Other algorithm studies
Read our other algorithm studies for current, future and multi-missions.
26 May 2023
02 July 2018
The objectives of this study are to:
A prototype 2Dvar retrieval algorithm written in python language was developed and demonstrated on synthetic METimage and real MERIS data. LUTs were defined to provide the fast RTM required for the measurements: reflectance at 0.865/0.64 microns and the reflectance ratio between the O2 band pair at 0.763 and 0.752 microns. LUTs were based on parameterised climatologically varying cloud extinction profiles and geometrical depths (from CloudSat, Calipso data).
The parameterisation is a function of cloud optical thickness COT and top pressure CTP and the underlying (slow) RTM model was ARTDECO. The algorithm framework was used to examine retrieval sensitivities to calibration, extinction profile assumptions, BRDF errors and more.
Applied to the data the scheme produced COTs and CTPs that compared reasonably to the truth using simulated data and operational products in the case of MERIS.
One major conclusion was that the 2Dvar framework tended to converge in a single iteration because of the evenly constrained nature of the inverse problem. While making the schema potentially fast, it also implied no sensitivity to anomalous conditions, in particular when more than one cloud layer is present.
A follow-on study was commissioned to optimise some aspects of the scheme, to refine the sensitivity study and to examine the case for adding a further absorbing channel (e.g. 0.91 water vapour) in order to provide visibility of multi-layer cloud.