• T V S UDAYA BHASKAR

      Articles written in Journal of Earth System Science

    • Optimal parameters for generation of gridded product of Argo temperature and salinity using DIVA

      RAVI KUMAR JHA T V S UDAYA BHASKAR

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      Determining an oceanographic parameter on regular grid positions, using a set of data at random locations both in space and time, is the most sought after typical problem since long in the field of oceanography. This is usually called the gridding problem, and the outcome is useful for many applications such as data analysis, graphical display, forcing or initialization of models, etc. In the present study temperature and salinity profiles data obtained from Argo profiling floats were used, and data on regular grids were generated. Data-interpolating variational analysis (DIVA) method was chosen for generating the gridded product. Extensive analysis was done to obtain correct choices of correlation length (L) and signal-to-noise ratio ($\lambda$), which results in an optimal gridded product. The gridded data obtained for different choices of L and $\lambda$ were later validated with datasets deliberately set aside before performing the analyses. For each combination of L and $\lambda$, the resultant gridded data was also validated with subsurface data from OMNI buoys. Based on the statistics of comparison with OMNI, the best-fit choice for L and $\lambda$ was concluded. Later, a comparative analysis was performed with the obtained gridded products from DIVA against the gridded product obtained from objective analysis (OA) to demonstrate the method's reliability. The resultant optimal combination of L and $\lambda$ will be used for generating Argo gridded data, which will be subsequently used for generating value-added products like mixed layer depth, ocean heat content, D20, etc., and will be made available on INCOIS Live Access Server.

    • Enhanced marine meteorological atlas for tropical Indian Ocean

      NUNNA KAMESHWARI T V S UDAYA BHASKAR E PATTABHI RAMA RAO VENKATA JAMPANA

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      A new marine meteorological climatology named Marine Meteorological Atlas for Tropical Indian Ocean (MaMetAtTIO) is generated for tropical Indian Ocean (TIO). The climatology is derived from ship-based observations of International Comprehensive Ocean-Atmosphere Dataset (ICOADS) Release 3.0 and those obtained from the India Meteorological Department (IMD). The climatologies of several independent and derived variables are constructed and the framework is presented in detail. The enhancement in MaMetAtTIO is statistically evaluated with reference to ICOADS R3.0 climatology. ICOADS Release 3.0 dataset has been found to be self-robust, as there was no significant improvement in the monthly and annual climatology of independent variables in MaMetAtTIO even after adding new records to ICOADS Release 3.0. However, there are few filled grid points in the individual year–month summaries owing to the addition of unique data from IMD. An attempt to correct the systematic error in Beaufort estimated wind speed, has reduced the annual net heat flux for TIO by 14W/m$^2$. Furthermore, MaMetAtTIO is compared with in-situ data from moored buoys and TropCux datasets. Two case studies (Madden–Julian oscillation (MJO) study, empirical orthogonal function (EOF) analysis) were undertaken to highlight the importance of adding individual observations to ICOADS R3.0 and the gridded fields of MaMetAtTIO. Better correlation (difference being significant) was observed between the time series derived from MaMetAtTIO and MJO index and the addition of new data resulted in filling of gaps in individual year–month summaries favourable to carry out statistical analyses such as EOF.

      $\bf{Highlights}$

      $\bullet$ Marine meteorological atlas constructed exclusively from ship observations.

      $\bullet$ Gridded fields of annual, monthly climatologies and individual year–month summaries are available for all marine-meteorological parameters including fluxes.

      $\bullet$ A long climatology dataset showing well-defined features of most of the climate phenomenon and their influences across tropical Indian Ocean.

      $\bullet$ A 14 W/m$^2$ reduction in net annual heat flux for tropical Indian Ocean obtained through observational error correction.

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