Historical weather data for climate risk assessment.

Area of Science:

• Climate Science
• Environmental Risk Assessment
• Data Science

Background:

• Weather and climate hazards cause significant economic losses and societal impacts.
• Current climate risk assessment relies heavily on recent data, potentially overlooking valuable historical information.
• Future climate change necessitates robust methods for quantifying climate-related risks.

Purpose of the Study:

• To provide an overview of climate risk assessment methodologies.
• To explore the properties and applications of historical instrumental and documentary weather data.
• To demonstrate how historical environmental data can enhance current climate risk assessment.

Main Methods:

• Review of climate risk assessment methodologies.
• Analysis of historical instrumental and documentary environmental data.
• Application of numerical techniques including dynamical downscaling and analog methods.
• Case studies illustrating the integration of diverse data sources and methods.

Main Results:

• Historical environmental data can be used to develop and validate numerical model chains.
• Past data provides extensive statistical samples for hazard estimation and risk modeling.
• Historical events serve as crucial references for understanding potential 'worst-case' scenarios.

Conclusions:

• Integrating diverse historical data sources (reanalyses, digitized records, documents) is essential for effective climate risk assessment.
• Combining various analytical methods (e.g., dynamical downscaling, analog methods) on a case-by-case basis optimizes risk quantification.
• Historical data plays a vital role in improving the accuracy and reliability of climate risk assessments for present and future challenges.