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 (λ), which results in an optimal gridded product. The gridded data obtained for different choices of L and λ were later validated with datasets deliberately set aside before performing the analyses. For each combination of L and λ, 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 λ 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 λ 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.

使用一组在空间和时间上随机位置的数据来确定规则网格位置上的海洋参数，是海洋学领域长期以来最受追捧的典型问题。这通常被称为网格问题，其结果对许多应用都很有用，例如数据分析、图形显示、模型的强制或初始化等。 在本研究中，使用了从 Argo 剖面浮标获得的温度和盐度剖面数据，和生成了规则网格上的数据。选择数据插值变分分析（DIVA）方法来生成网格产品。进行了广泛的分析以获得正确选择相关长度 ( L ) 和信噪比 ( λ)，这会产生最佳的网格产品。为L和λ 的不同选择获得的网格数据后来在执行分析之前用故意留出的数据集进行验证。对于L和λ 的每个组合，所得网格数据也用来自 OMNI 浮标的地下数据进行了验证。根据与 OMNI 的比较统计，得出了L和λ的最佳选择。随后，将DIVA得到的网格化产品与客观分析(OA)得到的网格化产品进行对比分析，证明了该方法的可靠性。L和λ的最终最佳组合 将用于生成 Argo 网格数据，这些数据随后将用于生成混合层深度、海洋热含量、D20 等增值产品，并将在 INCOIS 实时访问服务器上提供。