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Updated: Dec 13, 2025

Using Generative Art to Convey Past and Future Climate Transitions

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

North Atlantic climate far more predictable than models imply.

D M Smith¹, A A Scaife^2,3, R Eade²

¹Met Office Hadley Centre, Exeter, UK. doug.smith@metoffice.gov.uk.

|July 31, 2020

Summary

This summary is machine-generated.

Climate models underestimate the predictability of North Atlantic winter climate variations. A new post-processing technique improves decadal climate predictions by better estimating the North Atlantic Oscillation signal.

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Area of Science:

Climate Science
Atmospheric Science
Meteorology

Background:

Quantifying climate signals and uncertainties is crucial for climate change detection, attribution, prediction, and projection.
While large-scale temperature signals show high inter-model agreement, atmospheric circulation dynamics and regional precipitation projections remain highly uncertain.
The chaotic nature of the climate system may imply irreducible signal uncertainties, complicating verification of climate projections.

Purpose of the Study:

To assess retrospective climate model predictions over the past six decades.
To investigate the predictability of decadal variations in North Atlantic winter climate.
To address the underestimation of the North Atlantic Oscillation signal in current climate models.

Main Methods:

Retrospective analysis of six decades of climate model predictions.
Assessment of the predictable signal of the North Atlantic Oscillation (NAO).
Implementation of a two-stage post-processing technique: variance adjustment and ensemble member selection.

Main Results:

Decadal variations in North Atlantic winter climate are highly predictable, despite inter-model disagreement and poor raw model output prediction.
Current climate models underestimate the predictable NAO signal by an order of magnitude, requiring 100 times more ensemble members to extract.
The post-processing technique significantly improves decadal predictions of European and North American winter climate and Atlantic multidecadal variability.

Conclusions:

The study highlights a critical underestimation of the signal-to-noise ratio in current climate models regarding the NAO.
The developed post-processing method enhances the accuracy of decadal climate predictions.
Correcting model errors in signal-to-noise ratio could reduce uncertainties in regional climate change projections beyond a decade.