Category 01
Temperature accuracy
Track high and low error, but also watch the day-to-night swing. Asheville often punishes models that smooth out terrain-driven changes too much.
Dedicated Asheville verification board
Asheville Weather Model Leaderboard
One page for comparing BlendedModel, GFS, EURO, and NAM against Asheville, North Carolina weather outcomes.
The page is live now. Numeric ranks should turn on only after verified Asheville observations are connected, so the board stays honest instead of publishing made-up scores.
Current Asheville board
This board is ready for real scoring. Until observed Asheville scorecards are published, every numeric cell stays pending.
Waiting on live verification
The hard part is not the front end. The hard part is consistently scoring each model against observed Asheville highs, lows, precipitation, timing, and storm behavior. This page is prepared for that next step.
| Rank | Model | Overall | Temp | Precip | Timing | Storm Signal | Status |
|---|---|---|---|---|---|---|---|
| -- | BlendedModel Orbital Overview local system Dedicated in-house forecast model and presentation layer built around readable local guidance. | Pending | Pending | Pending | Pending | Pending | Ready for live verification |
| -- | GFS Global forecast comparison Deterministic comparison slot for broader-scale temperature, pattern, and precipitation guidance. | Pending | Pending | Pending | Pending | Pending | Comparison slot ready |
| -- | EURO European model comparison Board slot for Euro guidance across mountain temperature swings and precipitation placement. | Pending | Pending | Pending | Pending | Pending | Comparison slot ready |
| -- | NAM Regional model comparison Regional guidance slot focused on shorter-range Asheville timing and mountain storm evolution. | Pending | Pending | Pending | Pending | Pending | Comparison slot ready |
Score categories that fit Asheville
A mountain-market board should reward the forecast details that actually change how Asheville weather feels day to day.
Category 02
Precipitation outcome
Reward models that correctly capture whether Asheville stays mostly dry, sees scattered coverage, or shifts into a wetter mountain setup.
Category 03
Timing window
Storm arrival and departure timing matters more than a generic rain chance. The board should score usable timing, not just precipitation existence.
Category 04
Storm signal skill
Mountain convection can look very different from quiet rain days. This lets BlendedModel compete on readable storm context, not only raw numbers.
How the live board can work
The page foundation is straightforward. The next step is piping model runs and observed Asheville weather into a repeatable scoring routine.
Step 01
Freeze one comparable forecast window.
Use the same lead window for BlendedModel, GFS, EURO, and NAM so the board compares like against like.
Step 02
Score against observed Asheville conditions.
Use real highs, lows, precipitation, timing, and storm behavior as the source of truth.
Step 03
Publish rolling ranks.
Once the feed exists, this page can show daily, weekly, or monthly performance without redesigning the layout.
Why Asheville
A strong mountain-market benchmark.
Terrain, convective timing, and temperature swings make Asheville a useful place to test whether a forecast system is actually disciplined.