• DocumentCode
    2413
  • Title

    Near-Real-Time Availability of Ocean Heat Content Over the North Indian Ocean

  • Author

    Chacko, Neethu ; Dutta, Dibyendu ; Ali, M.M. ; Sharma, Jaswant R. ; Dadhwal, Vinay K.

  • Author_Institution
    Regional Remote Sensing Centre-East, NRSC/ISRO, Kolkata, India
  • Volume
    12
  • Issue
    5
  • fYear
    2015
  • fDate
    May-15
  • Firstpage
    1033
  • Lastpage
    1036
  • Abstract
    Ocean heat content (OHC) is an important parameter in determining the heat flux in the ocean-atmosphere system, which can influence weather systems such as cyclones and monsoons. Hence, regular monitoring of OHC is required, which needs continuous subsurface temperature profiles. Due to the scarcity of in situ temperature profiles in space and time, remotely sensed sea surface temperature (SST) and sea surface height anomalies (SSHAs) are employed in the computation of OHC in the Indian Ocean. OHC derived from in situ temperature profiles from ARGO floats along with collocated SST, SSHA and OHC climatology during the period 2002-2012 are used to estimate OHC700 (heat content up to 700-m depth), using an artificial neural network model. The estimated OHC700 is validated and is found to be significantly correlated with the observed OHC700. Using this approach, OHC700 is being estimated daily on a near-real-time basis, and the products are available at http://bhuvan.nrsc.gov.in/data/download/index.php.
  • Keywords
    climatology; neural nets; ocean temperature; oceanographic regions; remote sensing; AD 2002 to 2012; North Indian Ocean; artificial neural network model; climatology; heat flux; in situ temperature profiles; ocean heat content; ocean-atmosphere system; sea surface height anomalies; sea surface temperature; Artificial neural networks; Atmospheric modeling; Estimation; Heating; Ocean temperature; Sea surface; Artificial neural network; ocean heat content; sea surface height anomaly; sea surface temperature;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2014.2375196
  • Filename
    7001245