Record-breaking statistics detect islands of cooling in a sea of warming
Record-breaking statistics are combined here with a geographic mode of exploration to introduce a record-breaking map. We examine time series of sea surface temperature (SST) values and show that high SST records have been broken far more frequently than the expected rate for a trend-free random var...
Published in: | Atmospheric Chemistry and Physics |
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Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2022
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Subjects: | |
Online Access: | https://doi.org/10.5194/acp-22-16111-2022 https://noa.gwlb.de/receive/cop_mods_00064142 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00063007/acp-22-16111-2022.pdf https://acp.copernicus.org/articles/22/16111/2022/acp-22-16111-2022.pdf |
Summary: | Record-breaking statistics are combined here with a geographic mode of exploration to introduce a record-breaking map. We examine time series of sea surface temperature (SST) values and show that high SST records have been broken far more frequently than the expected rate for a trend-free random variable (TFRV) over the vast majority of oceans (83 % of the grid cells). This, together with the asymmetry between high and low records and their deviation from a TFRV, indicates SST warming over most oceans, obtained using a distribution-independent, robust, and simple-to-use method. The spatial patterns of this warming are coherent and reveal islands of cooling, such as the “cold blob” in the North Atlantic and a surprising elliptical area in the Southern Ocean, near the Ross Sea gyre, not previously reported. The method was also applied to evaluate a global climate model (GCM), which reproduced the observed records during the study period. The distribution of records from the GCM pre-industrial (PI) control run samples was similar to the one from a TFRV, suggesting that the contribution of a suitably constrained internal variability to the observed record-breaking trends is negligible. Future forecasts show striking SST trends, with even more frequent high records and less frequent low records. |
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