Climate model large ensembles as test beds for applied compound event research.

Area of Science:

• Climate Science
• Environmental Science
• Meteorology

Background:

• Impactful climate and weather events often arise from compounding drivers.
• Assessing current and future risks from compound events requires understanding sources of uncertainty.
• Internal climate variability and response uncertainty complicate climate change attribution and projections.

Purpose of the Study:

• To discuss the opportunities and challenges in assessing uncertainty for compound climate events.
• To highlight the role of climate model large ensembles in understanding uncertainty.
• To provide an outlook on application-oriented compound event research with large ensembles, focusing on water resources.

Main Methods:

• Review of existing research on climate model large ensembles and uncertainty quantification.
• Discussion of the necessity for rigorous model validation and observational constraints.
• Case study perspective focusing on water resources.

Main Results:

• Climate model large ensembles are valuable tools for assessing uncertainty in compound event research.
• Rigorous model validation and observational constraints are essential for the practical utility of large ensembles.
• Uncertainty in climate projections, combined with unknown emissions, creates a wide range of future scenarios.

Conclusions:

• Large ensembles offer unique capabilities for understanding climate uncertainties related to compound events.
• Integrating large ensembles with validation and observational data is critical for reliable risk assessment.
• Future research should focus on application-oriented studies using large ensembles for practical insights, particularly in water resource management.