Combined IR-microwave satellite retrieval of temperature and moisture profiles using the ICI inversion system and its application in the MM5 model

Abstract

Radiance measurements from satellites offer the opportunity to retrieve atmospheric variables at much higher horizontal resolution than is presently afforded by in-situ measurements (e.g., radiosondes). However, the accuracy of these retrievals is crucial to their usefulness, and the ill-posed nature of the problem precludes a straightforward solution. A number of retrieval approaches have been investigated, including empirical techniques, coupling with numerical weather prediction models, and data analysis techniques such as regression. In this paper, the inversion coupled with imager (ICI) scheme is used to retrieve vertical temperature and moisture profiles from infrared and microwave brightness temperatures from a polar-orbiting satellite. The bias and root mean square (RMS) deviations were assessed for the winter and summer conditions over land and sea, separately, using the National Center for Environmental Prediction (NCEP) reanalysis data. The results showed the RMS error of temperature in the lower troposphere to be about 2 K. On the other hand, the RMS errors of the moisture profiles are found to be about 1 g kg^-1. However, below 850 hPa the errors were of the order of about 3.5 K and 3 g kg^-1 for the temperature and moisture profiles over the land and about 2.5 K and 2.0 g kg^-1 over the sea. Two numerical experiments are designed, one control simulation without assimilation of observations, and another in which the advanced microwave sounding unit (AMSU) together with high-resolution infrared radiacion sounder (HIRS) retrieved temperature and moisture profiles are assimilated for the prediction of two tropical cyclones, which formed over the Bay of Bengal during 24 to 27 November 2002 and during 16 to 18 May 2004. The model run with assimilation of AMSU and HIRS could simulate the wind and thermodynamic structures associated with a tropical cyclone better than the control run. The spatial pattern of the precipitation simulated by the model with assimilation is in good agreement with the Tropical Rainfall Measuring Mission (TRMM) rainfall observations for the November 2002 cyclone case. The time series of minimum sea level pressure and maximum wind speed simulated by the model run with assimilation are closer to the corresponding observations when compared with the control simulation.