Estimating Advective Near-surface Currents from Ocean Color Satellite Images
Abstract
Improved maximum cross correlation (MCC) techniques are used to retrieve ocean surface currents from the sequential ocean color imagery provided by multiple newer generations of satellite sensors on hourly scales in the Yellow Sea and the U.S. East and Gulf coasts. The MCC calculation is validated in a series of Bio-Optical Forecasting (BioCast) experiments with predetermined synthetic velocities, and its products are evaluated by examining the errors and biases with respect to the High Frequency Radar (HFRadar) measurements. The root-mean-square (RMS) errors in our best current products derived from the overlap of satellite sensor swath between the VIIRS sequential orbits are less than 0.17 m s 1 in the evaluation area outside of the Chesapeake Bay. The most accurate current products are those derived from the imagery data of Rrs(551), Bb(551) and C(551), while the image sequences of Bb(551) and Zeu_lee are identified as the most suited products for the retrieval of currents because of their best production capcities of valid velocity vectors. Mechanisms between the advective processes and the dynamic changes of bio-optical properties are discussed regarding the performances of various color products on the retrieval of currents. Similarities of velocity distribution in the retrieved vector arrays are collected across different MCC products derived from ocean color datasets that are of different types and derived from different spectral channels of satellite overpasses. The inter-product similarities themselves can be used to characterize the near-surface advection as well and usually have smaller errors than each of the individual MCC currents. Moreover, efforts are also under way to improve the ocean color derived currents by merging several of the MCC.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2015
- Accession Number
- ADA612609
Entities
People
- Haoping Yang
- Jason K. Jolliff
- Robert A. Arnone
Organizations
- United States Naval Research Laboratory