Abstract

ARGO program was conceived with an aim to generate near real-time ocean observations as the primary in-situ sources for use in operational oceanography studies. Two decades-long ARGO near-surface temperature data set was used for generating monthly gridded ARGO sea surface temperature (ASST) product on a climatological scale. Data interpolating variational analysis (DIVA) method was employed for generating the product with a spatial resolution of 0.25° x 0.25° for the Tropical Indian Ocean. This monthly ASST product was evaluated using five different climatological SST products derived from in-situ and satellite measurements. Various statistics such as BIAS, RMSE, coefficient of correlation, and skill scores were generated to evaluate the reliability of the ASST product. Further, the ASST product was validated with climatological in-situ SST obtained from RAMA and OMNI moorings deployed in the Indian Ocean. Statistical comparisons showed low BIAS and RMSE, and high correlation and skill scores with most of the buoys locations and the gridded SST products. Results concluded that the near-surface temperature data from ARGO can be used along with other SST data sets in the generation of high-resolution blended SST products.

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