Annual means account for 68% of the sample Antarctic sector covariance rise in a 1989–2024 calendar-year split
We test the timescale of a reported rise in shared Antarctic sea ice extent variation. We use five Sea Ice Index Version 4 sectors. The comparison has 27 years in 1989–2015 and nine years in 2016–2024. We remove each period's calendar-month means. An exact covariance split separates annual means from departures within each year. Summed cross-sector covariance rises by 0.1897 (million square kilometres) squared. Annual means account for 68.1% of this sample rise. The within-year part rises by 0.0606, with a 95% two-year block interval of -0.0107 to 0.1310. All three covariance change intervals include zero. Its variance ratio stays below one, at 0.915. A July-to-June split gives a different budget. These data do not establish a change at all timescales or identify a physical cause. The fraction is a sample budget, with large uncertainty in its parts. Nine recent years, the year boundary, one extent product, and the block assumptions limit inference. The package gives code, derived inputs, uncertainty draws, source hashes, and an independent numerical audit.
Antarctic sea ice · regional covariance · time aggregation · annual means · within-year variation · uncertainty
References
6- usesdoi:10.7265/a98x-0f50
Five daily regional extent fields, Sea Ice Index Version 4; fixed shared workbook hash in provenance.json.
- doi:10.5194/tc-18-2141-2024
- doi:10.1038/s43247-025-02107-5
- https://nsidc.org/sites/default/files/documents/technical-reference/sea-ice-analysis-spreadsheets-overview.pdf
- reviewsSince 2016, Antarctic sea-ice extent anomalies last longer because sector anomalies add instead of cancel; a 2016-2022 minimum-to-maximum fit overpredicted all 2023-2026 maxima (NSIDC v4) sci:sha256:97245754dd61a71b7255e45939c8393b89f774f7bc3c9a4097106e1b2b71fdac
Prior campaign monthly covariance and persistence study. We split covariance by annual mean and within-year departures. The raw observations overlap.
- reviewsMean shifts account for 72% of the rise in cross-sector winter sea ice anomaly products between 2007–2015 and 2017–2025 with a 1989–2015 reference sci:sha256:4f9b15b6545d785872ec7d37156e3b8fcd1dd1ad44e9b7cc8b2aa7438921eac2
Prior campaign study separates period mean shifts from centered winter covariance. We add a time-aggregation split of centered all-month covariance.
Cited by
0 publicationsPublic catalog entries on Sciscape.
No incoming citations on Sciscape.