Weather Decisions & Methodology
How PlaneWX selects, filters, and uses weather data to build your briefing.
Proxy TAF Selection
When your departure or arrival airport doesn't have a Terminal Aerodrome Forecast (TAF), PlaneWX uses a terrain-aware proxy TAF from the nearest airport that does have one.
Terrain-Aware Distance Limits
The maximum distance for a proxy TAF depends on terrain complexity:
- 35 SMFlat terrain (Kansas, Nebraska, Florida) — weather patterns are similar over larger distances
- 25 SMRolling terrain (Arkansas, Missouri, Texas) — moderate terrain effects
- 20 SMComplex terrain (California, Oregon, Washington, North Carolina) — terrain significantly affects weather
- 12 SMMountain terrain (Colorado, Wyoming, Montana) — weather can vary dramatically over short distances
How it works: PlaneWX maintains a database of proxy TAF mappings for all airports. When generating a briefing, if your airport doesn't have a direct TAF, the system automatically uses the mapped proxy airport's TAF. The briefing clearly indicates when a proxy TAF is being used, showing both the proxy airport code and distance.
Route Corridor Filtering
PlaneWX filters weather products to only include data relevant to your flight path. Corridor widths are dynamic — they automatically adjust based on your route distance and aircraft speed to ensure the right level of weather awareness for every flight.
Why dynamic corridors? Since PlaneWX doesn't have your exact GPS route, IFR flights may follow airways that deviate from a straight line. Longer routes have more potential deviation. Slower aircraft also give weather systems more time to drift into the flight path. The corridor system accounts for both factors automatically.
METARs (Current Conditions)
- Corridor:40–60 NM (scales with route distance and aircraft speed)
- Sampling:Every 50–75 NM along route (denser for imminent flights)
Always includes departure and arrival airports, plus airports near sample points along the route.
TAFs (Terminal Forecasts)
- Corridor:40–60 NM (scales with route distance and aircraft speed)
- En-route TAFs:Up to 8 en-route TAFs, evenly spaced along route
- 12+ hours out:Departure and arrival TAFs only
Always includes departure and arrival airports (or their proxy TAFs). En-route TAFs are selected to provide even coverage along the flight path.
SIGMETs & AIRMETs (Hazard Advisories)
- Route proximity:65–100 NM corridor (scales with route distance and aircraft speed)
- Time window:2 hours before departure through arrival time
- Altitude filtering:Only includes products affecting your cruise altitude
Altitude Categories: Flights below 18,000 ft (LOW) only see products with base altitude < 18,000 ft. Flights at or above 18,000 ft (HIGH) only see products with top altitude ≥ 18,000 ft. G-AIRMETs with polygon data use precise route-polygon intersection testing for accuracy.
PIREPs (Pilot Reports)
- Route proximity:50–75 NM corridor (scales with route distance and aircraft speed)
- Altitude range:±4,000 ft from your cruise altitude
- Recency:Only includes PIREPs from the last 2 hours
Winds Aloft Forecasts
PlaneWX uses a multi-model consensus approach to wind data, drawing from the same numerical weather prediction models used by professional forecasters — for every flight, regardless of how far out you're planning.
Primary: Multi-Model Consensus Winds
PlaneWX uses a consensus of HRRR, GFS, NAM, and ECMWF upper-air model dataaccessed via the Open-Meteo API. This provides accurate, day-specific wind forecasts from the current hour out to 16 days.
- • Models: HRRR, GFS, NAM, and ECMWF — blended for best accuracy
- • Multi-point sampling: 3-7 points along your route (more for longer routes)
- • Altitude interpolation: Proper interpolation between pressure levels for your exact cruise altitude
- • Coverage: Current hour through 16 days out
Why model consensus? Blending multiple models reduces the impact of any single model's errors and produces more reliable headwind/tailwind estimates than any single source alone.
Fallback: Historical Climatology
If model data is unavailable, PlaneWX falls back to NCEP/NCAR 30-year climatological averages. This provides a baseline expectation based on historical patterns for that month and location.
- • Based on 30-year monthly means (1981-2010 baseline)
- • Shows typical wind patterns for that time of year
- • Useful for long-range planning but not specific day forecasts
- • Clearly labeled as "Historical Winds Aloft" in briefings
Route-Averaged Winds
Regardless of the data source, PlaneWX samples winds at multiple points along your flight path and averages them. This gives you a more accurate picture of headwind/tailwind than a single-point measurement, especially for longer routes where winds may vary significantly.
Ground speed is calculated using the proper wind triangle formula, which accounts for the crab angle required in crosswind conditions — giving you more accurate flight time estimates than a simple headwind subtraction.
Timeframe-Based Product Selection
PlaneWX automatically selects which weather products to include based on how far in advance you're planning. This ensures you get relevant, accurate data without information overload.
Imminent (0-2 hours)
Current conditions and very short-term forecasts
Near-Term (2-6 hours)
Short-term forecasts and current trends
METARs/PIREPs excluded (too current for this timeframe)
Medium-Term (6-12 hours)
Forecast products and area discussions
Extended (12-24 hours)
Area forecasts and model guidance
WPC/GFS included if >18 hours out
Long-Range (24-72 hours)
Pattern-based forecasts and outlooks
Very Long-Range (72+ hours)
Climatology and extended outlooks
GFS model winds used for accurate extended-range flight planning (up to 16 days)
Key Principles
1. Relevance Over Volume
We filter aggressively to show only weather that affects your specific route, altitude, and timeframe. This prevents information overload and helps you focus on what matters.
2. Timeframe-Appropriate Data
We don't show current METARs for flights 3 days out—they're irrelevant. We don't show 7-day GFS model runs for flights tomorrow—they're too uncertain. Each timeframe gets the most appropriate data.
3. Terrain Awareness
Our proxy TAF system recognizes that weather patterns in mountain regions are more localized than in flat terrain. Distance limits adjust accordingly.
4. Altitude-Specific Filtering
SIGMETs, AIRMETs, and PIREPs are filtered by your cruise altitude. You won't see high-altitude turbulence reports for a low-altitude flight, or vice versa.
5. Transparency
When we use a proxy TAF, extend a forecast beyond its normal validity, or use historical data, we clearly label it in your briefing so you understand the data source and its limitations.
Weather Sources & Data Confidence
Every briefing shows which weather products were used and a Data Confidence score. Understanding these helps you interpret how reliable your briefing is.
Weather Sources
The "Weather Sources" section shows all weather products that were retrieved and used to generate your briefing. Each product contributes points to the Data Confidence score:
- +20 ptsTAFs — Terminal Aerodrome Forecasts (most reliable for airports)
- +15 ptsMETARs — Current surface observations
- +15 ptsNBM — Hourly probabilistic forecasts
- +10 ptsRegional Watch — AI-synthesized regional weather
- +8 ptsWPC Discussions — Weather Prediction Center guidance
- +8 ptsGFS MAV — Model output statistics
- +5 ptsNational Synopsis, AFDs, Winds Aloft, PIREPs, CPC Outlook
- +3 ptsAIRMETs, SIGMETs, CWAs
Products may be marked as "unavailable" if they're not applicable for your timeframe (e.g., METARs for flights 3 days out) or if the data source is temporarily unavailable.
Data Confidence Score
The Data Confidence score (0-100%) measures how reliable your briefing is based on:
- • Product Availability (~60 points) — Which weather products were successfully retrieved
- • Data Freshness (~15 points) — How recent the observations/forecasts are
- • Timeframe (~15 points) — How far in advance you're planning (closer = higher confidence)
- • Source Agreement (~10 points) — Whether multiple sources show similar conditions
Excellent
All key products available, fresh data, sources agree
Good
Most products available, reliable forecast
Moderate
Some products missing or data aging
Limited
Key products missing or long-range forecast
Low
Very limited data or very long-range planning
Data Confidence vs. GO Score
These are two different things:
Data Confidence (0-100%)
Measures how reliable the forecast is based on what data is available. A high confidence score means you have good data to work with. A low score means the forecast is based on limited or aging data.
Example: 51% confidence for a 3-day-out flight is normal—you're using pattern-based forecasts, not specific TAFs.
GO Score (0-100%)
Measures how well conditions match your personal minimums. A high GO score means conditions are favorable. A low GO score means conditions don't meet your minimums.
Example: You can have 80% GO score with 40% data confidence (good conditions but limited forecast data), or 30% GO score with 90% data confidence (poor conditions but very reliable forecast).
Key Point: Data Confidence tells you how much to trust the forecast. GO Score tells you whether conditions are good enough to fly. A low Data Confidence score means you should check back closer to departure when better data is available. A low GO Score means conditions don't meet your minimums regardless of how confident the forecast is.
Expected Confidence by Timeframe
Data Confidence naturally varies based on how far in advance you're planning:
- 0-6 hours:Expect 70%+ confidence (METARs, TAFs, real-time data all available)
- 6-24 hours:Expect 55%+ confidence (TAFs and model data provide good guidance)
- 24-72 hours:Expect 40%+ confidence (NBM hourly forecasts available, but TAFs may not cover departure)
- 72+ hours:Expect 30-50% confidence (pattern-based forecasts, trend guidance, historical climatology)
Lower confidence scores for long-range flights are normal and expected. The system is designed to provide the best available guidance for your timeframe, even if that means using less precise data sources.
About This Documentation
These methodologies are continuously refined based on pilot feedback and weather data accuracy analysis. The system automatically adapts filtering parameters based on your flight's timeframe, route, and altitude to provide the most relevant briefing possible.