The eddy covariance technique provides long-term continuous monitoring of site-specific net ecosystem exchange of CO 2 (NEE) across a large range of forest types. However, these NEE estimates only represent fluxes at the scale of the tower footprint and need to be scaled up to quantify NEE over regions or continents. In the present study, we expanded a method developed previously and generated a new NEE model exclusively based on the Moderate Resolution Imaging Spectroradiometer (MODIS) products, including enhanced vegetation index (EVI), land surface water index (LSWI), land surface temperature (LST) and Terra nighttime LST'. This method, in our previous research, provided substantially good predictions of NEE and well reflected the seasonal dynamics of the deciduous broadleaf forest at the Harvard forest site. Studying NEE of forests in the middle-latitude regions of the Northern Hemisphere is significant because it may help to understand the 'missing carbon sink' from terrestrial ecosystems. In this study we selected eight eddy flux sites to represent the major forest ecosystems in the northern United States. Compared with the model based on a single site, we also established the general models that apply to evergreen needleleaf forest (ENF) and deciduous broadleaf forest (DBF), respectively. The results showed that our simpler model based entirely on MODIS products promised well to estimate NEE by the eddy covariance technique. The modeled annual mean NEE from DBF deviated from the measured NEE by 44.4%, whereas the modeled NEE from ENF was extremely close to the measured NEE within 5.5%. In the end, we also validated both general models for ENF and DBF using independent flux sites. It demonstrated this method performed well for estimating NEE.
- Eddy covariance