Benchmark seasonal prediction skill estimates based on regional indices

Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. In this stud...

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Published in:The Cryosphere
Main Authors: J. E. Walsh, J. S. Stewart, F. Fetterer
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2019
Subjects:
Online Access:https://doi.org/10.5194/tc-13-1073-2019
https://doaj.org/article/07d00a267b9947a1b07309707cb7dcdb
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spelling ftdoajarticles:oai:doaj.org/article:07d00a267b9947a1b07309707cb7dcdb 2023-05-15T14:56:56+02:00 Benchmark seasonal prediction skill estimates based on regional indices J. E. Walsh J. S. Stewart F. Fetterer 2019-04-01T00:00:00Z https://doi.org/10.5194/tc-13-1073-2019 https://doaj.org/article/07d00a267b9947a1b07309707cb7dcdb EN eng Copernicus Publications https://www.the-cryosphere.net/13/1073/2019/tc-13-1073-2019.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-13-1073-2019 1994-0416 1994-0424 https://doaj.org/article/07d00a267b9947a1b07309707cb7dcdb The Cryosphere, Vol 13, Pp 1073-1088 (2019) Environmental sciences GE1-350 Geology QE1-996.5 article 2019 ftdoajarticles https://doi.org/10.5194/tc-13-1073-2019 2022-12-31T01:20:25Z Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. In this study we use observational data to evaluate the contribution of the trend to the skill of persistence-based statistical forecasts of monthly and seasonal ice extent on the pan-Arctic and regional scales. We focus on the Beaufort Sea for which the Barnett Severity Index provides a metric of historical variations in ice conditions over the summer shipping season. The variance about the trend line differs little among various methods of detrending (piecewise linear, quadratic, cubic, exponential). Application of the piecewise linear trend calculation indicates an acceleration of the winter and summer trends during the 1990s. Persistence-based statistical forecasts of the Barnett Severity Index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the data are detrended. In only a few regions does September ice extent correlate significantly with antecedent ice anomalies in the same region more than 2 months earlier. The springtime <q>predictability barrier</q> in regional forecasts based on persistence of ice extent anomalies is not reduced by the inclusion of several decades of pre-satellite data. No region shows significant correlation with the detrended September pan-Arctic ice extent at lead times greater than a month or two; the concurrent correlations are strongest with the East Siberian Sea. The Beaufort Sea's ice extent as far back as July explains about 20 % of the variance of the Barnett Severity Index, which is primarily a September metric. The Chukchi Sea is the only other region showing a significant association with the Barnett Severity Index, although only at a lead ... Article in Journal/Newspaper Arctic Beaufort Sea Chukchi Chukchi Sea East Siberian Sea Sea ice The Cryosphere Directory of Open Access Journals: DOAJ Articles Arctic Chukchi Sea East Siberian Sea ENVELOPE(166.000,166.000,74.000,74.000) The Cryosphere 13 4 1073 1088
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Environmental sciences
GE1-350
Geology
QE1-996.5
spellingShingle Environmental sciences
GE1-350
Geology
QE1-996.5
J. E. Walsh
J. S. Stewart
F. Fetterer
Benchmark seasonal prediction skill estimates based on regional indices
topic_facet Environmental sciences
GE1-350
Geology
QE1-996.5
description Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. In this study we use observational data to evaluate the contribution of the trend to the skill of persistence-based statistical forecasts of monthly and seasonal ice extent on the pan-Arctic and regional scales. We focus on the Beaufort Sea for which the Barnett Severity Index provides a metric of historical variations in ice conditions over the summer shipping season. The variance about the trend line differs little among various methods of detrending (piecewise linear, quadratic, cubic, exponential). Application of the piecewise linear trend calculation indicates an acceleration of the winter and summer trends during the 1990s. Persistence-based statistical forecasts of the Barnett Severity Index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the data are detrended. In only a few regions does September ice extent correlate significantly with antecedent ice anomalies in the same region more than 2 months earlier. The springtime <q>predictability barrier</q> in regional forecasts based on persistence of ice extent anomalies is not reduced by the inclusion of several decades of pre-satellite data. No region shows significant correlation with the detrended September pan-Arctic ice extent at lead times greater than a month or two; the concurrent correlations are strongest with the East Siberian Sea. The Beaufort Sea's ice extent as far back as July explains about 20 % of the variance of the Barnett Severity Index, which is primarily a September metric. The Chukchi Sea is the only other region showing a significant association with the Barnett Severity Index, although only at a lead ...
format Article in Journal/Newspaper
author J. E. Walsh
J. S. Stewart
F. Fetterer
author_facet J. E. Walsh
J. S. Stewart
F. Fetterer
author_sort J. E. Walsh
title Benchmark seasonal prediction skill estimates based on regional indices
title_short Benchmark seasonal prediction skill estimates based on regional indices
title_full Benchmark seasonal prediction skill estimates based on regional indices
title_fullStr Benchmark seasonal prediction skill estimates based on regional indices
title_full_unstemmed Benchmark seasonal prediction skill estimates based on regional indices
title_sort benchmark seasonal prediction skill estimates based on regional indices
publisher Copernicus Publications
publishDate 2019
url https://doi.org/10.5194/tc-13-1073-2019
https://doaj.org/article/07d00a267b9947a1b07309707cb7dcdb
long_lat ENVELOPE(166.000,166.000,74.000,74.000)
geographic Arctic
Chukchi Sea
East Siberian Sea
geographic_facet Arctic
Chukchi Sea
East Siberian Sea
genre Arctic
Beaufort Sea
Chukchi
Chukchi Sea
East Siberian Sea
Sea ice
The Cryosphere
genre_facet Arctic
Beaufort Sea
Chukchi
Chukchi Sea
East Siberian Sea
Sea ice
The Cryosphere
op_source The Cryosphere, Vol 13, Pp 1073-1088 (2019)
op_relation https://www.the-cryosphere.net/13/1073/2019/tc-13-1073-2019.pdf
https://doaj.org/toc/1994-0416
https://doaj.org/toc/1994-0424
doi:10.5194/tc-13-1073-2019
1994-0416
1994-0424
https://doaj.org/article/07d00a267b9947a1b07309707cb7dcdb
op_doi https://doi.org/10.5194/tc-13-1073-2019
container_title The Cryosphere
container_volume 13
container_issue 4
container_start_page 1073
op_container_end_page 1088
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