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  • Author or Editor: Suzanne W. Seemann x
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Suzanne W. Seemann, Jun Li, W. Paul Menzel, and Liam E. Gumley

Abstract

The algorithm for operational retrieval of atmospheric temperature and moisture distribution, total column ozone, and surface skin temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) longwave infrared radiances is presented. The retrieval algorithm uses clear-sky radiances measured by MODIS over land and ocean for both day and night. The algorithm employs a statistical retrieval with an option for a subsequent nonlinear physical retrieval. The synthetic regression coefficients for the statistical retrieval are derived using a fast radiative transfer model with atmospheric characteristics taken from a dataset of global radiosondes of atmospheric temperature, moisture, and ozone profiles. Evaluation of retrieved total precipitable water vapor (TPW) is performed by a comparison with retrievals from the Geostationary Operational Environmental Satellite (GOES) sounder, radiosonde observations, and data from ground-based instrumentation at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) in Oklahoma. Comparisons over one and one-half years show that the operational regression-based MODIS TPW agrees with the microwave radiometer (MWR) TPW at the ARM CART site in Oklahoma with an rmse of 4.1 mm. For moist cases, the physical retrieval improves the retrieval performance. For dry atmospheres (TPW less than 17 mm), both physical and regression-based retrievals from MODIS radiances tend to overestimate the moisture by 3.7 mm on average. Global maps of MODIS atmospheric-retrieved products are compared with the Special Sensor Microwave Imager (SSM/I) moisture and Total Ozone Mapping Spectrometer (TOMS) ozone products. MODIS retrievals of temperature, moisture, and ozone are in general agreement with the gradients and distributions from the other satellites, and MODIS depicts more detailed structure with its improved spatial resolution.

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Suzanne W. Seemann, Eva E. Borbas, Robert O. Knuteson, Gordon R. Stephenson, and Hung-Lung Huang

Abstract

A global database of infrared (IR) land surface emissivity is introduced to support more accurate retrievals of atmospheric properties such as temperature and moisture profiles from multispectral satellite radiance measurements. Emissivity is derived using input from the Moderate Resolution Imaging Spectroradiometer (MODIS) operational land surface emissivity product (MOD11). The baseline fit method, based on a conceptual model developed from laboratory measurements of surface emissivity, is applied to fill in the spectral gaps between the six emissivity wavelengths available in MOD11. The six available MOD11 wavelengths span only three spectral regions (3.8–4, 8.6, and 11–12 μm), while the retrievals of atmospheric temperature and moisture from satellite IR sounder radiances require surface emissivity at higher spectral resolution. Emissivity in the database presented here is available globally at 10 wavelengths (3.6, 4.3, 5.0, 5.8, 7.6, 8.3, 9.3, 10.8, 12.1, and 14.3 μm) with 0.05° spatial resolution. The wavelengths in the database were chosen as hinge points to capture as much of the shape of the higher-resolution emissivity spectra as possible between 3.6 and 14.3 μm. The surface emissivity from this database is applied to the IR regression retrieval of atmospheric moisture profiles using radiances from MODIS, and improvement is shown over retrievals made with the typical assumption of constant emissivity.

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