In climate-related scenario analysis, one assesses the risk of various climate-related hazards under different global warming scenarios, ranging from 1.5°C to 6°C above pre-industrial levels. Here's a breakdown of its components: - **Risks**: Indicate the types of climate hazards being considered, such as hurricanes, tornadoes, tsunamis, floods, droughts, extreme heat, and winter weather. - **Scenarios**: represent the temperature increases associated with global warming, specifically the rise above pre-industrial average temperatures. - **Frequency**: The numbers (like 1/50, 1/100, 1/250) denote the frequency of the events. For example, "1/50" could mean that the event is expected to happen once every 50 years. - **Metrics**: types of measurements or outcomes to be filled in for each scenario, including: - **% increase of AAL (Average Annual Loss)**: This would be the percentage increase in the expected yearly financial loss due to each hazard under the given warming scenario. - **Probable Maximum Loss (Gross & Net PML)**: This could refer to the estimated maximum loss for a given event, both before (gross) and after (net) considerations like insurance and mitigation efforts. This type of analysis is critical for understanding how climate change can affect the frequency and severity of hazardous events and for planning appropriate risk management and adaptation strategies. It's an important tool for policymakers, urban planners, insurance companies, and other stakeholders involved in climate risk management. A table with this analysis would have to be constructed for each distinct geographic area in the client's portfolio of insured products - they require geographical disaggregation. [[Climate Modelling MoC]]