GMD Geoscientific Model Development GMD Geosci. Model Dev. 1991-9603 Copernicus Publications Göttingen, Germany 10.5194/gmd-7-1829-2014 Optimization of a prognostic biosphere model for terrestrial biomass and atmospheric CO<sub>2</sub> variability Saito M. 1 2 Ito A. https://orcid.org/0000-0001-5265-0791 1 Maksyutov S. https://orcid.org/0000-0002-1200-9577 1 Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan previously at: Laboratoire des Sciences du Climat et de l'Environnement, UMR8212, CEA-CNRS-UVSQ, 91191 Gif sur Yvette, France 29 08 2014 7 4 1829 1840 Copyright: © 2014 M. Saito et al. 2014 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://gmd.copernicus.org/articles/7/1829/2014/gmd-7-1829-2014.html The full text article is available as a PDF file from https://gmd.copernicus.org/articles/7/1829/2014/gmd-7-1829-2014.pdf

This study investigates the capacity of a prognostic biosphere model to simulate global variability in atmospheric CO<sub>2</sub> concentrations and vegetation carbon dynamics under current environmental conditions. Global data sets of atmospheric CO<sub>2</sub> concentrations, above-ground biomass (AGB), and net primary productivity (NPP) in terrestrial vegetation were assimilated into the biosphere model using an inverse modeling method combined with an atmospheric transport model. In this process, the optimal physiological parameters of the biosphere model were estimated by minimizing the misfit between observed and modeled values, and parameters were generated to characterize various biome types. Results obtained using the model with the optimized parameters correspond to the observed seasonal variations in CO<sub>2</sub> concentration and their annual amplitudes in both the Northern and Southern Hemispheres. In simulating the mean annual AGB and NPP, the model shows improvements in estimating the mean magnitudes and probability distributions for each biome, as compared with results obtained using prior simulation parameters. However, the model is less efficient in its simulation of AGB for forest type biomes. This misfit suggests that more accurate values of input parameters, specifically, grid mean AGB values and seasonal variabilities in physiological parameters, are required to improve the performance of the simulation model.

 References Barrett, D. J.: Steady state turnover time of carbon in the Australian terrestrial biosphere, Global Biogeochem. Cy., 16, 1108, <a href="http://dx.doi.org/10.1029/2002GB001860">https://doi.org/10.1029/2002GB001860</a>, 2002. Berg, B. and Laskowski, R.: Litter decomposition: a guide to carbon and nutrient turnover, Adv. Ecol. Res., 38, 1–423, 2006. Berry, J. and Björkman, O.: Photosynthetic response and adaptation to temperature in higher plants, Annu. Rev. Plant Phys., 31, 491–543, 1980. Bousquet, P., Peylin, P., Ciais, P., Le Quéré, C., Friedlingstein, P., and Tans, P. P.: Regional Changes in Carbon Dioxide Fluxes of Land and Oceans Since 1980, Science, 290, 1342–1346, 2000. Braswell, B. H., Sacks, W. J., Linder, E., and Schimel, D. S.: Estimating diurnal to annual ecosystem parameters by synthesis of a carbon flux model with eddy covariance net ecosystem exchange observations, Glob. Change Biol., 11, 335–355, 2005. Brooks, A. and Farquhar, G. D.: Effect of temperature on the CO<sub>2</sub>/O<sub>2</sub> specificity of ribulose-1,5-bisphosphate carboxylase/oxygenase and the rate of respiration in the light, Planta, 165, 397–406, 1985. Callaway, R. M., DeLucia, E. H., and Schlesinger, W. H.: Biomass allocation of montane and desert ponderosa pine: an analog for response to climate change, Ecology, 75, 1474–1481, 1994. Carvalhais, N., Reichstein, M., Ciais, P., Collatz, G. J., Mahecha, M. D., Montagnani, L., Papale, D., Rambal, S., and Seixas, J.: Identification of vegetation and soil carbon pools out of equilibrium in a process model via eddy covariance and biometric constraints, Global Change Biol., 16, 2813–2829, 2010. Ciais, P., Tans, P. P., Trolier, M., White, J. W. C., and Francey, R. J.: A Large Northern Hemisphere Terrestrial CO}<sub>2</sub> Sink Indicated by the <sup>13</sup>C/<sup>12</sup>C Ratio of Atmospheric {CO<sub>2</sub>, Science, 269, 1098–1102, 1995. Cramer, W., Kicklighter, D. W., Bondeau, A., Moor III, B., Churkina, G., Nemry, B., Ruimy, A., Schloss, A. L., and the participants of the Potsdam NPP Model intercomparison: Comparing global models of terrestrial net primary productivity (NPP): overview and key results, Global Change Biol., 5, 1–15, 1999. Enting, I. G., Trudinger, C. M., and Francey, R. J.: A synthesis inversion of the concentration and δ<sup>13</sup>C of atmospheric CO<sub>2</sub>, Tellus, 47, 35–52, 1995. Field, C. B., Behrenfeld, M. J., Randerson, J. T., and Falkowski, P.: Primary Production of the Biosphere: Integrating Terrestrial and Oceanic Components, Science, 281, 237–240, 1998. Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V., Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C., Joos, F., Kato, T., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D., Raddatz, T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K.-G., Schnur, R., Strassmann, K., Weaver, A. J., Yoshikawa, C., and Zeng, N.: Climate-Carbon Cycle Feedback Analysis: Results from the C4MIP Model Intercomparison, J. Climate, 19, 3337–3353, 2006. GLOBALVIEW-CO<sub>2</sub>: Cooperative Atmospheric Data Integration Project–Carbon Dioxide, NOAA ESRL, 2010. Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Baker, D., Bousquet, P., Bruhwiler, L., Chen, Y. H., Ciaisand, P., Fan, S., Fung, I. Y., Gloor, M., Heimann, M., Higuchi, K., John, J., Maki, T., Maksyutov, S., Masarie, K., Peylin, P., Prather, M., Pak, B. C., Randerson, J., Sarmiento, J., Taguchi, S., Takahashi, T., and Yuen, C. W.: Towards robust regional estimates of CO<sub>2</sub> sources and sinks using atmospheric transport models, Nature, 415, 626–630, 2002. Howell, J. F. and Mahrt, L.: An adaptive decomposition: Application to turbulence, in: Wavelets in Geophysics, edited by: Foufoula-Georgiou, E. and Kumar, P., Vol. 1, 107–128, Academic Press, 1994. Ichii, K., Suzuki, T., Kato, T., Ito, A., Hajima, T., Ueyama, M., Sasai, T., Hirata, R., Saigusa, N., Ohtani, Y., and Takagi, K.: Multi-model analysis of terrestrial carbon cycles in Japan: limitations and implications of model calibration using eddy flux observations, Biogeosciences, 7, 2061–2080, <a href="http://dx.doi.org/10.5194/bg-7-2061-2010">https://doi.org/10.5194/bg-7-2061-2010</a>, 2010. IPCC: Climate Change 2007: The Physical Science Basis, Cambridge University Press, 2007. Ito, A.: Changing ecophysiological processes and carbon budget in East Asian ecosystems under near-future changes in climate: Implications for long-term monitoring from a process-based model, J. Plant Res., 123, 577–588, 2010. Ito, A. and Oikawa, T.: A simulation model of the carbon cycle in land ecosystems (Sim-CYCLE): a description based on dry-matter production theory and plot-scale validation, Ecol. Model., 151, 143–176, 2002. Jung, M., Henkel, K., Herold, M., and Churkina, G.: Exploiting synergies of global land cover products for carbon cycle modeling, Remote Sens. Environ., 101, 534–553, 2006. Jung, M., Vetter, M., Herold, M., Churkina, G., Reichstein, M., Zaehle, S., Ciais, P., Viovy, N., Bondeau, A., Chen, Y., Trusilova, K., Feser, F., and Heimann, M.: Uncertainties of modeling gross primary productivity over Europe: A systematic study on the effects of using different drivers and terrestrial biosphere models, Global Biogeochem. Cy., 21, GB4021, <a href="http://dx.doi.org/10.1029/2006GB002915">https://doi.org/10.1029/2006GB002915</a>, 2007. Kaminski, T., Knorr, W., Rayner, P. J., and Heimann, M.: Assimilating atmospheric data into a terrestrial biosphere model: A case study of the seasonal cycle, Global Biogeochem. Cy., 16, 1066, <a href="http://dx.doi.org/10.1029/2001GB001463">https://doi.org/10.1029/2001GB001463</a>, 2002. Kindermann, G. E., McCallum, I., Fritz, S., and Obersteiner, M.: A global forest growing stock, biomass and carbon map based on FAO statistics, Silva Fennica, 42, 387–396, 2008. Kuroiwa, S.: Dry matter production by plants, Modern Biology, 9, 71–100, 1966. Law, R. M., Rayner, P. J., Denning, A. S., Erickson, D., Fung, I. Y., Heimann, M., Piper, S. C., Ramonet, M., Taguchi, S., Taylor, J. A., Trudinger, C. M., and Watterson, I. G.: Variations in modeled atmospheric transport of carbon dioxide and the consequences for CO<sub>2</sub> inversions, Global Biogeochem. Cy., 10, 783–796, 1996. Luo, Y., Ogle, K., Tucker, C., Fei, S., Gao, C., LaDeau, S., Clark, J. S., and Schimel, D. S.: Ecological forecasting and data assimilation in a data-rich era, Ecol. Appl., 21, 1429–1442, 2011. Maherali, H. and DeLucia, E. H.: Influence of climate-driven shifts in biomass allocation on water transport and storage in ponderosa pine, Oecologia, 129, 481–491, 2001. Maksyutov, S., Patra, P. K., Onishi, R., Saeki, T., and Nakazawa, T.: NIES/FRCGC Global Atmospheric Tracer Tnansport Model: description, validation, and surface sources and sinks inversion, J. Earth Sim., 9, 3–18, 2008. Meziane, D. and Shipley, B.: Interacting determinants of specific leaf area in 22 herbaceous species: effects of irradiance and nutrient availability, Plant Cell Environ., 22, 447–459, 1999. Monsi, M. and Saeki, T.: Über den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung für die Stoffproduktion, Jpn. J. Bot., 14, 22–52, 1953. Monson, R. K., Stidham, M. A., Williams, G. J., Edwards, G. E., and Uribe, E. G.: Temperature dependence of photosynthesis in <i>Agropyron smithii</i> Rydb. I. Factors affecting net CO<sub>2</sub> uptake in intact leaves and contribution from ribulose-1, 5-bisphosphate carboxylase measured <i>in vivo and in vitro</i>, Plant Physiol., 69, 921–928, 1982. Oda, T. and Maksyutov, S.: A very high-resolution (1 km × 1 km) global fossil fuel CO<sub>2</sub> emission inventory derived using a point source database and satellite observations of nighttime lights, Atmos. Chem. Phys., 11, 543–556, <a href="http://dx.doi.org/10.5194/acp-11-543-2011">https://doi.org/10.5194/acp-11-543-2011</a>, 2011. Olson, R. J., Johnson, K. R., Zheng, D. L., and Scurlock, J. M. O.: Global and Regional Ecosystem Modeling: Databases of Model Drivers and Validation Measurements, Ork Ridge National Laboratory, 2001. Onogi, K., Tsutsui, J., Koide, H., Sakamoto, M., Kobayashi, S., Hatsushika, H., Matsumoto, T., Yamazaki, N., Kamahori, H., Takahashi, K., Kadokura, S., Wada, K., Kato, K., Oyama, R., Ose, T., Mannoji, N., and Taira, R.: The JRA-25 Reanalysis, J. Meteorol. Soc. Jpn., 85, 369–432, 2007. Peylin, P., Bousquet, P., Le Quéré, C., Sitch, S., Friedlingstein, P., McKinley, G., Gruber, N., Rayner, P., and Ciais, P.: Multiple constraints on regional CO<sub>2</sub> flux variations over land and oceans, Global Biogeochem. Cy., 19, GB1011, <a href="http://dx.doi.org/10.1029/2003GB002214">https://doi.org/10.1029/2003GB002214</a>, 2005. Pierce, L. L., Running, S. W., and Walker, J.: Regional-scale relationships of leaf area index to specific leaf area and leaf nitrogen content, Ecol. Appl., 4, 313–321, 1994. Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P. M., Moonet, H. A., and Klooster, S. A.: Terrestrial ecosystem production: a process model based on global satellite and surface data, Global Biogeochem. Cy., 7, 811–841, 1993. Raupach, M. R., Rayner, P. J., Barrett, D. J., DeFries, R. S., Heimann, M., Ojima, D. S., Quegan, S., and Schmullius, C. C.: Model-data synthesis in terrestrial carbon observation: methods, data requirements and data uncertainty specifications, Global Change Biol., 11, 378–397, 2005. Rayner, P. J., Scholze, M., Knorr, W., Kaminski, T., Giering, R., and Widmann, H.: Two decades of terrestrial carbon fluxes from a carbon cycle data assimilation system (CCDAS), Global Biogeochem. Cy., 19, GB2026, <a href="http://dx.doi.org/10.1029/2004GB002254">https://doi.org/10.1029/2004GB002254</a>, 2005. Reich, P. B., Walters, M. B., and Ellsworth, D. S.: From tropics to tundra: global convergence in plant functioning, P. Natl. Acad. Sci. USA, 94, 13730–13734, 1997. Reich, P. B., Walters, M. B., Ellsworth, D. S., Vose, J. M., Volin, J. C., Gresham, C., and Bowman, W. D.: Relationships of leaf dark respiration to leaf nitrogen, specific leaf area and leaf life-span: a test across biomes and functional groups, Oecologia, 114, 471–482, 1998. Reichstein, M., Tenhunen, J., Roupsard, O., Ourcival, J. M., Rambal, S., Miglietta, F., Peressotti, A., Pecchiari, M., Tirone, G., and Valentini, R.: Inverse modeling of seasonal drought effects on canopy CO<sub>2</sub>/H<sub>2</sub>O exchange in three Mediterranean ecosystems, J. Geophys. Res., 108, 4726, <a href="http://dx.doi.org/10.1029/2003JD003430">https://doi.org/10.1029/2003JD003430</a>, 2003. Running, S. W. and Hunt, E. R.: Generalization of a forest ecosystem process model for other biomes, BIOME-BGC, and an application for global scale models, in: Scaling Physiological Processes: Leat to Globe, edited by: Ehleringer, J. R. and Field, C. B., 141–158, Academic Press, 1993. Saatchi, S. S., Harris, N. L., Brown, S., Lefsky, M., Mitchard, E. T. A., Salas, W., Zutta, B. R., Buermann, W., Lewis, S. L., Hagen, S., Petrova, S., White, L., Silman, M., and Morel, A.: Benchmark map of forest carbon stocks in tropical regions across three continents, P. Natl. Acad. Sci. USA, 108, 9899–9904, 2011. Sacks, W. J., Schimel, D. S., Monson, R. K., and Braswell, B. H.: Model-data synthesis of diurnal and seasonal CO}<sub>2</sub> fluxes at {Niwot Ridge, Global Change Biol., 12, 240–259, 2006. Saito, M., Maksyutov, S., Hirata, R., and Richardson, A. D.: An empirical model simulating diurnal and seasonal CO<sub>2</sub> flux for diverse vegetation types and climate conditions, Biogeosciences, 6, 585–599, <a href="http://dx.doi.org/10.5194/bg-6-585-2009">https://doi.org/10.5194/bg-6-585-2009</a>, 2009. Saito, M., Ito, A., and Maksyutov, S.: Evaluation of biases in JRA-25/JCDAS precipitation and their impact on the global terrestrial carbon balance, J. Climate, 24, 4109–4125, 2011. Schimel, D. S.: Terrestrial ecosystems and the carbon cycle, Glob. Change Biol., 1, 77–91, 1995. Schubert, S. D., Rood, R. B., and Pfaendtner, J.: An Assimilated Dataset for Earth Science Applications, B. Am. Meteorol. Soc., 74, 2331–2342, 1993. Scurlock, J. M. O., Cramer, W., Olson, R. J., Parton, W. J., and Prince, S. D.: Terrestrial NPP: toward a consistent data set for global model evaluation, Ecol. Appl., 9, 913–919, 1999. Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M., Piao, S. L., Betts, R., Ciais, P., Cox, P., Friedlingstein, P., Jones, C. D., Prentice, I. C., and Woodward, F. I.: 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, 2008. Tans, P. P., Fung, I. Y., and Takahashi, T.: Observational Contrains on the Global Atmospheric CO<sub>2</sub> Budget, Science, 247, 1431–1438, 1990. Tarantola, A.: Inverse Problem Theory and Methods for Model Parameter Estimation, Society for Indstrial and Applied Mathematics, 2005. Valsala, V. and Maksyutov, S.: Simulation and assimilation of global ocean <i>p</i>CO<sub>2</sub> and air-sea CO<sub>2</sub> fluxes using ship observations of surface ocean <i>p</i>CO<sub>2</sub> in a simplified biogeochemical offline model, Tellus B, 62, 821–840, 2010. van der Werf, G. R., Morton, D. C., DeFries, R. S., Olivier, J. G. J., Kasibhatla, P. S., Jackson, R. B., Collatz, G. J., and Randerson, J. T.: CO<sub>2</sub> emissions from forest loss, Nat. Geosci., 2, 737–738, 2009. Wang, Y. P., Trudinger, C. M., and Enting, I. G.: A review of applications of model-data fusion to studies of terrestrial carbon fluxes at different scales, Agr. Forest Meteorol., 149, 1829–1842, 2009. Zhou, T. and Luo, Y.: Spatial patterns of ecosystem carbon residence time and NPP}-driven carbon uptake in the conterminous {United States, Global Biogeochem. Cy., 22, GB3032, <a href="http://dx.doi.org/10.1029/2007GB002939">https://doi.org/10.1029/2007GB002939</a>, 2008.