Assessing Global Vegetation–Climate Feedbacks from Observations

Zhengyu Liu Center for Climatic Research, University of Wisconsin—Madison, Madison, Wisconsin

Search for other papers by Zhengyu Liu in
Current site
Google Scholar
PubMed
Close
,
M. Notaro Center for Climatic Research, University of Wisconsin—Madison, Madison, Wisconsin

Search for other papers by M. Notaro in
Current site
Google Scholar
PubMed
Close
,
J. Kutzbach Center for Climatic Research, University of Wisconsin—Madison, Madison, Wisconsin

Search for other papers by J. Kutzbach in
Current site
Google Scholar
PubMed
Close
, and
Naizhuang Liu Nanjing Institute of Meteorology, Nanjing, China

Search for other papers by Naizhuang Liu in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The feedback between global vegetation greenness and surface air temperature and precipitation is assessed using remote sensing observations of monthly fraction of photosynthetically active radiation (FPAR) for 1982 to 2000 with a 2.5° grid resolution. Lead/lag correlations are used to infer vegetation–climate interactions. Furthermore, a statistical method is used to quantify the efficiency of vegetation feedback on climate in the observations. This feedback analysis provides a first quantitative assessment of global vegetation feedback on climate. In northern mid- and high latitudes, vegetation variability is found to be driven predominantly by temperature; in the meantime, vegetation also exerts a strong positive feedback on temperature with the feedback accounting for over 10%–25% of the total monthly temperature variance. The strongest positive feedback occurs in the boreal regions of southern Canada/northern United States, northern Europe, and southern Siberia, where the feedback efficiency exceeds 1°C (0.1 FPAR)−1. Over most of the Tropics and subtropics (outside the equatorial rain belt), vegetation is driven primarily by precipitation. However, little vegetation feedback is found on local precipitation when averaged year-round, with the feedback explained variance usually accounting for less than 5% of the total precipitation variance. Nevertheless, in a few isolated small regions such as Northeast Brazil, East Africa, East Asia, and northern Australia, there appears to be some positive vegetation feedback on local precipitation, with the feedback efficiency over 1 cm month−1 (0.1 FPAR)−1. Further studies suggest a significant seasonal variation of the vegetation feedback in some regions. A preliminary analysis also seems to suggest an enhanced intensity of the vegetation feedback, especially on precipitation, at longer time scales and over a larger grid box area. Limitations and implications of the assessment of vegetation feedback are also discussed. The assessed vegetation feedback is shown to be valuable for the evaluation of vegetation–climate feedback in coupled climate–vegetation models.

* CCR Contribution Number 874

Corresponding author address: Z. Liu, Center for Climatic Research, 1225 West Dayton Street, Madison, WI 53706. Email: zliu3@wisc.edu

Abstract

The feedback between global vegetation greenness and surface air temperature and precipitation is assessed using remote sensing observations of monthly fraction of photosynthetically active radiation (FPAR) for 1982 to 2000 with a 2.5° grid resolution. Lead/lag correlations are used to infer vegetation–climate interactions. Furthermore, a statistical method is used to quantify the efficiency of vegetation feedback on climate in the observations. This feedback analysis provides a first quantitative assessment of global vegetation feedback on climate. In northern mid- and high latitudes, vegetation variability is found to be driven predominantly by temperature; in the meantime, vegetation also exerts a strong positive feedback on temperature with the feedback accounting for over 10%–25% of the total monthly temperature variance. The strongest positive feedback occurs in the boreal regions of southern Canada/northern United States, northern Europe, and southern Siberia, where the feedback efficiency exceeds 1°C (0.1 FPAR)−1. Over most of the Tropics and subtropics (outside the equatorial rain belt), vegetation is driven primarily by precipitation. However, little vegetation feedback is found on local precipitation when averaged year-round, with the feedback explained variance usually accounting for less than 5% of the total precipitation variance. Nevertheless, in a few isolated small regions such as Northeast Brazil, East Africa, East Asia, and northern Australia, there appears to be some positive vegetation feedback on local precipitation, with the feedback efficiency over 1 cm month−1 (0.1 FPAR)−1. Further studies suggest a significant seasonal variation of the vegetation feedback in some regions. A preliminary analysis also seems to suggest an enhanced intensity of the vegetation feedback, especially on precipitation, at longer time scales and over a larger grid box area. Limitations and implications of the assessment of vegetation feedback are also discussed. The assessed vegetation feedback is shown to be valuable for the evaluation of vegetation–climate feedback in coupled climate–vegetation models.

* CCR Contribution Number 874

Corresponding author address: Z. Liu, Center for Climatic Research, 1225 West Dayton Street, Madison, WI 53706. Email: zliu3@wisc.edu

Save
  • Bonan, G., 2002: Ecological Climatology: Concepts and Applications. Cambridge University Press, 678 pp.

  • Bonan, G., D. Pollard, and S. Thompson, 1992: Effects of boreal forest vegetation on global climate. Nature, 359 , 716718.

  • Bonan, G., S. Levis, S. Sitch, M. Vertenstein, and K. W. Oleson, 2003: A dynamic global vegetation model for use with climate models: Concepts and description of simulated vegetation dynamics. Global Change Biol, 9 , 15431566.

    • Search Google Scholar
    • Export Citation
  • Bounoua, L., G. J. Collatz, S. O. Los, P. J. Sellers, D. A. Dazlich, C. J. Tucker, and D. A. Randall, 2000: Sensitivity of climate to changes in NDVI. J. Climate, 13 , 22772292.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., and D. Battisti, 2000: An interpretation of the results from atmospheric general circulation models forced by the time history of the observed sea surface temperature distribution. Geophys. Res. Lett, 27 , 767770.

    • Search Google Scholar
    • Export Citation
  • Budyko, M. I., 1974: Climate and Life. Academic Press, 608 pp.

  • Buermann, W., J. Dong, X. Zeng, R. B. Nyneni, and R. E. Dickinson, 2001: Evaluation of the utility of satellite-based vegetation leaf area index data for climate simulations. J. Climate, 14 , 35363550.

    • Search Google Scholar
    • Export Citation
  • Chen, X., and W. Pan, 2002: Relationships among phenological growing season, time-integrated normalized difference vegetation index and climate forcing in the temperate region of eastern China. Int. J. Climatol, 22 , 17811792.

    • Search Google Scholar
    • Export Citation
  • Claussen, M., C. Kubatzki, V. Brovkin, A. Ganopolski, P. Hoelzmann, and H. J. Pachur, 1999: Simulation of an abrupt change in Saharan vegetation in the mid-Holocene. Geophys. Res. Lett, 26 , 20372040.

    • Search Google Scholar
    • Export Citation
  • Cramer, W., and Coauthors, 2001: Global response of terrestrial ecosystem structure and function to CO2 and climate change: Results from six dynamic global vegetation models. Global Change Biol, 7 , 357373.

    • Search Google Scholar
    • Export Citation
  • Czaja, A., and C. Frankignoul, 2002: Observed impact of Atlantic SST anomalies on the North Atlantic Oscillation. J. Climate, 15 , 606623.

    • Search Google Scholar
    • Export Citation
  • DeFries, R. S., J. R. G. Townshend, and M. C. Hansen, 1999: Continuous fields of vegetation characteristics at the global scale at 1km resolution. J. Geophys. Res, 104 , 1691116925.

    • Search Google Scholar
    • Export Citation
  • DeFries, R. S., M. C. Hansen, J. R. G. Townshend, A. C. Janetos, and T. R. Loveland, 2000: A new global 1-km dataset of percentage tree cover derived from remote sensing. Global Change Biol, 6 , 247254.

    • Search Google Scholar
    • Export Citation
  • Dickinson, R. E., and A. Henderson-Sellers, 1988: Modeling tropical deforestation: A study of GCM land–surface parameterizations. Quart. J. Roy. Meteor. Soc, 114 , 439462.

    • Search Google Scholar
    • Export Citation
  • Dickinson, R. E., and M. Shaikh, 1998: Interactive canopies for a climate model. J. Climate, 11 , 28232836.

  • Eugster, W., and Coauthors, 2000: Land–atmosphere energy exchange in Arctic tundra and boreal forest: Available data and feedbacks to climate. Global Change Biol, 6 , 84115.

    • Search Google Scholar
    • Export Citation
  • Foley, J. A., S. Levis, I. C. Prentice, D. Pollard, and S. L. Thompson, 1998: Coupling dynamic models of climate and vegetation. Global Change Biol, 4 , 561579.

    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., and K. Hasselmann, 1977: Stochastic climate models. Part II: Application to sea surface temperature anomalies and thermocline variability. Tellus, 29 , 289305.

    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., and E. Kestenare, 2002: The surface heat flux feedback, Part I: Estimates from observations in the Atlantic and the North Pacific. Climate Dyn, 19 , 622647.

    • Search Google Scholar
    • Export Citation
  • Frankignoul, C., A. Czaja, and B. L'Heveder, 1998: Air–sea feedback in the North Atlantic and surface boundary conditions for ocean models. J. Climate, 11 , 23102324.

    • Search Google Scholar
    • Export Citation
  • Freedman, J. M., D. R. Fitzjarrald, K. E. Moore, and R. K. Sakai, 2001: Boundary layer clouds and vegetation–atmosphere feedbacks. J. Climate, 14 , 180197.

    • Search Google Scholar
    • Export Citation
  • Gallimore, R., and J. Kutzbach, 1996: Role of orbitally induced changes in tundra area in the onset of glaciation. Nature, 381 , 503505.

    • Search Google Scholar
    • Export Citation
  • Gallimore, R., R. Jacob, and J. Kutzbach, 2005: Coupled atmosphere–ocean–vegetation simulations for modern and mid-Holocene climates: Role of extratropical vegetation cover feedbacks. Climate Dyn, 25 , 755776.

    • Search Google Scholar
    • Export Citation
  • GLACE team, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305 , 11381140.

  • Granger, C. W. J., 1969: Investigating causal relations by econometric models and cross spectral models. Econometrica, 37 , 424438.

  • Huete, A. R., 1988: A soil adjusted vegetation index (SAVI). Remote Sens. Environ, 25 , 295309.

  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc, 77 , 437471.

  • Kaufmann, R. K., L. Zhou, Y. Knyazikhin, N. V. Shabanov, R. B. Myneni, and C. J. Tucker, 2000: Effect of orbital drift and sensor changes on the time series of AVHRR vegetation index data. IEEE Trans. Geosci. Remote Sens, 38 , 25842597.

    • Search Google Scholar
    • Export Citation
  • Kaufmann, R. K., L. Zhou, R. B. Myneri, C. J. Tucker, D. Slayback, N. V. Shabanov, and J. Pinzon, 2003: The effect of vegetation on surface temperature: A statistical analysis of NDVI and climate data. Geophys. Res. Lett, 30 .2147, doi:10.1029/2003GL018251.

    • Search Google Scholar
    • Export Citation
  • Kutzbach, J. E., P. J. Bartlein, J. A. Foley, S. P. Harrison, S. W. Hostetler, Z. Liu, I. C. Prentice, and T. Webb III, 1996: Potential role of vegetation feedback in the climate sensitivity of high-latitude regions: A case study at 6000 years BP. Global Biogeochem. Cycles, 10 , 727736.

    • Search Google Scholar
    • Export Citation
  • Levis, S., G. B. Bonan, and C. Bonfils, 2004: Soil feedback drives the mid-Holocene North African monsoon northward in fully coupled CCSM2 simulations with a dynamic vegetation model. Climate Dyn, 23 .doi:10.1007/s00382-004-0477-y.

    • Search Google Scholar
    • Export Citation
  • Liu, Z., and L. Wu, 2004: Atmospheric response to North Pacific SST: The role of ocean–atmosphere coupling. J. Climate, 17 , 18591882.

    • Search Google Scholar
    • Export Citation
  • Los, S. O., and Coauthors, 2000: A global 9-yr biophysical land surface dataset from NOAA AVHRR data. J. Hydrometeor, 1 , 183199.

  • Myneni, R. B., R. R. Nemani, and S. W. Running, 1997: Estimation of global leave area index and absorbed PAR using radiative transfer models. IEEE Trans. Geosci. Remote Sens, 35 , 13801393.

    • 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
  • Notaro, M., Z. Liu, R. Gallimore, S. Vavrus, J. Kutzbach, C. Prentice, and R. Jacob, 2005: Simulated and observed preindustrial to modern vegetation and climate changes. J. Climate, 18 , 36503671.

    • Search Google Scholar
    • Export Citation
  • Notaro, M., Z. Liu, and J. Williams, 2006: Observed vegetation–climate feedback in the United States. J. Climate, 19 , 763786.

  • Pielke, R., R. Avissar, M. Raupach, A. J. Dolman, X. Zhen, and A. S. Denning, 1998: Interactions between the atmosphere and terrestrial ecosystems: Influence on weather and climate. Global Change Biol, 4 , 461475.

    • Search Google Scholar
    • Export Citation
  • Prentice, I. C., 2001: Interactions of climate change and the terrestrial biosphere. GeosphereBiosphere Interactions and Climate, L. O. Bengtsson and C. U. Hammer, Eds., Cambridge University Press, 176–195.

    • Search Google Scholar
    • Export Citation
  • Prentice, I. C., and Coauthors, 2000: Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa. J. Biogeogr, 27 , 507519.

    • Search Google Scholar
    • Export Citation
  • Schaefer, K., A. S. Denning, N. Suits, J. Kaduk, I. Baker, S. Los, and L. Prihodko, 2002: Effect of climate on interannual variability of terrestrial CO2 fluxes. Global Biogeochem. Cycles, 16 .1102, doi:10.1029/2002GB001928.

    • Search Google Scholar
    • Export Citation
  • Schultz, P. A., and M. S. Halpert, 1993: Global correlation of temperature, NDVI and precipitation. Adv. Space Res, 13 , 277280.

  • Schwartz, M. D., 1992: Phenology and springtime surface-layer change. Mon. Wea. Rev, 120 , 25702578.

  • Schwartz, M. D., 1996: Examining the spring discontinuity in daily temperature ranges. J. Climate, 9 , 803808.

  • Schwartz, M. D., and T. R. Karl, 1990: Spring phenology: Nature's experiment to detect the effect of ‘green-up’ on surface maximum temperatures. Mon. Wea. Rev, 118 , 883890.

    • Search Google Scholar
    • Export Citation
  • Shukla, J., and Y. Mintz, 1982: Influence of land–surface evapotranspiration on the Earth's climate. Science, 215 , 14981501.

  • Sitch, S., and Coauthors, 2003: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biol, 9 , 161185.

    • 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
  • Trenberth, K. E., 1999: Atmospheric moisture recycling: Role of advection and local evaporation. J. Climate, 12 , 13681381.

  • Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc, 78 , 25392558.

    • Search Google Scholar
    • Export Citation
  • Zeng, X., P. Rao, R. DeFries, and M. C. Hansen, 2003: Interannual variability and decadal trend of global fractional vegetation cover from 1982 to 2000. J. Appl. Meteor, 42 , 15251530.

    • Search Google Scholar
    • Export Citation
  • Zhang, H., A. Henderson-Sellers, and K. McGuffie, 1996: Impacts of tropical deforestation. Part I: Process analysis of local climatic change. J. Climate, 9 , 14971517.

    • Search Google Scholar
    • Export Citation
  • Zhang, J. Y., W. J. Dong, C. B. Fu, and L. Y. Wu, 2003: The influence of vegetation cover on summer precipitation in China: A statistical analysis of NDVI and climate data. Adv. Atmos. Sci, 20 , 10021006.

    • Search Google Scholar
    • Export Citation
  • Zhou, L., R. K. Kaufmann, Y. Tian, R. B. Myneni, and C. J. Tucker, 2003: Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999. J. Geophys. Res, 108D .4004, doi:10.1029/2002JD002510.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1647 636 26
PDF Downloads 973 256 25