The study is carried out to estimate the satellite-derived partial pressure of carbon dioxide (pCO2) in the Bay of Bengal (BoB) and Arabian Sea (AS) using sea surface temperature (SST)-based algorithm. The relationship of satellite-derived pCO2 with SST and chlorophyll has been understood in different seasonal months and years. The SST images are generated for the Bay of Bengal and Arabian Sea during two distinct seasonal months, December 2013 and 2014 and April 2014 and 2015. The daily and 8 days, monthly composite SST images are generated using INSAT-3D, MODIS-Aqua, and GHRSST datasets. The corresponding overpass time of MODIS-Aqua and INSAT-3D 13:30Hrs SST data has been archived. The SST is observed in the range of 24–32 °C. The SST-based pCO2 algorithm is applied over the northern Indian ocean and the pCO2 variability in two different seasons monitored. The pCO2 ranged around 350–750 μatm. The INSAT-3D derived 30-min time interval images processed on intra-day basis having 48 passes per day. The pCO2 images observed directly proportional relationship with the SST images during summer and inverse trend during winter. With the increase in SST by 1–2 °C, there has been increase in pCO2 by 2–5% during summer. The comparison of pCO2 on weekly and monthly time scales using the INSAT-3D, MODIS and GHRSST data has been observed to be interesting and showed matching trend. This exemplifies the preliminary study to understand the hourly, daily, weekly, monthly, and seasonal trend of SST and pCO2 variability in the northern Indian Ocean basins using satellite datasets. The MODIS-Aqua monthly composite chlorophyll images indicate that the high chlorophyll (0.8–1.4 mg m−3) patches are matching well with the high pCO2 concentration (400–450 μatm) patches during winter month and similar trend is not observed during summer month. Main findings of the paper are to have the pCO2 estimation using SST data in Indian scenario using multiple satellite datasets from MODIS-Aqua, INSAT, and GHRSST datasets and the comparison with ocean productivity using satellite-derived chlorophyll data. This study has a strong relevance in terms of ocean acidification monitoring using satellite data- and model-based time-series map generation. The study is important from the point of view of air-sea interaction, ocean acidification, and ocean biogeochemistry. The in situ pCO2 measurements, data validation, and fine-tuning would rely on the scope for regional algorithm development as future study and trend analysis from climate change perspective.
Sarangi R. K., 2025. Remote sensing observation of sea surface temperature (SST) and pCO2 over the Bay of Bengal and Arabian Sea and its relation with chlorophyll variability. In: Barathan B. P., Velupillai V., Perumal S. & Kannan K. (Eds.), Navigating Climate Change: Impacts on Biodiversity and Ecosystem Resilience, pp. 447-466. Singapore: Springer Nature Singapore. Chapter.
