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" How well do CMIP5 climate simulations replicate historical trends and patterns of meteorological droughts? "
Nasrollahi, N; Aghakouchak, A; Cheng, L; Damberg, L; Phillips, TJ; Miao, C; Hsu, K; Sorooshian, S
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AL
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911438
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LA65v3d3t3
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| Title & Author
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How well do CMIP5 climate simulations replicate historical trends and patterns of meteorological droughts? [Article]\ Nasrollahi, N; Aghakouchak, A; Cheng, L; Damberg, L; Phillips, TJ; Miao, C; Hsu, K; Sorooshian, S
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2015
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UC Irvine
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| Abstract
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© 2015. American Geophysical Union. All Rights Reserved. Assessing the uncertainties and understanding the deficiencies of climate models are fundamental to developing adaptation strategies. The objective of this study is to understand how well Coupled Model Intercomparison-Phase 5 (CMIP5) climate model simulations replicate ground-based observations of continental drought areas and their trends. The CMIP5 multimodel ensemble encompasses the Climatic Research Unit (CRU) ground-based observations of area under drought at all time steps. However, most model members overestimate the areas under extreme drought, particularly in the Southern Hemisphere (SH). Furthermore, the results show that the time series of observations and CMIP5 simulations of areas under drought exhibit more variability in the SH than in the Northern Hemisphere (NH). The trend analysis of areas under drought reveals that the observational data exhibit a significant positive trend at the significance level of 0.05 over all land areas. The observed trend is reproduced by about three-fourths of the CMIP5 models when considering total land areas in drought. While models are generally consistent with observations at a global (or hemispheric) scale, most models do not agree with observed regional drying and wetting trends. Over many regions, at most 40% of the CMIP5 models are in agreement with the trends of CRU observations. The drying/wetting trends calculated using the 3 months Standardized Precipitation Index (SPI) values show better agreement with the corresponding CRU values than with the observed annual mean precipitation rates. Pixel-scale evaluation of CMIP5 models indicates that no single model demonstrates an overall superior performance relative to the other models.
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