Proposal: build ensembles to produce a burn-probability map, not just "run N simulations". Wind forecasts are uncertain, and users (civil protection, insurers, land managers) need probabilities, not a single perimeter. Already listed in tools/TODO.md:10.
It also allows calibration. propagationSpeedAdjustmentFactor=0.6 and windReductionFactor=0.4 (tests/runff/params.ff) are tuned for Corsica. An ensemble lets us fit them against observed fires (tools/TODO.md:17).
This makes throughput more important than per-run speed, so threads matter more than MPI.
Prerequisites: #159 (leak per domain), #165 (log volume), #160 (exit(0) kills the run).
First step, no C++ changes: a Python driver that samples wind and the two factors, runs N simulations through pyforefire, and adds up the arrival-time rasters into one probability grid.
Drafted with Claude Opus 5, reviewed by a maintainer.
Proposal: build ensembles to produce a burn-probability map, not just "run N simulations". Wind forecasts are uncertain, and users (civil protection, insurers, land managers) need probabilities, not a single perimeter. Already listed in
tools/TODO.md:10.It also allows calibration.
propagationSpeedAdjustmentFactor=0.6andwindReductionFactor=0.4(tests/runff/params.ff) are tuned for Corsica. An ensemble lets us fit them against observed fires (tools/TODO.md:17).This makes throughput more important than per-run speed, so threads matter more than MPI.
Prerequisites: #159 (leak per domain), #165 (log volume), #160 (
exit(0)kills the run).First step, no C++ changes: a Python driver that samples wind and the two factors, runs N simulations through
pyforefire, and adds up the arrival-time rasters into one probability grid.Drafted with Claude Opus 5, reviewed by a maintainer.