Skilful decadal predictions of subpolar North Atlantic SSTs using CMIP model-analogues
Predicting regional climate variability is a key goal of initialised decadal predictions and the North Atlantic has been a major focus due to its high level of predictability and potential impact on European climate. These predictions often focus on decadal variability in sea surface temperatures (S...
| Published in: | Environmental Research Letters |
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| Main Authors: | , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
IOP Publishing
2021
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| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ac06fb https://doaj.org/article/08230074b1cd414aaa50b2f557cbaac3 |
| Summary: | Predicting regional climate variability is a key goal of initialised decadal predictions and the North Atlantic has been a major focus due to its high level of predictability and potential impact on European climate. These predictions often focus on decadal variability in sea surface temperatures (SSTs) in the North Atlantic subpolar gyre (NA SPG). In order to understand the value of initialisation, and justify the high costs of such systems, predictions are routinely measured against technologically simpler benchmarks. Here, we present a new model-analogue benchmark that aims to leverage the latent information in uninitialised climate model simulations to make decadal predictions of NA SPG SSTs. This system searches through more than one hundred thousand simulated years in Coupled Model Intercomparison Project archives and yields skilful predictions in its target region comparable to initialised systems. Analysis of the underlying behaviour of the system suggests the origins of this skill are physically plausible. Such a system can provide a useful benchmark for initialised systems within the NA SPG and also suggests that the limits in initialised decadal prediction skill in this region have not yet been reached. |
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