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Updated: Jul 14, 2026
10:22
Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Irreducible imprecision in atmospheric and oceanic simulations
1Department of Atmospheric and Oceanic Sciences and Institute of Geophysics and Planetary Physics, University of California, Los Angeles, CA 90095-1565, USA. jcm@atmos.ucla.edu
Summary
Computational models of Earth's systems, like climate models, inherently possess irreducible imprecision due to design choices. Ensemble simulations across diverse model families are crucial for estimating this uncertainty in forecasts.
Area of Science:
- Earth System Science
- Computational Modeling
- Climate Science
Background:
- Atmospheric and oceanic computational models accurately simulate complex natural phenomena.
- Model success relies on non-unique choices in algorithms and parameterizations, introducing structural instability.
- This inherent instability leads to irreducible imprecision in quantitative comparisons with nature.
Purpose of the Study:
- To explain the source of irreducible imprecision in computational simulation models.
- To highlight the necessity of ensemble modeling for quantifying forecast uncertainty.
- To emphasize the limitations of single model calibrations for precise nature correspondence.
Main Methods:
- Analysis of structural instability in computational models arising from discrete choices.
- Examination of the impact of parameterizations and coupled processes on model fidelity.
- Investigation of ensemble simulation methodologies across systematic model families.
Main Results:
- Computational models, despite successes, contain irreducible imprecision due to inherent structural instabilities.
- Careful calibration to empirical data does not eliminate this fundamental uncertainty.
- Ensemble modeling provides a framework for estimating the level of irreducible imprecision in forecasts.
Conclusions:
- Expect inherent imprecision in quantitative climate forecasts from simulation models.
- Ensemble simulations are essential for robustly estimating forecast uncertainty.
- Understanding and quantifying irreducible imprecision is key for reliable climate projections.
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