The sensitivity of tree growth to air mass variability and the Pacific Decadal Oscillation in coastal Alabama
International audience A statistical learning method called random forests is applied to the prediction of transitions between weather regimes of wintertime Northern Hemisphere (NH) atmospheric low-frequency variability. A dataset composed of 55 winters of NH 700-mb geopotential height anomalies is...
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ftecoleponts:oai:HAL:hal-04110175v1 2024-09-15T18:23:40+00:00 The sensitivity of tree growth to air mass variability and the Pacific Decadal Oscillation in coastal Alabama Kondrashov, D. Shen, J. Berk, R. D'Andrea, F. Ghil, M. Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X) Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) 2007 https://hal.science/hal-04110175 https://doi.org/10.1007/s00382-007-0293-2 en eng HAL CCSD Springer Verlag info:eu-repo/semantics/altIdentifier/doi/10.1007/s00382-007-0293-2 hal-04110175 https://hal.science/hal-04110175 BIBCODE: 2007ClDy.29.535K doi:10.1007/s00382-007-0293-2 ISSN: 0020-7128 EISSN: 1432-1254 International Journal of Biometeorology https://hal.science/hal-04110175 International Journal of Biometeorology, 2007, 51, pp.483-491. ⟨10.1007/s00382-007-0293-2⟩ Dendroclimatology Spatial synoptic classification Air mass Alabama Pacific Decadal Oscillation [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2007 ftecoleponts https://doi.org/10.1007/s00382-007-0293-2 2024-08-13T23:47:27Z International audience A statistical learning method called random forests is applied to the prediction of transitions between weather regimes of wintertime Northern Hemisphere (NH) atmospheric low-frequency variability. A dataset composed of 55 winters of NH 700-mb geopotential height anomalies is used in the present study. A mixture model finds that the three Gaussian components that were statistically significant in earlier work are robust; they are the Pacific-North American (PNA) regime, its approximate reverse (the reverse PNA, or RNA), and the blocked phase of the North Atlantic Oscillation ( BNAO). The most significant and robust transitions in the Markov chain generated by these regimes are PNA → BNAO, PNA → RNA and BNAO → PNA. The break of a regime and subsequent onset of another one is forecast for these three transitions. Taking the relative costs of false positives and false negatives into account, the random-forests method shows useful forecasting skill. The calculations are carried out in the phase space spanned by a few leading empirical orthogonal functions of dataset variability. Plots of estimated response functions to a given predictor confirm the crucial influence of the exit angle on a preferred transition path. This result points to the dynamic origin of the transitions. Article in Journal/Newspaper North Atlantic North Atlantic oscillation École des Ponts ParisTech: HAL Climate Dynamics 29 5 535 551 |
institution |
Open Polar |
collection |
École des Ponts ParisTech: HAL |
op_collection_id |
ftecoleponts |
language |
English |
topic |
Dendroclimatology Spatial synoptic classification Air mass Alabama Pacific Decadal Oscillation [SDU]Sciences of the Universe [physics] |
spellingShingle |
Dendroclimatology Spatial synoptic classification Air mass Alabama Pacific Decadal Oscillation [SDU]Sciences of the Universe [physics] Kondrashov, D. Shen, J. Berk, R. D'Andrea, F. Ghil, M. The sensitivity of tree growth to air mass variability and the Pacific Decadal Oscillation in coastal Alabama |
topic_facet |
Dendroclimatology Spatial synoptic classification Air mass Alabama Pacific Decadal Oscillation [SDU]Sciences of the Universe [physics] |
description |
International audience A statistical learning method called random forests is applied to the prediction of transitions between weather regimes of wintertime Northern Hemisphere (NH) atmospheric low-frequency variability. A dataset composed of 55 winters of NH 700-mb geopotential height anomalies is used in the present study. A mixture model finds that the three Gaussian components that were statistically significant in earlier work are robust; they are the Pacific-North American (PNA) regime, its approximate reverse (the reverse PNA, or RNA), and the blocked phase of the North Atlantic Oscillation ( BNAO). The most significant and robust transitions in the Markov chain generated by these regimes are PNA → BNAO, PNA → RNA and BNAO → PNA. The break of a regime and subsequent onset of another one is forecast for these three transitions. Taking the relative costs of false positives and false negatives into account, the random-forests method shows useful forecasting skill. The calculations are carried out in the phase space spanned by a few leading empirical orthogonal functions of dataset variability. Plots of estimated response functions to a given predictor confirm the crucial influence of the exit angle on a preferred transition path. This result points to the dynamic origin of the transitions. |
author2 |
Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X) Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) |
format |
Article in Journal/Newspaper |
author |
Kondrashov, D. Shen, J. Berk, R. D'Andrea, F. Ghil, M. |
author_facet |
Kondrashov, D. Shen, J. Berk, R. D'Andrea, F. Ghil, M. |
author_sort |
Kondrashov, D. |
title |
The sensitivity of tree growth to air mass variability and the Pacific Decadal Oscillation in coastal Alabama |
title_short |
The sensitivity of tree growth to air mass variability and the Pacific Decadal Oscillation in coastal Alabama |
title_full |
The sensitivity of tree growth to air mass variability and the Pacific Decadal Oscillation in coastal Alabama |
title_fullStr |
The sensitivity of tree growth to air mass variability and the Pacific Decadal Oscillation in coastal Alabama |
title_full_unstemmed |
The sensitivity of tree growth to air mass variability and the Pacific Decadal Oscillation in coastal Alabama |
title_sort |
sensitivity of tree growth to air mass variability and the pacific decadal oscillation in coastal alabama |
publisher |
HAL CCSD |
publishDate |
2007 |
url |
https://hal.science/hal-04110175 https://doi.org/10.1007/s00382-007-0293-2 |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
ISSN: 0020-7128 EISSN: 1432-1254 International Journal of Biometeorology https://hal.science/hal-04110175 International Journal of Biometeorology, 2007, 51, pp.483-491. ⟨10.1007/s00382-007-0293-2⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00382-007-0293-2 hal-04110175 https://hal.science/hal-04110175 BIBCODE: 2007ClDy.29.535K doi:10.1007/s00382-007-0293-2 |
op_doi |
https://doi.org/10.1007/s00382-007-0293-2 |
container_title |
Climate Dynamics |
container_volume |
29 |
container_issue |
5 |
container_start_page |
535 |
op_container_end_page |
551 |
_version_ |
1810463917939359744 |