Electromagnetic bias estimation using in situ and satellite data: 2. A nonparametric approach

Abstract

For the most recent satellite altimeter (Jason-1), the largest single error budget contribution is the electromagnetic (EM) bias. Nonparametric models have been proposed to reduce the variability of EM bias estimates. In previous work, nonparametric models have been estimated using satellite crossover differences. Using tower data, we show that nonparametric models using wind speed and significant wave height provide some improvement over parametric models. In support of Part I of this paper [Millet et al., 2003], inclusion of the RMS long wave slope improves nonparametric EM bias estimation error values by over 50%. In addition, nonparametric models reduce the historical discrepancy between satellite and tower EM bias measurements.