| description abstract | The application of Special Sensor Microwave/Imager (SSM/I) multiparameter satellite retrievals in operational weather analysis and forecasting is addressed. More accurate multiparameter satellite retrievals are now available from an SSM/I neural network algorithm. It also provides greater areal coverage than some of the initial algorithms. These retrievals (ocean surface wind speed, columnar water vapor, and columnar liquid water), when observed together, provide a meteorologically consistent description of synoptic weather patterns over the oceans. Three SSM/I sensors are currently in orbit, which provide sufficient amounts of data to be used in a real-time operational environment. Several examples are presented to illustrate that important synoptic meteorological features such as fronts, storms, and convective areas can be identified and observed in the SSM/I fields retrieved by the new algorithm. The most recent version of the neural network algorithm retrieves simultaneously four geophysical parameters: ocean-surface wind speed, columnar water vapor, columnar liquid water, and sea surface temperature, allowing the knowledge of each variable to contribute directly to better accuracy in ocean surface wind speed retrievals. The neural network wind speed data were recently incorporated as a part of operational Global Data Assimilation System at the National Centers for Environmental Prediction. | |
