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Sensitivity of high-resolution Arctic regional climate model projections to different implementations of land surface processes

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Abstract

This paper discusses the effects of vegetation cover and soil parameters on the climate change projections of a regional climate model over the Arctic domain. Different setups of the land surface model of the regional climate model HIRHAM were realized to analyze differences in the atmospheric circulation caused by (1) the incorporation of freezing/thawing of soil moisture, (2) the consideration of top organic soil horizons typical for the Arctic and (3) a vegetation shift due to a changing climate. The largest direct thermal effect in 2 m air temperature was found for the vegetation shift, which ranged between −1.5 K and 3 K. The inclusion of a freeze/thaw scheme for soil moisture shows equally large sensitivities in spring over cool areas with high soil moisture content. Although the sensitivity signal in 2 m air temperature for the experiments differs in amplitude, all experiments show changes in mean sea level pressure (mslp) and geopotential height (z) throughout the troposphere of similar magnitude (mslp: −2 hPa to 1.5 hPa, z: −15 gpm to 5 gpm). This points to the importance of dynamical feedbacks within the atmosphere-land system. Land and soil processes have a distinct remote influence on large scale atmospheric circulation patterns in addition to their direct, regional effects. The assessment of induced uncertainties due to the changed implementations of land surface processes discussed in this study demonstrates the need to take all those processes for future Arctic climate projections into account, and demonstrates a clear need to include similar implementations in regional and global climate models.

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References

  • ACIA (2004) Arctic climate impact assessment. Cambridge University Press

  • Beringer JA, Lynch H, Chapin FS III, Mack M, Bonan GB (2001) The representation of Arctic soils in the Land Surface Model (LSM): the importance of mosses. J Clim 14:3324–3335

    Article  Google Scholar 

  • Bonan GB (1996) A land surface model (LSM version 1.0) for ecological, hydrological, and atmospheric studies: technical description and user’s guide. NCAR Tech. Note TN-417+STR, National Center for Atmospheric Research, Boulder

  • Bunn AG, Goetz SJ, Kimball JS, Zhang K (2007) Northern high-latitude ecosystems respond to climate change. Eos Trans Amer Geophys Union. doi:10.1029/2007EO340001

  • Chapman WL, Walsh JE (2007) Simulations of Arctic temperature and pressure by global coupled models. J Clim 20:609–632

    Article  Google Scholar 

  • Christensen JH, Christensen OB, Lopez P, van Meijgaard E, Botzet M (1996) The HIRHAM4 regional atmospheric climate model. DMI Sci. Rep. 96–4, Dan. Meteorol. Inst., Copenhagen

  • Cook BI, Bonan GB, Levis S, Epstein HE (2008) Rapid vegetation responses and feedbacks amplify climate model response to snow cover changes. Clim Dyn 30:391–406

    Google Scholar 

  • Crucifix M, Betts RA, Cox PM (2005) Vegetation and climate variability: a GCM modelling study. Clim Dyn 24:457–467

    Article  Google Scholar 

  • Francis JA, White DM, Cassano JJ, Gutowski WJ Jr, Hinzman LD, Holland MM, Steele MA, Vörösmarty CJ (2009) An arctic hydrologic system in transition: feedbacks and impacts on terrestrial, marine, and human life. J Geophys Res. doi:10.1029/2008JG000902

  • Göttel H, Alexander J, Keup-Thiel E, Rechid D, Hagemann S, Blome T, Wolf A, Jacob D (2008) Influence of changed vegetations fields on regional climate simulations in the Barents Sea Region. Clim Change 87:35–50

    Article  Google Scholar 

  • Gustafsson N (1993) HIRLAM2 final report, HIRLAM Tech. Rep. 9, Swed. Meteorol. And Hydrol. Inst., Norrköping

  • Hagemann S (2002) An improved land surface parameter dataset for global and regional climate models. MPI Report No. 336, Max-Planck-Institute for Meteorology, Hamburg

  • IPCC (2007) Climate change 2007: the physical scientific basis. In: Solomon S, Qin D, Manning M (eds) Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Lawrence DM, Slater AG (2008) Incorporating organic soil into a global climate model. Clim Dyn 30:145–160

    Article  Google Scholar 

  • Luo L et al (2003) Effects of frozen soil on soil temperature, spring infiltration, and runoff: results from the PILPS 2(d) experiment at Valdai, Russia. J Hydrol Meteorol 4:334–351

    Google Scholar 

  • Marsland SJ, Haak H, Jungclaus JH, Latif M, Roeske F (2003) The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Model 5:91–127

    Article  Google Scholar 

  • Matthes H, Rinke A, Dethloff K (2009) Variability of observed temperature-derived climate indices in the Arctic. Global Planet Change 69:214–224

    Article  Google Scholar 

  • McGuire AD, Walsh J, Kimball JS, Clein JS, Euskirchen SE, Drobot S, Herzfeld UC, Maslanik J, Lammers RB, Rawlins MA, Vorosmarty CJ, Rupp TS, Wu W, Calef M (2008) The Western Arctic Linkage Experiment (WALE): overview and synthesis. Earth Interact 12:1–13

    Article  Google Scholar 

  • Miller PA, Wania R, Biasi C, Crill P, Friborg T, Johansson T, Kiepe I, Kuhry P, Martikainen P, Patova E, Repo M, Rinke A, Sivkov M, Susiluoto S, Sykes M, Wolf A, Virtanen T. Present-day and future carbon fluxes from Northwestern Russian Tundra—an integrative approach (in preparation)

  • Rinke A, Dethloff K (2008) Simulated circum-Arctic climate changes by the end of the 21st century. Global Planet Change 62:173–186

    Article  Google Scholar 

  • Rinke A, Kuhry P, Dethloff K (2008) Importance of a soil organic layer for Arctic climate: a sensitivity study with an Arctic RCM. Geophys Res Lett. doi:10.1029/2008GL034052

  • Rinke A, Matthes H, Dethloff K (2010) Regional characteristics of Arctic temperature variability: comparison of observations with regional climate simulations. Clim Res 41(3):177–192

    Article  Google Scholar 

  • Roeckner E, Arpe K, Bengtsson L, Christoph M, Claussen M, D’umenil L, Esch M, Giorgetta M, Schlese U, Schulzweida U (1996) The atmospheric general circulation model ECHAM-4: Model description and simulation of present-day climate. MPI Rep. 218, Max Planck Inst. for Meteorol. Hamburg, Hamburg

  • Roeckner E, Bäuml G, Bonaventura L, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kirchner I, Kornblueh L, Manzini E, Rhodin A, Schlese U, Schulzweida U, Tompkins A (2003) The atmospheric general circulation model ECHAM5. Part I: model description. MPI Rep. 349, Max Planck Inst. for Meteorol. Hamburg, Hamburg

  • Saha SK, Rinke A, Dethloff K, Kuhry P (2006) The influence of a complex land surface scheme on Arctic climate simulations. J Geophys Res. doi:10.1029/2006JD007188

  • Smith B, Prentice IC, Sykes MT (2001) Representation of vegetation dynamics in the modeling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecol Biogeogr 10:621–637

    Article  Google Scholar 

  • Sturm M, Douglas T (2005) Changing snow cover and shrub conditions effect albedo with global implications. J Geophys Res. doi:10.1029/2005JG000013

  • Tape K, Sturm M, Racine C (2006) The evidence for shrub expansion in Northern Alaska and the Pan-Arctic. Global Change Biol 12:686–702

    Article  Google Scholar 

  • Thompson C, Beringer J, Chapin FS III, McGuire AD (2004) Structural complexity and land-surface energy exchange along a gradient from arctic tundra to boreal forest. J Veg Sci 15:397–406

    Article  Google Scholar 

  • Verbyla D (2008) The greening and browning of Alaska based on 1982–2003 satellite data. Global Ecol Biogeogr 17:547–555

    Article  Google Scholar 

  • Viterbo P, Beljaars A, Mahfouf JF, Teixeira J (1999) The representation of soil moisture freezing and its impact on the stable boundary layer. Q J R Meteorol Soc 125:1–30

    Article  Google Scholar 

  • Wania, R, Ross, I, Prentice IC (2009) Integrating peatlands and permafrost into a dynamic global vegetation model: I. Evaluation and sensitivity of physical land surface processes. Global Biogeochemical Cycles 23:GB3014. doi:10.1029/2008GB003412

  • Wolf A, Callaghan TV, Larson K (2008) Future changes in vegetation and ecosystem function of the Barents Region. Clim Chang 87:51–73. doi:10.1007/s10584-007-9342-4

    Article  Google Scholar 

  • Yamazaki T, Yabuki H, Ishii Y, Ohta T, Ohata T (2004) Water and energy exchanges at forests and a grassland in Eastern Siberia evaluated using a one-dimensional land surface model. J Hydrometeor 5:504–515

    Article  Google Scholar 

Download references

Acknowledgments

This research has been funded by the European Union project CARBO-North. We are grateful to Ines Hebestadt for programming support. We also thank Rita Wania for support with the LPJ-GUESS model.

We thank two anonymous reviewers for their contributions and suggestions which helped to improve the paper.

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Correspondence to Heidrun Matthes.

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Matthes, H., Rinke, A., Miller, P.A. et al. Sensitivity of high-resolution Arctic regional climate model projections to different implementations of land surface processes. Climatic Change 111, 197–214 (2012). https://doi.org/10.1007/s10584-011-0138-1

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  • DOI: https://doi.org/10.1007/s10584-011-0138-1

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