Different human influences on the joint changes in temperature, rainfall and aridity — Australian Meteorological and Oceanographic Society
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Different human influences on the joint changes in temperature, rainfall and aridity (#125)

Céline Bonfils 1 , Benjamin Santer 1 , John C. Fyfe 2 , Kate Marvel 3 , Thomas Phillips 1 , Susan Zimmerman 1
  1. Program for Climate Model Diagnosis and Intercomparison (PCDMI), Lawrence Livermore National Laboratory, Livermore, CA, USA
  2. Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada
  3. Columbia University, and NASA Goddard Institute for Space Studies, New York, USA

For centuries, droughts have affected human and environmental systems. Despite their pervasive impacts, the large-scale mechanisms conducive to regional drying remain poorly understood. While fingerprint detection and attribution (D&A) techniques have helped to identify a discernible human influence in observational records of the hydrological cycle (including water vapor, rainfall, soil moisture, snowpack, or river runoff) D&A techniques remain, until recently, under-utilized in aridity research. Here, we use a pattern-based approach to investigate the influence of external forcings on large-scale changes in temperature and precipitation conducive to regional drying. Based on CMIP5 climate simulations and employing the LLNL fingerprint detection and attribution technique, we investigate the individual influences of time-varying greenhouse gases, anthropogenic aerosols and natural (volcanic and solar) changes on the hydrological cycle. We have identified large-scale, externally forced mechanisms impacting the recent changes in continental aridity at regional scale and found that we can formally identify different human contributions in the observed changes in aridity.

Acknowledgments: This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. We also acknowledge the support of the U.S. Department of Energy, Office of Science, Climate and Environmental Sciences Division, Regional and Global Modeling and Analysis Program.

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