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Smith, Benjamin; Samuelsson, Patrick; Wramneby, Anna; Rummukainen, Markku (2011)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
Regional climate models (RCMs) primarily represent physical components of the climate system, omitting vegetation dynamics, ecosystem biogeochemistry and their associated feedbacks. To account for such feedbacks, we implemented a novel plant individual-based vegetation dynamics-ecosystem biogeochemistry scheme within the RCA3 RCM. Variations in leaf area index (LAI) of seven plant functional type (PFTs) in response to physical forcing and evolving vegetation state feed back to climate via adjustments in surface energy fluxes and surface properties. In an ERA-40- driven simulation over Europe, the model reproduces the recent past climate with comparable accuracy to the standard RCM. Large-scale patterns of LAI, net primary production and vegetation composition were comparable with observations, although winter LAI was systematically overestimated compared to satellite estimates. Analysis of the ERA-40 simulation and an A1B climate-change simulation revealed considerable covariation among dynamic variables of the physical climate and vegetation. At a Mediterranean site, periodic soil water limitation led to fluctuations in leaf cover and a likely positive feedback to near-surface temperature. At an alpine site, rising temperatures led to forest advance onto tundra areas, reducing albedo and effecting a likely positive feedback on temperature. Climate–vegetation coupling was less pronounced but still apparent at intermediate temperate and boreal sites.
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    • Betts, R. 2000. Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature 408, 187-190.
    • Betts, R. A., Cox, P. M., Collins, M., Harris, P. P., Huntingford, C. and co-authors. 2004. The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Theor. Appl. Climatol. 78, 157-175.
    • Brovkin, V., Claussen, M., Driesschaert, E., Fischefet, T., Kicklighter, D. and co-authors. 2006. Biogeophysical effects of historical land cover changes simulated by six Earth system models of intermediate complexity. Clim. Dyn. 26, 587-600.
    • Bugmann, H. 2001. A review of forest gap models. Clim. Change 51, 259-305.
    • Chase, T. N., Pielke, R. A., Kittel, T. G. F., Nemani, R. and Running, S. W. 1996. Sensitivity of a general circulation model to global changes in leaf area index. J. Geophys. Res. 101, 7393-7408.
    • Cook, B. I., Bonan, G. B., Levis, S. and Epstein, H. E. 2008. Rapid vegetation responses and feedbacks amplify climate model response to snow cover changes. Clim. Dyn. 30, 391-406.
    • Cooley, W. W. and Lohnes, P. R. 1971. Multivariate Data Analysis, Wiley, New York.
    • Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A. and Totterdell, I. J. 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408, 184-187.
    • Cramer, W., Bondeau, A., Woodward, F. I., Prentice, I. C., Betts, R. A. and co-authors. 2001. Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models. Global Change Biol. 7, 357-373.
    • Denman, K. L., Brasseur, G., Chidthaisong, A., Ciais, P., Cox, P. M. and co-authors. 2007. Couplings between changes in the climate system and biogeochemistry. In: Climate Change 2007: The Physical Science Basis (eds S. Solomon, D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. and co-editors). Cambridge University Press, Cambridge, 499-587.
    • Diffenbaugh, N. S., Pal, J. S., Trapp, R. J. and Giorgi, F. 2005. Fine-scale processes regulate the response of extreme events to global climate change. Proc. Natl. Acad. Sci. 102, 15774-15778.
    • Do¨scher, R., Wille´n, U., Jones, C., Rutgersson, A., Meier, H. E. M. and co-authors. 2002. The development of the coupled regional oceanatmosphere model RCAO. Boreal Environ. Res., 7, 183-192.
    • Do¨scher, R., Wyser, K., Meier, H. E. M., Qian, M. and Redler, R. 2010. Quantifying Arctic contributions to climate predictability in a regional coupled ocean-ice-atmosphere model. Clim. Dyn. 34, 1157-1176.
    • Fischer, E. M. and Scha¨r, C. 2009. Future changes in daily summer temperature variability: driving processes and role for temperature extremes. Clim. Dyn. 33, 917-935.
    • Friedlingstein, P., Dufresne, J.-L., Cox, P. M. and Rayner, P. 2003. How positive is the feedback between climate change and the carbon cycle? Tellus 55B, 692-700.
    • Friedlingstein, P., Cox, P., Betts, R., Bopp, L., Von Bloh, W. and co-authors. 2006. Climate-carbon cycle feedback analysis: Results from the (CMIP)-M-4 model intercomparison. J. Climate 19, 3337- 3353.
    • Frei, C., Christensen, J., Deque´, M., Jacob, D. and Vidale, P. 2003. Daily precipitation statistics in regional climate models: evaluation and intercomparison for the European Alps. J. Geophys. Res. 108, 4124-4142.
    • Gerten, D., Schaphoff, S., Haberlandt, W., Lucht, W. and Sitch, S. 2004. Terrestrial vegetation and water balance - hydrological evaluation of a dynamic global vegetation model. J. Hydrol. 286, 249-270.
    • Giorgi, F., 1995. Perspectives for regional earth system modelling. Global Planet. Change 10, 23-42.
    • Go¨ttel, H., Alexander, J., Keup-Thiel, E., Rechid, D., Hagemann, S. and co-authors. 2008. Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region. Clim. Change 87, 35-50.
    • Hickler, T., Smith, B., Sykes, M. T., Davis, M. B., Sugita, S. and coauthors. 2004. Using a generalized vegetation model to simulate vegetation dynamics in the western Great Lakes region, USA, under alternative disturbance regimes. Ecology 85, 519-530.
    • Hickler, T., Smith, B., Prentice, I. C., Mjo¨fors, K., Miller, P. and coauthors. 2008. CO2 fertilization in temperate forest FACE experiments not representative of boreal and tropical forests. Global Change Biol. 14, 1-12.
    • IPCC, 2001. Climate Change 2001. The Scientific Basis. Contribution of working group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK.
    • Jeltsch, F., Moloney, K. A., Schurr, F. M., Ko¨chy, M. and Schwager, M. 2008. The state of plant population modelling in light of environmental change. Perspect. Plant Ecol. Evol. Syst. 9, 171-189.
    • Jones C. D., Cox, P. and Huntingford, C. 2003. Uncertainty in climatecarbon-cycle projections associated with the sensitivity of soil respiration to temperature. Tellus 55B, 642-648.
    • Kjellstro¨m, E., Ba¨rring, L., Gollvik, S., Hansson, U., Jones, C. and co-authors. 2005. A 140-year simulation of European climate with the new version of the Rossby Centre regional atmospheric climate model (RCA3). Reports Meteorol. Climatol. 108, SMHI, Norrko¨ping, Sweden.
    • Los, S. O., Collatz, G. J., Sellers, P. J., Malmstro¨m, C. M., Pollack, N. H. and co-authors. 2000. A global 9-year biophysical land-surface data set from NOAA AVHRR data. J. Hydrometeor. 1, 183-199.
    • Manly, B. J. F., 1994. Multivariate Statistical Methods: A Primer, 2nd ed. Chapman & Hall, London.
    • Masson, V., Champeaux, J.-L., Chauvin, F., Meriguet, C. and Lacaze, R. 2003. A global database of Land Surface Parameters at 1-km Resolution in Meteorological and Climate Models. J. Climate 16, 1261-1282.
    • McGuire, A. D., Sitch, S., Clein, J. S., Dargaville, R., Esser, G. and co-authors. 2001. Carbon balance of the terrestrial biosphere in the twentieth century: Analyses of CO2, climate and land use effects with four process-based ecosystem models. Global Biogeoch. Cycl. 15, 183-206.
    • Meehl, G. A., Stocker, T. F., Collins, W. D., Friedlingstein, P., Gaye, A. T. and co-authors. 2007. Global Climate Projections. In: Climate Change 2007: The Physical Science Basis, eds. S. Solomon, D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. Tignor, H. L. Miller, Jr. and Z. Chen. Cambridge University Press, Cambridge, 747-845.
    • Moorcroft, P. R. 2003. Recent advances in ecosystem-atmosphere interactions: an ecological perspective. Proc. Roy. Soc. London B 270, 1215-1227.
    • Nakicenovic, N. and Swart, R. (eds) 2000. Special Report on Emissions Scenarios: A Special Report of Working Group III of the Intergovernmental Panel on Climate change. Cambridge University Press, Cambridge, UK.
    • New, M., Hulme, M. and Jones, P. D. 2000. Representing twentieth century space-time climate variability. Part 2: development of 1901- 96 monthly grids of terrestrial surface climate. J. Climate 13, 2217- 2238.
    • Notaro, M., Vavrus, S. and Liu, Z. 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, 70-90.
    • Olson, R. J., Johnson, K. R., Zheng, D. L. and Scurlock, J. M. O. 2001. Global and Regional Ecosystem Modeling: Databases of Model Drivers and Validation Measurements. Oak Ridge National Laboratory Report ORNL/TM-2001/196. Department of Energy, Oak Ridge, Tennessee, U.S.A.
    • Persson, G., Ba¨rring, L., Kjellstro¨m, E., Strandberg, G. and Rummukainen, M. 2007. Climate indices for vulnerability assessments. Reports Meteorol. Climatol. 111, SMHI, Norrko¨ping, Sweden.
    • Rinke, A., Gerdes, R., Dethloff, K., Kandlbinder, T., Karcher, M. and coauthors. 2003. A case study of the anomalous Arctic sea ice conditions during 1990: Insights from coupled and uncoupled regional climate model simulations. J. Geophys. Res. 108, 4275.
    • Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S. and co-authors. 2006. Sensitivity of simulated climate to horizontal and vertical resolution in the ECHAM5 atmosphere model. J. Climate 19, 3771-3791.
    • Rummukainen, M., 2010. State-of-the-art with regional climate models. WIRE Adv. Rev. 1, 82-96.
    • Samuelsson, P., Bringfelt, B. and Graham, L. P. 2003. The role of aerodynamic roughness for runoff and snow evaporation in land-surface schemes-comparison of uncoupled and coupled simulations. Global Planet. Change 38, 93-99.
    • Samuelsson, P., Gollvik, S. and Ullerstig, A. 2006. The land-surface scheme of the Rossby Centre regional atmospheric climate model (RCA3). Reports Meteorol. Climatol. 122, SMHI, Norrko¨ping, Sweden.
    • Samuelsson, P., Jones, C., Wille´n, U., Gollvik, S., Hansson, U. and coauthors. 2011. The Rossby Centre Regional Climate Model RCA3: Model description and performance. Tellus 63A, 4-23.
    • Sasaki, H., Kurihara, K., Takayabu, I., Murazaki, K., Sato, Y. and coauthors. 2006. Preliminary results from the coupled atmosphere-ocean regional climate model developed at the Meteorological Research Institute. J. Meteor. Soc. Japan 84, 389-403.
    • Sellers, P. J., Los, S. O., Tucker, C. J., Justice, C. O., Dazlich, D. A. and co-authors. 1996. A revised land surface parameterization (SiB2) for atmospheric GCMs. Part 2: The generation of global fields of terrestrial biophysical parameters from satellite data. J. Climate 9, 706-737.
    • Seneviratne, S. I., Lu¨thi, D., Litschi, M. and Scha¨r, C. 2006. Landatmosphere coupling and climate change in Europe. Nature 443, 205-209.
    • Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M. and co-authors. 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, 2015-2039.
    • Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A. and coauthors. 2003. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ Dynamic Global Vegetation Model. Global Change Biol. 9, 161-185.
    • Smith, B., Prentice, I. C. and Sykes, M. T. 2001. Representation of vegetation dynamics in modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecol. Biogeog. 10, 621-637.
    • Tømmervik, H., Jonansen, B., Tombre, I., Thannheiser, D., Høgda, K. A. and co-authors. 2004. Vegetation changes in the nordic mountain birch forest: the influence of grazing and climate change. Arctic Antarctic Alpine Res. 36, 323-332.
    • Uppala, S. M., Ka˚llberg, P. W., Simmons, A. J., Andrae, U., da Costa Bechtold, V. and co-authors. 2005. The ERA-40 re-analysis. Q. J. Roy. Meteorol. Soc. 131, 2961-3012.
    • Wille´n, U., 2008. Preliminary use of CM-SAF cloud and radiation products for evaluation of regional climate simulations. Reports Meteorol. Climatol. 131, SMHI, Norrko¨ping, Sweden.
    • Wramneby, A., Smith, B. and Samuelsson, P. Hotspots of vegetationclimate feedbacks under future greenhouse forcing in Europe. J. Geophys. Res., doi:10.1029/2010JD014307.
    • Wramneby, A., Smith, B., Zaehle, S. and Sykes, M. T. 2008. Parameter uncertainties in the modelling of vegetation dynamics-effects on tree community structure and ecosystem functioning in European forest biomes. Ecol. Mod. 216, 277-290.
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