The cloud identification processing is a series of tests aimed at identifying different types of cloud (or snow) present on output images acquired by SLSTR.
The identification of cloud-affected pixels is accomplished by applying a series of tests in turn to the brightness temperature data in the 12, 11 and 3.7 µm channels, and to the reflectance data in the 1.6 µm, 1.375 µm channel, and in the visible channels. The table below summarises the cloud clearing tests to be applied, including one test flagging snow-covered surfaces.
Table: Basic Cloud identification test list
Some of the tests depend on results from the tests performed previously and hence the order in which they are applied is important.
The infra-red histogram test is applied after the other tests, and only uses those pixels that have not been flagged as cloudy by any of the preceding tests.
The 1.6 micron histogram test operates only on pixels not previously flagged as cloudy by the gross cloud test or the thin cirrus and 11 micron spatial coherence tests, and must therefore follow these tests.
Each test makes use of a look-up table of parameters with which the brightness temperature or reflectance data is compared. Where tests are applied to oblique and nadir view images separately, the parameters may be defined separately for the two cases. More generally, the comparison parameters may depend on the air mass in the line of sight, and this is implemented by allowing the tabular parameters to depend on the across track position.
Some tests are only applied under certain conditions (during day or night time only, over land or sea pixels only), as described in the table above.
A Bayesian and Probabilistic method of cloud screening is also used. As these cloud screening methods use the Meteorological data, they occur after the meteorological annotations processing stage.