ASSIMILATION OF GLOBAL VERSUS LOCAL DATA SETS INTO A REGIONAL MODEL OF THE GULF-STREAM SYSTEM .1. DATA EFFECTIVENESS

The primary objective of this paper is to assess the relative effectiv eness of data sets with different space coverage and time resolution w hen they are assimilated into an ocean circulation model. We focus on obtaining realistic numerical simulations of the Gulf Stream system ty pically of the order of 3-month duration by constructing a ''synthetic '' ocean simultaneously consistent with the model dynamics and the obs ervations. The model used is the Semispectral Primitive Equation Model . The data sets are the ''global'' Optimal Thermal Interpolation Schem e (OTIS) 3 of the Fleet Numerical Oceanography Center providing temper ature and salinity fields with global coverage and with bi-weekly freq uency, and the localized measurements, mostly of current velocities, f rom the central and eastern array moorings of the Synoptic Ocean Predi ction (SYNOP) program, with daily frequency but with a very small spat ial coverage. We use a suboptimal assimilation technique (''nudging'') . Even though this technique has already been used in idealized data a ssimilation studies, to our knowledge this is the first study in which the effectiveness of nudging is tested by assimilating real observati ons of the interior temperature and salinity fields. This is also the first work in which a systematic assimilation is carried out of the lo calized, high-quality SYNOP data sets in numerical experiments longer than 1-2 weeks, that is, not aimed to forecasting. We assimilate (1) t he global OTIS 3 alone, (2) the local SYNOP observations alone, and (3 ) both OTIS 3 and SYNOP observations. We assess the success of the ass imilations with quantitative measures of performance, both on the glob al and local scale. The results can be summarized as follows. The inte rmittent assimilation of the global OTIS 3 is necessary to keep the mo del ''on track'' over 3-month simulations on the global scale. As OTIS 3 is assimilated at every model grid point, a ''gentle'' weight must be prescribed to it so as not to overconstrain the model. However, in these assimilations the predicted velocity fields over the SYNOP array s are greatly in error. The continuous assimilation of the localized S YNOP data sets with a strong weight is necessary to obtain local reali stic evolutions. Then assimilation of velocity measurements alone reco vers the density structure over the array area. However, the spatial c overage of the SYNOP measurements is too small to constrain the model on the global scale. Thus the blending of both types of datasets is ne cessary in the assimilation as they constrain different time and space scales. Our choice of ''gentle'' nudging weight for the global OTIS 3 and ''strong'' weight for the local SYNOP data provides for realistic simulations of the Gulf Stream system, both globally and locally, on the 3- to 4-month-long timescale, the one governed by the Gulf Stream jet internal dynamics.