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- Author or Editor: Trevor H. Guymer x
- Journal of Atmospheric and Oceanic Technology x
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Abstract
An investigation into a potentially important, but little-studied effect on altimeter data—rain contamination—has been carried out using ERS-1. The method involves identifying large changes in the radar backscatter coefficient and relating these to atmospheric liquid water estimates obtained from an onboard microwave radiometer. The latter is found to provide a useful means of distinguishing between wind and rain events. In general, the backscatter coefficient is reduced most when the liquid water content is high, and by an amount that is consistent with atmospheric attenuation at the radar frequency in use. However, some examples of enhanced backscatter were also observed indicating a possible reduction in surface roughness by the impact of raindrops on the ocean surface. Examination of return pulse shapes across significant rain events reveals behavior consistent with published theoretical work and shows how rain may lead to loss-of-lock in extreme conditions. The results of this study have implications for improved data quality flagging procedures and correction of ERS-1 altimeter winds.
Abstract
An investigation into a potentially important, but little-studied effect on altimeter data—rain contamination—has been carried out using ERS-1. The method involves identifying large changes in the radar backscatter coefficient and relating these to atmospheric liquid water estimates obtained from an onboard microwave radiometer. The latter is found to provide a useful means of distinguishing between wind and rain events. In general, the backscatter coefficient is reduced most when the liquid water content is high, and by an amount that is consistent with atmospheric attenuation at the radar frequency in use. However, some examples of enhanced backscatter were also observed indicating a possible reduction in surface roughness by the impact of raindrops on the ocean surface. Examination of return pulse shapes across significant rain events reveals behavior consistent with published theoretical work and shows how rain may lead to loss-of-lock in extreme conditions. The results of this study have implications for improved data quality flagging procedures and correction of ERS-1 altimeter winds.
Abstract
The Along Track Scanning Radiometer (ATSR) was launched in July 1991 on the European Space Agency's first remote sensing satellite ERS-1. ATSR has the potential to measure sea surface temperature (SST) to a precision of 0.3 K, which is more than double the accuracy of any previously flown infrared radiometer. A key factor limiting ATSR's performance is remnant cloud contamination. Examination of the 0.5° spatially averaged ATSR SST data (version 500) from the South Atlantic for the whole of 1992 and 1993 shows the presence of regional cloud contamination in the night SST measurements. The authors establish a figure of 5.7% as a lower limit for this nighttime cloud contamination. The contamination leads to differences between day and night mean SSTs and to poor comparisons with in situ thermosalinograph SST data. A new cloud filtering process designed for postprocessing of the data is proposed to remove the contamination. The algorithm presented here relies on assumptions that the day data are less cloud contaminated than the night data and that a large proportion of the SST variability can he explained by an annual and semiannual model. Testing the filtering algorithm shows that differences between the day and night SST signals are substantially reduced and that comparisons with the thermosalinograph SST data improve by a factor of 3 in rms scatter and by 0.3 K in the mean difference.
Abstract
The Along Track Scanning Radiometer (ATSR) was launched in July 1991 on the European Space Agency's first remote sensing satellite ERS-1. ATSR has the potential to measure sea surface temperature (SST) to a precision of 0.3 K, which is more than double the accuracy of any previously flown infrared radiometer. A key factor limiting ATSR's performance is remnant cloud contamination. Examination of the 0.5° spatially averaged ATSR SST data (version 500) from the South Atlantic for the whole of 1992 and 1993 shows the presence of regional cloud contamination in the night SST measurements. The authors establish a figure of 5.7% as a lower limit for this nighttime cloud contamination. The contamination leads to differences between day and night mean SSTs and to poor comparisons with in situ thermosalinograph SST data. A new cloud filtering process designed for postprocessing of the data is proposed to remove the contamination. The algorithm presented here relies on assumptions that the day data are less cloud contaminated than the night data and that a large proportion of the SST variability can he explained by an annual and semiannual model. Testing the filtering algorithm shows that differences between the day and night SST signals are substantially reduced and that comparisons with the thermosalinograph SST data improve by a factor of 3 in rms scatter and by 0.3 K in the mean difference.
