Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods
Abstract Five initialization and ensemble generation methods are investigated with respect to their impact on the prediction skill of the German decadal prediction system “Mittelfristige Klimaprognose” (MiKlip). Among the tested methods, three tackle aspects of model‐consistent initialization using...
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doaj-ff7b729bc3974e2b97c0a407cb98e42d2020-11-24T21:38:23ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662019-01-0111114917210.1029/2018MS001439Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different MethodsIuliia Polkova0Sebastian Brune1Christopher Kadow2Vanya Romanova3Gereon Gollan4Johanna Baehr5Rita Glowienka‐Hense6Richard J. Greatbatch7Andreas Hense8Sebastian Illing9Armin Köhl10Jürgen Kröger11Wolfgang A. Müller12Klaus Pankatz13Detlef Stammer14Institute of Oceanography Universität Hamburg, CEN Hamburg GermanyInstitute of Oceanography Universität Hamburg, CEN Hamburg GermanyInstitute for Meteorology Freie Universität Berlin Berlin GermanyMeteorological Institute University of Bonn Bonn GermanyGEOMAR Helmholtz Centre for Ocean Research Kiel Kiel GermanyInstitute of Oceanography Universität Hamburg, CEN Hamburg GermanyMeteorological Institute University of Bonn Bonn GermanyGEOMAR Helmholtz Centre for Ocean Research Kiel Kiel GermanyMeteorological Institute University of Bonn Bonn GermanyInstitute for Meteorology Freie Universität Berlin Berlin GermanyInstitute of Oceanography Universität Hamburg, CEN Hamburg GermanyMax Planck Institute for Meteorology Hamburg GermanyMax Planck Institute for Meteorology Hamburg GermanyDeutscher Wetterdienst Offenbach GermanyInstitute of Oceanography Universität Hamburg, CEN Hamburg GermanyAbstract Five initialization and ensemble generation methods are investigated with respect to their impact on the prediction skill of the German decadal prediction system “Mittelfristige Klimaprognose” (MiKlip). Among the tested methods, three tackle aspects of model‐consistent initialization using the ensemble Kalman filter, the filtered anomaly initialization, and the initialization method by partially coupled spin‐up (MODINI). The remaining two methods alter the ensemble generation: the ensemble dispersion filter corrects each ensemble member with the ensemble mean during model integration. And the bred vectors perturb the climate state using the fastest growing modes. The new methods are compared against the latest MiKlip system in the low‐resolution configuration (Preop‐LR), which uses lagging the climate state by a few days for ensemble generation and nudging toward ocean and atmosphere reanalyses for initialization. Results show that the tested methods provide an added value for the prediction skill as compared to Preop‐LR in that they improve prediction skill over the eastern and central Pacific and different regions in the North Atlantic Ocean. In this respect, the ensemble Kalman filter and filtered anomaly initialization show the most distinct improvements over Preop‐LR for surface temperatures and upper ocean heat content, followed by the bred vectors, the ensemble dispersion filter, and MODINI. However, no single method exists that is superior to the others with respect to all metrics considered. In particular, all methods affect the Atlantic Meridional Overturning Circulation in different ways, both with respect to the basin‐wide long‐term mean and variability and with respect to the temporal evolution at the 26° N latitude.https://doi.org/10.1029/2018MS001439decadal prediction systeminitialization methodsensemble generation methods |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Iuliia Polkova Sebastian Brune Christopher Kadow Vanya Romanova Gereon Gollan Johanna Baehr Rita Glowienka‐Hense Richard J. Greatbatch Andreas Hense Sebastian Illing Armin Köhl Jürgen Kröger Wolfgang A. Müller Klaus Pankatz Detlef Stammer |
spellingShingle |
Iuliia Polkova Sebastian Brune Christopher Kadow Vanya Romanova Gereon Gollan Johanna Baehr Rita Glowienka‐Hense Richard J. Greatbatch Andreas Hense Sebastian Illing Armin Köhl Jürgen Kröger Wolfgang A. Müller Klaus Pankatz Detlef Stammer Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods Journal of Advances in Modeling Earth Systems decadal prediction system initialization methods ensemble generation methods |
author_facet |
Iuliia Polkova Sebastian Brune Christopher Kadow Vanya Romanova Gereon Gollan Johanna Baehr Rita Glowienka‐Hense Richard J. Greatbatch Andreas Hense Sebastian Illing Armin Köhl Jürgen Kröger Wolfgang A. Müller Klaus Pankatz Detlef Stammer |
author_sort |
Iuliia Polkova |
title |
Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods |
title_short |
Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods |
title_full |
Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods |
title_fullStr |
Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods |
title_full_unstemmed |
Initialization and Ensemble Generation for Decadal Climate Predictions: A Comparison of Different Methods |
title_sort |
initialization and ensemble generation for decadal climate predictions: a comparison of different methods |
publisher |
American Geophysical Union (AGU) |
series |
Journal of Advances in Modeling Earth Systems |
issn |
1942-2466 |
publishDate |
2019-01-01 |
description |
Abstract Five initialization and ensemble generation methods are investigated with respect to their impact on the prediction skill of the German decadal prediction system “Mittelfristige Klimaprognose” (MiKlip). Among the tested methods, three tackle aspects of model‐consistent initialization using the ensemble Kalman filter, the filtered anomaly initialization, and the initialization method by partially coupled spin‐up (MODINI). The remaining two methods alter the ensemble generation: the ensemble dispersion filter corrects each ensemble member with the ensemble mean during model integration. And the bred vectors perturb the climate state using the fastest growing modes. The new methods are compared against the latest MiKlip system in the low‐resolution configuration (Preop‐LR), which uses lagging the climate state by a few days for ensemble generation and nudging toward ocean and atmosphere reanalyses for initialization. Results show that the tested methods provide an added value for the prediction skill as compared to Preop‐LR in that they improve prediction skill over the eastern and central Pacific and different regions in the North Atlantic Ocean. In this respect, the ensemble Kalman filter and filtered anomaly initialization show the most distinct improvements over Preop‐LR for surface temperatures and upper ocean heat content, followed by the bred vectors, the ensemble dispersion filter, and MODINI. However, no single method exists that is superior to the others with respect to all metrics considered. In particular, all methods affect the Atlantic Meridional Overturning Circulation in different ways, both with respect to the basin‐wide long‐term mean and variability and with respect to the temporal evolution at the 26° N latitude. |
topic |
decadal prediction system initialization methods ensemble generation methods |
url |
https://doi.org/10.1029/2018MS001439 |
work_keys_str_mv |
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