Extracting Multiyear Surface Currents from Sequential Thermal Imagery Using the Maximum Cross-Correlation Technique

Abstract

Ocean surface circulation can be estimated by automated tracking of thermal infrared features in pairs of sequential satellite imagery. A 7-yr time series of velocity, extracted from thermal imagery of the East Australian Current using the maximum cross-correlation (MCC) technique, provides enough measurements for a more statistical evaluation of the method than has previously been possible. Excluding 1 yr with extensive cloud cover, the method produces about 8000 velocity estimates per month with some seasonal variation. Method precision is estimated to be between 0.08 and 0.2 m s Ϫ1 rms, the lower value with more restrictive compositing. Mean flow, time-dependent flow, and eddy kinetic energy from the time series are compared with values derived from a dynamic height climatology, altimeter analyses, and drifter datasets in the region. The observations reproduce similar features in the flow. The differences between the observations are discussed in relation to noise in the methods and differences in the types of velocities they measure.

Computing Coastal Ocean Surface Currents from MODIS and VIIRS Satellite Imagery

“…This method has been used to measure a variety of ocean surface currents over the past several decades [6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Its effectiveness for retrieving ocean surface currents from Advanced Very High Resolution Radiometer (AVHRR) thermal infrared (IR) images has been repeatedly demonstrated [6][7][8][9][10][11]. Also, ocean color (OC) images collected from Coastal Zone Color Scanner (CZCS) [12], Moderate-Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) [9], and Geostationary Ocean Color Imager (GOCI) [13][14][15] have been used successfully to compute the space-time variability of the surface currents.…”

“…More recently, sequential synthetic aperture radar (SAR) images derived from ERS-2, Envisat [16], TerraSAR-X (TSX) [17], TanDEM-X (TDX) and COSMO-SkyMed (CSK) [18] have also been used with the MCC method to map the space-time variations of coastal currents. Moreover, this MCC method is not region-specific, and has been used to study the current structure in diverse regions such as the California Current [9,11], the Gulf Stream [7,10], the East Australian Current [8,19], the Tsushima Currents [14] and the Kuroshio Current [15].…”

“…Previous studies have validated the MCC derived currents as having root mean square (RMS) errors of 8-25 cm · s −1 compared with ADCPs, drifters or HF radar currents [8,10,14,20]. Tokmakian et al [20] proved that the RMS errors between the IR derived MCC currents, and the ADCP and geostrophic velocities estimated from hydrologic data were on the order of 25 cm · s −1 .…”

“…Tokmakian et al [20] proved that the RMS errors between the IR derived MCC currents, and the ADCP and geostrophic velocities estimated from hydrologic data were on the order of 25 cm · s −1 . Bowen et al [8] used 7 years of AVHRR images and compared the MCC currents with geostrophic currents and currents inferred from the trajectories of drifting buoys drifting buoys. The estimate accuracy of the MCC currents was 8-20 cm · s −1 .…”

Workflows and extensions to the Kepler scientific workflow system to support environmental sensor data access and analysis

“…They are used to delineate water masses, as indicators of the near surface density field from which geostrophic estimates are made for near surface currents (Kelly et al, 1999;Dong and Kelly, 2003), as tracers for estimating surface currents (Emery et al, 1992;Bowen et al, 2002), in support of in situ observations (Cornillon et al, 1988), in support of operational activities such as search and rescue, and in biological applications for a variety of species related studies (Hare et al, 2002;Baumgartner et al, 2003;Barcena et al, 2004). In addition, SST fields play an important role in air-sea interactions both at large scales (Chelton et al, 2001;O'Neill et al, 2003) and at small scales (Park and Cornillon, 2002;Song et al, 2004;Park et al, 2006) and they are beginning to be used in operational systems by the National Weather Service (Ginis, personal communication, 2006).…”