The third generation wind-wave model Mike21-SW was used to study spectral characteristics of waves generated by the historical Cyclone Gonu in June 2007 along and off the Iranian coasts on the northern Oman Sea. The model was forced with the cyclone wind field generated using a Holland (1980) model based on cyclone data obtained from the Joint Typhon Warning Center (JTWC). The wave model was calibrated for the northern Oman Sea using bulk and spectral wave data at a station out of the Chabahar Bay. Evolution of directional-frequency spectra during the cyclone was investigated for two locations near the entrance and off the Chabahar Bay. At the offshore station, energy was contributed to the spectrum over an approximately 180 degree directional span that included different local and remotely generated waves. As the cyclone proceeded northwestward, all spectral directions continuously rotated in the clockwise direction at both locations. Frequency spectra at these locations were investigated for four different times corresponding to different locations of Cyclone's eye and were justified using the sea growth parameter of the Joint North Sea Wave Project (JONSWAP) experiment. Using the modified JONSWAP parameters for hurricane conditions resulted in a frequency spectrum consistent with simulation results.

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Suspended particulate matter (SPM) is regarded as an energy source and a water quality indicator in coastal and marine ecosystems. To estimate SPM from ocean color sensors and land observing satellites, an accurate and robust atmospheric correction must be done. We evaluated the capabilities of ocean color and land observing satellite for estimation of SPM concentrations over Louisiana continental shelf in the northern Gulf of Mexico, using the Operational Land Imager (OLI) on Landsat-8, and Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua. In high turbidity waters, the traditional atmospheric correction algorithms based on near-infrared (NIR) bands underestimate SPM concentrations due to the inaccurate removal of the aerosol contribution to the top of atmosphere signals. Therefore, atmospheric correction in high turbidity waters is a challenge. Four atmospheric correction algorithms were implemented on remote sensing reflectance (Rrs) values to select suitable atmospheric correction algorithms for each sensor in our study area. We evaluated short-wave infrared (SWIR) and NIR atmospheric correction algorithms on Rrs products from Landsat-8 OLI and Management Unit of the North Sea Mathematical Models (MUMM) and SWIR.NIR atmospheric correction algorithms on Rrs products from MODIS-Aqua. SPM was retrieved from a band-ratio SPM-retrieval algorithm for each sensor. Our results indicated that SWIR atmospheric correction algorithm was the suitable algorithm for Landsat-8 OLI and SWIR.NIR atmospheric correction algorithm outperformed MUMM algorithm for MODIS.

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