Objectively Derived Daily “Winds” from Satellite Scatterometer Data

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Abstract
An objective technique is used to create regularly gridded daily “wind” fields from NASA scatterometer (NSCAT) observations for the Pacific Ocean north of 40°S. The objective technique is a combination of direct minimization, and cross validation with multigridding. The fields are created from the minimization of a cost function. The cost function is developed to maximize information from the observational data and minimize smoothing. Three constraints are in the cost function: a misfit to observations, a smoothing term, and a misfit of the curl. The second and third terms are relative to a background field. The influence of the background field is controlled by weights on the smoothing constraints. Weights are objectively derived by the method of cross validation. Cross validation is a process that removes observations from the input to the cost function and determines tuning parameters (weights) by the insensitivity of the removed observations to the output field. This method is computationally expensive; thus the technique of multigridding is incorporated into cross validation. Multigridding solves for the weights by cross validation on a coarse grid, then these weights are used to determine pseudostress on the original fine grid. This allows for the practical application of cross validation with only modest computational resources required. Daily pseudostress fields are generated on a 1° × 1° resolution grid for the NSCAT period. These objectively derived fields are compared to independent data sources (NCEP and Florida State University winds). The kinetic energy of the NSCAT fields exceeds that of the independent NCEP reanalysis and is similar to observations. Pseudostresses for the equatorial cold tongue region (15°S–15°N, 180°–90°W) are extracted from the objectively derived NSCAT fields and a complex empirical orthogonal function (CEOF) analysis is performed. The analysis shows a large amount of variability in intraseasonal timescales for the Southern Hemisphere trade winds. This variability is supported by in situ observations.

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