Remote Sensing Evaluation of CLM4 GPP for the Period 2000–09

Jiafu Mao Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee

Search for other papers by Jiafu Mao in
Current site
Google Scholar
PubMed
Close
,
Peter E. Thornton Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee

Search for other papers by Peter E. Thornton in
Current site
Google Scholar
PubMed
Close
,
Xiaoying Shi Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee

Search for other papers by Xiaoying Shi in
Current site
Google Scholar
PubMed
Close
,
Maosheng Zhao Numerical Terradynamic Simulation Group, Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, Montana

Search for other papers by Maosheng Zhao in
Current site
Google Scholar
PubMed
Close
, and
Wilfred M. Post Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee

Search for other papers by Wilfred M. Post in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

Remote sensing can provide long-term and large-scale products helpful for ecosystem model evaluation. The authors compare monthly gross primary production (GPP) simulated by the Community Land Model, version 4 (CLM4) at a half-degree resolution with satellite estimates of GPP from the Moderate Resolution Imaging Spectroradiometer (MODIS) GPP product (MOD17) for the 10-yr period January 2000–December 2009. The assessment is presented in terms of long-term mean carbon assimilation, seasonal mean distributions, amplitude and phase of the annual cycle, and intraannual and interannual GPP variability and their responses to climate variables. For the long-term annual and seasonal means, major GPP patterns are clearly demonstrated by both products. Compared to the MODIS product, CLM4 overestimates the magnitude of GPP for tropical evergreen forests. CLM4 has a longer carbon uptake period than MODIS for most plant functional types (PFTs) with an earlier onset of GPP in spring and a later decline of GPP in autumn. Empirical orthogonal function analysis of the monthly GPP changes indicates that, on the intraannual scale, both CLM4 and MODIS display similar spatial representations and temporal patterns for most terrestrial ecosystems except in northeast Russia and in the very dry region of central Australia. For 2000–09, CLM4 simulated increases in annual averaged GPP over both hemispheres; however, estimates from MODIS suggest a reduction in the Southern Hemisphere (−0.2173 PgC yr−1), balancing the significant increase over the Northern Hemisphere (0.2157 PgC yr−1). The evaluations highlight strengths and weaknesses of the CLM4 primary production and illuminate potential improvements and developments.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-11-00401.s1.

Corresponding author address: Jiafu Mao, Environmental Sciences Division, Oak Ridge National Laboratory, P.O. Box 2008, MS6301, Oak Ridge, TN 37831-6301. E-mail: maoj@ornl.gov

Abstract

Remote sensing can provide long-term and large-scale products helpful for ecosystem model evaluation. The authors compare monthly gross primary production (GPP) simulated by the Community Land Model, version 4 (CLM4) at a half-degree resolution with satellite estimates of GPP from the Moderate Resolution Imaging Spectroradiometer (MODIS) GPP product (MOD17) for the 10-yr period January 2000–December 2009. The assessment is presented in terms of long-term mean carbon assimilation, seasonal mean distributions, amplitude and phase of the annual cycle, and intraannual and interannual GPP variability and their responses to climate variables. For the long-term annual and seasonal means, major GPP patterns are clearly demonstrated by both products. Compared to the MODIS product, CLM4 overestimates the magnitude of GPP for tropical evergreen forests. CLM4 has a longer carbon uptake period than MODIS for most plant functional types (PFTs) with an earlier onset of GPP in spring and a later decline of GPP in autumn. Empirical orthogonal function analysis of the monthly GPP changes indicates that, on the intraannual scale, both CLM4 and MODIS display similar spatial representations and temporal patterns for most terrestrial ecosystems except in northeast Russia and in the very dry region of central Australia. For 2000–09, CLM4 simulated increases in annual averaged GPP over both hemispheres; however, estimates from MODIS suggest a reduction in the Southern Hemisphere (−0.2173 PgC yr−1), balancing the significant increase over the Northern Hemisphere (0.2157 PgC yr−1). The evaluations highlight strengths and weaknesses of the CLM4 primary production and illuminate potential improvements and developments.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-11-00401.s1.

Corresponding author address: Jiafu Mao, Environmental Sciences Division, Oak Ridge National Laboratory, P.O. Box 2008, MS6301, Oak Ridge, TN 37831-6301. E-mail: maoj@ornl.gov

Supplementary Materials

    • Supplemental Materials (PDF 1.56 MB)
Save
  • Baker, I. T., A. S. Denning, and R. Stöckli, 2010: North American gross primary productivity: Regional characterization and interannual variability. Tellus, 62B, 533549.

    • Search Google Scholar
    • Export Citation
  • Beer, C., and Coauthors, 2010: Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate. Science, 329, 834838.

    • Search Google Scholar
    • Export Citation
  • Bonan, G. B., and S. Levis, 2010: Quantifying carbon-nitrogen feedbacks in the Community Land Model (CLM4). Geophys. Res. Lett., 37, L07401, doi:10.1029/2010GL042430.

    • Search Google Scholar
    • Export Citation
  • Bonan, G. B., P. J. Lawrence, K. W. Oleson, S. Levis, M. Jung, M. Reichstein, D. M. Lawrence, and S. C. Swenson, 2011: Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data. J. Geophys. Res., 116, G02014, doi:10.1029/2010JG001593.

    • Search Google Scholar
    • Export Citation
  • Ciais, P., and Coauthors, 1997: A three-dimensional synthesis study of δ18O in atmospheric CO2 1. Surface fluxes. J. Geophys. Res., 102 (D5), 58575872.

    • Search Google Scholar
    • Export Citation
  • Coops, N. C., C. J. Ferster, R. H. Waring, and J. Nightingale, 2009: Comparison of three models for predicting gross primary production across and within forested ecoregions in the contiguous United States. Remote Sens. Environ., 113, 680690.

    • Search Google Scholar
    • Export Citation
  • Cox, P. M., R. A. Betts, C. D. Jones, S. A. Spall, and I. J. Totterdell, 2000: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature, 408, 184187.

    • Search Google Scholar
    • Export Citation
  • Cramer, W., and Coauthors, 1999: Comparing global models of terrestrial net primary productivity (NPP): Overview and key results. Global Change Biol., 5, 115.

    • Search Google Scholar
    • Export Citation
  • Frankenberg, C., and Coauthors, 2011: New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity. Geophys. Res. Lett., 38, L17706, doi:10.1029/2011GL048738.

    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P., and Coauthors, 2006: Climate–carbon cycle feedback analysis: Results from the C4MIP model intercomparison. J. Climate, 19, 33373353.

    • Search Google Scholar
    • Export Citation
  • Fung, I. Y., S. C. Doney, K. Lindsay, and J. John, 2005: Evolution of carbon sinks in a changing climate. Proc. Natl. Acad. Sci. USA, 102, 11 20111 206.

    • Search Google Scholar
    • Export Citation
  • Heinsch, F. A., and Coauthors, 2006: Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Trans. Geosci. Remote Sens., 44, 19081925.

    • Search Google Scholar
    • Export Citation
  • Jones, C., J. Lowe, S. Liddicoat, and R. Betts, 2009: Committed terrestrial ecosystem changes due to climate change. Nat. Geosci., 2, 484487.

    • Search Google Scholar
    • Export Citation
  • Jung, M., and Coauthors, 2007: Uncertainties of modeling gross primary productivity over Europe: A systematic study on the effects of using different drivers and terrestrial biosphere models. Global Biogeochem. Cycles, 21, GB4021, doi:10.1029/2006GB002915.

    • Search Google Scholar
    • Export Citation
  • Jung, M., M. Reichstein, and A. Bondeau, 2009: Towards global empirical upscaling of FLUXNET eddy covariance observations: Validation of a model tree ensemble approach using a biosphere model. Biogeosciences, 6, 52715304.

    • Search Google Scholar
    • Export Citation
  • Justice, C. O., J. R. G. Townshend, E. F. Vermote, E. Masuoka, R. E. Wolfe, N. Saleous, D. P. Roy, and J. T. Morisette, 2002: An overview of MODIS land data processing and product status. Remote Sens. Environ., 83, 315.

    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., W. Ebisuzaki, J. Woolen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311643.

    • Search Google Scholar
    • Export Citation
  • Kanniah, K. D., J. Beringer, L. B. Hutley, N. J. Tapper, and X. Zhu, 2009: Evaluation of collections 4 and 5 of the MODIS gross primary productivity product and algorithm improvement at a tropical savanna site in northern Australia. Remote Sens. Environ., 113, 18081822.

    • Search Google Scholar
    • Export Citation
  • Lawrence, D. M., and Coauthors, 2011: Parameterization improvements and functional and structural advances in version 4 of the Community Land Model. J. Adv. Model. Earth Syst., 3, M03001, doi:10.1029/2011MS000045.

    • Search Google Scholar
    • Export Citation
  • Lawrence, P. J., and T. N. Chase, 2007: Representing a new MODIS consistent land surface in the Community Land Model (CLM 3.0). J. Geophys. Res., 112, G01023, doi:10.1029/2006JG000168.

    • Search Google Scholar
    • Export Citation
  • Mitchell, T. D., and P. D. Jones, 2005: An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int. J. Climatol., 25, 693712.

    • Search Google Scholar
    • Export Citation
  • Myneni, R. B., and Coauthors, 2002: Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ., 83, 214231.

    • Search Google Scholar
    • Export Citation
  • Nemani, R. R., C. D. Keeling, H. Hashimoto, W. M. Jolly, S. C. Piper, C. J. Tucker, R. B. Myneni, and S. W. Running, 2003: Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 300, 15601563.

    • Search Google Scholar
    • Export Citation
  • North, G. R., T. L. Bell, R. F. Cahalan, and F. J. Moeng, 1982: Sampling errors in the estimation of empirical orthogonal functions. Mon. Wea. Rev., 110, 699706.

    • Search Google Scholar
    • Export Citation
  • Oleson, K. W., G. B. Bonan, C. Schaaf, F. Gao, Y. F. Jin, and A. Strahler, 2003: Assessment of global climate model land surface albedo using MODIS data. Geophys. Res. Lett., 30, 1443, doi:10.1029/2002GL016749.

    • Search Google Scholar
    • Export Citation
  • Oleson, K. W., and Coauthors, 2010: Technical description of version 4.0 of the Community Land Model (CLM). NCAR Tech. Note NCAR/TN-478+STR, 257 pp.

  • Randerson, J. T., and Coauthors, 2009: Systematic assessment of terrestrial biogeochemistry in coupled climate–carbon models. Global Change Biol., 15, 24622484.

    • Search Google Scholar
    • Export Citation
  • Running, S. W., D. D. Baldocchi, D. P. Turner, S. T. Gower, P. S. Bakwin, and K. A. Hibbard, 1999: A global terrestrial monitoring network integrating tower fluxes, flask sampling, ecosystem modeling and EOS satellite data. Remote Sens. Environ., 70, 108127.

    • Search Google Scholar
    • Export Citation
  • Running, S. W., R. R. Nemani, F. A. Heinsch, M. S. Zhao, M. Reeves, and H. Hashimoto, 2004: A continuous satellite-derived measure of global terrestrial primary production. Bioscience, 54, 547560.

    • Search Google Scholar
    • Export Citation
  • Shi, X., J. Mao, P. E. Thornton, M. H. Forrest, and M. P. Wilfred, 2011: The impact of climate, CO2, nitrogen deposition and land use change on simulated contemporary global river flow. Geophys. Res. Lett., 38, L08704, doi:10.1029/2011GL046773.

    • Search Google Scholar
    • Export Citation
  • Sitch, S., and Coauthors, 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, 20152039.

    • Search Google Scholar
    • Export Citation
  • Solomon, S., D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. Tignor, H. L. Miller Jr., and Z. Chen, Eds., 2007: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.

  • Stöckli, R., T. Rutishauser, D. Dragoni, J. O’Keefe, P. E. Thornton, M. Jolly, L. Lu, and A. S. Denning, 2008: Remote sensing data assimilation for a prognostic phenology model. J. Geophys. Res., 113, G04021, doi:10.1029/2008JG000781.

    • Search Google Scholar
    • Export Citation
  • Thornton, P. E., and N. A. Rosenbloom, 2005: Ecosystem model spin-up: Estimating steady state conditions in a coupled terrestrial carbon and nitrogen cycle model. Ecol. Modell., 189, 2548.

    • Search Google Scholar
    • Export Citation
  • Thornton, P. E., and N. E. Zimmermann, 2007: An improved canopy integration scheme for a land surface model with prognostic canopy structure. J. Climate, 20, 39023923.

    • Search Google Scholar
    • Export Citation
  • Thornton, P. E., and Coauthors, 2009: Carbon-nitrogen interactions regulate climate-carbon cycle feedbacks: Results from an atmosphere-ocean general circulation model. Biogeosciences, 6, 20992120.

    • Search Google Scholar
    • Export Citation
  • Tian, Y., and Coauthors, 2004: Comparison of seasonal and spatial variations of leaf area index and fraction of absorbed photosynthetically active radiation from Moderate Resolution Imaging Spectroradiometer (MODIS) and Common Land Model. J. Geophys. Res., 109, D01103, doi:10.1029/2003JD003777.

    • Search Google Scholar
    • Export Citation
  • Townsend, A. R., C. C. Cleveland, B. Z. Houlton, C. B. Alden, and J. W. C. White, 2011: Multi-element regulation of the tropical forest carbon cycle. Front. Ecol. Environ., 9, 917, doi:10.1890/100047.

    • Search Google Scholar
    • Export Citation
  • Turner, D. P., W. D. Ritts, M. S. Zhao, S. A. Kurc, A. L. Dunn, S. C. Wofsy, E. E. Small, and S. W. Running, 2006a: Assessing interannual variation in MODIS-based estimates of gross primary production. IEEE Trans. Geosci. Remote Sens., 44, 18991907.

    • Search Google Scholar
    • Export Citation
  • Turner, D. P., and Coauthors, 2006b: Evaluation of MODIS NPP and GPP products across multiple biomes. Remote Sens. Environ., 102, 282292.

    • Search Google Scholar
    • Export Citation
  • Wang, W., J. Dungan, H. Hashimoto, A. R. Michaelis, C. Milesi, K. Ichil, and R. R. Nemani, 2011: Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multimodel ensemble experiment: 1. Primary production. Global Change Biol., 17, 13501366.

    • Search Google Scholar
    • Export Citation
  • Wang, Z., X. Zeng, M. Barlage, R. E. Dickinson, F. Gao, and C. B. Schaaf, 2004: Using MODIS BRDF and albedo data to evaluate global model land surface albedo. J. Hydrometeor., 5, 314.

    • Search Google Scholar
    • Export Citation
  • Xiao, J., and Coauthors, 2008: Estimation of net ecosystem carbon exchange for the conterminous United States by combining MODIS and AmeriFlux data. Agric. For. Meteor., 148, 18271847.

    • Search Google Scholar
    • Export Citation
  • Zaehle, S., S. Sitch, B. Smith, and F. Hatterman, 2005: Effects of parameter uncertainties on the modeling of terrestrial biosphere dynamics. Global Biogeochem. Cycles, 19, GB3020, doi:10.1029/2004GB002395.

    • Search Google Scholar
    • Export Citation
  • Zhao, M., and S. W. Running, 2010: Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science, 329, 940943.

    • Search Google Scholar
    • Export Citation
  • Zhao, M., and S. W. Running, 2011: Response to comments on “Drought-induced reduction in global terrestrial net primary production from 2000 through 2009.” Science, 333, 1093.

    • Search Google Scholar
    • Export Citation
  • Zhao, M., F. A. Heinsch, R. R. Nemani, and S. W. Running, 2005: Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sens. Environ., 95, 164176.

    • Search Google Scholar
    • Export Citation
  • Zhao, M., S. W. Running, and R. R. Nemani, 2006: Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses. J. Geophys. Res., 111, G01002, doi:10.1029/2004JG000004.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2096 991 167
PDF Downloads 807 173 13