Abstract
The problem of assessing the state of the sea surface by combining satellite and ship measurements is considered. Information about the strength and direction of the wind at the sea surface is important to ensure safe navigation and planning of vessel transit routes. It is of key importance for weather forecasting and excitement. Wind data is traditionally obtained from passing ships and buoys. Ship data covers only limited areas of the World Ocean and is received unevenly, buoy data is highly sparse, which makes it impossible to obtain an adequate picture of the distribution of atmospheric currents. The use of remote sensing satellites has made it possible to increase the density of measurements of wind speed and direction by orders of magnitude, and the relevance of the data obtained. However, satellite measurements can be distorted. In particular, the influence of atmospheric precipitation (rain) can give a two-fold error in measuring wind speed. Strong and weak winds also create problems: in strong winds, the measured data underestimate the true wind speed, in weak winds they overestimate. A method for correcting satellite data on wind speed and direction is proposed. The essence of the method is to use subsatellite ship measurements in conjunction with satellite information. Knowing the weather data measured locally (from the ship), it is possible to calculate regression parameters for correcting satellite data. By applying regressions with calculated parameters to satellite images in the water area, it is possible to obtain more accurate weather data in the area of the vessel's route. The results of calculations based on real satellite and on-board data in the waters of the Sea of Okhotsk are presented. A polynomial of the second degree is taken as a regression function. It is shown that the correction using subsatellite ship measurements more accurately characterizes the wave than the data directly received from the satellite.
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More From: Vestnik of Astrakhan State Technical University. Series: Marine engineering and technologies
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