Author
XIAO, J. - PURDUE UNIVERSITY | |
ZHUANG, Q. - PURDUE UNIVERSITY | |
BALDOCCHI, D. - UNIV. OF CALIF. BERKELEY | |
LAW, B. - OREGON STATE UNIV. | |
RICHARDSON, A. - UNIV. OF NEW HAMPSHIRE | |
CHEN, J. - UNIV. OF TOLEDO | |
OREN, R. - DUKE UNIVERSITY | |
STARR, G. - UNIV. OF ALABAMA | |
NOORMETS, A. - NORTH CAROLINA STATE UNIV | |
MA, S. - UNIV. OF CALIF. BERKELEY | |
VERMA, S. - UNIV. OF NEBRASKA | |
WHARTON, S. - UNIV. OF CALIF. DAVIS | |
WOFSY, S. - HARVARD UNIVERSITY | |
BOLSTAD, P. - UNIV. OF MINNESOTA | |
BURNS, S. - UNIV. OF COLORADO | |
COOK, D. - ARGONNE NAT'L. LAB | |
CURTIS, P. - OHIO STATE UNIVERSITY | |
DRAKE, B. - SMITHSONIAN ENVIR. CNTR. | |
FALK, M. - UNIV. OF CALIF. DAVIS | |
FISHCER, M. - LAWRENCE BERKELEY LAB | |
FOSTER, D. - HARVARD UNIVERSITY | |
GU, L. - OAK RIDGE NAT'L LAB | |
HADLEY, J. - HARVARD UNIVERSITY | |
HOLLINGER, D. - USDA FOREST SERVICE | |
KATUL, G. - DUKE UNIVERSITY | |
LITVAK, M. - UNIV. OF NEW MEXICO | |
MARTIN, T. - UNIVERSITY OF FLORIDA | |
MATAMALA, R. - ARGONNE NAT'L.LAB | |
MCNULTY, S. - USDA FOREST SERVICE | |
MEYERS, T. - NOAA/ARL | |
MONSON, R. - UNIVERSITY OF COLORADO | |
MUNGER, J. - HARVARD UNIVERSITY | |
OECHEL, W. - SAN DIEGO STATE UNIV. | |
PAW U, K. - UNIV. OF CALIF. DAVIS | |
SCHMID, H. - INDIANA UNIVERSITY | |
Scott, Russell - Russ | |
SUN, G. - USDA FOREST SERVICE | |
SUYKER, A. - UNIV. OF NEBRASKA | |
TORN, M. - LAWRENCE BERKELY LAB |
Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 6/26/2008 Publication Date: 10/20/2008 Citation: Xiao, J., Zhuang, Q., Baldocchi, D., Law, B., Richardson, A., Chen, J., Oren, R., Starr, G., Noormets, A., Ma, S., Verma, S., Wharton, S., Wofsy, S., Bolstad, P., Burns, S., Cook, D., Curtis, P., Drake, B., Falk, M., Fishcer, M., Foster, D., Gu, L., Hadley, J., Hollinger, D., Katul, G., Litvak, M., Martin, T., Matamala, R., Mcnulty, S., Meyers, T., Monson, R., Munger, J., Oechel, W., Paw U, K., Schmid, H., Scott, R.L., Sun, G., Suyker, A., Torn, M. 2008. Estimation of Net Ecosystem Carbon Exchange for the Conterminous United States by Combining MODIS and AmeriFlux Data. Agricultural and Forest Meteorology. 148:1827-1847. Interpretive Summary: In the face of climate change, in part caused by increases in atmospheric carbon dioxide due to human activities, it is important to properly account for amount of carbon dioxide that is released or taken in by Earth’s biosphere. This study used a combination of satellite measurements and measurements of carbon dioxide exchange over a large diversity of ecosystems to develop a relationship that was used to estimate the exchange of carbon dioxide between the atmosphere and land surface for every eight days in 2005 over the conterminous United States. The relationship between the satellite data and the carbon dioxide measurements produced fairly accurate results when compared with measurements and captured the expected patterns of the exchange both in time and space over the U.S. This study demonstrates that this approach can produce results that are accurate enough to be used to test new predictive tools that are being developed to quantify the Earth’s terrestrial carbon budgets. Technical Abstract: Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectrometer MODIS) instrument on board NASA’s Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a regression tree approach. The predictive model was trained and validated using NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE reasonably well at the site level. We then applied the model to the continental scale and estimated NEE for each 1 km × 1 km cell across the conterminous U.S. for each 8-day period in 2005 using spatially-explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets for large areas. |