Cloud clearing techniques over land for land surface temperature retrieval from the Advanced Along Track Scanning Radiometer

Bulgin, C. E. ORCID: https://orcid.org/0000-0003-4368-7386, Sembhi, H., Ghent, D., Remedios, J. J. and Merchant, C. ORCID: https://orcid.org/0000-0003-4687-9850 (2014) Cloud clearing techniques over land for land surface temperature retrieval from the Advanced Along Track Scanning Radiometer. International Journal of Remote Sensing, 35 (10). pp. 3594-3615. ISSN 0143-1161 doi: 10.1080/01431161.2014.907941

Abstract/Summary

We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along Track Scanning Radiometer (AATSR) instrument and compare these with the standard threshold based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud detection methods improves algorithm true skill scores by 8-9 % over SADIST (maximum score of 77.93 % compared to 69.27 %). We present an assessment of the impact of imperfect cloud masking, in relation to the reference cloud mask, on the retrieved AATSR LST imposing a 2 K tolerance over a 3x3 pixel domain. We find an increase of 5-7 % in the observations falling within this tolerance when using Bayesian methods (maximum of 92.02 % compared to 85.69 %). We also demonstrate that the use of dynamic thresholds in the tests employed by SADIST can significantly improve performance, applicable to cloud-test data to provided by the Sea and Land Surface Temperature Radiometer (SLSTR) due to be launched on the Sentinel 3 mission (estimated 2014).

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/36212
Identification Number/DOI	10.1080/01431161.2014.907941
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Taylor & Francis
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