Overestimated Impact in CLIMADA Despite Calibrated Exposure and Flattened Impact Functions (SIDR Case Study) #1102
Description
Summary
I am modeling the 2007 SIDR cyclone using CLIMADA's TC module, LitPop exposure via API, and district-level damage data from Bangladesh. I've scaled exposure values to match actual damage totals and manually flattened impact functions to reflect realistic vulnerability tiers.
Despite this, modeled impact is still 3,000–15,000% higher than actual damage across all districts.
What I have Done
- Used IBTrACS track for SIDR
- Fetched LitPop exposure via CLIMADA API
- Spatially joined exposure to 5 affected districts
- Scaled exposure totals to match actual damage
- Assigned district-wise impact functions:
- Satkhira: steep (now flattened to MDD 0.7–0.85)
- Barisal/Khulna: moderate (MDD 0.5–0.7)
- Patuakhali/Barguna: gentle (MDD 0.35–0.6)
- Ran impact calculation and compared modeled vs actual damage
Results
| District | Actual Damage (USD) | Modeled Impact (USD) | Error (%) |
|---|---|---|---|
| Satkhira | 90M | 13.85B | +15,296% |
| Khulna | 110M | 14.25B | +12,859% |
| Barisal | 100M | 8.28B | +8,182% |
| Patuakhali | 130M | 8.04B | +6,087% |
| Barguna | 150M | 4.69B | +3,032% |
Screenshot attached..
Question
Is this a known issue with TC modeling in CLIMADA? Are there recommended practices for further calibrating impact or validating hazard intensity?
Would appreciate any insights or suggestions. Happy to share code snippets or rerun diagnostics if needed.
Thanks!