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But SST is also important for management of fishery, ocean acoustic communication, and the science including studies of climate and marine life. To \"blend\" the SST data from many different satellite is a tricky business. Satellite-based environmental data are usually irregularly sampled and always noisy. Every satellite has a unique sensor that measures SST. The infra-red (IR) type sensor can offer a very high resolution (down to 1 km in horizontal distance) but suffer from contamination by clouds and aerosols that block the signal. The micro-wave (MW) measurements are more reliable because of cloud-penetrating coverage but are coarser (25 km) in resolution and are not useful along the coasts due to contamination from land.So we are interested in making use of the best characteristics of each sensor data — be it resolution or coverage — and finding an optimal and objective ways to fill the data-voids under the clouds and near the coasts. || ", "release_date": "2013-03-14T00:00:00-04:00", "update_date": "2025-02-02T23:24:25.663322-05:00", "main_image": { "id": 427641, "url": "https://svs.gsfc.nasa.gov/vis/a030000/a030000/a030008/large_cenlon180_rotate_multi_bm_frame00001_searchweb.png", "filename": "large_cenlon180_rotate_multi_bm_frame00001_searchweb.png", "media_type": "Image", "alt_text": "Multiscale Ultra Resolution Sea Surface Temperature on a rotating globe.", "width": 320, "height": 180, "pixels": 57600 } } ], "sources": [], "products": [], "newer_versions": [], "older_versions": [], "alternate_versions": [] }