Climate extremes in the context of natural climate variability and climate change - A step towards the prediction of climate extremes
Final Report Abstract
Climate extremes are an important aspect of the climate's variability and climate change. The investigation of their nature and the improvement of their prediction are of major concern for our society to minimize the substantial human and financial losses induced by these extremes. The overall aim of this project was to assess the ability of GCMs to simulate climate extremes and their relationship to patterns of climate variability. The project started with the improvement of the methodology for the statistical modeling of extreme winter temperatures under the inclusion of an important circulation pattern (i.e., atmospheric blocking) as a covariate and the estimation of uncertainties in the return value calculations. The main part of the project dealt with the calculation and analysis of indices for climate extremes for a large set of global climate models participating in the Coupled Model Intercomparison Project Phase 3 and 5 (CMIP3 and CMIP5). The extremes indices calculated from historical model simulations were compared to various reanalysis datasets and an observation-based dataset (HadEX2). The analysis showed that the CMIP5 ensemble is generally able to simulate climate extremes and their trend patterns compared to observations. Substantial discrepancies between the reanalysis datasets were revealed, indicating considerable uncertainties depending on the region and index under consideration. This kind of model evaluation and assessment of individual model performance has not been done before and contributed to the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC AR5). The extremes indices were further calculated for the scenario simulations of the CMIP3 and CMIP5 models following different emission scenarios (Special Report on Emission Scenarios (SRES) and Representative Concentration Pathways (RCP) respectively). The global and regional analysis performed in this project were able to support and complement previous findings on changes in climate extremes. Changes in extremes indices based on daily minimum temperatures are found to be more pronounced than in indices based on daily maximum temperatures. Extreme precipitation generally increases faster than total wet-day precipitation. In regions, such as Australia, Central America, South Africa, and the Mediterranean, increases in consecutive dry days coincide with decreases in heavy precipitation days and maximum consecutive 5 day precipitation, which indicates future intensification of dry conditions. Particularly for the precipitation-based indices, there can be a wide disagreement about the sign of change between the models in some regions. Changes in temperature and precipitation indices are most pronounced under RCP8.5 (highest greenhouse gas emissions), with projected changes exceeding those discussed in previous studies based on SRES scenarios. The project also showed that besides modes of climate variability, also feedback mechanisms between climate extremes and, for instance, aerosols, soil moisture, and vegetation play an important role in the assessment of climate extremes and further process understanding is needed to improve the their simulation and projection. A first study on the aerosol effect on climate extremes was able to show that a global aerosol reduction greatly enforces the general warming effect due to greenhouse gases and results in significant increases of temperature and precipitation extremes. Future research studies are needed involving multimodel simulations of complex Earth system models to account for modelrelated uncertainties and relevant feedback mechanisms between the interacting climate system components.
Publications
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2011: Extreme cold winter temperatures in Europe under the influence of North Atlantic atmospheric blocking. J. Climate, 24, 5899–5913
Sillmann, J., M. Croci-Maspoli, M. Kallache, R. W. Katz
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2013: Climate extremes indices in the CMIP5 multi-model ensemble. Part 1: Model evaluation in the present climate. J. Geophys. Res., 118, 1716–1733
Sillmann, J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh
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2013: Climate extremes indices in the CMIP5 multi-model ensemble. Part 2: Future projections. J. Geophys. Res., 118, 2473–2493
Sillmann, J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh
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2013c: Aerosol effect on climate extremes in Europe under different future scenarios, Geophys. Res. Lett., 40, 2290–2295
Sillmann, J., L. Pozzoli, E. Vignati, S. Kloster, and J. Feichter
