Cloud masking schemes for satellite ocean colour data in the Baltic sea and applications to cyanobacteria bloom analysis

One of the most important steps in utilizing ocean colour remote sensing data is subtracting the contribution of the atmosphere from the signal at the satellite to obtain marine water leaving radiance. To be done accurately this requires clear sky conditions, i.e. all clouds need to be excluded or masked from the data prior to atmospheric correction. The standard cloud mask used routinely in the processing of NASA's global ocean colour data is based on a simple threshold applied to the Rayleigh-corrected top-of-atmosphere radiance. The threshold is kept purposefully low to ensure high quality processing at a global scale. As a consequence, the standard scheme can sometimes inadvertently mask extreme optical events such as intense blue-green algal (cyanobacteria) blooms in the Baltic Sea. These blooms have important ecological and environmental impacts on the basin and require appropriate monitoring. Therefore, an assessment of 5 existing cloud masking schemes that could provide valuable alternatives for the Baltic Sea was carried out by systematically testing their application to time series of SeaWiFS, MODIS and MERIS data. By applying them to a number of years of satellite data, temporal and spatial implications were analyzed and a new hybrid cloud mask was developed and similarly tested. The results indicate that, by replacing the standard cloud mask, an increase of an average of 22% in ocean coverage over the course of a seasonal cycle in the Baltic Sea may be possible. Major occurrences of intense blooms can be recovered whilst at the same time not introducing any significant extra cloud into the processing. The full inclusion of the cyanobacteria blooms, even their most intense manifestations, into Baltic data series allows a more comprehensive analysis of their spectral characteristics with powerful implications for their detection, monitoring, and interannual evolution.