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ENVIROMIS -2006, 1-8 July 2006, Tomsk, Russia Modeling of ecosystem dynamics and carbon cycling with coupled climate model - LPJ-DGV model. . Krupchatnikoff V. ( (ICMMG SB RAS/SibRHMRI, Novosibirsk, e-mail: vkrup@ommfao1.sscc.ru)


  1. ENVIROMIS -2006, 1-8 July 2006, Tomsk, Russia Modeling of ecosystem dynamics and carbon cycling with coupled climate model - LPJ-DGV model. . Krupchatnikoff V. ( (ICMMG SB RAS/SibRHMRI, Novosibirsk, e-mail: vkrup@ommfao1.sscc.ru)

  2. ACKNOWLEDGMENTS I would like to thank S. Sitch (PIK, Potsdam) who provide code of LPJ model. I am grateful to E. Volodin for providing the results of run with CM3.0 model. Finally, this effort is supported by RFBR grant number 05-05-64989

  3. Introduction Climate models are powerful tools for assessing future climate and n interpreting observations. Model simulations can be diagnosed to assess contributing causes of particular phenomena. Climate is not controllable system. The models are only available tools for forecasting plausible climates in years and decades ahead. The biosphere plays pivotal role in the climate system. Land ecosystems are a dynamic component of the global carbon and water cycle. More than one third of CO2 in the atmosphere is exchange annually with the land biosphere. Land ecosystem processes also control exchange of energy and momentum between atmosphere and surface. We must better understand the global evolution land ecosystem as main agent in Earth Climate System dynamics. The need has been driving the development of dynamic global vegetation models. Lund-Potsdam-Jena dynamic global vegetation model coupled with INM/RAS climate model is described in this presentation.

  4. Model Description CGCM/INM RAS 5x4 horizontal resolution and 21-level vertical n resolution LSM/ICMMG SB RAS - biophysical and biochemical surface model n Lund-Potsdam-Jena dynamic global vegetation model (line-off) n

  5. Coupled atmospheric - ocean model (INM/RAS): Terrain-following vertical coordinate (21 σ -levels) n Semi-implicit formulation of integration in time n Energy conservation finite-difference schemes (5x 4) (Arakawa-Lamb,1981) n Convection (deep, middle, shallow) n Radiation (H2O, CO2, O3, CH4, N2O, O2; 18 spectral bands for SR and 10 spectral n bands for LR) PBL (5 σ -levels) n Gravity wave drag over irregular terrain n

  6. Land surface model(ICM&MG/SB RAS): Vegetation composition, structure n Radiative fluxes n Momentum and energy fluxes n Vegetation and ground temperature n Soil and lake temperature n Surface hydrology (snow, runoff, soil water, canopy water n etc.) CO2 emissions from terrestrial vegetation n CH4 emissions from natural wetlands n

  7. Leaf area index

  8. Grid structure in land surface model

  9. Global Net CO2 fluxes(mmol CO2/m^2 c), (coupled simulation)

  10. Lund-Potsdam-Jena dynamic global vegetation model (S. Sitch et al., //Global ChangeBiology,(2003)9,161-185) Plant functional types (10 PFT) n Annual vegetation and carbon dynamics n Penology n Production n - water availability - photosynthesis - respiration - reproduction - allocation - mortality Input data (monthly mean temperature, precipitation and n cloud cover)

  11. LPJ dynamic global vegetation model • is able to reproduce carbon and water exchange with atmosphere on seasonal time scale; • is able to simulate spatial distributions of soil, litter and vegetation pools and NPP, runoff within their accepted ranges and agree with observed patterns • is able to reproduce global vegetation distribution in general agreement with satellite derived maps of phenology and leaf type • is able to evaluate seasonal cycle of CO2

  12. Plant functional type

  13. LPJ-simulated dominant PFT

  14. Model were driven by CM3.0(INM) (scenario A2)

  15. A2 Storyline and Scenario Family The A2 scenario family represents a differentiated world . Compared to the A1 storyline it is characterized by lower trade flows, relatively slow capital stock turnover, and slower technological change. The A2 world "consolidates" into a series of economic regions. Self-reliance in terms of resources and less emphasis on economic, social, and cultural interactions between regions are characteristic for this future. Economic growth is uneven and the income gap between now-industrialized and developing parts of the world does not narrow, unlike in the A1 and B1 scenario families . The A2 world has less international cooperation than the A1 or B1 worlds. People, ideas, and capital are less mobile so that technology diffuses more slowly than in the other scenario families. High-income but resource-poor regions shift toward advanced post-fossil technologies (renewables or nuclear), while low-income resource-rich regions generally rely on older fossil technologies. . As in other SRES storylines, the intention in this storyline is not to imply that the underlying dynamics of A2 are either good or bad.

  16. INM-simulation cloudiness, 2010, dcld = cld(2040) – cld(2010) and dcld = cld(2080) – cld(2040 )

  17. INM-simulation of temperature 2010, dTemp = T(2040) - T(2010) and dTemp = T(2080) – T(2040)

  18. INM-simulation of precipitation 2010, dPrec = Prec(2040) - Prec(2010) and dPrec = Prec(2080) – Prec(2040)

  19. Increasing of CO2 concentration (ppm) according to scenario A2

  20. Table of PFT • TrBE - tropical broad-leaved evergreen • TrBR - tropical broad-leaved raingreen • TeNE – temperate needle – leaved evergreen • TeBE - temperate broad – leaved evergreen • TeBS - temperate broad – leaved summergreen • BoNE – boreal needle – leaved evergreen • BoNS - boreal needle – leaved summergreen • BoBS - boreal broad – leaved summergreen • TeH - temperate herbaceous • TrH - tropical herbaceous

  21. LPJ/INM(RAS)-simulation (scenario A2) Temperate(TeBS) (black), Boreal(BoNE) (green) forest dynamics for grid cell(60E,60N)

  22. LPJ/INM(RAS)-simulation (scenario A2) Boreal(BoBS) forest (green) and Temperate(TeH) herbaceous (yellow) dynamics for grid cell(60E,60N)

  23. LPJ/INM(RAS)-simulation (scenario A2) of carbon pools, (60E,60N) vegc – green, soilc – black, litterc - yellow

  24. LPJ/INM(RAS)-simulation (scenario A2) flux C due to fire(gC/m^2),(60E,60N)

  25. LPJ/INM(RAS)-simulation (scenario A2) of carbon pools(left) and flux C due to fire(gC/m^2),(20E,40N)

  26. LPJ/INM(RAS)-simulation (scenario A2) Temperate(TeNE,TeBE, TeBS), forest and Temperate(TeH),Tropical(TrH) herbaceous dynamics for grid cell(20E,40N)

  27. LPJ/INM(RAS)-simulation (scenario A2) of carbon pools (g C/m^2), (90E,60N)

  28. LPJ/INM(RAS)-simulation (scenario A2) flux C due to fire(gC/m^2),(90E,60N)

  29. LPJ/INM(RAS)-simulation (scenario A2) Annual grid cell NPP, NEP = Firec + RH - NPP, RH(gC/m^2/month) (90E,60N)

  30. LPJ/INM(RAS)-simulation (scenario A2) Boreal (BoNE, BoBS) forest dynamics for grid cell(90E,60N)

  31. LPJ/INM(RAS)-simulation (scenario A2) Temperate(TeH) herbaceous dynamics for grid cell(90E,60N)

  32. Conclusion LPJ model includes • explicit representation of vegetation structure, dynamics and competition between PFT over greed cell, soil biogeochemistry; • LPJ run of modern climate are in agreement with other models; The study showed that simulated PFT after 2050 year (at ~ 500ppm) • begin to lose stability and reaches new balance.

  33. “Those who have knowledge, do not predict, Those who predict, do not have knowledge.” (Lao Tzu)

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