Singular vectors, predictability and ensemble forecasting for weather and climate
The local instabilities of a nonlinear dynamical system can be characterized by the leading singular vectors of its linearized operator. The leading singular vectors are perturbations with the greatest linear growth and are therefore key in assessing the system's predictability. In this paper,...
| Asıl Yazarlar: | , |
|---|---|
| Materyal Türü: | Journal article |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
2013
|
| _version_ | 1826265891227041792 |
|---|---|
| author | Palmer, T Zanna, L |
| author_facet | Palmer, T Zanna, L |
| author_sort | Palmer, T |
| collection | OXFORD |
| description | The local instabilities of a nonlinear dynamical system can be characterized by the leading singular vectors of its linearized operator. The leading singular vectors are perturbations with the greatest linear growth and are therefore key in assessing the system's predictability. In this paper, the analysis of singular vectors for the predictability of weather and climate and ensemble forecasting is discussed. An overview of the role of singular vectors in informing about the error growth rate in numerical models of the atmosphere is given. This is followed by their use in the initialization of ensemble weather forecasts. Singular vectors for the ocean and coupled ocean-atmosphere system in order to understand the predictability of climate phenomena such as ENSO and meridional overturning circulation are reviewed and their potential use to initialize seasonal and decadal forecasts is considered. As stochastic parameterizations are being implemented, some speculations are made about the future of singular vectors for the predictability of weather and climate for theoretical applications and at the operational level. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to 'Lyapunov analysis: from dynamical systems theory to applications'. © 2013 IOP Publishing Ltd. |
| first_indexed | 2024-03-06T20:30:42Z |
| format | Journal article |
| id | oxford-uuid:30ef5018-e056-4c0f-a3a6-02ce013cda62 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:30:42Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:30ef5018-e056-4c0f-a3a6-02ce013cda622022-03-26T13:04:42ZSingular vectors, predictability and ensemble forecasting for weather and climateJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:30ef5018-e056-4c0f-a3a6-02ce013cda62EnglishSymplectic Elements at Oxford2013Palmer, TZanna, LThe local instabilities of a nonlinear dynamical system can be characterized by the leading singular vectors of its linearized operator. The leading singular vectors are perturbations with the greatest linear growth and are therefore key in assessing the system's predictability. In this paper, the analysis of singular vectors for the predictability of weather and climate and ensemble forecasting is discussed. An overview of the role of singular vectors in informing about the error growth rate in numerical models of the atmosphere is given. This is followed by their use in the initialization of ensemble weather forecasts. Singular vectors for the ocean and coupled ocean-atmosphere system in order to understand the predictability of climate phenomena such as ENSO and meridional overturning circulation are reviewed and their potential use to initialize seasonal and decadal forecasts is considered. As stochastic parameterizations are being implemented, some speculations are made about the future of singular vectors for the predictability of weather and climate for theoretical applications and at the operational level. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to 'Lyapunov analysis: from dynamical systems theory to applications'. © 2013 IOP Publishing Ltd. |
| spellingShingle | Palmer, T Zanna, L Singular vectors, predictability and ensemble forecasting for weather and climate |
| title | Singular vectors, predictability and ensemble forecasting for weather and climate |
| title_full | Singular vectors, predictability and ensemble forecasting for weather and climate |
| title_fullStr | Singular vectors, predictability and ensemble forecasting for weather and climate |
| title_full_unstemmed | Singular vectors, predictability and ensemble forecasting for weather and climate |
| title_short | Singular vectors, predictability and ensemble forecasting for weather and climate |
| title_sort | singular vectors predictability and ensemble forecasting for weather and climate |
| work_keys_str_mv | AT palmert singularvectorspredictabilityandensembleforecastingforweatherandclimate AT zannal singularvectorspredictabilityandensembleforecastingforweatherandclimate |