Pan Liang

Evaluation of modeled microwave land surface emissivities with satellite-based estimates

An accurate estimate of the microwave surface emissivity is necessary for the retrieval of atmospheric quantities from microwave imagers or sounders. The objective of this study is to evaluate the microwave land surface emissivity modeling of the Community Radiative Transfer Model (CRTM), providing quantitative statistic information for further model improvements. First, the model-simulated emissivity is compared to emissivity estimates derived from satellite observations (TELSEM, Tool to Estimate Land Surface Emissivities at Microwaves). The model simulations agree reasonably well with TELSEM over snow-free vegetated areas, especially at vertical polarization up to 40 GHz. For snow-free surfaces, the mean difference between CRTM and TELSEM emissivities at vertical polarization is lower than 0.01 below 40 GHz and increases to 0.02 at 89 GHz. At horizontal polarization, it increases with frequency, from 0.01 at 10.6 GHz to 0.04 at 89 GHz. Over deserts and snow, larger differences are observed, which can be due to the lack of quality inputs to the model in these complex environments. A further evaluation is provided by comparing brightness temperature (Tbs) simulations with AMSR-E observations, where CRTM emissivity and TELSEM emissivity are coupled into a comprehensive radiative transfer model to simulate the brightness temperatures, respectively. The comparison shows smaller RMS errors with the satellite-derived estimates than with the model, despite some significant bias at midday with the satellite-derived emissivities at high frequencies. This study confirms and extends to the global scale previous evaluations of land surface microwave emissivity model. It emphasizes the needs for better physical modeling in arid regions and over snow-covered surfaces.

Fast and Accurate Radiative Transfer in the Thermal Regime by Simultaneous Optimal Spectral Sampling over All Channels

AbstractThe optimal spectral sampling (OSS) method provides a fast and accurate way to model radiometric observations and their Jacobians (required for inversion problems) as a linear combination of monochromatic quantities. The method is flexible and versatile with respect to the treatment of variable constituents, and the method’s fidelity to reference line-by-line (LBL) calculations is tunable. The focus of this paper is on the modeling of radiances from hyperspectral infrared sounders in both clear and cloudy (scattering) atmospheres for application to retrieval and data assimilation. In earlier articles, the authors presented an approach that performed spectral sampling for each channel sequentially. This approach is particularly robust in terms of preserving fidelity to LBL models and yields ratios of monochromatic calculations per channel of approximately 1:1 for such hyperspectral sensors as the Infrared Atmospheric Sounding Interferometer (IASI) or the Atmospheric Infrared Sounder (AIRS) (when tu...

Sources of discrepancies between satellite‐derived and land surface model estimates of latent heat fluxes

Monthly-average estimates of latent heat flux have been derived from a combination of satellite-derived microwave emissivities, day-night differences in land surface temperature (from microwave AMSR-E), downward solar and infrared fluxes from ISCCP cloud analysis, and MODIS visible and near-infrared surface reflectances. The estimates, produced with a neural network, were compared with data from the Noah land surface model, as produced for GLDAS-2, and with two alternative estimates derived from different datasets and methods. Areas with extensive, persistent, substantial discrepancies between the satellite and land surface model fluxes have been analyzed with the aid of data from flux towers. The sources of discrepancies were found to include problems with the model surface roughness length and turbulent exchange coefficients for midlatitude cropland areas in summer, inaccuracies in the precipitation data that were used as forcing for the land surface model, and model underestimation of transpiration in some forests during dry periods. At the tower sites analyzed, agreement with tower data was generally closer for our satellite-derived fluxes than for the land surface model fluxes, in terms of monthly averages.

An AMSR-E Land Surface Microwave Emissivity Database

Accurate knowledge of local surface emissivity is required for lower troposphere microwave remote sensing over land and for land surface parameter retrievals. Ideally, for a stand-alone microwave system (i.e., without an external source of surface temperature), a priori emissivity accuracies of 0.01 or less are needed to minimize the impact of cloud liquid water on temperature and water vapor retrievals and to improve surface temperature retrievals to 2 K or better. We are developing a system for land surface microwave emissivity retrieval and using it to derive emissivities in the AMSR-E channels over a full year. The system now incorporates both AMSR-E and SSM/I brightness temperatures and MODIS-derived land surface temperature (LST) products. We have examined the temporal variability of retrieved local surface emissivities and describe approaches developed to identify and minimize sources of error in the retrieval. The emissivity retrieval system is a precursor for a dynamic emissivity database to be fully implemented for NPOESS CMIS with coincident VIIRS LST observations available up to six times per day. Keywords-AMSR-E; Aqua; MODIS; CMIS; NPOESS; microwave emissivity; microwave radiometry; 1-D VAR.

Global Microwave Emission Depth Analyses from AMSR-E, SSMI, and MODIS

A global analysis of microwave emission depth signatures shows that the characteristic temporal behaviors associated with subsurface emission in sand deserts carry over to arid and semi-arid regions worldwide. Previous work showed that the greatly reduced diurnal range of SSM/I brightness temperatures compared to skin temperatures in deserts could be explained by microwave effective emission depths that depended on soil type and microwave wavelength. Here, a similar methodology is applied globally with coincident Aqua AMSR-E and MODIS data used in addition to SSM/I, providing a more complete sample of diurnal cycle extremes. The signatures of significant microwave emission depths can be seen to occur in drier regions globally not dominated by dense forest or crop cover-including, for example, the western half of the continental United States, south central Asia, Australia, and southern Africa and South America.