Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes
A transition to renewable energy is needed to mitigate climate change. In Europe, this transition has been led by wind energy, which is one of the fastest growing energy sources. However, energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple...
Published in: | Environmental Research Letters |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | http://hdl.handle.net/10852/105487 https://doi.org/10.1088/1748-9326/acb6aa |
id |
ftoslouniv:oai:www.duo.uio.no:10852/105487 |
---|---|
record_format |
openpolar |
spelling |
ftoslouniv:oai:www.duo.uio.no:10852/105487 2023-11-05T03:44:09+01:00 Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes ENEngelskEnglishGaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes Tedesco, Paulina Souza Lenkoski, Frank Alexander Bloomfield, Hannah C. Sillmann, Jana 2023-05-04T10:42:24Z http://hdl.handle.net/10852/105487 https://doi.org/10.1088/1748-9326/acb6aa EN eng NFR/303411 NFR/309562 Tedesco, Paulina Souza Lenkoski, Frank Alexander Bloomfield, Hannah C. Sillmann, Jana . Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes. Environmental Research Letters. 2023, 18(3) http://hdl.handle.net/10852/105487 2145373 info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Environmental Research Letters&rft.volume=18&rft.spage=&rft.date=2023 Environmental Research Letters 18 3 0 https://doi.org/10.1088/1748-9326/acb6aa Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ 1748-9326 Journal article Tidsskriftartikkel Peer reviewed PublishedVersion 2023 ftoslouniv https://doi.org/10.1088/1748-9326/acb6aa 2023-10-11T22:39:28Z A transition to renewable energy is needed to mitigate climate change. In Europe, this transition has been led by wind energy, which is one of the fastest growing energy sources. However, energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple time scales. To accomplish the required balance between these two variables, critical conditions of high demand and low wind energy supply must be considered in the design of energy systems. We describe a methodology for modeling joint distributions of meteorological variables without making any assumptions about their marginal distributions. In this context, Gaussian copulas are used to model the correlated nature of cold and weak-wind events. The marginal distributions are modeled with logistic regressions defining two sets of binary variables as predictors: four large-scale weather regimes (WRs) and the months of the extended winter season. By applying this framework to ERA5 data, we can compute the joint probabilities of co-occurrence of cold and weak-wind events on a high-resolution grid (0.2◦).Our results show that (a) WRs must be considered when modeling cold and weak-wind events, (b) it is essential to account for the correlations between these events when modeling their joint distribution, (c) we need to analyze each month separately, and (d) the highest estimated number of days with compound events are associated with the negative phase of the North Atlantic Oscillation (3 days on average over Finland, Ireland, and Lithuania in January, and France and Luxembourg in February) and the Scandinavian blocking pattern (3 days on average over Ireland in January and Denmark in February). This information could be relevant for application in sub-seasonal to seasonal forecasts of such events Article in Journal/Newspaper North Atlantic North Atlantic oscillation Universitet i Oslo: Digitale utgivelser ved UiO (DUO) Environmental Research Letters 18 3 034008 |
institution |
Open Polar |
collection |
Universitet i Oslo: Digitale utgivelser ved UiO (DUO) |
op_collection_id |
ftoslouniv |
language |
English |
description |
A transition to renewable energy is needed to mitigate climate change. In Europe, this transition has been led by wind energy, which is one of the fastest growing energy sources. However, energy demand and production are sensitive to meteorological conditions and atmospheric variability at multiple time scales. To accomplish the required balance between these two variables, critical conditions of high demand and low wind energy supply must be considered in the design of energy systems. We describe a methodology for modeling joint distributions of meteorological variables without making any assumptions about their marginal distributions. In this context, Gaussian copulas are used to model the correlated nature of cold and weak-wind events. The marginal distributions are modeled with logistic regressions defining two sets of binary variables as predictors: four large-scale weather regimes (WRs) and the months of the extended winter season. By applying this framework to ERA5 data, we can compute the joint probabilities of co-occurrence of cold and weak-wind events on a high-resolution grid (0.2◦).Our results show that (a) WRs must be considered when modeling cold and weak-wind events, (b) it is essential to account for the correlations between these events when modeling their joint distribution, (c) we need to analyze each month separately, and (d) the highest estimated number of days with compound events are associated with the negative phase of the North Atlantic Oscillation (3 days on average over Finland, Ireland, and Lithuania in January, and France and Luxembourg in February) and the Scandinavian blocking pattern (3 days on average over Ireland in January and Denmark in February). This information could be relevant for application in sub-seasonal to seasonal forecasts of such events |
format |
Article in Journal/Newspaper |
author |
Tedesco, Paulina Souza Lenkoski, Frank Alexander Bloomfield, Hannah C. Sillmann, Jana |
spellingShingle |
Tedesco, Paulina Souza Lenkoski, Frank Alexander Bloomfield, Hannah C. Sillmann, Jana Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes |
author_facet |
Tedesco, Paulina Souza Lenkoski, Frank Alexander Bloomfield, Hannah C. Sillmann, Jana |
author_sort |
Tedesco, Paulina Souza |
title |
Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes |
title_short |
Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes |
title_full |
Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes |
title_fullStr |
Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes |
title_full_unstemmed |
Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes |
title_sort |
gaussian copula modeling of extreme cold and weak-wind events over europe conditioned on winter weather regimes |
publishDate |
2023 |
url |
http://hdl.handle.net/10852/105487 https://doi.org/10.1088/1748-9326/acb6aa |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_source |
1748-9326 |
op_relation |
NFR/303411 NFR/309562 Tedesco, Paulina Souza Lenkoski, Frank Alexander Bloomfield, Hannah C. Sillmann, Jana . Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes. Environmental Research Letters. 2023, 18(3) http://hdl.handle.net/10852/105487 2145373 info:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Environmental Research Letters&rft.volume=18&rft.spage=&rft.date=2023 Environmental Research Letters 18 3 0 https://doi.org/10.1088/1748-9326/acb6aa |
op_rights |
Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1088/1748-9326/acb6aa |
container_title |
Environmental Research Letters |
container_volume |
18 |
container_issue |
3 |
container_start_page |
034008 |
_version_ |
1781703330157821952 |