Possibility of predicting surface boundary layer winds over coastal land and ocean has been explored in this paper. Prediction has been effected using a modern nonlinear data-fitting algorithm known as genetic algorithm (GA) based on the Darwinian evolutionary theory. Time series of tower-mounted anemometer measured wind speed has been used for carrying out forecast over land while time series of satellite scatterometer derived winds has been used for forecast over coastal ocean. The prediction over land can feed into weather advisories required for rocket launching stations while prediction over coastal ocean can be of use in offshore industries.
Spaceborne radar scatterometers operating in microwave frequency bands have several science and operational applications in Oceanography, meteorology, agricultural and geophysical sciences. The basic parameter measured by a scatterometer is the Backscattering coefficient (&psigma;^0) for a certain frequency, polarization and observational geometry. Before addressing a specific application, it is needed that the &psigma;^0 signatures be analyzed over natural, undisturbed and uniform/quasi-uniform target areas. As a prelude to ISRO's forthcoming OceanSat-II mission, carrying a Ku-band scatterometer, QuikSCAT scatterometer measured &psigma;^0 data are analyzed over its dynamical range using the global natural targets.