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    Original Research Papers

    The surface energy, water, carbon flux and their intercorrelated seasonality in a global climate-vegetation coupled model

    Authors:

    Li Dan ,

    START Regional Center for Temperate East Asia and Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, CN
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    Jinjun Ji

    START Regional Center for Temperate East Asia and Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, CN
    X close

    Abstract

    The sensible and latent heat fluxes, representatives of the physical exchange processes of energy and water between land and air, are the two crucial variables controlling the surface energy partitioning related to temperature and humidity. The net primary production (NPP), the major carbon flux exchange between vegetation and atmosphere, is of great importance for the terrestrial ecosystem carbon cycle. The fluxes are simulated by a two-way coupled model, Atmosphere-Vegetation Interaction Model-Global Ocean-Atmosphere-Land System Model (AVIM-GOALS) in which the surface physical and physiological processes are coupled with general circulation model (GCM), and the global spatial and temporal variation of the fluxes is studied. The simulated terrestrial surface physical fluxes are consistent with the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA40) in the global distribution, but the magnitudes are generally 20–40 W/m2 underestimated. The annual NPP agrees well with the International Geosphere Biosphere Programme (IGBP) NPP data except for the lower value in northern high latitudes. The surface physical fluxes, leaf area index (LAI) and NPP of the global mid-latitudes, especially between 30 °N–50 °N, show great variation in annual oscillation amplitudes. And all physical and biological fields in northern mid-latitudes have the largest seasonality with a high statistical significance of 99.9%. The seasonality of surface physical fluxes, LAI and NPP are highly correlated with each other. The meridional three-peak pattern of seasonal change emerges in northern mid-latitudes, which indicates the interaction of topographical gradient variation of surface fluxes and vegetation phenology on these three latitudinal belts.

    How to Cite: Dan, L. and Ji, J., 2007. The surface energy, water, carbon flux and their intercorrelated seasonality in a global climate-vegetation coupled model. Tellus B: Chemical and Physical Meteorology, 59(3), pp.425–438. DOI: http://doi.org/10.1111/j.1600-0889.2007.00274.x
      Published on 01 Jan 2007
    Peer Reviewed
     CC BY 4.0
     Accepted on 24 Jan 2007            Submitted on 29 Apr 2006

    References

    1. Barford , C. C. , Wofsy , S. C. , Goulden , M. L. , Munger , J. W. , Pyle , E. H. and co-authors 2001. Factors controlling long- and short-term sequestration of atmospheric CO2 in a mid-latitude forest . Science 294 , 1688– 1691 .  

    2. Barrett , D. J . 2002 . Steady state turnover time of carbon in the Aus-tralian terrestrial biosphere . Global Biogeochem. Cycles 16 , 1108 , https://doi.org/10.1029/2002GB001860 .  

    3. Cao , M. K. , Prince , S. D. , Tao , B. , Small , J. and Li , K. R . 2005 . Regional pattern and interannual variations in global terrestrial carbon uptake in response to changes in climate and atmospheric CO2 . Tellus 57B , 210 – 217 .  

    4. Chen , F. and Dudhia , J . 2001 . Coupling an advanced land surface—hydrology model with the Penn State—NCAR MM5 modeling system Part I: model implementation and sensitivity. Mon . Weather Re v . 129 , 569 – 585 .  

    5. Chen , T. H. , Henderson-sellers , A. , Milly , P. C. D. and co-authors. 1997. Cabauw experimental results from the Project for Intercom-parison of Land-Surface Parametrization Schemes. J. Clim . 10 , 1194 – 1215 .  

    6. Collatz , G. , Ribas-Carbo , M. and Ball , J. A . 1992 . Coupled photosynthesis-stomatal conductance model for leaves of C4 plants . Australian J. Plant PhysioL 19 , 519 – 538 .  

    7. 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 .  

    8. Coquard , J. , Buffy , P. B. , Taylor , K. E. and Iorio , J. P . 2004 . Present and future surface climate in the western USA as simulated by 15 global climate models . Clim. Dyn . 23 , 455 – 472 .  

    9. Cramer , W. , Kicklighter , D. W. , Bondeau , A. , Moore , B. , Churkina , G. and co-authors and the participants of the Potsdam NPP Model Intercomparison. 1999.  

    10. Comparing global models of terrestrial net primary productivity (NPP): overview and key results . Global Change Biol. 5(Suppl. 1), 1 – 15.  

    11. Dan , L. , Ji , J. J. and Li , Y. P . 2005 . Climatic and biological simulations in a two-way coupled atmosphere-biosphere model (CABM) . Glob. Planet. Change 47 , 153 – 169 .  

    12. Elsner , J. B. and Tsonis , A. L. A . 1994 . Empirically derived climate predictability over the extratropical northern hemisphere . Nonlinear Process. Geophys . 1 , 41 – 44 .  

    13. Farquhar , G. D. , Caemmerer , S. von and Berry , J. A . 1980 . A biochemical model of photosynthetic CO2 assimilation in leaves of C3 plants . Planta 149 , 78 – 90 .  

    14. Farquhar , G. D. and Sharley , T. D . 1982 . Stomatal conductance and photosynthesis . Annu. Rev. Plant PhysioL 33 , 317 – 345 .  

    15. Field , C. B . 1983 . Allocating leaf nitrogen for the maximization of carbon gain: Leaf age as a control on the allocation program . Oecologia 56 , 341 – 347 .  

    16. Frankignoul , C. , Kestenare , E. , Botzet , M. , Carril , A. E , Drange , H. and co-authors. 2004. An intercomparison between the surface heat flux feedback in five coupled models, COADS and the NCEP reanalysis. Clim. Dyn. 22, 373 – 388.  

    17. Friedlingstein , R , Bopp , L. , Ciais , P. , Dufresne , J. , Fairhead , L. and co-authors. 2001. Positive feedback between future climate change and the carbon cycle. Geophys. Res. Lett., 28, 1543 – 1546.  

    18. Gao , G. D. and Lu , Y. R . 1981. Climatological atlas of China. China Agriculture Publishing House, 1-183 (in Chinese).  

    19. Govindasamy , B. , Thompson , S. , Mirin , A. , Wickett , M. , Caldeira , K. and co-authors. 2005. Increase of carbon cycle feedback with climate sensitivity: results from a coupled climate and carbon cycle model. Tellus 57B, 153 – 163.  

    20. Hagemann , S. , Botzet , M. , Dumenil , L. and Machenhauer , B . 1999 . Derivation of global GCM boundary conditions from I KM land use satellite data . Max Planck Institute for Meteorology (MPI) Report No . 289 , 1 – 34 .  

    21. Hagemann , S . 2002 . An improved land surface parameter dataset for global and regional climate models . Max Planck Institute for Meteo-rology (MPI) Report No . 336 , 1 – 21 .  

    22. Hunt , E. R. , Piper , S. C. , Nemani , R. , Keeling , C. D. , Otto , R. D. and co-authors. 1996. Global net carbon exchange and intra-annual at-mospheric CO2 concentrations predicted by an ecosystem process model and three-dimensional atmospheric transport model. Global Biogeochem. Cycles 10, 431 – 456.  

    23. Imhoff , M. L. , Bounoua , L. , Ricketts , T. , Loucks , C. , Harriss , R. and co-authors. 2004. Global patterns in human consumption of net primary production. Nature 429, 870 – 873.  

    24. Jacobs , C. M. J. , van den Hurk , B. J. J. M. and de Bruin , H. A. R . 1996 . Stomatal behaviour and photosynthetic rate of unstressed grapevines in semi-arid conditions . Agric. Forest MeteoroL 80 , 111 – 134 .  

    25. Ji , J. J . 1995 . A climate-vegetation interaction model: simulating physical and biological processes at the surface . J. Biogeogr 22 , 445 – 451 .  

    26. Ji , J. J. , and Hu , Y. C . 1989 . A simple land surface process model for use in climate studies . Acta MeteoroL Sinica 3 , 344 – 353 .  

    27. Ji , J. J. and Yu , L . 1999. A simulation study of coupled feedback mech-anism between physical and biogeochemical processes at the surface. Chinese J Atmos. Sci. 23,439-448 (in Chinese).  

    28. Ji , J. J. , Huang , M. and Liu , Q . 2005. Modeling studies of response mechanism of steppe productivity to climate change in middle latitude semiarid regions in China. Acta MeteoroL Sinica 63, 257-266 (in Chinese).  

    29. Koster , R. D. , Dirmeyer , P. A. , Hahmann , A. N. , Ijpelaar , R. , Tyahla , L. and co-authors. 2002. Comparing the degree of land—atmosphere interaction in four atmospheric general circulation models. J. Hydrom-eteoroL 3, 363 – 375.  

    30. Li , F. S. , Kang , S. Z. and Zhang , F. C . 2003. Effects of CO2 enrichment, nitrogen and water on photosynthesis, evapotranspiration and water use efficiency. Chinese If Applied Ecol. 14, 387-393 (in Chinese).  

    31. Li , Y. P. and Ji , J. J. 2001. Model estimates of global carbon flux between vegetation and the atmosphere. Advance Atmos. Sci. 18, 807 – 818.  

    32. Liu , Y. M. , Wu , G. X. , Liu , H. and Liu , P . 2001 . Condensation heating of the Asian summer monsoon and the subtropical anticyclone in the Eastern Hemisphere . Clim. Dyn . 19 , 327 – 338 .  

    33. Liu , Y. M. , Wu , G. X. and Ren , R. C . 2004 . Relationship between the subtropical anticyclone and diabatic heating . J. Clim . 17 , 682 – 698 .  

    34. Lu , J. H. and Ji , J. J . 2002a. A simulation study of atmosphere-vegetation interactions over the Tibetan Plateau, Part I: physical flux and param-eters. Chinese J. Atmos. Sci. 26, 111-126 (in Chinese).  

    35. Lu , J. H. and Ji , J. J . 2002b. A simulation study of atmosphere-vegetation interactions over the Tibetan Plateau, Part II: net primary productivity and leaf area index. Chinese J. Atmos. Sci. 26, 254-262 (in Chinese).  

    36. Lu , J. H. and Ji , J. J . 2006 . A simulation and mechanism of long-term variations at land surface over arid/semi-arid area in north China . J. Geophys. Res . 111 , D09306 , https://doi.org/10.1029/2005JDO06252 .  

    37. Myneni , R. B. Dong , J. , Tucker , C. J. , Kaufmann , R. K. , Kauppi , P. E. and co-authors. 2001. A large carbon sink in the woody biomass of northern forest. Proc. Natl. Acad. Sci. 98, 4784 – 14789.  

    38. Olsen , S. C. and Randerson , J. T . 2004 . Differences between surface and column atmospheric CO2 and implications for carbon cycle research . J. Geophys. Res . 109 , D02301 , https://doi.org/10.1029/2003JD003968 .  

    39. Phillips , N. A . 1973. Principles of large scale numerical weather predic-tion. In: Dynamic Meteorology (ed. P. Morel ). D. Reidel Publishing Comp, Dordrecht, Holland, pp 96.  

    40. Pitman , A. J. , Henderson-seller , A. , Desborough , C. E. , Yang , Z. L. , Abramopoulos , F. and other co-authos. 1999 . Key results and implications from phase 1(c) of the Project for Intercompari-son of Land-surface Parametrization Schemes . Clim. Dyn . 15 , 673 – 684 .  

    41. Riedo , M. , Gyalistras , D. , Fischlin , A. and Fuhrer , J . 1999 . Using an ecosystem model linked to GCM-derived local weather scenarios to analyse effects of climate change ande levated CO2 on dry matter pro-duction and partitioning, and water use in temperate managed grass-lands . Global Change Biol . 5 , 213 – 223 .  

    42. Schulze , E. D. , Kelliher , F. M. , Ko-rner , C. , Lloyd , J. and Leuning , R . 1994 . Relationships among maximum stomatal conductance, ecosys-tem surface conductance, carbon assimilation rate, and plant nitrogen nutrition: A global ecology scaling exercise . Annual Rev. EcoL Sys-tematics 25 , 629 – 660 .  

    43. Sellers , P. J. , Dickinson , R. E. , Randall , D. A. , Betts , A. K. , Hall , F. G. and co-authors. 1997. Modelling the exchanges of energy, water and carbon between the continents and the atmosphere. Science 275, 502 – 509.  

    44. Shao , Y. and Henderson-Sellers , A . 1996 . Modeling soil moisture: a Project for Intercomparison of Land Surface Parametrization Schemes Phase2 (b) . J. Geophys. Res . 101 , 7227 – 7250 .  

    45. Shukla , J. and Mintz , Y . 1982 . Influence of land-surface evapotranspira-tion on the earth's climate . Science 215 , 1498 – 1501 .  

    46. Simmons , A. J. and Gibson , J. K . 2000. The ERA-40 project plan. ERA-40 Project Report Series 1, ECMWF, Shinfield Park, Reading, United Kingdom, pp. 63.  

    47. Sun , H. Y. , Liu , C. M. , Zhang , X. Y. , Shen , Y. J. and Zhang , Y. Q . 2006 . Effects of irrigation on water balance, yield and WUE of winter wheat in the North China Plain . Agric. Water Manage . 85 , 211 – 218 .  

    48. Varejao-Silva , M. A. , Franchito , S. H. and Rao , V. B . 1998. A coupled biosphere—atmosphere climate model suitable for studies of climatic change due to land surface alterations. J. Clim. 11 , 1749 – 1767. Wang, B., Liu, H. and Shi, G. Y. 2000. In: Chapter 3: Radiation and cloud scheme, IAP Global Ocean Atmosphere-Land System Model (eds. X. H. Zhang et al.). Science Press , Beijing, New York , pp. 28 – 49.  

    49. Woodward , F. I. , Smith , T. M. and Emanuel , W. R. 1995. A global land primary productivity and phytogeography model. Global Biogeochem. Cycles 9, 471 – 490.  

    50. Wu , G. X. , Zhang , X. H. , Liu , H. , Yu , Y. Q. , Jin , X. Z. and co-authors. 1997. Global ocean-atmosphere-land system model of LASG (GOALS/LASG) and its performance in simulation study. Q.J. Appl Meteorol. 8, 15-28 (in Chinese).  

    51. Xue , Y. , Juang , H. M. H. , Li , W. P. , Prince , S. , DeFries , R. and co-authors. 2004. Role of land surface processes in monsoon devel-opment: East Asia and West Africa J. Geophy. Res. 109, D03105, https://doi.org/10.1029/2003JD003556 .  

    52. Yu , J. Y. and Mechoso , C. R . 1999. A discussion on the errors in the surface heat fluxes simulated by a coupled GCM. J. Clim . 12 , 416 - 426 .  

    53. Zeng , Q. C. 1963. Characteristic parameters and dynamical equations of atmospheric motions. Acta Meteorol. Sinica , 33 , 472 - 498 (in Chinese).  

    54. Zhang , T. , Wu , G. X. and Guo , Y. F . 2002. Energy budget bias in global coupled ocean-atmosphere-land model. Acta Meteorol. Sinica 60, 278-289 (in Chinese).  

    55. Zheng , D. L. , Prince , S. and Wright , R . 2003 . Terrestrial net primary production estimates for 0.5o grid cells from field observations- a con-tribution to global biogeochemical modelling . Global Change Biol . 9 , 46 – 64 .  

    56. Zhuang , Q. , Mguire , A. D. , Melillo , J. M. , Clein , J. S. , Dargaville , R. J. and co-authors. 2003. Carbon cycling in extratropical terrestrial ecosystems of the Northern Hemisphere during the 20th century: a modeling analysis of the influences of soil thermal dynamics. Tellus 55B, 751 – 776.  

    57. Zobler , L . 1986. A world soil file for global climate modeling. NASA Tech. Memo. 87802, NASA Goddard Institute for Space Studies, New York, USA, 1 – 33.  

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