{'fraction_non_alphanumeric': 0.016300940438871474, 'fraction_numerical': 0.010031347962382446, 'mean_word_length': 5.384, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Development of sea surface temperature retrieval algorithm for INSAT-3D

Radiative transfer simulation based study was carried for developing sea surface temperature algorithms for ISRO's next geostationary satellite INSAT-3D that will be similar to GOES-9 configuration. Characterization of Indian tropical marine atmosphere was done by utilising the surface and atmospheric parameters like temperature, pressure and humidity observed onboard research vessels, covering entire Indian oceans. These parameters were further perturbed in order to achieve the full temporal and spatial variability in the Indian region. 1392 such atmospheric profiles were generated as input to the radiative transfer model. Brightness temperatures for INSAT-3D imager and sounder channels were simulated for these profiles. Various combinations of the channels suitable for sea surface temperature and total water vapor estimation were considered and depending on the statistical parameters and retrieval errors, daytime and nighttime SST retrieval equations were finalised. These equations were applied to GOES-9 data over eastern pacific and the retrieved SST fields were validated with insitu ship observations. The rms error achieved was ~ 0.68 K. Finally SST retrieval equations were suggested for INSAT-3D. The advantage of frequent sampling by geostationary satellites was also demonstrated by studying the diurnal variability of SST and improving the cloud free SST fields using INSAT-3A data. It was found that cloud free fields can be increased to ~ 25% in a day by compositing eight images for that day.