Estimation of Net Ecosystem Carbon Exchange for the Conterminous UnitedStates by Combining MODIS and AmeriFlux Data

Journal Article · Fri Mar 06 04:00:00 EST 2009 · Agricultural and Forest Meteorology

OSTI ID:964406

Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D; Law, Beverly E; Richardson, Andrew D; Chen, Jiquan; Oren, Ram; Starr, Gregory; Noormets, Asko; Ma, Siyan; Verma, Shashi B; Wharton, Sonia; Wofsy, Steven C; Bolstad, Paul V; Burns, Sean P; Cook, David R; Curtis, Peter S; Drake, Bert G; Falk, Matthias; Fischer, Marc L ; Foster, David R; Gu, Lianhong; Hadley, Julian L; Hollinger, David Y; Katul, Gabriel G; Litvak, Marcy; Martin, Timothy A; Matamala, Roser; McNulty, Steve; Meyers, Tilden P; Monson, Russell K; Munger, J William; Oechel, Walter C; U, Kyaw Tha Paw; Schmid, Hans Peter; Scott, Russell L; Sun, Ge; Suyker, Andrew E; Torn, Margaret S

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 x 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.

• Research Organization: Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US)
• Sponsoring Organization: Earth Sciences Division; Environmental Energy Technologies Division
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 964406
• Report Number(s): LBNL-2175E
• Journal Information: Agricultural and Forest Meteorology, Journal Name: Agricultural and Forest Meteorology; ISSN AFMEEB; ISSN 0168-1923
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
BIOSPHERE
CARBON
CARBON DIOXIDE
CLIMATES
ECOSYSTEMS
RESOLUTION
SATELLITES
SPECTROMETERS