Assimilation of the aqua/AMSR-E data to numerical weather predictions

Abstract

An application of satellite information to numerical weather predictions (NWPs) is one of the most expected achievements in satellite remote sensing. In some meteorological agencies, the data of the space-borne microwave radiometers (MWRs) have been used in their operational weather forecasts. The Japan Meteorological Agency (JMA) introduced the assimilation system of rain rate (RR) and total column precipitable water (TCPW) derived from Special Sensor Microwave/Imager (SSM/I) and TRMM microwave imager (TMI) for the operational mesoscale model in October 2003 and we are trying some observation system experiments about TCPW assimilation using the global model. These water-related data are very useful to detect tropical and extratropical cyclones over ocean. The advanced microwave scanning radiometer (AMSR) for EOS (AMSR-E) on board the Aqua satellite was launched in May 2002. The AMSR-E measures several parameters related to global water circulation at 1:30 a.m./p.m. in local time in which no MWR observation is implemented so far. The MWR constellation composed of AMSR-E, SSM/I, and TMI is satisfactory for global observation at six-hour refresh rate. The refresh rate is essential to give homogeneous initial field for the Global Model and to detect and assimilate the signal of severe weather phenomena with short lifetime such as heavy rain for the mesoscale model. We are investigating the impacts of the retrieved TCPW and RR by the MWR constellation with the JMA NWP systems. In the global model experiments, the homogeneous data distribution with the constellation improves the performance of the data assimilation and the forecast. In the mesoscale model experiments, the frequent observation with the constellation succeeds in detecting the signal of heavy rain and improving the short-range rainfall forecast for disaster prevention.