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Global assessment of trends in wetting and drying over land

A Corrigendum to this article was published on 28 September 2014

This article has been updated

Abstract

Changes in the hydrological conditions of the land surface have substantial impacts on society1,2. Yet assessments of observed continental dryness trends yield contradicting results3,4,5,6,7. The concept that dry regions dry out further, whereas wet regions become wetter as the climate warms has been proposed as a simplified summary of expected8,9,10 as well as observed10,11,12,13,14 changes over land, although this concept is mostly based on oceanic data8,10. Here we present an analysis of more than 300 combinations of various hydrological data sets of historical land dryness changes covering the period from 1948 to 2005. Each combination of data sets is benchmarked against an empirical relationship between evaporation, precipitation and aridity. Those combinations that perform well are used for trend analysis. We find that over about three-quarters of the global land area, robust dryness changes cannot be detected. Only 10.8% of the global land area shows a robust ‘dry gets drier, wet gets wetter’ pattern, compared to 9.5% of global land area with the opposite pattern, that is, dry gets wetter, and wet gets drier. We conclude that aridity changes over land, where the potential for direct socio-economic consequences is highest, have not followed a simple intensification of existing patterns.

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Figure 1: Vegetation-adjusted Budyko framework.
Figure 2: Budyko validation of hydrological data set combinations for the 1984–2005 period.
Figure 3: Detection of robust dryness changes.
Figure 4: Investigating the DDWW paradigm.

Change history

  • 24 September 2014

    In the version of this Letter originally published, in the main text, the number of different combinations given for each grid point in Fig. 3 were incorrect and should have read "28 (77)". Additionally, the second sentence describing the parameters in the final equation should have read "Significance at the 5% level is thus assigned for n = 28 combinations of E and P data sets if DM2 1.5 and for n = 44 combinations of Ep and P data sets also if DM2 1.5." Furthermore, in the key for Fig. 4a, the values should have read 1.5 (-1.5). These errors have no influence on the results of the study, and have now been corrected in the online versions of the Letter.

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Acknowledgements

The Center for Climate Systems Modeling (C2SM) at ETH Zurich is acknowledged for providing technical support. This work was supported by ETH Research Grant CH2-01 11-1. We acknowledge participants of the TRENDY model intercomparison project for access to their simulation results. These include, C. Huntingford (TRIFFID), B. Poulter (LPJ), A. Ahlström, A. Arneth, B. Smith (LPJ-GUESS), M. Lomas (SDGVM), P. Levy (HyLand), S. Levis, G. Bonan (NCAR-CLM4), S. Zaehle (OCN), N. Viovy (Orchidee), and S. Sitch and P. Friedlingstein (project coordinators). We acknowledge D. Miralles (University of Bristol) for access to the GLEAM data set. CRU data were obtained from the University of East Anglia Climate Research Unit (CRU), British Atmospheric Data Centre, 2008, available from http://badc.nerc.ac.uk/data/cru. The GPCP combined precipitation data were developed and computed by the NASA/Goddard Space Flight Centers Laboratory for Atmospheres as a contribution to the GEWEX Global Precipitation Climatology Project. GPCC precipitation data are available from the GPCC homepage: http://gpcc.dwd.de. CPC merged analysis of precipitation data, PREC/L precipitation data, NCEP reanalysis data, UDel air temperature and precipitation data were provided by the NOAA/OAR/ESRL PSD, from their website at http://www.esrl.noaa.gov/psd/. We acknowledge the Global Modeling and Assimilation Office and the GES DISC for the dissemination of MERRA and MERRA-LAND, and the ECMWF for the dissemination of ERA-Interim data. The CFSR data are from the Research Data Archive, which is maintained by the Computational and Information Systems Laboratory at the National Center for Atmospheric Research (NCAR). NCAR is sponsored by the National Science Foundation. The original data are available from the Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. http://rda.ucar.edu/datasets/ds093.2/. Support for the Twentieth Century Reanalysis Project data set is provided by the US Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office. SRB data were obtained from the NASA Langley Research Center Atmospheric Sciences Data Center NASA/GEWEX SRB Project.

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P.G., B.O. and S.I.S. designed the study and wrote the manuscript. P.G. performed all computations. B.M. provided support with the collection of evapotranspiration data sets. J.S. and M.R. provided data sets to the study. All authors commented on the manuscript.

Corresponding authors

Correspondence to Peter Greve or Sonia I. Seneviratne.

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The authors declare no competing financial interests.

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Greve, P., Orlowsky, B., Mueller, B. et al. Global assessment of trends in wetting and drying over land. Nature Geosci 7, 716–721 (2014). https://doi.org/10.1038/ngeo2247

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