In this paper, a variational data assimilation approach is used to assimilate the rain rate (RR) data together with precipitable water (PW) measurements from the Experiment on Rapidly Intensifying Cyclones over the Atlantic (ERICA) (4-5 January 1989; IOP-4 cyclone). The PW and RR, which are assimilated into the Pennsylvania State University-NCAR Mesoscale Model version 5 (MM5), are computed from the Special Sensor Microwave/Imager (SSM/I) raw data-brightness temperatures-via a statistical

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... sion method. The SSM/Iderived RR and PW at 0000 UTC and/or 0930 UTC are assimilated into the MM5. The data at 2200 UTC are used for verification of the prediction results. Numerical experiments are performed using the MM5. Two horizontal resolutions of 50 km and 25 km are used in the authors' studies. Comparisons are made between the experiments with and without SSM/I-measured PW and RR observations. Results from these experiments showed the following. These results show that the SSM/I-measured PW and RR have great potential to improve the initial conditions for a mesoscale model, especially over the data-sparse oceanic regions. The case study carried out in this paper shows that the variational assimilation of SSM/I-measured PW and RR data produces adjustments in the model states and results in a positive impact on the forecast of the ERICA IOP-4 cyclone. Future experimentation is planned to assimilate the brightness temperature directly into a mesoscale model.