Improvement of Short-Term Forecasting in the Northwest Pacific through Assimilating Argo Data into Initial Fields
Journal article preprint
NAVAL POSTGRADUATE SCHOOL MONTEREY CA NAVAL OCEAN ANALYSIS AND PREDICTION LAB
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The impact of assimilating Argo data into initial field on the short-term forecasting accuracy of temperature and salinity is quantitatively estimated by using a forecasting system of the western North Pacific, on the base of the Princeton Ocean Model with generalized coordinate system POMgcs. This system uses a sequential multi-grid three-dimensional variational 3DVAR analysis scheme to assimilate observation data. Two numerical experiments were conducted with and without Argo temperature and salinity profile data besides conventional temperature and salinity profile data and sea surface height anomaly SSHa and sea surface temperature SST in the process of assimilating data into initial fields. The forecast errors are estimated through using independent temperature and salinity profiles during the forecasting period, including the vertical distributions of the horizontally averaged root mean square errors H-RMSEs and horizontal distributions of the vertically averaged mean errors MEs and temporal variation of spatially averaged root mean square errors S-RMSEs. Comparison between the two experiments shows that the assimilation of Argo data significantly improves the forecast accuracy, with 24 reduction of H-RMSE maximum for the temperature, and the salinity forecasts are improved more obviously, averagely dropping of 50 for H-RMSEs in depth shallower than 300m. Such improvement is caused by relatively uniform sampling of both temperature and salinity from the Argo drifters in time and space.
- Physical and Dynamic Oceanography