Seasonal transition dates can reveal biases in Arctic sea ice simulations
Arctic sea ice experiences a dramatic annual cycle, and seasonal ice loss and growth can be characterized by various metrics: melt onset, breakup, opening, freeze onset, freeze-up, and closing. By evaluating a range of seasonal sea ice metrics, CMIP6 sea ice simulations can be evaluated in more deta...
Published in: | The Cryosphere |
---|---|
Main Authors: | , , |
Format: | Text |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://doi.org/10.5194/tc-14-2977-2020 https://tc.copernicus.org/articles/14/2977/2020/ |
id |
ftcopernicus:oai:publications.copernicus.org:tc84605 |
---|---|
record_format |
openpolar |
spelling |
ftcopernicus:oai:publications.copernicus.org:tc84605 2023-05-15T14:50:48+02:00 Seasonal transition dates can reveal biases in Arctic sea ice simulations Smith, Abigail Jahn, Alexandra Wang, Muyin 2020-09-14 application/pdf https://doi.org/10.5194/tc-14-2977-2020 https://tc.copernicus.org/articles/14/2977/2020/ eng eng doi:10.5194/tc-14-2977-2020 https://tc.copernicus.org/articles/14/2977/2020/ eISSN: 1994-0424 Text 2020 ftcopernicus https://doi.org/10.5194/tc-14-2977-2020 2020-09-21T16:22:14Z Arctic sea ice experiences a dramatic annual cycle, and seasonal ice loss and growth can be characterized by various metrics: melt onset, breakup, opening, freeze onset, freeze-up, and closing. By evaluating a range of seasonal sea ice metrics, CMIP6 sea ice simulations can be evaluated in more detail than by using traditional metrics alone, such as sea ice area. We show that models capture the observed asymmetry in seasonal sea ice transitions, with spring ice loss taking about 1–2 months longer than fall ice growth. The largest impacts of internal variability are seen in the inflow regions for melt and freeze onset dates, but all metrics show pan-Arctic model spreads exceeding the internal variability range, indicating the contribution of model differences. Through climate model evaluation in the context of both observations and internal variability, we show that biases in seasonal transition dates can compensate for other unrealistic aspects of simulated sea ice. In some models, this leads to September sea ice areas in agreement with observations for the wrong reasons. Text Arctic Sea ice Copernicus Publications: E-Journals Arctic The Cryosphere 14 9 2977 2997 |
institution |
Open Polar |
collection |
Copernicus Publications: E-Journals |
op_collection_id |
ftcopernicus |
language |
English |
description |
Arctic sea ice experiences a dramatic annual cycle, and seasonal ice loss and growth can be characterized by various metrics: melt onset, breakup, opening, freeze onset, freeze-up, and closing. By evaluating a range of seasonal sea ice metrics, CMIP6 sea ice simulations can be evaluated in more detail than by using traditional metrics alone, such as sea ice area. We show that models capture the observed asymmetry in seasonal sea ice transitions, with spring ice loss taking about 1–2 months longer than fall ice growth. The largest impacts of internal variability are seen in the inflow regions for melt and freeze onset dates, but all metrics show pan-Arctic model spreads exceeding the internal variability range, indicating the contribution of model differences. Through climate model evaluation in the context of both observations and internal variability, we show that biases in seasonal transition dates can compensate for other unrealistic aspects of simulated sea ice. In some models, this leads to September sea ice areas in agreement with observations for the wrong reasons. |
format |
Text |
author |
Smith, Abigail Jahn, Alexandra Wang, Muyin |
spellingShingle |
Smith, Abigail Jahn, Alexandra Wang, Muyin Seasonal transition dates can reveal biases in Arctic sea ice simulations |
author_facet |
Smith, Abigail Jahn, Alexandra Wang, Muyin |
author_sort |
Smith, Abigail |
title |
Seasonal transition dates can reveal biases in Arctic sea ice simulations |
title_short |
Seasonal transition dates can reveal biases in Arctic sea ice simulations |
title_full |
Seasonal transition dates can reveal biases in Arctic sea ice simulations |
title_fullStr |
Seasonal transition dates can reveal biases in Arctic sea ice simulations |
title_full_unstemmed |
Seasonal transition dates can reveal biases in Arctic sea ice simulations |
title_sort |
seasonal transition dates can reveal biases in arctic sea ice simulations |
publishDate |
2020 |
url |
https://doi.org/10.5194/tc-14-2977-2020 https://tc.copernicus.org/articles/14/2977/2020/ |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
eISSN: 1994-0424 |
op_relation |
doi:10.5194/tc-14-2977-2020 https://tc.copernicus.org/articles/14/2977/2020/ |
op_doi |
https://doi.org/10.5194/tc-14-2977-2020 |
container_title |
The Cryosphere |
container_volume |
14 |
container_issue |
9 |
container_start_page |
2977 |
op_container_end_page |
2997 |
_version_ |
1766321852636987392 |