Sea Surface Wind Speed Retrieval Based on X-Band SAR Satellites on the Coast of Korean Peninsula

Ocean status information, such as sea surface wind speed, is an important indicator for determining the degree of navigational risks. Therefore, it is essential to find out the information rapidly on the state of the ocean to respond to events in the ocean. However, some problems make it difficult to obtain ocean condition information: the limited number of ground observation instruments, the images of low spatial resolution, the long data acquisition times. Synthetic Aperture Radar (SAR) satellite solve some of these problems. SAR satellite images can observe the region of interest at high resolution in all weather condition. In addition, SAR images are useful for identifying ocean surface variables because they can directly observe the degree of roughness and scattering in the ocean. Due to the high utilization of these SAR characteristics in ocean regions that require continuous monitoring, research has recently been actively conducted to estimate ocean status information using SAR images. Furthermore, the Korean government recently plans to operate a number of SAR cluster satellites, and expects to conduct marine monitoring at a high spatiotemporal resolution by utilizing the images of these satellites. To provide users with images taken from SAR cluster satellites, this project has been developing a satellite image utilization platform. Several information from the ocean will be provided through the platform, and technical research is being conducted to monitor the marine situation and respond to accidents on the Korean Peninsula and surrounding seas. One of the algorithms on the platform is the sea surface wind speed estimation algorithm based on the SAR images. In this study, we developed the algorithms for estimating the sea surface wind speed on the coast of Korean peninsula using X-band SAR satellite images. We used the KOMPSAT-5 and ICEYE SAR images because these satellites are in the same band as the cluster satellites to be launched. The XMOD model, one of the geophysical model function (GMF), was used to calculate the wind speed from the SAR image. We updated the model's empirical coefficient of the model by corresponding each KOMPSAT-5 and ICEYE SAR images to ocean observation buoy data. In addition, the numerical model wind direction information was used and applied for wind direction input information required for the XMOD model. In order to analyze the performance of the developed algorithm, the wind speed was verified with the ocean buoy observation on the coast of the Korean peninsula. When the cluster SAR satellites are launched in the future, algorithm optimization will be performed by applying the new satellite images to the wind speed estimation algorithm through updating the coefficient in the XMOD model. Consequently, the developed algorithm will be linked to a satellite image utilization platform and used by users.