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Weather & Climate FAWP Detection

Detect the Information-Control Exclusion Principle in atmospheric forecast systems.

The core question

"Is there a regime where the atmosphere remains forecastable, but weather-modifying interventions have already lost their effect?"

That is FAWP in the weather domain: prediction persists, control has collapsed.

Install

pip install "fawp-index[weather]"

Three entry points

1. From ERA5 reanalysis data (no API key)

from fawp_index.weather import fawp_from_open_meteo

result = fawp_from_open_meteo(
    latitude    = 51.5,    # London
    longitude   = -0.1,
    variable    = "temperature_2m",
    start_date  = "2015-01-01",
    end_date    = "2024-12-31",
    horizon_days = 7,      # 7-day forecast horizon
)
print(result.summary())

2. Multi-location grid scan

from fawp_index.weather import scan_weather_grid

cities = [
    {"lat": 51.5,  "lon": -0.1,  "name": "London"},
    {"lat": 48.9,  "lon":  2.4,  "name": "Paris"},
    {"lat": 40.7,  "lon": -74.0, "name": "New York"},
]
results = scan_weather_grid(cities, variable="temperature_2m",
                            start_date="2015-01-01", end_date="2024-12-31")
for r in results:
    flag = "🔴 FAWP" if r.fawp_found else "—"
    print(f"{r.location:<20} {flag}  gap={r.peak_gap_bits:.4f}b")

3. From your own NWP forecast arrays

from fawp_index.weather import fawp_from_forecast

result = fawp_from_forecast(
    forecast     = nwp_output,       # model forecast values
    observed     = verification,     # actual measurements
    intervention = model_nudge,      # forecast adjustment / ensemble spread
    horizon_days = 5,
    variable     = "temperature_2m",
    location     = "50.0N 0.0E",
)
print(result.summary())

Supported variables (ERA5 via Open-Meteo)

Variable Description
temperature_2m 2m air temperature (°C)
precipitation_sum Daily precipitation (mm)
wind_speed_10m 10m wind speed (m/s)
surface_pressure Surface pressure (hPa)
cloud_cover Cloud cover fraction (%)
et0_fao_evapotranspiration Reference ET (mm)
shortwave_radiation Solar radiation (W/m²)

Interpreting results

Field Meaning
fawp_found FAWP regime detected — prediction persists but control collapsed
peak_gap_bits Maximum leverage gap (bits) — larger = stronger FAWP
odw_start/end Operational Detection Window (Ï„ range)
tau_h_plus Post-zero agency horizon — where control first vanishes
tau_f Failure cliff — where the system becomes fully uncontrollable

Physical interpretations

  • High peak_gap_bits: The forecast model retains skill at lags where interventions (nudges, corrections, warnings) have already lost effect.
  • Narrow ODW: FAWP window is short — small lead time available before cliff.
  • FAWP in precipitation: Predictability persists into a regime where cloud-seeding or model re-initialization no longer changes outcomes.
  • FAWP in wind energy: Grid operator can forecast output but can no longer route or curtail fast enough to affect the outcome.

Papers

  • E1–E7: doi:10.5281/zenodo.18663547
  • E8: doi:10.5281/zenodo.18673949
  • E9 (SPHERE_15): Experiment 9 confirmation suite