STATISTICAL ITERATIVE SCHEME FOR ESTIMATING ATMOSPHERIC RELATIVE-HUMIDITY PROFILES

Estimation of atmospheric relative humidity profiles using passive rem ote sensing techniques is difficult when the temperature profile is no t well known, and such retrievals approach singularity when the atmosp here is nearly isothermal. A retrieval method that is more robust near isothermal regions and temperature inversions is described here. Its robust character results from an iterative combination of statistical methods based on a priori data, which stabilize the effects of any sin gularities, and physical methods that reflect the nonlinear character of the equation of radiative transfer and the dependence of measuremen ts on uncertain surface reflectivities and temperature profiles. This method can be used to interpret data from meteorological satellites. I t was tested extensively using simulated clear-sky microwave observati ons 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 sensiti ve to the atmospheric temperature profile. Humidity profiles from the tropical, midlatitude, and arctic regions were retrieved. Relative hum idity profiles retrieved using the statistical iterative method typica lly 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 pol ar regions, and represented significantly better performances than a l inear statistical retrieval method.