Oceanic upper mixed layer depth determination by the use of satellite data

• Published in: Remote sensing of environment 1990-04, Vol.32 (1), p.55-74
• Main Authors: Yan, Xiao-Hai, Schubel, J.R., Pritchard, D.W.
• Format: Article
• Language: English
• Subjects: diurnal variations; Marine; mixed layer depth; ocean circulation; Oceanography; Sargasso Sea; satellite sensing; satellites; temperature gradients
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/0034-4257(90)90098-7

We have developed a method to determine the oceanic daily mean mixed layer depth from satellite observations and a mixed layer thermal inertia (MLTI) model. Temporal variations in the spatial distribution of the thermal inertia of the mixed layer provide information applicable to studies of variations in the upper ocean daily mean mixed layer depth in regions of the ocean where diurnal variations in the thermal structure of the upper layer due to horizontal advection and horizontal diffusion are relatively small. The algorithms were developed to use remotely-sensed values of sea surface temperature, albedo, and surface wind speeds to calculate the thermal inertia and to predict changes in subsurface diurnal mixed layer depth. The MLTI model, based on a mixed layer model of the upper ocean, has been used to simulate the diurnal mixing process and thermal inertia distribution in the Sargasso Sea around 34°N, 70°W. Sea surface temperature and albedo have been obtained from the NOAA7-AVHRR images. Surface wind speeds have been derived from the Scanning Multichannel Microwave Radiometer (SMMR) aboard Nimbus 7. Image processing was performed for images gathered between June and July 1982. The daily mean mixed layer depths predicted by the MLTI model agree well with data gathered at the LOTUS mooring located in the Sargasso Sea. This suggests that vertical mixing is the dominant physical process that controls the thermal inertia distribution in the midocean, far from major current systems, and that remote sensing is a promising tool to study such upper ocean processes. The MLTI model, which also provides information on the total heat flux into the upper ocean within the diurnal cycle, could be improved by using other data such as Altimeter data from improved satellite sensors, thus opening up the possibility of applications to operational upper ocean forecasting.