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Anderson, Bruce T.; Lintner, Benjamin R.; Langenbrunner, Baird; Neelin, J. David; Hawkins, Ed; Syktus, Jozef (2015)
Publisher: American Geophysical Union
Languages: English
Types: Article
Pronounced intermodel differences in the projected response of land surface precipitation (LSP) to future anthropogenic forcing remain in the Coupled Model Intercomparison Project Phase 5 model integrations. A large fraction of the intermodel spread in projected LSP trends is demonstrated here to be associated with systematic differences in simulated sea surface temperature (SST) trends, especially the representation of changes in (i) the interhemispheric SST gradient and (ii) the tropical Pacific SSTs. By contrast, intermodel differences in global mean SST, representative of differing global climate sensitivities, exert limited systematic influence on LSP patterns. These results highlight the importance to regional terrestrial precipitation changes of properly simulating the spatial distribution of large-scale, remote changes as reflected in the SST response to increasing greenhouse gases. Moreover, they provide guidance regarding which region-specific precipitation projections may be potentially better constrained for use in climate change impact assessments.
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    • Allen, M. R., and W. J. Ingram (2002), Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 224-232.
    • Alley, R. B., et al. (2003), Abrupt climate change, Science, 299, 2005-2010, doi:10.1126/science.1081056.
    • Anderson, B. T. (2003), Tropical Pacific sea-surface temperatures and preceding sea-level pressure anomalies in the subtropical North Pacific, J. Geophys. Res., 108(D23), 4732, doi:10.1029/2003JD003805.
    • Anderson, B. T., C. Reifen, and R. Toumi (2009), Consistency in global climate change model predictions of regional precipitation trends, Earth Interact., 13, 1-23, doi:10.1175/2009EI273.1.
    • Barnett, T. P., and R. Preisendorfer (1987), Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysis, Mon. Weather Rev., 15, 1825-1850.
    • Bretherton, C. S., C. Smith, and J. M. Wallace (1992), An intercomparison of methods for finding coupled patterns in climate data, J. Clim., 5, 541-560.
    • Cherry, S. (1996), Singular value decomposition analysis and canonical correlation analysis, J. Clim., 9, 2003-2009.
    • Chiang, J. C., and C. M. Bitz (2005), Influence of high latitude ice cover on the marine intertropical convergence zone, Clim. Dyn., 25, 477-496, doi:10.1007/s00382-005-0040-5.
    • Chou, C., J. D. Neelin, J.-Y. Tu, and C.-T. Chen (2006), Regional tropical precipitation change mechanisms in ECHAM4/OPYC3 under global warming, J. Clim., 19(17), 4207-4223, doi:10.1175/JCLI3858.1.
    • Deser, C., A. Phillips, V. Bourdette, and H. Teng (2012a), Uncertainty in climate change projections: The role of internal variability, Clim. Dyn., 38, 527-546.
    • Deser, C., A. S. Phillips, R. A. Tomas, Y. M. Okumura, M. A. Alexander, A. Capotondi, J. D. Scott, Y.-O. Kwon, and M. Ohba (2012b), ENSO and Pacific decadal variability in the Community Climate System Model version 4, J. Clim., 25, 2622-2651, doi:10.1175/JCLI-D-11-00301.1.
    • Entekhabi, D., et al. (2010), The soil moisture active passive (SMAP) mission, Proc. IEEE, 98, 704-716.
    • Frierson, D. M. W., and Y.-T. Hwang (2012), Extratropical influence on ITCZ shifts in slab ocean simulations of global warming, J. Clim., 25, 720-733, doi:10.1175/JCLI-D-11-00116.1.
    • Frierson, D. M. W., Y.-T. Hwang, N. S. Fučkar, R. Seager, S. M. Kang, A. Donohoe, E. A. Maroon, X. Liu, and D. S. Battisti (2013), Contribution of ocean overturning circulation to tropical rainfall peak in the Northern Hemisphere, Nat. Geosci., 6, 940-944, doi:10.1038/ngeo1987.
    • Gent, P. R., et al. (2011), The Community Climate System Model version 4, J. Clim., 24, 4973-4991.
    • Giannini, A., R. Saravanan, and P. Chang (2003), Oceanic forcing of Sahel rainfall on interannual to interdecadal time scales, Science, 302, 1027-1030.
    • Giorgi, F. (2005), Climate change prediction, Clim. Change, 73, 239-265.
    • Graham, N. E., J. Michaelsen, and T. P. Barnett (1987), An investigation of the El Niño-Southern Oscillation cycle with statistical models: 1. Predictor field characteristics, J. Geophys. Res., 92, 14,251-14,270, doi:10.1029/JC092iC13p14251.
    • He, J., B. J. Soden, and B. Kirtman (2014), The robustness of the atmospheric circulation and precipitation response to future anthropogenic surface warming, Geophys. Res. Lett., 41, 2614-2622, doi:10.1002/2014GL059435.
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