L: cost function for VPRM parameterization

In Timothy-W-Hilton/VPRMLandSfcModel: R implementation of VPRM with parameter estimation

cost function for VPRM parameterization

Description

calculate sum of squared errors (SSE) for VPRM NEE, given a set of VPRM parameters and a a set of NEE observations.

Usage

L(par, driver_data, model_form = "Mahadevan07")

Arguments

par	four-element numeric vector containing lambda, alpha, beta, PAR_0 (in that order)
driver_data	May be a VPRM_driver_data object or a data frame. If a data frame, driver_data must contain the variables Tscale, Pscale, Wscale, EVI, and PAR, and NEE_obs.
model_form	string, optional; form of VPRM model to use. Options are "Mahadevan07" (default) to use the VPRM formulation of Mahadevan et al. (2007), or "urban" to use the urbanVPRM formulation of Hardiman et al. (2017). If set to "urban", the driver data must include variables ISA proportion (impervious surface area, 0.0 to 1.0) and refEVI (reference EVI).

Details

"L" abbreviations likelihood; currently SSE is a standin for a statistically proper likelihood function for land surface model residuals.

Value

sum of squared errors for VPRM NEE residuals for the specified parameters and NEE observations.

Author(s)

Timothy W. Hilton

References

Mahadevan, P., Wofsy, S., Matross, D., Xiao, X., Dunn, A., Lin, J., Gerbig, C., Munger, J., Chow, V., and Gottlieb, E.: A satellite-based biosphere parameterization for net ecosystem CO2 exchange: Vegetation Photosynthesis and Respiration Model (VPRM), Global Biogeochem. Cy., 22, GB2005, doi:10.1029/2006GB002735, 2008.

Hardiman, B. S., Wang, J. A., Hutyra, L. R., Gately, C. K., Getson, J. M., & Friedl, M. A. (2017). Accounting for urban biogenic fluxes in regional carbon budgets. Science of The Total Environment, 592, 366–372. https://doi.org/10.1016/j.scitotenv.2017.03.028

Timothy-W-Hilton/VPRMLandSfcModel documentation built on Nov. 17, 2024, 1:56 p.m.