Investigation of links between dynamical scenarios and particularly high impact of Aeolus on numerical weather prediction (NWP) forecasts
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Published:2023-03-28
Issue:1
Volume:4
Page:249-264
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ISSN:2698-4016
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Container-title:Weather and Climate Dynamics
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language:en
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Short-container-title:Weather Clim. Dynam.
Author:
Martin Anne, Weissmann MartinORCID, Cress Alexander
Abstract
Abstract. Global wind profiles from the Aeolus satellite mission provide an important source of wind information for numerical weather prediction (NWP). Data assimilation experiments show large mean changes in the analysis and a significant reduction in forecast errors. At Deutscher Wetterdienst (DWD), a 3-month observing system experiment (OSE), from July 2020 to October 2020, was performed to evaluate the impact of the Aeolus horizontal line-of-sight (HLOS) wind observations in the operational data assimilation system of the ICOsahedral Nonhydrostatic (ICON) global model. To better understand the underlying dynamics leading to the overall beneficial impact, specific time periods and regions with a particularly high impact of Aeolus are investigated. In this study, we illustrate three examples of atmospheric phenomena that constitute dynamical scenarios for significant forecast error reduction through the assimilation of Aeolus: the phase shift of large-scale tropical circulation systems, namely the Quasi-Biennial Oscillation (QBO) and the El Niño–Southern Oscillation (ENSO), and the interaction of tropical cyclones undergoing extratropical transition (ET) with the midlatitude waveguide.
Funder
Bundesministerium für Wirtschaft und Energie Deutsche Forschungsgemeinschaft
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference55 articles.
1. Anstey, J. A. and Shepherd, T. G.: High-latitude influence of the quasi-biennial oscillation, Q. J. Roy. Meteor. Soc., 140, 1–21, https://doi.org/10.1002/qj.2132, 2014. a 2. Anstey, J. A., Banyard, T. P., Butchart, N., Coy, L., Newman, P. A., Osprey,
S., and Wright, C. J.: Prospect of Increased Disruption to the QBO in a
Changing Climate, Geophys. Res. Lett., 48, e2021GL093058,
https://doi.org/10.1029/2021GL093058, 2021. a, b 3. Baker, W. E., Atlas, R., Cardinali, C., Clement, A., Emmitt, G. D., Gentry, B. M., Hardesty, R. M., Källén, E., Kavaya, M. J., Langland, R., Ma,
Z., Masutani, M., McCarty, W., Pierce, R. B., Pu, Z., Riishojgaard, L. P.,
Ryan, J., Tucker, S., Weissmann, M., and Yoe, J.: Lidar-measured wind
profiles: The missing link in the Global Observing System, B. Am. Meteorol. Soc., 95, 543–564, https://doi.org/10.1175/BAMS-D-12-00164.1, 2014. a 4. Baldwin, M. P., Gray, L. J., Dunkerton, T. J., Hamilton, K., Haynes, P. H.,
Randel, W. J., Holton, J. R., Alexander, M. J., Hirota, I., Horinouchi, T.,
Jones, D. B. A., Kinnersley, J. S., Marquardt, C., Sato, K., and Takahashi,
M.: The quasi-biennial oscillation, Rev. Geophys., 39, 179–229,
https://doi.org/10.1029/1999RG000073, 2001. a, b 5. Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical
weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015. a
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