Abstract's details

Empirical, Nonparametric Estimation of the Sea State Bias using the Interpolation Method

Alexa Putnam (University of Colorado Boulder, Colorado Center for Astrodynamics Research, United States)


Shailen Desai (Jet Propulsion Laboratory, USA); R. Steven Nerem (University of Colorado, Colorado Center for Astrodynamics Research, USA)

Event: 2022 Ocean Surface Topography Science Team Meeting

Session: Instrument Processing: Propagation, Wind Speed and Sea State Bias

Presentation type: Type Poster

Contribution: PDF file


An alternative approach to empirical, non-parametric sea state bias (SSB) modeling was developed with intention of providing a simple, transparent and efficient means to derive both a raw and smoothed SSB solution. This alternative approach, referred to as the interpolation method, maintains the flexibility to generate 2-D or 3-D models using either direct or difference measurements of the sea level anomaly uncorrected for SSB (uSLA). The interpolation method was further used to introduce a combined, or joint (JNT), SSB solution using a weighted combination of collinear and crossover uSLA measurements. The raw and smoothed SSB solutions derived using the interpolation method are obtained over three steps, with a supplemental fourth step that consists of estimating a model-dependent dual-frequency ionosphere calibration bias to correct for a relative range+SSB error.

We have generated SSB models for Topex/Poseidon and Jason-1 through -3 using the interpolation method. By applying the same SSB modeling method that includes a dual-frequency ionosphere calibration bias to four sequential satellites, we explore the potential benefits to the long-term sea level time series.

Poster show times:

Room Start Date End Date
Mezzanine Tue, Nov 01 2022,17:15 Tue, Nov 01 2022,18:15
Mezzanine Thu, Nov 03 2022,14:00 Thu, Nov 03 2022,15:45
Alexa Putnam
University of Colorado Boulder, Colorado Center for Astrodynamics Research
United States