NH13B-1927
Quantifying the weather-signal in national crop-yield variability
Monday, 14 December 2015
Poster Hall (Moscone South)
Katja Frieler1, Almut Arneth2, Juraj Balkovic3, James Chryssanthacopoulos4, Delphine Deryng5, Joshua Wright Elliott6, Christian Folberth3, Nikolay Khabarov3, Christoph Mueller1, Stefan Olin7, Thomas Pugh2, Sibyll Schaphoff1, Jacob Schewe1, Erwin Schmid8, Bernhard Schauberger1, Lila Warszawski1 and Anders Levermann1, (1)Potsdam Institute for Climate Impact Research, Potsdam, Germany, (2)Karlsruhe Institute of Technology, Karlsruhe, Germany, (3)IIASA International Institute for Applied Systems Analysis, Laxenburg, Austria, (4)Columbia University of New York, Center for Climate Systems Research, Palisades, NY, United States, (5)University of East Anglia, Climatic Research Unit, Norwich, United Kingdom, (6)University of Chicago, Chicago, IL, United States, (7)Lund University, Department of Physical Geography and Ecosystem Science, Lund, Sweden, (8)Institute for Sustainable Economic Development, Vienna, Austria
Abstract:
Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations with particularly severe consequences for people in developing countries. The fluctuations can be induced by weather conditions but also by management decisions, diseases, and pests. To get a better understanding of future sensitivities to climate change it is important to quantify the degree to which historical crop yields are determined by weather fluctuations. This separation from other influences is usually done by highly simplified empirical models. In contrast, here we provide a conservative estimate of the fraction of the observed national yield variability that is caused by weather, using state-of-the-art process-based crop model simulations. As these models provide a detailed representation of our current understanding of the underlying processes they are also suitable to assess potential adaptation options. We provide an identification of the countries where the weather induced variability of crop yields is particularly high (explained variance > 50%). In addition, inhibiting water stress by simulating yields assuming full irrigation shows that water limitation is the main driver of the observed variations in most of these countries.
