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Inflated Uncertainty in Multimodel-Based Regional Climate Projections.
Marianne Sloth Madsen1, Peter L Langen1, Fredrik Boberg1
1Danish Meteorological Institute Copenhagen Ø Denmark.
Geophysical Research Letters
|February 6, 2018
Summary
Analyzing climate models can overestimate future climate change. Presenting data by grid point leads to unrealistic projections, potentially overestimating climate impacts and risks globally and regionally.
Area of Science:
- Climate Science
- Earth System Science
- Environmental Modeling
Background:
- Multimodel ensembles are standard for estimating future regional climate change.
- Projections are often visualized using maps of multimodel means and grid-point scale uncertainties.
Purpose of the Study:
- To investigate potential overestimation in climate change projections due to common statistical methods.
- To identify physically implausible patterns arising from ensemble analysis.
Main Methods:
- Analysis of a set of Coupled Model Intercomparison Project Phase 5 (CMIP5) models.
- Examination of statistical presentation of multimodel ensemble results at the grid point scale.
Main Results:
- Presenting climate model statistics at the grid point scale leads to an overestimation of the projected range.
- This method generates physically implausible patterns of change on both global and regional scales.
- Similar inconsistencies are found in impact analyses using regional-scale multimodel data.
Conclusions:
- Standard methods for analyzing climate model ensembles can overestimate projected climate change ranges.
- This overestimation can lead to inaccurate impact assessments and an overstatement of climate risks.
- A more nuanced approach is needed to avoid exaggerating climate change impacts.
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