• Fulltext


        Click here to view fulltext PDF

      Permanent link:

    • Keywords


      Surface wind speed; data buoy; time series; auto-correlation; microwave radiometer

    • Abstract


      The nature of the inherent temporal variability of surface winds is analyzed by comparison of winds obtained through different measurement methods. In this work, an auto-correlation analysis of a time series data of surface winds measuredin situ by a deep water buoy in the Indian Ocean has been carried out. Hourly time series data available for 240 hours in the month of May, 1999 were subjected to an auto-correlation analysis. The analysis indicates an exponential fall of the autocorrelation in the first few hours with a decorrelation time scale of about 6 hours. For a meaningful comparison between satellite derived products andin situ data, satellite data acquired at different time intervals should be used with appropriate ‘weights’, rather than treating the data as concurrent in time. This paper presents a scheme for temporal weighting using the auto-correlation analysis. These temporal ‘weights’ can potentially improve the root mean square (rms) deviation between satellite andin situ measurements. A case study using the TRMM Microwave Imager (TMI) and Indian Ocean buoy wind speed data resulted in an improvement of about 10%.

    • Author Affiliations


      Abhijit Sarkar1 Sujit Basu1 A K Varma1 Jignesh Kshatriya1

      1. Oceanic Sciences Division, Meteorology and Oceanography Group, Space Applications Centre (ISRO), Ahmedabad, India
    • Dates

  • Journal of Earth System Science | News

    • Editorial Note on Continuous Article Publication

      Posted on July 25, 2019

      Click here for Editorial Note on CAP Mode

© 2022-2023 Indian Academy of Sciences, Bengaluru.