Abstract
Earlier studies of spatial variability in sea surface temperature (SST) using ship-based radiometric data suggested that variability at scales smaller than 1 km is significant and affects the perceived uncertainty of satellite-derived SSTs. Here, we compare data from the Ball Experimental Sea Surface Temperature (BESST) thermal infrared radiometer flown over the Arctic Ocean against coincident Moderate Resolution Imaging Spectroradiometer (MODIS) measurements to assess the spatial variability of skin SSTs within 1-km pixels. By taking the standard deviation, σ, of the BESST measurements within individual MODIS pixels, we show that significant spatial variability of the skin temperature exists. The distribution of the surface variability measured by BESST shows a peak value of O(0.1) K, with 95% of the pixels showing σ < 0.45 K. Significantly, high-variability pixels are located at density fronts in the marginal ice zone, which are a primary source of submesoscale intermittency near the surface. SST wavenumber spectra indicate a spectral slope of −2, which is consistent with the presence of submesoscale processes at the ocean surface. Furthermore, the BESST wavenumber spectra not only match the energy distribution of MODIS SST spectra at the satellite-resolved wavelengths, they also span the spectral slope of −2 by ~3 decades, from wavelengths of 8 km to <0.08 km.
Highlights
Increased spatial resolution in observations of the upper ocean has revealed an abundance of processes on lateral scales of O(1) km (e.g., Thomas et al [1])
Increased scientific understanding has been enabled by the improvements in instrumentation and computational models, and has established that submesoscale processes play an important role in the vertical transport and mixing of properties and tracers between the surface mixed layer and the thermocline
Submesoscale instabilities are shown to cause rapid changes in the stratification and buoyancy transport of the mixed layer that cannot be explained by heating and cooling alone, and far exceed what can be achieved through mesoscale baroclinic instability [5,6,7]
Summary
Increased spatial resolution in observations of the upper ocean has revealed an abundance of processes on lateral scales of O(1) km (e.g., Thomas et al [1]). If the variance within the pixel is small, the point value is a good representation of the overall pixel, but as the variance increases, as in frontal regions and coastal and high-latitude regions, the estimation error increases This sub-pixel variability can, contribute to the estimated uncertainty of a satellite-derived SST retrieval when it is validated against an observation with a finer spatial resolution. Calibration and/or validation of satellite-retrieved SSTs are usually done by comparing the retrieved values with in situ temperatures from IR radiometers deployed from ships or from thermistor chains on buoys These platforms cannot collect continuous in situ SSTs over an area as large as 1 km fast enough to resolve the spatial and temporal scales of the processes that control the variability of the skin layer of the ocean. Collecting data at altitudes closer to the sea surface has the added benefit of minimizing the atmospheric error in the radiometric SST retrievals
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