Articles | Volume 15, issue 9
https://doi.org/10.5194/amt-15-3031-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-3031-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 May 2022
Research article |
| 17 May 2022
| 17 May 2022
Improving discrimination between clouds and optically thick aerosol plumes in geostationary satellite data
School of Earth, Atmosphere and Environment, Monash University, Melbourne, VIC 3800, Australia
ARC Centre of Excellence for Climate Extremes, Monash University, Melbourne, VIC 3800, Australia
Caroline Poulsen
School of Earth, Atmosphere and Environment, Monash University, Melbourne, VIC 3800, Australia
Bureau of Meteorology, Melbourne, VIC, 3001, Australia
Steven Siems
School of Earth, Atmosphere and Environment, Monash University, Melbourne, VIC 3800, Australia
ARC Centre of Excellence for Climate Extremes, Monash University, Melbourne, VIC 3800, Australia
ARC SRI Securing Antarctica's Environmental Future, Melbourne, VIC 3800, Australia
Simon Proud
National Centre for Earth Observation, University of Oxford, Clarendon Laboratory, Parks Road, Oxford, OX1 3PU, UK
STFC RAL Space and the National Centre for Earth Observation, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
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Short summary
A neural network (NN)-based cloud mask for a geostationary satellite instrument, AHI, is developed using collocated data and is better at not classifying thick aerosols as clouds versus the Japanese Meteorological Association and the Bureau of Meteorology masks, identifying 1.13 and 1.29 times as many non-cloud pixels than each mask, respectively. The improvement during the day likely comes from including the shortest wavelength bands from AHI in the NN mask, which the other masks do not use.
A neural network (NN)-based cloud mask for a geostationary satellite instrument, AHI, is...
