作者: Neethu Chacko , Dibyendu Dutta , M. M. Ali , Jaswant R. Sharma , Vinay K. Dadhwal
DOI: 10.1109/LGRS.2014.2375196
关键词:
摘要: Ocean heat content (OHC) is an important parameter in determining the flux ocean–atmosphere system, which can influence weather systems such as cyclones and monsoons. Hence, regular monitoring of OHC required, needs continuous subsurface temperature profiles. Due to scarcity situ profiles space time, remotely sensed sea surface (SST) height anomalies (SSHAs) are employed computation Indian Ocean. derived from ARGO floats along with collocated SST, SSHA climatology during period 2002–2012 used estimate $\text{OHC}_{700} $ (heat up 700-m depth), using artificial neural network model. The estimated validated found be significantly correlated observed $\text{OHC}_{700}$ . Using this approach, being daily on a near-real-time basis, products available at http://bhuvan.nrsc.gov.in/data/download/index.php