Neural network based retrieval of wind and temperature Profiles from combined surface and satellite observations

Neural network techniques were used to retrieve temperature and wind from a combination of NOAA polar orbiter satellite observations and ground-based measurements. Back-propagation neural networks were constructed which used satellite radiances, simulated microwave radiometer measurements, and other ground-based measurements as inputs and produced temperature and wind profiles as outputs. The network was trained with rawindsonde measurements used as truth-values.