Deliverable No. 1.3 Provision of novel metrics, which can be effectively determined from short time series, through ESMValTool

Field campaigns in the Arctic, like the ongoing Year Of Polar Prediction (YOPP, 2017-2019) or the upcoming Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC, 2019-2020) are key opportunities to conduct an evaluation of Earth System Models (ESMs) at the process level. Thi...

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Main Author: Massonnet, François
Format: Text
Language:English
Published: Zenodo 2018
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.3569273
https://zenodo.org/record/3569273
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spelling ftdatacite:10.5281/zenodo.3569273 2023-05-15T14:50:54+02:00 Deliverable No. 1.3 Provision of novel metrics, which can be effectively determined from short time series, through ESMValTool Massonnet, François 2018 https://dx.doi.org/10.5281/zenodo.3569273 https://zenodo.org/record/3569273 en eng Zenodo https://dx.doi.org/10.5281/zenodo.3569274 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY Text Project deliverable article-journal ScholarlyArticle 2018 ftdatacite https://doi.org/10.5281/zenodo.3569273 https://doi.org/10.5281/zenodo.3569274 2021-11-05T12:55:41Z Field campaigns in the Arctic, like the ongoing Year Of Polar Prediction (YOPP, 2017-2019) or the upcoming Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC, 2019-2020) are key opportunities to conduct an evaluation of Earth System Models (ESMs) at the process level. This raises, however, a number of challenges as ESMs are not necessarily in phase with the actual climate for periods as short as one or two years. Here, a metric is developed to evaluate ESMs on their ability to simulate the snow and ice thicknesses and the underlying process of vertical heat conduction. The metric is derived from a diagnostic called the “heat conductivity index” that has the appealing property to be stable over time, and hence suitable for evaluation of Arctic sea ice where trends are generally strong and interannual variability high. The metric has been incorporated to the ESMValTool, a reference package for model evaluation. This will ensure wider use by the APPLICATE partners (WP1, 2, 4) but also by researchers analyzing the Coupled Model Intercomparison Project, phase 6 (CMIP6) dataset. Text Arctic Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
description Field campaigns in the Arctic, like the ongoing Year Of Polar Prediction (YOPP, 2017-2019) or the upcoming Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC, 2019-2020) are key opportunities to conduct an evaluation of Earth System Models (ESMs) at the process level. This raises, however, a number of challenges as ESMs are not necessarily in phase with the actual climate for periods as short as one or two years. Here, a metric is developed to evaluate ESMs on their ability to simulate the snow and ice thicknesses and the underlying process of vertical heat conduction. The metric is derived from a diagnostic called the “heat conductivity index” that has the appealing property to be stable over time, and hence suitable for evaluation of Arctic sea ice where trends are generally strong and interannual variability high. The metric has been incorporated to the ESMValTool, a reference package for model evaluation. This will ensure wider use by the APPLICATE partners (WP1, 2, 4) but also by researchers analyzing the Coupled Model Intercomparison Project, phase 6 (CMIP6) dataset.
format Text
author Massonnet, François
spellingShingle Massonnet, François
Deliverable No. 1.3 Provision of novel metrics, which can be effectively determined from short time series, through ESMValTool
author_facet Massonnet, François
author_sort Massonnet, François
title Deliverable No. 1.3 Provision of novel metrics, which can be effectively determined from short time series, through ESMValTool
title_short Deliverable No. 1.3 Provision of novel metrics, which can be effectively determined from short time series, through ESMValTool
title_full Deliverable No. 1.3 Provision of novel metrics, which can be effectively determined from short time series, through ESMValTool
title_fullStr Deliverable No. 1.3 Provision of novel metrics, which can be effectively determined from short time series, through ESMValTool
title_full_unstemmed Deliverable No. 1.3 Provision of novel metrics, which can be effectively determined from short time series, through ESMValTool
title_sort deliverable no. 1.3 provision of novel metrics, which can be effectively determined from short time series, through esmvaltool
publisher Zenodo
publishDate 2018
url https://dx.doi.org/10.5281/zenodo.3569273
https://zenodo.org/record/3569273
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
genre_facet Arctic
Sea ice
op_relation https://dx.doi.org/10.5281/zenodo.3569274
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.3569273
https://doi.org/10.5281/zenodo.3569274
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