Retrieving surface parameters for climate models from Moderate Resolution Imaging Spectroradiometer (MODIS)-Multiangle Imaging Spectroradiometer (MISR) Albedo Products

We present a computer efficient software package enabling us to assimilate operational remote sensing flux products into a state of the art two-stream radiation transfer scheme suitable for climate models. This package implements the adjoint and Hessian codes, generated using automatic differentiation techniques, of a cost function. This cost function balances two main contributions, namely 1) the deviation from the a priori knowledge on the model parameter values and, 2) the misfit of the observed remote sensing fluxes the two-stream model simulations. The individual weights of these contributions are specified notably via covariance matrices of the uncertainties in the a priori knowledge on the model parameters and the measurements. The proposed procedure delivers a Gaussian approximation of the probability density functions of the retrieved model parameter values. This is achieved by evaluating the Hessian of the cost function at its minimum. The a posteriori covariance matrix is further exploited to evaluate, in turn, the posterior probability density functions of the radiant fluxes simulated by the two stream model, including those that are not measured, e.g., the fraction of radiation absorbed in the ground. A series of applications are conducted over mid-latitude Earth Observing System (EOS) validation sites using MODIS and MISR broadband surface albedo products. It turns out that the limited differences between these two albedo sets may translate into discernible signatures on some retrieved model parameters. Meanwhile, adding the JRC-FAPAR SeaWiFS products into the measurement configuration yields a very significant reduction of uncertainties on the model parameters, such as the Leaf Area Index (LAI). Results from these applications overall indicate that the products retrieved from the proposed two-stream inversion procedure 1) exhibit much less variability than those generated by the operational MODIS and MISR algorithms for such quantities as the LAI and FAPAR and 2) are in very good agreement with the available ground-based estimates.

PINTY Bernard;  LAVERGNE Thomas;  VOSSBECK Michael;  KAMINSKI Thomas;  AUSSEDAT Ophelie;  GIERING Ralf;  GOBRON Nadine;  TABERNER Malcolm;  VERSTRAETE Michel;  WIDLOWSKI Jean-Luc; 

2007-06-07

AMER GEOPHYSICAL UNION

JRC36167

https://publications.jrc.ec.europa.eu/repository/handle/JRC36167,