Derivation of Atmospheric Motion Vectors from Projected Low Earth Orbit Images
Atmospheric Motion Vectors (AMVs) are an important input to many Numerical Weather Prediction (NWP) models. EUMETSAT derives AMVs from several of its orbiting satellites, including the geostationary satellites (METEOSAT), and its Low-Earth Orbit (LEO) satellites. The algorithm extracting the AMVs uses pairs or triplets of images, and tracks the motion of clouds features or water vapour features from one image to another. Currently, EUMETSAT LEO satellite AMVs are retrieved from georeferenced images form the Advanced Very-High-Resolution Radiometer (AVHRR) on board the MetOp satellites. In the future EUMETSAT plans to derive operational AMVs from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3 satellites and from the Visible and Infrared Imager (VII) on board the future generation of polar satellites, EPS-SG. A new framework adaptable to any radiometer on board a LEO satellite is presently under development where the images are first projected on an equal-area grid, before applying the AMV extraction algorithm. This approach has multiple advantages. First, individual pixels represent areas of equal size, which is crucial to ensure that the tracking is consistent throughout the images, and from one image to another. Second, this allows to track features that would otherwise leave the frame of the reference image, so more AMVs can be derived. Third, the same framework will be used for any LEO satellite allowing an overall consistency of EUMETSAT AMV products. In this work, we present the results of this method for SLSTR and simulated images of VII by comparing the AMVs to the forecast model. We validate our results against AMVs currently derived from AVHRR, and we present a timeline for the implementation of these new AMVs and their operational derivation.
