The time series of satellite infrared AVHRR data from 1985 to 2005 has been used to produce a daily series of optimally interpolated SST maps over the regular grid of the operational MFSTEP OGCM model of the Mediterranean basin. A complete validation of this OISST (Optimally Interpolated Sea Surface Temperature) product with in situ measurements has been performed in order to exclude any possib...

Abstract In this paper, we perform the super-resolution of sea surface temperature data with enhanced generative adversarial network (ESRGAN), which is a deep neural network-based single-image (SISR) method that uses (GAN). We generate high-quality ESRGAN and convolutional (SRCNN) residual-in-residual dense block (RRDBNet) methods, are based on networks (CNNs). The images generated these method...

This study investigates the impact of sea surface temperature (SST) on forecast two typhoons, which consecutively hit South Korea in 2020. SST data were obtained from Daily Optimum Interpolation Sea Surface Temperature (OISST) version 2 and HYbrid Coordinate Ocean Model/Navy Coupled Data Assimilation (HYCOM/NCODA; GLBy0.08/expt_93.0). When verified using situ observational data, OISST did not a...

predicting the quality of water and air is a particular challenge for forecasting systems that support them. in order to represent the small-scale phenomena, a high-resolution model needs accurate capture of air and sea circulations, significant for forecasting environmental pollution. data assimilation is one of the state of the art methods to be used for this purpose. due to the importance of...

Despite the widely recognized warming of New England Continental Shelf (NES), climate patterns shelf’s economically and ecologically important coastal environments remain less examined. Here we use a satellite sea-surface temperature (SST) analysis gridded on 0.05°C spatial resolution to show, for first time, existence warm cold spot in environs Cape Cod, Massachusetts amid NES past 15 years. T...

Abstract Using high-resolution NOAA Optimum Interpolation sea surface temperature (OISST) data, the temporal and spatial characteristics of typical oceanic fronts in past 39 years, including Oyashio front, Gulf Stream Peru current front southern Indian Ocean polar are analyzed. The results show that intensities four have all strengthened, among which is most significant South weakest. movement ...

A radial basis function network (RBFN) method is proposed to reconstruct daily Sea surface temperatures (SSTs) with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°E–135°E) are selected when the tropical storm Hagibis arrived in June 2014, and these SST samples are obtained from the OISST products accordi...

The present study proposes a sensor selection method based on the proximal splitting algorithm and A-optimal design of experiment using alternating direction multipliers (ADMM) algorithm. performance proposed was evaluated with random problem compared previously methods such as greedy convex relaxation. is better than an existing in terms A-optimality criterion. In addition, requires longer com...

The trend of global Sea Surface Temperature (SST) has attracted widespread attention in several ocean-related fields such as warming, marine environmental protection and biodiversity. surface temperature is influenced by climate change; with the accumulation data from ocean remote sensing observations year year, many scholars have started to use deep learning methods for SST prediction. In this...