Using model cloud information to reassign low level AMVs for NWP

TitleUsing model cloud information to reassign low level AMVs for NWP
Publication TypeReport
Date Published06/2021
Series/CollectionEUMETSAT/ECMWF Fellowship Programme Research Report
Document Number56
TypeEUMETSAT/ECMWF Fellowship Programme Research Report
AuthorsLean, K, Bormann, N
Report Number56

Atmospheric Motion Vectors (AMVs) provide single-level wind estimates derived by tracking cloud features in image sequences from geostationary and polar orbiting satellites. They are established inputs to global as well as regional Numerical Weather Prediction (NWP) systems. Nevertheless, determining the heights of the winds as well as the assumption that clouds are passive tracers remain key sources of uncertainty in the use of AMVs. These aspects are often very difficult to examine, primarily due to a lack of  independent wind observations over large parts of the oceanic regions, though the availability of Aeolus data has opened new possibilities in this respect. This report presents recent work focused on investigating possible height assignment issues in low level AMVs, particularly inspired by a study in the Indian Ocean which highlighted challenging regions for the assimilation of AMVs in tropical inversion regions. These regions are often associated with relatively sharp changes in the wind speed in the vertical, leading to a particular sensitivity to AMV height assignment errors.
Errors in the height assignment of low level AMVs are investigated using estimates of the cloud layer height provided by the ECMWF model. Analysis of background departure statistics (comparison of  observations with the model background) showed that AMVs placed above the model cloud show larger deviations from the model fields compared to those placed unrealistically close to the surface. Reassigning the pressure of AMVs diagnosed above the model cloud layer to either the model cloud top,  base or average pressure leads to improvements in Root Mean Square Vector Difference (RMSVD) and  speed bias against the background wind fields. In assimilation experiments, reassigning the AMVs to  either of these options resulted in positive impact on the vector wind field in the verification against own analysis. In the fit of independent observations to the model background, changes to conventional wind  observations remained neutral however, positive signals were seen in Aeolus and scatterometer winds and in microwave imagers which are primarily sensitive to changes in the cloud. Overall, the reassignment to the cloud base or average pressure performed better than the cloud top in assimilation experiments. Combined with the results from the background departures, the option to reassign the heights of AMVs diagnosed above the model cloud to the average pressure of the cloud layer is recommended for future operational use.

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