Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information

We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the G...

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Published in:Scientific Reports
Main Authors: Steirou, E., Gerlitz, L., Sun, X., Apel, H., Agarwal, A., Totz, S., Merz, B.
Format: Article in Journal/Newspaper
Language:unknown
Published: 2022
Subjects:
Online Access:https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364_1/component/file_5012885/5012364.pdf
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spelling ftgfzpotsdam:oai:gfzpublic.gfz-potsdam.de:item_5012364 2023-05-15T18:18:21+02:00 Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information Steirou, E. Gerlitz, L. Sun, X. Apel, H. Agarwal, A. Totz, S. Merz, B. 2022 application/pdf https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364_1/component/file_5012885/5012364.pdf unknown info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-022-16633-1 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364_1/component/file_5012885/5012364.pdf info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ CC-BY Scientific Reports info:eu-repo/semantics/article 2022 ftgfzpotsdam https://doi.org/10.1038/s41598-022-16633-1 2022-12-12T00:32:16Z We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead. Article in Journal/Newspaper Sea ice GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam) Scientific Reports 12 1
institution Open Polar
collection GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam)
op_collection_id ftgfzpotsdam
language unknown
description We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead.
format Article in Journal/Newspaper
author Steirou, E.
Gerlitz, L.
Sun, X.
Apel, H.
Agarwal, A.
Totz, S.
Merz, B.
spellingShingle Steirou, E.
Gerlitz, L.
Sun, X.
Apel, H.
Agarwal, A.
Totz, S.
Merz, B.
Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
author_facet Steirou, E.
Gerlitz, L.
Sun, X.
Apel, H.
Agarwal, A.
Totz, S.
Merz, B.
author_sort Steirou, E.
title Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
title_short Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
title_full Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
title_fullStr Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
title_full_unstemmed Towards seasonal forecasting of flood probabilities in Europe using climate and catchment information
title_sort towards seasonal forecasting of flood probabilities in europe using climate and catchment information
publishDate 2022
url https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364_1/component/file_5012885/5012364.pdf
genre Sea ice
genre_facet Sea ice
op_source Scientific Reports
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-022-16633-1
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5012364_1/component/file_5012885/5012364.pdf
op_rights info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/
op_rightsnorm CC-BY
op_doi https://doi.org/10.1038/s41598-022-16633-1
container_title Scientific Reports
container_volume 12
container_issue 1
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