Statistical iterative scheme for estimating atmospheric relative humidity profiles

Estimation of atmospheric relative humidity profiles using passive remote sensing techniques is difficult when the temperature profile is not well known, and such retrievals approach singularity when the atmosphere is nearly isothermal. A retrieval method that is more robust near isothermal regions and temperature inversions is described. Its robust character results from an iterative combination of statistical methods based on a priori data, which stabilize the effects of any singularities, and physical methods that reflect the nonlinear character of the equation of radiative transfer and the dependence of measurements on uncertain surface reflectivities and temperature profiles. This method can be used to interpret data from meteorological satellites. It was tested extensively using simulated clear-sky microwave observations from space at 89 GHz, 166 GHz, and three frequencies near the 183-GHz water vapor resonance and the 60-GHz oxygen band, which is sensitive to the atmospheric temperature profile. Humidity profiles from the tropical, midlatitude, and arctic regions were retrieved. Relative humidity profiles retrieved using the statistical iterative method typically had errors between 5 and 10% in the 300-1000 mbar pressure region. These errors were somewhat less in the tropics and greater in the polar regions, and represented significantly better performances than a linear statistical retrieval method