Tailored Ensemble Prediction Systems: Application of Seamless Scale Bred Vectors

Show simple item record

dc.contributor.author Hermoso, A.
dc.contributor.author Homar, V.
dc.contributor.author Greybush, J.S.
dc.contributor.author Stensrud, D.J.
dc.date.accessioned 2021-02-09T06:38:10Z
dc.date.available 2021-02-09T06:38:10Z
dc.identifier.uri http://hdl.handle.net/11201/155023
dc.description.abstract [eng] Uncertainty in numerical weather forecasts arising from an imperfect knowledge of the initial condition of the atmospheric system and the discrete modeling of physical processes is addressed with ensemble prediction systems. The breeding method allows the creation of initial condition perturbations in a simple and computationally inexpensive way. This technique uses the full nonlinear dynamics of the system to identify fast-growing modes in the analysis fields, obtained from the difference between control and perturbed runs rescaled at regular time intervals. This procedure is more suitable for the high-resolution ensemble forecasts required to reproduce small-scale high-impact weather events, as the complete nonlinear model is employed to generate the perturbations. The underdispersion commonly observed in ensemble forecasts emphasizes the need to develop methods that increase ensemble spread and diversity at no cost to forecast skill. In this sense, we investigate the benefits of different breeding techniques in terms of ensemble diversity and forecast skill for a mesoscale ensemble over the Western Mediterranean region. In addition, we propose a new method, Bred Vectors Tailored Ensemble Perturbations, designed to control the scale of the perturbations and indirectly the ensemble spread. The combination of this method with orthogonal bred vectors shows significant improvements in terms of ensemble diversity and forecast skill with respect to the current arithmetic methods.
dc.format application/pdf
dc.relation.isformatof https://doi.org/10.2151/jmsj.2020-053
dc.relation.ispartof Journal of the Meteorological Society of Japan, 2020, vol. 98, num. 5, p. 1029-1050
dc.rights , 2020
dc.subject.classification 53 - Física
dc.subject.other 53 - Physics
dc.title Tailored Ensemble Prediction Systems: Application of Seamless Scale Bred Vectors
dc.type info:eu-repo/semantics/article
dc.date.updated 2021-02-09T06:38:10Z
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.identifier.doi https://doi.org/10.2151/jmsj.2020-053

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Repository

Advanced Search


My Account