FAQs

In progress

1. What measures are in place to validate and ensure the accuracy and reliability of the Climate Risk Index?

   1. Slide on data selection criteria to ensure data quality and reliability

   2. Validation of data with users. Especially for the near term risks.

   3. Function for users to report questions on accuracy and helpfulness of our data.

2. How exactly do you normalize event intensities of different perils? What are the underlying assumptions when combining normalized values from different perils?

   1. Damage functions mapping intensity to 0-100.

   2. Assume damage functions pegging to 10th and 90th percentile of intensity.

3. According to the Whitepaper, AlphaGeo has a resolution of 300 meter for Flood and 25 km for storm – why do you think this is adequate enough?

   1. Source data can be higher res. For example, flood can go up to 30-100 meters.

   2. But as our insight goes, 300 meters is sufficiently good to capture the general risk trend in a location.

   3. Higher res data is helpful if blended with other property info, which we don’t have globally.

   4. Resolution is enhanced using resilience (adaptive capacity data).

   5. The concept of scale here matters.

4. How is the tropical cyclone risk considered in areas where no storms made landfall in the historic reference period? Would additional tracks in IBTrACS change the final risk maps?

   1. If both IBTrACS and future simulations did not touch, then no risk.

5. How is the change of annual expected losses for future scenarios calibrated? What is the baseline?

   1. Baseline is current period of 2015-2025

6. Explain the downscaling process AlphaGeo is applying in more details

   1. Slide. DeepSD, + GAN based models

   2. How does the methodology used in the AlphaGeo Climate Risk Index ensure accurate and comprehensive risk assessments?

7. What are the biases and limitations in the methodology?

8. How do the fire-related sub-indexes correlate with observed fire occurrence? Why not using fire-related indices such as the FWI instead?

   1. Limited by data availability. FWI is a daily index which requires PR, RH, etc.

   2. How are the sub-indexes (e.g., Heat Stress, Drought, Inland Flooding) calculated?

   3. In the paper. Intensity + Frequency

9. What GCM variables are used for assessing the expected change for the different perils?

   1. TAS, TASMAX, TASMIN, PR

10. What GCMs are used for the future scenarios? How are they downscaled to 25km resolution?

    1. DeepSD. Ensemble of couple of GCMs such as CanESM5, MRI-ESM1

11. How does the approach for estimating the adaptive capacity perform in data-sparse (typically non-resilient) regions?

    1. Not yet. But we have plans to estimate the data using our generative model.

12. What are the most relevant data sources for adaptation measures besides OSM?

    1. Global Reservoir, EarthEnv Land Cover, WUDAPT Local Climate Zone

13. Could you be more specific on the “comprehensive spatial analysis” of the adaptation measures?

14. What’s the update cycle?

• Incorporate GAM Feedback to data

• 1. Add STORM dataset to hurricane map

• 2. Add 30m flood data to the flood

• 3. Insurance calculations ( risk premium - annual expected damage 50%) (overheads = 50%)

• • Loss ration, expense ratio

  • Impact * loss ratio

  • Check out some of the annual report from insurance companies on their loss ratio vs expense ratio

• Uncertainty modeling for adaptation curves.

• Collab with GAM on sending