Sea Surface Temperature Warming Patterns and Future Vegetation Change

Sara A. Rauscher * Department of Geography, University of Delaware, Newark, Delaware

Search for other papers by Sara A. Rauscher in
Current site
Google Scholar
PubMed
Close
,
Xiaoyan Jiang Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Xiaoyan Jiang in
Current site
Google Scholar
PubMed
Close
,
Allison Steiner Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, Michigan

Search for other papers by Allison Steiner in
Current site
Google Scholar
PubMed
Close
,
A. Park Williams Lamont Doherty Earth Observatory, Columbia University, Palisades, New York

Search for other papers by A. Park Williams in
Current site
Google Scholar
PubMed
Close
,
D. Michael Cai Intelligence and Space Research Division, Los Alamos National Laboratory, Los Alamos, New Mexico

Search for other papers by D. Michael Cai in
Current site
Google Scholar
PubMed
Close
, and
Nathan G. McDowell ** Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico

Search for other papers by Nathan G. McDowell in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Recent modeling studies of future vegetation change suggest the potential for large-scale forest die-off in the tropics. Taken together with observational evidence of increasing tree mortality in numerous ecosystem types, there is clearly a need for projections of vegetation change. To that end, the authors have performed an ensemble of climate–vegetation experiments with the National Science Foundation–DOE Community Atmosphere Model (CAM) coupled to the Community Land Model (CAM–CLM-CN) with its dynamic vegetation model enabled (CAM–CLM-CNDV). To overcome the limitations of using a single model, the authors employ the sea surface temperature (SST) warming patterns simulated by eight different models from the Coupled Model Intercomparison Program phase 3 (CMIP3) as boundary conditions. Since the SST warming pattern in part dictates how precipitation may change in the future, in this way a range of future vegetation–climate trajectories can be produced.

On an annual average basis, this study’s CAM–CLM-CN simulations do not produce as large a spread in projected precipitation as the original CMIP3 archive. These differences are due to the tendency of CAM–CLM-CN to increase tropical precipitation under a global warming scenario, although this response is modulated by the SST warming patterns imposed. However, the CAM–CLM-CN simulations reproduce the enhanced dry season in the tropics simulated by CMIP3. These simulations show longer fire seasons and increases in fractional area burned. In one ensemble member, extreme droughts over tropical South America lead to fires that remove vegetation cover in the eastern Amazon, suggesting that large-scale die-offs are an unlikely but still possible event.

Corresponding author address: Sara A. Rauscher, Dept. of Geography, University of Delaware, 219 Pearson Hall, Newark, DE 19716. E-mail: rauscher@udel.edu

Abstract

Recent modeling studies of future vegetation change suggest the potential for large-scale forest die-off in the tropics. Taken together with observational evidence of increasing tree mortality in numerous ecosystem types, there is clearly a need for projections of vegetation change. To that end, the authors have performed an ensemble of climate–vegetation experiments with the National Science Foundation–DOE Community Atmosphere Model (CAM) coupled to the Community Land Model (CAM–CLM-CN) with its dynamic vegetation model enabled (CAM–CLM-CNDV). To overcome the limitations of using a single model, the authors employ the sea surface temperature (SST) warming patterns simulated by eight different models from the Coupled Model Intercomparison Program phase 3 (CMIP3) as boundary conditions. Since the SST warming pattern in part dictates how precipitation may change in the future, in this way a range of future vegetation–climate trajectories can be produced.

On an annual average basis, this study’s CAM–CLM-CN simulations do not produce as large a spread in projected precipitation as the original CMIP3 archive. These differences are due to the tendency of CAM–CLM-CN to increase tropical precipitation under a global warming scenario, although this response is modulated by the SST warming patterns imposed. However, the CAM–CLM-CN simulations reproduce the enhanced dry season in the tropics simulated by CMIP3. These simulations show longer fire seasons and increases in fractional area burned. In one ensemble member, extreme droughts over tropical South America lead to fires that remove vegetation cover in the eastern Amazon, suggesting that large-scale die-offs are an unlikely but still possible event.

Corresponding author address: Sara A. Rauscher, Dept. of Geography, University of Delaware, 219 Pearson Hall, Newark, DE 19716. E-mail: rauscher@udel.edu
Save
  • Adams, H. D., A. P. Williams, C. Xu, S. A. Rauscher, X. Jiang, and N. G. McDowell, 2013: Empirical and process-based approaches to climate-induced forest mortality models. Front. Plant Sci., 4, 438, doi:10.3389/fpls.2013.00438.

    • Search Google Scholar
    • Export Citation
  • Allen, C. D., and Coauthors, 2010: A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. Manage., 259, 660684, doi:10.1016/j.foreco.2009.09.001.

    • Search Google Scholar
    • Export Citation
  • Ballantyne, A. P., C. B. Alden, J. B. Miller, P. P. Tans, and J. W. C. White, 2012: Increase in observed net carbon dioxide uptake by land and oceans during the past 50 years. Nature, 488, 7072, doi:10.1038/nature11299.

    • Search Google Scholar
    • Export Citation
  • Biasutti, M., and A. H. Sobel, 2009: Delayed Sahel rainfall and global seasonal cycle in a warmer climate. Geophys. Res. Lett, 36, L23707, doi:10.1029/2009GL041303.

    • Search Google Scholar
    • Export Citation
  • Chou, C., and J. D. Neelin, 2004: Mechanisms of global warming impacts on regional tropical precipitation. J. Climate, 17, 26882701, doi:10.1175/1520-0442(2004)017<2688:MOGWIO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chou, C., J. D. Neelin, C.-A. Chen, and J.-Y. Tu, 2009: Evaluating the “rich-get-richer” mechanism in tropical precipitation change under global warming. J. Climate, 22, 19822005, doi:10.1175/2008JCLI2471.1.

    • Search Google Scholar
    • Export Citation
  • Cook, B., N. Zeng, and J.-H. Yoon, 2012: Will Amazonia dry out? Magnitude and causes of change from IPCC climate model projections. Earth Interact., 16, 127, doi:10.1175/2011EI398.1.

    • Search Google Scholar
    • Export Citation
  • Cox, P. M., R. A. Betts, C. D. Jones, S. A. Spall, and I. J. Totterdell, 2000: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature, 408, 184187, doi:10.1038/35041539.

    • Search Google Scholar
    • Export Citation
  • Cox, P. M., R. A. Betts, M. Collins, P. P. Harris, C. Huntingford, and C. D. Jones, 2004: Amazonian forest dieback under climate-carbon cycle projections for the 21st century. Theor. Appl. Climatol., 78, 137156, doi:10.1007/s00704-004-0049-4.

    • Search Google Scholar
    • Export Citation
  • Galbraith, D., P. Levy, S. Sitch, C. Huntingford, P. Cox, M. Williams, and P. Meir, 2010: Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change. New Phytol., 187, 647665, doi:10.1111/j.1469-8137.2010.03350.x.

    • Search Google Scholar
    • Export Citation
  • Gent, P. R., and Coauthors, 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991, doi:10.1175/2011JCLI4083.1.

    • Search Google Scholar
    • Export Citation
  • Giannini, A., 2010: Mechanisms of climate change in the semiarid African Sahel: The local view. J. Climate, 23, 743756, doi:10.1175/2009JCLI3123.1.

    • Search Google Scholar
    • Export Citation
  • Gotangco Castillo, C. K., S. Levis, and P. Thornton, 2012: Evaluation of the new CNDV option of the Community Land Model: Effects of dynamic vegetation and interactive nitrogen on CLM4 means and variability. J. Climate, 25, 37023714, doi:10.1175/JCLI-D-11-00372.1.

    • Search Google Scholar
    • Export Citation
  • Harris, P. P., C. Huntingford, and P. M. Cox, 2008: Amazon basin climate under global warming: The role of the sea surface temperature. Philos. Trans. Roy. Soc. London, 363B, 17531759, doi:10.1098/rstb.2007.0037.

    • Search Google Scholar
    • Export Citation
  • Huang, P., S.-P. Xie, K. Hu, G. Huang, and R. Huang, 2013: Patterns of the seasonal response of tropical rainfall to global warming. Nat. Geosci., 6, 357361, doi:10.1038/ngeo1792.

    • Search Google Scholar
    • Export Citation
  • Huntingford, C., and Coauthors, 2013: Simulated resilience of tropical rainforests to CO2-induced climate change. Nat. Geosci., 6, 268273, doi:10.1038/ngeo1741.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J. W., J. J. Hack, D. Shea, J. M. Caron, and J. Rosinski, 2008: A new sea surface temperature and sea ice boundary dataset for the Community Atmosphere Model. J. Climate, 21, 51455153, doi:10.1175/2008JCLI2292.1.

    • Search Google Scholar
    • Export Citation
  • IPCC, 2000: Special Report on Emissions Scenarios. Cambridge University Press, 570 pp. [Available online at http://www.ipcc.ch/ipccreports/sres/emission/index.php?idp=0.]

  • Janowiak, J. E., and P. Xie, 1999: CAMS–OPI: A global satellite–rain gauge merged product for real-time precipitation monitoring applications. J. Climate, 12, 33353342, doi:10.1175/1520-0442(1999)012<3335:COAGSR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Jiang, X., and Coauthors, 2013: Projected future changes in vegetation in western North America in the twenty-first century. J. Climate, 26, 36713687, doi:10.1175/JCLI-D-12-00430.1.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 11381140, doi:10.1126/science.1100217.

    • Search Google Scholar
    • Export Citation
  • Lamarque, J. F., and Coauthors, 2010: Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: Methodology and application. Atmos. Chem. Phys., 10, 70177039, doi:10.5194/acp-10-7017-2010.

    • Search Google Scholar
    • Export Citation
  • Lawrence, D. M., and Coauthors, 2011: Parameterization improvements and functional and structural advances in version 4 of the Community Land Model. J. Adv. Model. Earth Syst., 3, M03001, doi:10.1029/2011MS000045.

    • Search Google Scholar
    • Export Citation
  • Leloup, J., and A. Clement, 2009: Why is there a minimum in projected warming in the tropical North Atlantic Ocean? Geophys. Res. Lett., 36, L14802, doi:10.1029/2009GL038609.

    • Search Google Scholar
    • Export Citation
  • Levis, S., G. B. M. Vertenstein, and K. Oleson, 2004: The Community Land Model’s Dynamic Global Vegetation Model (CLM-DGVM): Technical description and user’s guide. NCAR Tech. Note NCAR/TN-459+IA, 50 pp. [Available online at http://www.cgd.ucar.edu/tss/clm/distribution/clm3.0/DGVMDoc/TN-459+IA.pdf.]

  • Lewis, S. L., P. M. Brando, O. L. Phillips, G. M. F. van der Heijden, and D. Nepstad, 2011: The 2010 Amazon drought. Science, 331, 554, doi:10.1126/science.1200807.

    • Search Google Scholar
    • Export Citation
  • Li, F., X. D. Zeng, and S. Levis, 2012: A process-based fire parameterization of intermediate complexity in a dynamic global vegetation model. Biogeosci. Discuss., 9, 32333287, doi:10.5194/bgd-9-3233-2012.

    • Search Google Scholar
    • Export Citation
  • Li, W., R. Fu, and R. E. Dickinson, 2006: Rainfall and its seasonality over the Amazon in the 21st century as assessed by the coupled models for the IPCC AR4. J. Geophys. Res., 111, D02111, doi:10.1029/2005JD006355.

    • Search Google Scholar
    • Export Citation
  • Lyon, B., and A. G. Barnston, 2005: ENSO and the spatial extent of interannual precipitation extremes in tropical land areas. J. Climate, 18, 50955109, doi:10.1175/JCLI3598.1.

    • Search Google Scholar
    • Export Citation
  • Ma, J., and S.-P. Xie, 2013: Regional patterns of sea surface temperature change: A source of uncertainty in future projections of precipitation and atmospheric circulation. J. Climate, 26, 24822501, doi:10.1175/JCLI-D-12-00283.1.

    • Search Google Scholar
    • Export Citation
  • Malhi, Y., and Coauthors, 2009: Exploring the likelihood and mechanism of a climate-change-induced dieback of the Amazon rainforest. Proc. Natl. Acad. Sci. USA, 106, 20 61020 615, doi:10.1073/pnas.0804619106.

    • Search Google Scholar
    • Export Citation
  • Marengo, J., and Coauthors, 2008: The drought of Amazonia in 2005. J. Climate, 21, 495516, doi:10.1175/2007JCLI1600.1.

  • McDowell, N. G., and Coauthors, 2013: Evaluating theories of drought-induced vegetation mortality using a multimodel experiment framework. New Phytol., 200, 304321, doi:10.1111/nph.12465.

    • Search Google Scholar
    • Export Citation
  • Meehl, G. A., C. Covey, K. E. Taylor, T. Delworth, R. J. Stouffer, M. Latif, B. McAvaney, and J. F. B. Mitchell, 2007: The WCRP CMIP3 multimodel dataset: A new era in climate change research. Bull. Amer. Meteor. Soc., 88, 13831394, doi:10.1175/BAMS-88-9-1383.

    • Search Google Scholar
    • Export Citation
  • Neale, R. B., and Coauthors, 2010: Description of the NCAR Community Atmosphere Model (CAM 4.0). NCAR Tech. Note NCAR/TN-485+STR, 212 pp. [Available online at http://www.cesm.ucar.edu/models/ccsm4.0/cam/docs/description/cam4_desc.pdf.]

  • Notaro, M., S. Vavrus, and Z. Liu, 2007: Global vegetation and climate change due to future increases in CO2 as projected by a fully coupled model with dynamic vegetation. J. Climate, 20, 7090, doi:10.1175/JCLI3989.1.

    • Search Google Scholar
    • Export Citation
  • Oleson, K. W., and Coauthors, 2010: Technical description of version 4.0 of the Community Land Model (CLM). NCAR Tech. Note NCAR/TN-478+STR, 257 pp. [Available online at http://www.cesm.ucar.edu/models/ccsm4.0/clm/CLM4_Tech_Note.pdf.]

  • Qian, T., A. Dai, K. E. Trenberth, and K. W. Oleson, 2006: Simulation of global land surface conditions from 1948 to 2004. Part I: Forcing data and evaluations. J. Hydrometeor., 7, 953975, doi:10.1175/JHM540.1.

    • Search Google Scholar
    • Export Citation
  • Rammig, A., and Coauthors, 2010: Estimating the risk of Amazonian forest dieback. New Phytol., 187, 694706, doi:10.1111/j.1469-8137.2010.03318.x.

    • Search Google Scholar
    • Export Citation
  • Rauscher, S. A., F. Giorgi, N. Diffenbaugh, and A. Seth, 2008: Extension and intensification of the Meso-American mid-summer drought in the twenty-first century. Climate Dyn., 31, 551571, doi:10.1007/s00382-007-0359-1.

    • Search Google Scholar
    • Export Citation
  • Rauscher, S. A., F. Kucharski, and D. B. Enfield, 2011: The role of regional SST warming variations in the drying of Meso-America in future climate projections. J. Climate, 24, 20032016, doi:10.1175/2010JCLI3536.1.

    • Search Google Scholar
    • Export Citation
  • Seth, A., M. Rojas, and S. Rauscher, 2010: CMIP3 projected changes in the annual cycle of the South American monsoon. Climatic Change, 98, 331357, doi:10.1007/s10584-009-9736-6.

    • Search Google Scholar
    • Export Citation
  • Seth, A., S. Rauscher, M. Rojas, A. Giannini, and S. Camargo, 2011: Enhanced spring convective barrier for monsoons in a warmer world? Climatic Change, 104, 403414, doi:10.1007/s10584-010-9973-8.

    • Search Google Scholar
    • Export Citation
  • Seth, A., S. Rauscher, M. Biasutti, A. Giannini, S. J. Camargo, and M. Rojas, 2013: CMIP5 projected changes in the annual cycle of precipitation in monsoon regions. J. Climate, 26, 73287351, doi:10.1175/JCLI-D-12-00726.1.

    • Search Google Scholar
    • Export Citation
  • Sitch, S., and Coauthors, 2003: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biol., 9, 161185, doi:10.1046/j.1365-2486.2003.00569.x.

    • Search Google Scholar
    • Export Citation
  • Sitch, S., and Coauthors, 2008: Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five dynamic global vegetation models (DGVMs). Global Change Biol., 14, 20152039, doi:10.1111/j.1365-2486.2008.01626.x.

    • Search Google Scholar
    • Export Citation
  • Sobel, A. H., J. Nilsson, and L. M. Polvani, 2001: The weak temperature gradient approximation and balanced tropical moisture waves. J. Atmos. Sci., 58, 36503665, doi:10.1175/1520-0469(2001)058<3650:TWTGAA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Steiner, A. L., J. S. Pal, S. A. Rauscher, J. L. Bell, N. S. Diffenbaugh, A. Boone, L. C. Sloan, and F. Giorgi, 2009: Land surface coupling in regional climate simulations of the West African monsoon. Climate Dyn., 33, 869892, doi:10.1007/s00382-009-0543-6.

    • Search Google Scholar
    • Export Citation
  • Tan, P.-H., C. Chou, and J.-Y. Tu, 2008: Mechanisms of global warming impacts on robustness of tropical precipitation asymmetry. J. Climate, 21, 55855602, doi:10.1175/2008JCLI2154.1.

    • Search Google Scholar
    • Export Citation
  • Thonicke, K., S. Venevsky, S. Sitch, and W. Cramer, 2001: The role of fire disturbance for global vegetation dynamics: Coupling fire into a dynamic global vegetation model. Global Ecol. Biogeogr., 10, 661677, doi:10.1046/j.1466-822X.2001.00175.x.

    • Search Google Scholar
    • Export Citation
  • Thornton, P. E., J.-F. Lamarque, N. A. Rosenbloom, and N. M. Mahowald, 2007: Influence of carbon-nitrogen cycle coupling on land model response to CO2 fertilization and climate variability. Global Biogeochem. Cycles, 21, GB4018, doi:10.1029/2006GB002868.

    • Search Google Scholar
    • Export Citation
  • Williams, A. P., and Coauthors, 2013: Temperature as a potent driver of regional forest drought stress and tree mortality. Nat. Climate Change, 3, 292297, doi:10.1038/nclimate1693.

    • Search Google Scholar
    • Export Citation
  • Willmott, C. J., and K. Matsuura, 1995: Smart interpolation of annually averaged air temperature in the United States. J. Appl. Meteor., 34, 25772586, doi:10.1175/1520-0450(1995)034<2577:SIOAAA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Willmott, C. J., and K. Matsuura, 2001: Terrestrial air temperature and precipitation: Monthly and annual time series (1950–1999). [Available online at http://climate.geog.udel.edu/~climate/html_pages/README.ghcn_ts2.html.]

  • Xie, P., and P. A. Arkin, 1996: Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions. J. Climate, 9, 840858, doi:10.1175/1520-0442(1996)009<0840:AOGMPU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Xie, S.-P., C. Deser, G. A. Vecchi, J. Ma, H. Teng, and A. T. Wittenberg, 2010: Global warming pattern formation: Sea surface temperature and rainfall. J. Climate, 23, 966986, doi:10.1175/2009JCLI3329.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 343 97 12
PDF Downloads 208 82 6