Variational Retrieval of Temperature and Humidity Profiles from TRMM Precipitation Data

Abstract

This paper examines the performance of a one-dimensional variational (1DVAR) assimilation of Tropical Rainfall Measuring Mission satellite-derived surface rainfall rates from the Microwave Imager TMI. Temperature and specific humidity profiles are retrieved that are consistent with both observed and model short-range forecast rain rates. Two atmospheric situations are examined from ECMWF short-range forecasts at TL319L31 resolution. They encompass tropical cyclones, frontal bands, and mesoscale convective systems. Results show that 1DVAR is generally able to find modified profiles within the range of forecast errors (specified from the operational ECMWF statistics) that provide a precipitation field close to observations. Increments of temperature with respect to the background state are small indicating that 1DVAR essentially adjusts specific humidity to modify precipitation amounts. Consistency checks have been defined in order to discard profiles producing too large departures from the observed rainfall rates or having too little sensitivity of model rain rates to changes in temperature and humidity. Moreover, the current 1DVAR approach is unable to modify profiles when the model rain rate is zero and the observed rain rate is nonzero. Sensitivity experiments are performed to the specification of observation errors. Observation errors are increased from 25% of the observed value to 50%. It is shown that 1DVAR is still able to assimilate some information from observations. To decrease the computational cost of 1DVAR, two simplifications are explored:a reduction of the control vector by not including temperature profiles and the use of one background field and one observation field instead of seven for each assimilation window. These two approaches will be further evaluated when 1DVAR products are assimilated in the ECMWF four-dimensional variational system.