Biological soil crusts (BSCs) are thin microbiological vegetation layers that naturally develop in unfavorable higher plant conditions (i.e., low precipitation rates and high temperatures) in global drylands. They consist of poikilohydric organisms capable of adjusting their metabolic activities depending on the water availability. However, they, and with them, their ecosystem functions, are endangered by climate change and land-use intensification. Remote sensing (RS)-based studies estimated the BSC cover in global drylands through various multispectral indices, and few of them correlated the BSCs’ activity response to rainfall. However, the allocation of BSCs is not limited to drylands only as there are areas beyond where smaller patches have developed under intense human impact and frequent disturbance. Yet, those areas were not addressed in RS-based studies, raising the question of whether the methods developed in extensive drylands can be transferred easily. Our temperate climate study area, the ‘Lieberoser Heide’ in northeastern Germany, is home to the country’s largest BSC-covered area. We applied a Random Forest (RF) classification model incorporating multispectral Sentinel-2 (S2) data, indices derived from them, and topographic information to spatiotemporally map the BSC cover for the first time in Central Europe. We further monitored the BSC response to rainfall events over a period of around five years (June 2015 to end of December 2020). Therefore, we combined datasets of gridded NDVI as a measure of photosynthetic activity with daily precipitation data and conducted a change detection analysis. With an overall accuracy of 98.9%, our classification proved satisfactory. Detected changes in BSC activity between dry and wet conditions were found to be significant. Our study emphasizes a high transferability of established methods from extensive drylands to BSC-covered areas in the temperate climate. Therefore, we consider our study to provide essential impulses so that RS-based biocrust mapping in the future will be applied beyond the global drylands