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Quantifying Uncertainty Due to Stochastic Weather Generators in Climate Change Impact Studies
Fosco M Vesely1, Livia Paleari2, Ermes Movedi2
1University of Milan, ESP, Cassandra Lab, via Celoria 2, 20133, Milan, Italy. fosco.vesely@unimi.it.
Scientific Reports
|June 27, 2019
Summary
The choice of weather generators significantly impacts local climate change assessments. This uncertainty can affect crop yield predictions more than the climate scenario itself.
Area of Science:
- Climate Science
- Agricultural Meteorology
- Environmental Modeling
Background:
- Climate change studies require downscaling coarse projections to local scales.
- Weather generators are commonly used for this downscaling process, introducing uncertainty.
- The impact of this uncertainty on climate-sensitive assessments, like crop yield, is not fully understood.
Purpose of the Study:
- To analyze the behavior of different weather generators (CLIMAK, LARS-WG, WeaGETS) in downscaling climate data.
- To quantify the uncertainty introduced by weather generators in site-specific climate change assessments.
- To evaluate the influence of this uncertainty on crop yield impact assessments.
Main Methods:
- Designed downscaling experiments using three distinct weather generators.
- Assessed impacts on precipitation and air temperature for 15 global sites.
- Utilized a rice yield model and a comprehensive set of climate metrics to evaluate changes.
Main Results:
- The selection of a weather generator demonstrated a substantial influence on downscaled climate variability.
- Weather generator choice had a greater impact on crop yield estimates than the chosen climate scenario.
- Significant uncertainty was quantified in local-scale climate impact assessments due to generator selection.
Conclusions:
- The choice of weather generator is a critical factor in climate change impact studies.
- Existing climate change impact assessments using weather generators may require re-evaluation.
- Highlighting the need for careful consideration and reporting of weather generator uncertainty in climate research.
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