Experimental weather intelligence platform — not for life safety decisions. Always follow NWS official guidance.
Dakota Storm Watch
 Dashboard

Forecast Engine Changelog

Every major change to DSW's prediction system, documented for transparency. Our post-mortem grades are tied to the engine version that made the forecast.

Current: v4 — Multi-model expansion, deployed June 10, 2026
v4 June 10, 2026 CURRENT

Multi-Model Expansion

Massively expanded the data foundation from 4 global models to 7+ models including US high-resolution CAMs, and from 82 ensemble members to 173 across 4 systems. Added 10 pressure levels for better hodograph calculations.

7+ forecast models — Added HRRR (3km), NAM (12km), NBM (National Blend), best_match, and GFS-GraphCast (AI) via Open-Meteo API alongside existing GFS/ECMWF/GEM/ICON.
173 ensemble members — GEFS (31) + ECMWF ENS (51) + ICON EPS (40) + ECMWF AIFS (51). Probabilities now derived from 4 independent ensemble systems instead of just GEFS alone.
10 pressure levels — Expanded from 4 (850/700/500/300) to 10 (1000/975/950/925/900/850/700/500/300/250 hPa) for better hodograph resolution and SRH calculation.
Automated post-mortems — Every L2+ forecast gets an AI-written after-action report with honest grading. Published on the Post-Mortems page.
Changelog & versioning — All forecasts tagged with engine version. Full public changelog for transparency.
v3 June 10, 2026 SAME DAY

Post-Bust Calibration

After the June 9 bust where DSW (and NWS) over-forecast a severe event that never materialized in the RRV, we applied four major corrections based on verification data.

CIN/cap penalty doubled — Moderate CIN now reduces scores by 50% (was 15%). The STP formula's CIN term was also fixed (was mathematically inverted).
Ensemble reality check — When 0% of GEFS ensemble members produce severe gusts, the threat score is now penalized. Previously this signal was noted but not acted on.
Distance-filtered severe warnings — Tornado warnings 200+ miles away no longer inflate the local threat score. Local (<75mi) = full weight, nearby = half, distant = minimal.
Conditional CI risk reduced — When HRRR doesn't fire storms, we no longer override it with surface boundary detection. The model was right; the cap held.
AI calibration warning — AI now receives DSW's over-forecast bias history and weighs initiation probability as heavily as environment quality.
Automated post-mortems — Every L2+ forecast now gets an after-action review with AI-written analysis.
Public/deep analysis toggle — Plain-language summary by default, technical deep analysis expandable.
Trigger: June 9, 2026 bust — MODERATE forecast, MARGINAL actual. Cap held, zero severe in RRV.
v2 June 9, 2026 1 DAY

Major Rebuild — Original Analysis Platform

Complete overhaul from a data aggregator to an original analysis platform. 13 bugs fixed, 15 new analysis engines built. This version was deployed mid-event on June 9.

HRRR expanded to 26+ parameters — Updraft helicity, model-computed shear/SRH/storm motion, VIL, reflectivity, LCL/LFC, 0-3km CAPE.
15 analysis engines — HRRR storm simulation, run-to-run trending, multi-model CI timing, hodograph SRH, storm mode predictor, ensemble severe probabilities, surface mesoanalysis, NAM Nest comparison, nowcast bridge, verification bias correction, and more.
Fixed silent AI failure — AI enhancement had been broken for all outlooks due to f-string escaping bug. Every outlook was running "algorithmic" only.
Fixed SRH underestimation — Was using crude "shear x 4" approximation giving 92 m/s when real value was 300+. Now uses multi-hour HRRR peak values.
Data-driven storm motion — Replaced hardcoded SW-to-NE assumption with 500hPa steering flow.
Auto AI model selection — Sonnet for high-threat days, Haiku for quiet days.
Known issue: CIN weighting too lenient, ensemble probs not yet moderating scores. Fixed in v3.
v1-alpha January — June 8, 2026 RETIRED

Alpha Prediction Engine

Initial system focused on data aggregation with basic threshold scoring. Limited original analysis.

Basic HRRR integration (10 parameters, analysis time only)
Rule-based probabilities (hardcoded lookup tables)
No AI enhancement (broken since deployment)
Crude SRH estimation (shear x 4 approximation)
Hardcoded SW-to-NE storm motion assumption
No distance filtering on warnings
No surface mesoanalysis or multi-CAM comparison
Verification record: 1/14 correct (7% accuracy). High false alarm rate driven by over-sensitive thresholds and broken AI.

Our Approach

DSW is an experimental platform that aims to produce genuinely original severe weather analysis for the Red River Valley — not just repackage NWS data. We use HRRR 3km storm simulations, multi-model comparison, surface boundary detection, and ensemble probabilities to generate predictions you can't get from weather.gov.

We publish our mistakes as prominently as our hits. Every significant forecast gets an automated post-mortem with an honest grade. When we bust, we document why and build the fix into the next version. That's how the system improves.