Effect of surface wind speed and sensor view zenith angle dependence of emissivity on SST retrieval from thermal infrared data: ATSR
- 10 September 1994
- journal article
- research article
- Published by Taylor & Francis in International Journal of Remote Sensing
- Vol. 15 (13) , 2615-2625
- https://doi.org/10.1080/01431169408954270
Abstract
The Along Track Scanning Radiometer (ATSR) data are currently being processed at various places within the European community including the Rutherford Appleton Laboratory (RAL) in the U.K. In generating an atmospherically corrected sea-surface temperature (SST) field, the emissivity of the sea surface is assumed to be independent of the sensor view zenith angle, sea state and wavelength (Ian Barton, RAL, personal communication). The sensor view zenith angle dependence of the emissivity is generally not known because of the complications introduced by the surface wind speed. This paper attempts to evaluate the uncertainties introduced in the SST due to the variation of emissivity with the sensor view zenith angle and surface roughness generated by the wind speed. Using the Cox and Munk formulation, Takashima and Takayama have simulated the sea water emissivities as a function of wind speed of up to 15ms-1 and a range of the sensor view zenith angles. Their emissivity data for 11 and 12μm channels corresponding to the viewing geometry of the ATSR have been used in this work. It is shown that, depending on the value of the SST, there can be significant errors due to the sensor view zenith angle and sea surface roughness dependence of the emissivity. For example, if the SST is 10°C and the wind speed is 0ms-1, then the errors due to the sensor view zenith angle dependence of the emissivity are shown to be 0·77°C and 0·55°C in 11 and 12μm channels, respectively, and at 15 ms-l the respective errors reach about 1·ldeg K and 0·86 deg K. The errors due to the deviations of the emissivities from unity for nadir view in calm conditions are about 2·1°C and 3·5°C, respectively, in the 11 and 12μm channels. All of these errors are additive, indicating the importance of the calibration and validation.Keywords
This publication has 8 references indexed in Scilit:
- Vegetation dynamics, CO2 cycle and El Niño phenomenonInternational Journal of Remote Sensing, 1992
- Estimation of sea surface temperature via AVHRR of NOAA-9—ison with fixed buoy data†International Journal of Remote Sensing, 1991
- Emissivity of pure and sea waters for the model sea surface in the infrared window regionsRemote Sensing of Environment, 1988
- Satellite multichannel infrared measurements of sea surface temperature of the N.E. Atlantic Ocean using AVHRR/2Quarterly Journal of the Royal Meteorological Society, 1984
- Removal of atmospheric effects on a pixel by pixel basis from the thermal infrared data from instruments on satellites. The Advanced Very High Resolution Radiometer (AVHRR)International Journal of Remote Sensing, 1984
- Light Emerging from the Sea — Interpretation and Uses in Remote SensingPublished by Springer Nature ,1983
- Emissivity and reflectance of the model sea surface for the use of AVHRR data of NOAA satellites.Papers in Meteorology and Geophysics, 1981
- Measurement of the Roughness of the Sea Surface from Photographs of the Sun’s GlitterJournal of the Optical Society of America, 1954