Wladimir-Peter-Köppen-Prize

Franziska Strauss been awarded the internationally renowned Wladimir-Peter-Köppen-Prize for her outstanding dissertation “Modeling climate change and impacts on crop production in Austria” in climate research. She wrote her dissertation at the Institute for Sustainable Economic Development, Department of Economics and Social Sciences, under the supervision of Prof. Dr. Erwin Schmid. The prize is awarded by the excellence cluster CliSAP (Integrated Climate System Analysis and Prediction) at the University Hamburg, Germany. The international jury says about the cumulative dissertation  „Die fachübergreifenden bzw. interdisziplinären Arbeiten werden angeführt von F. Strauss, die in ihrer Arbeit den Einfluss des Klimawandels auf die Getreideproduktion in Österreich analysiert. Ihre Arbeit zeigt nach Ansicht der Jury in dieser Gruppe den höchsten Anteil an Interdisziplinarität und Innovation. Die Kandidatin entwickelt ein praxisnahes statistisches Modell für die regionale Klimavorhersage in Österreich für die nächsten drei Dekaden, das eine solide Grundlage für mittelfristige Planungen in der Agrarwirtschaft bilden kann. Grundlagen, Fehlerabschätzungen, Signifikanz werden seriös und vielseitig diskutiert. Die Anwendung der Modellergebnisse auf Ernteprognosen für Feldfrüchte ist innovativ und wegweisend für weitere Anwendungen. Mit diesem Ansatz bereichert die Autorin substantiell das Wissen über zukünftige Entwicklungen im Bereich der Landwirtschaft im Sinne einer wissenschaftsbasierten Landwirtschaftspolitik."   Abstract of the thesis: Modeling impacts of climate change on crop production for the next three decades requires climate change scenario data with a high degree of meteorological consistency and spatial and temporal resolution. In the course of this cumulative thesis, the statistical climate model ACLiReM (Austrian Climate model based on Linear Regression Methods) has been developed to produce climate change scenarios including daily weather data on minimum and maximum temperatures, solar radiation, precipitation, relative humidity and wind speed for Austria at 1 km² grid resolution and the period 1975-2040. The climate change scenarios have been statistically tested to assure physical and spatio-temporal consistencies. Developing near future climate change scenarios by using statistical methods and observed weather station data is seen as a valuable alternative to the well-known General Circulation Models (GCMs) and Regional Climate Models (RCMs). Furthermore, the statistical approach allows the modeling of extreme weather events such as increased drought occurrences, which is also demonstrated in this thesis. Biophysical process models like EPIC (Environmental Policy Integrated Climate) have the potential to depict impacts on crop production of all anticipated variations in input data (i.e. climate, topography, soils, management). Therefore, sensitivity analyses have been performed which are important for providing valuable information about the usefulness and appropriateness of such process models in impact studies (e.g. for large scale applications) as well as for model inter-comparisons. In this thesis, several economic optimization models have been developed and applied in case study contexts. They integrate EPIC simulation data to derive optimal crop management portfolios and investment strategies under consideration of production risks and uncertainties both arising from future weather conditions. The analyses of the thesis demonstrate that the developed climate change scenarios in conjunction with EPIC and economic optimization models are adequate tools to assess the impacts on climate sensitive sectors such as agriculture, which can be used to design effective adaptation policies. Link: http://www.klimacampus.de/631+M55fcd77fd91.html?&L=1