We have developed two methods to determine the tropospheric path delay for microwaves. One uses a dosed form model of the atmosphere in which two parameters are used to describe the decrease in temperature with height and the relation between total pressure and water vapor partial pressure, respectively. The other method uses numerical integration of refractivity profiles, which are computed from temperature and humidity profiles obtained by statistical regression. The two methods have been tested on two sets of observations and compared with simultaneous radio soundings. The best results show an improvement of 10% in one case and 30% in the other compared with a presently used model. Possibilities to improve the statistical model further are discussed. values for the constants k•, k 2 and k3 used by Saasta-file and the surface-correlated profile as estimates of moinen, which differ slightly from the values given by the water vapor profile. It can be seen that the im-Thayer [1974]. provement achieved by surface correlation is large J. W. Marini (internal NASA memorandum, 1974) for lower altitudes and that it becomes gradually modified (27)to smaller with increasing altitude. For further details about minimum-variance estimation see Melsa and AL = [1/f(tp, H)] Cohn [1978]. This method to obtain estimates of temperature (28) and humidity profiles has earlier been used to prosin (EL) + [B/(A + B)]/[sin (EL) + 0.015] vide the initial guess needed in atmospheric profiling ASKNE AND NORDIUS: TROPOSPHERIC DELAY FOR MICROWAVES 383

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Above-ground forest biomass is a significant variable in the terrestrial carbon budget, but is still estimated with relatively large uncertainty. Remote sensing methods can improve the characterization of the spatial distribution and estimation accuracy of biomass; in this respect, it is important to examine the potential offered by new sensors. To assess the contribution of the TanDEM-X mission, eighteen interferometric Synthetic Aperture Radar (SAR) image pairs acquired over the hemi-boreal test site of Remningstorp in Sweden were investigated. Three models were used for interpretation of TanDEM-X signatures and above-ground biomass retrieval: Interferometric Water Cloud Model (IWCM), Random Volume over Ground (RVoG) model, and a simple model based on penetration depth (PD). All use an allometric expression to relate above-ground biomass to forest height measured by TanDEM-X. The retrieval was assessed on 201 forest stands with a minimum size of 1 ha, and ranging from 6 to 267 Mg/ha (mean biomass of 105 Mg/ha) equally divided into a model training dataset and a validation test dataset. Biomass retrieved using the IWCM resulted in a Root Mean Square Error (RMSE) between 17% OPEN ACCESS Remote Sens. 2013, 5 5575 and 33%, depending on acquisition date and image acquisition geometry (angle of incidence, interferometric baseline, and orbit type). The RMSE in the case of the RVoG and the PD models were slightly higher. A multitemporal estimate of the above-ground biomass using all eighteen acquisitions resulted in an RMSE of 16% with R 2 = 0.93. These results prove the capability of TanDEM-X interferometric data to estimate forest aboveground biomass in the boreal zone.

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