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THE PHYSICAL BASIS OF SST MEASUREMENTS Validation and evaluation of derived SST products

THE PHYSICAL BASIS OF SST MEASUREMENTS Validation and evaluation of derived SST products.

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THE PHYSICAL BASIS OF SST MEASUREMENTS Validation and evaluation of derived SST products

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  1. THE PHYSICAL BASIS OF SST MEASUREMENTSValidation and evaluation of derived SST products To develop systematic approaches to L4 product intercomparison and validation, including validation of uncertainty estimates; judicious approaches to selection of data to use in L4 products vs data to be withheld for validation; to consider more sophisticated validation studies, e.G. OSSE To develop systematic approaches to clarifying and communicating the actual smoothness of individual l4 products versus their nominal grid resolution; to investigate the influence of these parameters on the data set error

  2. DATA MERGING AND GRIDDING-2Problem description & background Widening demand for gridded SST data sets To develop approaches to estimating uncertainties relevant to nonlinear statistics appearing in societal applications, e.g. uncertainty (and bias) of SST gradient magnitudes estimated from Level 4 products and uncertainty in flux estimates based on L4 SST products. Target variables for gridded SST data sets Further research towards clarification of SSTfnd, SSTbulk, and SSTml relationship when there are significant predawn temperature variations in the top few meters of the ocean is needed A gradual shift towards simultaneous estimation of the entire surface depth profile in L4 products is warranted; a reasonable first step is to start reporting simulated diurnal variability solutions on which SST depth profile adjustments are based

  3. DATA MERGING AND GRIDDING-2Level 3 Products and Their Uncertainty Characterization To start accounting for correlated data error in implementations of data gridding procedures

  4. DATA MERGING AND GRIDDING-3Outstanding Issues A Priori Parameters of OA Procedures and Sub-Optimality: Research on the impact of the misspecification of a priori OI parameters (signal and error autocovariances) on OA fields and their error estimates  Advanced OA procedures: Further research into practical ways to deal with the major conceptual problem of OA, the statistical non-stationarity of the true SST field: accounting for nonstationary structures via covariance dependence on location, season, various parameters (e.g. velocities), types of weather/climate state; further development and use of multiscale OI formulation; use of simplified additional dynamical constraints in the OA of SST fields  Inter-Sensor Bias Correction: Research efforts into optimizing inter-sensor bias correction, objective choices of data input and reference sets for producing L4 products with the robust bias correction as a goal, intercomparison of ensembles of different L4 products

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