Publications

Sarangi, RK; Devi, KN (2017). Space-based observation of chlorophyll, sea surface temperature, nitrate, and sea surface height anomaly over the Bay of Bengal and Arabian Sea. ADVANCES IN SPACE RESEARCH, 59(1), 33-44.

Abstract
Monthly chlorophyll and sea surface temperature (SST) images were generated using MODIS-Aqua data sets during 2014 and 2015 in the Bay of Bengal and Arabian Sea. The in situ data-based nitrate algorithm was used to generate nitrate images by using the satellite derived chlorophyll and SST images. To link ocean productivity with the sea surface features and sea level anomaly, the Indo-French altimeter mission SARAL-ALTTKA-derived sea surface height anomaly (SSHa) data sets were processed and maps were generated. The monthly average chlorophyll concentration ranged from 0.001 to 3.0 mg m(-3), SST ranged from 24 to 32 degrees C, nitrate concentration ranged from 0.01 to 6.0 mu M, and overall SSH anomaly ranged from -52 to +40 cm. Nitrate concentration was observed to be high (3-5 mu M) during December January, possibly due to convective eddies and winter cooling as well as atmospheric aerosols and dust inducing ocean productivity. The nitrate concentration was observed to be associated more with chlorophyll than SST, as nitrate inherently enhances the ocean chlorophyll and productivity, acting as proxy. The SSH anomaly showed irregular features and depicting few eddies, upwelling, and ocean circulation features. The low SSHa was mostly due to high chlorophyll concentration. It was observed that the low SST (similar to 24-26 degrees C) is attributed to high chlorophyll concentration (1.5-3.0 mg m(-3)) over the study area. The lag phase and enhancement in chlorophyll mean during September was due to the decrease in average SST during August. The SSHa showed seasonal trend over the study area during the monsoon period with observation of negative anomaly. Arabian Sea was found to have more negative SSH anomaly monthly mean values than Bay of Bengal. The impact and interrelationship of SSHa indicated better relationship with chlorophyll than with nitrate and SST, as observed from multiple regression analysis. The analysis of variance (ANOVA) results between the 2-year monthly data showed that the interannual variability is lowest for SST, followed by chlorophyll (p = 0.002), SSHa (p = 0.053), and nitrate (p = 0.068). (C) 2016 COSPAR. Published by Elsevier Ltd. All rights reserved.

DOI:
10.1016/j.asr.2016.08.038

ISSN:
0273-1177