Next Article in Journal
Robinia pseudoacacia L. Flower Analyzed by Using An Unmanned Aerial Vehicle (UAV)
Next Article in Special Issue
Reconstruction of Daily Sea Surface Temperature Based on Radial Basis Function Networks
Previous Article in Journal
Non-Cooperative Bistatic SAR Clock Drift Compensation for Tomographic Acquisitions
Previous Article in Special Issue
Environmental Variability and Oceanographic Dynamics of the Central and Southern Coastal Zone of Sonora in the Gulf of California
Open AccessFeature PaperArticle

Submesoscale Sea Surface Temperature Variability from UAV and Satellite Measurements

Colorado Center for Astrodynamics Research, University of Colorado, 431 UCB, Boulder, CO 80309, USA
NOAA Earth System Research Laboratory, Physical Sciences Division, R/PSD2 325 Broadway, Boulder, CO 80305, USA
Ball Aerospace, 1600 Commerce St., Boulder, CO 80301, USA
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(11), 1089;
Received: 24 September 2017 / Revised: 17 October 2017 / Accepted: 23 October 2017 / Published: 25 October 2017
(This article belongs to the Collection Sea Surface Temperature Retrievals from Remote Sensing)
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. View Full-Text
Keywords: spatial variability; sea surface temperature; submesoscale; wavenumber spectra spatial variability; sea surface temperature; submesoscale; wavenumber spectra
Show Figures

Graphical abstract

MDPI and ACS Style

Castro, S.L.; Emery, W.J.; Wick, G.A.; Tandy, W. Submesoscale Sea Surface Temperature Variability from UAV and Satellite Measurements. Remote Sens. 2017, 9, 1089.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop