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Harvard Forest EMS Tower (HFR1)

886-Harvard Forest EMS Tower (HFR1)

An air relative-humidity-based evapotranspiration model from eddy covariance data

Yan, H., & Shugart H. H. (2010).  An air relative-humidity-based evapotranspiration model from eddy covariance data. Journal of Geophysical Research. 115(D16), 

Estimating parameters in a land-surface model by applying nonlinear inversion to eddy covariance flux measurements from eight FLUXNET sites

WANG, Y. I. N. G. P. I. N. G., Baldocchi D., Leuning R., Falge E., & Vesala T. (2007).  Estimating parameters in a land-surface model by applying nonlinear inversion to eddy covariance flux measurements from eight FLUXNET sites. Global Change Biology. 13(3), 652 - 670.

Remote sensing data assimilation for a prognostic phenology model

Stöckli, R., Rutishauser T., Dragoni D., O'keefe J., Thornton P. E., Jolly M., et al. (2008).  Remote sensing data assimilation for a prognostic phenology model. Journal of Geophysical Research. 113(G4), 

Environmental and biological controls on the seasonal variations in latent heat fluxes derived from flux data for three forest sites

Schulz, K. (2004).  Environmental and biological controls on the seasonal variations in latent heat fluxes derived from flux data for three forest sites. Water Resources Research. 40(12), 

Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations

Heinsch, F. A., Zhao M., Running S. W., Kimball J. S., Nemani R. R., DAVIS K. J., et al. (2006).  Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Transactions on Geoscience and Remote Sensing. 44(7), 1908 - 1925.

FLUXNET and modelling the global carbon cycle

FRIEND, A. N. D. R. E. W. D., ARNETH A. L. M. U. T., KIANG N. A. N. C. Y. Y., LOMAS M. A. R. K., OGÉE J. É. R. Ô. M. E., RÖDENBECK C. H. R. I. S. T. I. A. N., et al. (2007).  FLUXNET and modelling the global carbon cycle. Global Change Biology. 13(3), 610 - 633.

Combined Simple Biosphere/Carnegie-Ames-Stanford Approach terrestrial carbon cycle model

SCHAEFER, K. E. V. I. N., Collatz J. G., Tans P., Denning S. A., Baker I., Berry J., et al. (2008).  Combined Simple Biosphere/Carnegie-Ames-Stanford Approach terrestrial carbon cycle model. Journal of Geophysical Research. 113(G3), 

An empirical model simulating diurnal and seasonal CO<sub>2</sub> flux for diverse vegetation types and climate conditions

Saito, M., Maksyutov S., Hirata R., & Richardson A. D. (2009).  An empirical model simulating diurnal and seasonal CO2 flux for diverse vegetation types and climate conditions. Biogeosciences. 6(4), 585 - 599.

Toward constraining regional-scale fluxes of CO <sub>2</sub> with atmospheric observations over a continent: 2. Analysis of COBRA data using a receptor-oriented framework

Gerbig, C. (2003).  Toward constraining regional-scale fluxes of CO 2 with atmospheric observations over a continent: 2. Analysis of COBRA data using a receptor-oriented framework. Journal of Geophysical Research. 108(D24), 

Influence of spring phenology on seasonal and annual carbon balance in two contrasting New England forests

Richardson, A. D., HOLLINGER D. Y., DAIL D. B., Lee J. T., MUNGER J. W., & O'keefe J. (2009).  Influence of spring phenology on seasonal and annual carbon balance in two contrasting New England forests. Tree Physiology. 29(3), 321 - 331.