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Related Experiment Video

Updated: Jul 14, 2026

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

Ensemble decadal predictions from analysed initial conditions.

Alberto Troccoli¹, T N Palmer

¹European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK. alberto.troccoli@ecmwf.int

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|June 16, 2007

Summary

This study shows that climate signals on interannual-to-decadal timescales are detectable, even with model drift. Initial conditions and greenhouse gas levels are key to understanding this predictability.

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Last Updated: Jul 14, 2026

Using Generative Art to Convey Past and Future Climate Transitions

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Published on: March 31, 2023

Sediment Core Extrusion Method at Millimeter Resolution Using a Calibrated, Threaded-rod

Sediment Core Extrusion Method at Millimeter Resolution Using a Calibrated, Threaded-rod

Published on: August 17, 2016

Area of Science:

Climate science
Ocean-atmosphere interaction
Predictability studies

Background:

Extending seasonal predictions to longer timescales is crucial for climate adaptation.
Understanding interannual-to-decadal climate variability is essential for climate projections.

Purpose of the Study:

To investigate the potential for interannual-to-decadal predictability using a coupled model.
To explore extending seasonal predictions to longer time scales.
To isolate the impact of initial conditions and greenhouse gases on predictability.

Main Methods:

Sensitivity experiments using a coupled model initialized from observational data.
Comparison of model runs starting from different climatic states (1965 and 1994).
Isolation of initial condition and greenhouse gas effects.

Main Results:

Climatic signals on interannual-to-decadal timescales are detectable despite model drift.
Predictability is influenced by initial conditions and greenhouse gas levels.
Two distinct climatic states (pre-cooling and pre-warming) were analyzed.

Conclusions:

Interannual-to-decadal climate predictability is feasible.
Initial conditions and greenhouse gas concentrations are significant drivers of predictability.
Further research can refine long-term climate predictions.