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Impact of Aeolus wind lidar observations on the representation of the West African monsoon circulation in the ECMWF and DWD forecasting systems

Borne, Maurus ORCID iD icon 1; Knippertz, Peter ORCID iD icon 2; Weissmann, Martin; Martin, Anne; Rennie, Michael; Cress, Alexander
1 Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT)
2 Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO), Karlsruher Institut für Technologie (KIT)


Aeolus is the first satellite mission to acquire vertical profiles of horizontal line-of-sight winds globally and thus fills an important gap in the Global Observing System, most notably in the Tropics. This study explores the impact of this dataset on analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Deutscher Wetterdienst (DWD), focusing specifically on the West African Monsoon (WAM) circulation during the boreal summers of 2019 and 2020. The WAM is notoriously challenging to forecast and is characterized by prominent and robust large-scale circulation features such as the African Easterly Jet North (AEJ-North) and Tropical Easterly Jet (TEJ). Assimilating Aeolus generally improves the prediction of zonal winds in both forecasting systems, especially for lead times above 24 h. These improvements are related to systematic differences in the representation of the two jets, with the AEJ-North weakened at its southern flank in the western Sahel in the ECMWF analysis, while no obvious systematic differences are seen in the DWD analysis. In addition, the TEJ core is weakened in the ECMWF analysis and strengthened on its southern edge in the DWD analysis. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000157752
Veröffentlicht am 19.04.2023
DOI: 10.1002/qj.4442
Zitationen: 3
Web of Science
Zitationen: 3
Zitationen: 7
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 0035-9009, 1477-870X
KITopen-ID: 1000157752
HGF-Programm 12.11.34 (POF IV, LK 01) Improved predictions from weather to climate scales
Erschienen in Quarterly Journal of the Royal Meteorological Society
Verlag John Wiley and Sons
Band 149
Heft 752
Seiten 933–958
Vorab online veröffentlicht am 14.03.2023
Nachgewiesen in Web of Science
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