Articles | Volume 12, issue 2
Atmos. Meas. Tech., 12, 1059–1076, 2019
https://doi.org/10.5194/amt-12-1059-2019

Special issue: Arctic mixed-phase clouds as studied during the ACLOUD/PASCAL...

Atmos. Meas. Tech., 12, 1059–1076, 2019
https://doi.org/10.5194/amt-12-1059-2019

Research article 18 Feb 2019

Research article | 18 Feb 2019

A cloud identification algorithm over the Arctic for use with AATSR–SLSTR measurements

Soheila Jafariserajehlou et al.

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Cited articles

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Arking, A. and Childs, J. D.: Retrieval of cloud cover parameters from multispectral satellites images, J. Clim. Appl. Meteorol., 24, 322–333, https://doi.org/10.1175/1520-0450(1985)024<0322:ROCCPF>2.0.CO;2, 1985. 
Arola, A., Eck, T. F., Kokkola, H., Pitkänen, M. R. A., and Romakkaniemi, S.: Assessment of cloud-related fine-mode AOD enhancements based on AERONET SDA product, Atmos. Chem. Phys., 17, 5991–6001, https://doi.org/10.5194/acp-17-5991-2017, 2017. 
Benesty, J., Chen, J., Huang, Y., and Cohen, I.: Noise Reduction in Speech Processing, Springer Topics in Signal Processing 2, Springer-Verlag Berlin Heidelberg, https://doi.org/10.1007/978-3-642-00296-0_5, 2009. 
Birks, A. R.: Improvements to the AATSR IPF relating to Land Surface Temperature Retrieval and Cloud Clearing over Land, AATSR Technical Note, Rutherford Appleton Laboratory, Chilton, UK, 2007. 
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Short summary
We developed a new algorithm for cloud identification over the Arctic. This algorithm called ASCIA, utilizes time-series measurements of Advanced Along-Track Scanning Radiometer (AATSR) on Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and -3B. The data product of ASCIA is compared with three satellite products: ASCIA shows an improved performance compared to them. We validated ASCIA by ground-based measurements and a promising agreement is achieved.