Subsurface expressions of sea surface temperature variability under low winds

In aerial surveys conducted during the Coupled Ocean Atmosphere Response Experiment (COARE) and the low wind component of the Coupled Boundary Layer Air-Sea Transfer (CBLAST-Low) oceanographic field programs, SST variability at relatively short spatial and temporal scales has been observed to increase dramatically under low wind conditions. Due to a dearth of sufficiently detailed observations, the reasons for this short scale variability have remained unclear. A number of fundamental questions about this variability remain unanswered. Is the surface temperature signal accompanied by a subsurface temperature signal? Is the spatial and temporal structure in SST accompanied by similar structure in other oceanographic surface properties such as salinity, velocity, and surface roughness? Does this short scale variability persist through the night (when the airplanes were not flying)? Once these types of questions have been addressed, we may be able to determine the cause(s) of this enhanced SST variability under low winds. The structures appear at a wide range of scales, and it is likely that both oceanic and atmospheric variability is imprinted on the SST field. Potentially important processes include Langmuir circulation, internal waves in the ocean and atmosphere, surface flux variability, and spatial variability in upper ocean mixing.

During the 2003 CBLAST-Low field program, an extensive data set was collected which will allow progress toward an understanding of this low-wind SST variability. Coordinated sampling by two airplanes and a ship provides a detailed record of surface and subsurface variability as well as air-sea fluxes of heat and momentum. These detailed spatial records are augmented by an array of heavily instrumented moorings, providing well resolved records of oceanic temperature, salinity, and velocity, as well as coincident surface meteorology and surface heat fluxes. We use this data set to examine SST variability in low-wind conditions. Specifically, we address the questions posed above through a combination of statistical analysis and process studies.