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A simpler approach of evaluating the representative error for data assimilation by regriding a high resolution ocean data into a coarser resolution grid structure
4th International Conference on Oceanography & Marine Biology
Deep Sankar Banerjee
Indian National Centre for Ocean Information Services, Hyderabad, India
Posters & Accepted Abstracts: J Marine Sci Res Dev
Abstract
The purpose of this investigation is to find out the Representative Error (RE) due to regridding a high resolution ocean data into a coarser resolution grid structure. RE is the component of observational error that creeps into model due to the subgrid scale unresolved processes. It can be included in Data Assimilation by blending it with the observational error covariance matrix (R) which will be used in further calculation regarding the assimilation of observational data. So it is very important to evaluate the RE with which one can get a model forecast that will be closer to the reality. In order to evaluate it in a simpler way a climatological output of ROMS of 1/12 degree resolution is assumed as the best possible model estimate. Our goal is to find out how much physical information is lost due to regridding it into a coarser resolution. In this regard an arithmetic mean of temperature is produced from the given ROMS output for a single time step in coarse resolution. Then every grid points from the given high resolution data are subtracted from the mean and the variance is calculated at each grid point. It is found that in the vicinity of Persian Gulf and Red Sea within the range of thermocline depth the variance, rather the RE is a bit higher which can be anticipated by the fact that in these regions there exists a certain number of mesoscale eddies which was underestimated after regridding the data into a coarser resolution.Biography
Email: deepsankarbanerjee@gmail.com
