An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
We present a framework that links in situ observations from the Biogeochemical Argo (BGC-Argo) array to biogeochemical models. The framework minimizes the technical effort required to construct a Lagrangian-type 1D modelling experiment along BGC-Argo tracks. We utilize the Argo data in two ways: (1)...
Published in: | Geoscientific Model Development |
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Copernicus Publications
2023
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00070120 2023-12-31T10:20:22+01:00 An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas Yumruktepe, Veli Çağlar Mousing, Erik Askov Tjiputra, Jerry Samuelsen, Annette 2023-11 electronic https://doi.org/10.5194/gmd-16-6875-2023 https://noa.gwlb.de/receive/cop_mods_00070120 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068479/gmd-16-6875-2023.pdf https://gmd.copernicus.org/articles/16/6875/2023/gmd-16-6875-2023.pdf eng eng Copernicus Publications Geoscientific Model Development -- http://www.bibliothek.uni-regensburg.de/ezeit/?2456725 -- http://www.geosci-model-dev.net/ -- 1991-9603 https://doi.org/10.5194/gmd-16-6875-2023 https://noa.gwlb.de/receive/cop_mods_00070120 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068479/gmd-16-6875-2023.pdf https://gmd.copernicus.org/articles/16/6875/2023/gmd-16-6875-2023.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess article Verlagsveröffentlichung article Text doc-type:article 2023 ftnonlinearchiv https://doi.org/10.5194/gmd-16-6875-2023 2023-12-04T00:22:44Z We present a framework that links in situ observations from the Biogeochemical Argo (BGC-Argo) array to biogeochemical models. The framework minimizes the technical effort required to construct a Lagrangian-type 1D modelling experiment along BGC-Argo tracks. We utilize the Argo data in two ways: (1) to drive the model physics and (2) to evaluate the model biogeochemistry. BGC-Argo physics data are used to nudge the model physics closer to observations to reduce the errors in the biogeochemistry stemming from physics errors. This allows us to target the model biogeochemistry and, by using the Argo biogeochemical dataset, we identify potential sources of model errors, introduce changes to the model formulation, and validate model configurations. We present experiments for the Nordic seas and showcase how we identify potential BGC-Argo buoys to model, prepare forcing, design experiments, and approach model improvement and validation. We use the ECOSMO II(CHL) model as the biogeochemical component and focus on chlorophyll a. The experiments reveal that ECOSMO II(CHL) requires improvements during low-light conditions, as the comparison to BGC-Argo reveals that ECOSMO II(CHL) simulates a late spring bloom and does not represent the deep chlorophyll maximum layer formation in summer periods. We modified the productivity and chlorophyll a relationship and statistically documented decreased bias and error in the revised model when using BGC-Argo data. Our results reveal that nudging the model temperature and salinity closer to BGC-Argo data reduces errors in biogeochemistry, and we suggest a relaxation time period of 1–10 d. The BGC-Argo data coverage is ever-growing and the framework is a valuable asset, as it improves biogeochemical models by performing efficient 1D model configurations and evaluation and then transferring the configurations to a 3D model with a wide range of use cases at the operational, regional/global and climate scales. Article in Journal/Newspaper Nordic Seas Niedersächsisches Online-Archiv NOA Geoscientific Model Development 16 22 6875 6897 |
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article Verlagsveröffentlichung Yumruktepe, Veli Çağlar Mousing, Erik Askov Tjiputra, Jerry Samuelsen, Annette An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas |
topic_facet |
article Verlagsveröffentlichung |
description |
We present a framework that links in situ observations from the Biogeochemical Argo (BGC-Argo) array to biogeochemical models. The framework minimizes the technical effort required to construct a Lagrangian-type 1D modelling experiment along BGC-Argo tracks. We utilize the Argo data in two ways: (1) to drive the model physics and (2) to evaluate the model biogeochemistry. BGC-Argo physics data are used to nudge the model physics closer to observations to reduce the errors in the biogeochemistry stemming from physics errors. This allows us to target the model biogeochemistry and, by using the Argo biogeochemical dataset, we identify potential sources of model errors, introduce changes to the model formulation, and validate model configurations. We present experiments for the Nordic seas and showcase how we identify potential BGC-Argo buoys to model, prepare forcing, design experiments, and approach model improvement and validation. We use the ECOSMO II(CHL) model as the biogeochemical component and focus on chlorophyll a. The experiments reveal that ECOSMO II(CHL) requires improvements during low-light conditions, as the comparison to BGC-Argo reveals that ECOSMO II(CHL) simulates a late spring bloom and does not represent the deep chlorophyll maximum layer formation in summer periods. We modified the productivity and chlorophyll a relationship and statistically documented decreased bias and error in the revised model when using BGC-Argo data. Our results reveal that nudging the model temperature and salinity closer to BGC-Argo data reduces errors in biogeochemistry, and we suggest a relaxation time period of 1–10 d. The BGC-Argo data coverage is ever-growing and the framework is a valuable asset, as it improves biogeochemical models by performing efficient 1D model configurations and evaluation and then transferring the configurations to a 3D model with a wide range of use cases at the operational, regional/global and climate scales. |
format |
Article in Journal/Newspaper |
author |
Yumruktepe, Veli Çağlar Mousing, Erik Askov Tjiputra, Jerry Samuelsen, Annette |
author_facet |
Yumruktepe, Veli Çağlar Mousing, Erik Askov Tjiputra, Jerry Samuelsen, Annette |
author_sort |
Yumruktepe, Veli Çağlar |
title |
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas |
title_short |
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas |
title_full |
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas |
title_fullStr |
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas |
title_full_unstemmed |
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas |
title_sort |
along-track biogeochemical argo modelling framework: a case study of model improvements for the nordic seas |
publisher |
Copernicus Publications |
publishDate |
2023 |
url |
https://doi.org/10.5194/gmd-16-6875-2023 https://noa.gwlb.de/receive/cop_mods_00070120 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068479/gmd-16-6875-2023.pdf https://gmd.copernicus.org/articles/16/6875/2023/gmd-16-6875-2023.pdf |
genre |
Nordic Seas |
genre_facet |
Nordic Seas |
op_relation |
Geoscientific Model Development -- http://www.bibliothek.uni-regensburg.de/ezeit/?2456725 -- http://www.geosci-model-dev.net/ -- 1991-9603 https://doi.org/10.5194/gmd-16-6875-2023 https://noa.gwlb.de/receive/cop_mods_00070120 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00068479/gmd-16-6875-2023.pdf https://gmd.copernicus.org/articles/16/6875/2023/gmd-16-6875-2023.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5194/gmd-16-6875-2023 |
container_title |
Geoscientific Model Development |
container_volume |
16 |
container_issue |
22 |
container_start_page |
6875 |
op_container_end_page |
6897 |
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1786830693419974656 |