Flybot is an AI Paragliding Forecast for the UK. It helps paraglider pilots spend more time flying and less time pondering weather forecasts. While checking a detailed forecast is essential before flying, Flybot quickly identifies which sites and dates/times are likely to work.
⚠️ Important Safety Notice
Always make your own decision before taking off. Local conditions may not be representative of current forecasts, and weather forecasts are often wrong! This is a forecast aid, not a definitive "go/no-go" decision tool. You are responsible for your own safety.
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Recommended workflow:
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Join Flybot TelegramThe forecast is displayed as a 6-track timeline showing hourly daytime conditions. Nighttime hours are automatically filtered out.
What it shows: A blue line representing the probability (0 to 100) that conditions are flyable.
The higher the score, the better! Low values indicate a lower probability of being flyable. When the score is high and XC Potential >50, the background turns purple indicating XC conditions.
What it shows: An orange line showing suitability for mini wing paragliders (0-100%). Mini wings are small, high-performance paragliders designed for strong-wind ridge soaring in smooth, laminar conditions.
What conditions create mini wing suitability? The model identifies very specific conditions where mini wings excel:
Core Requirements (Coastal and Inland sites):
Additional Requirements for Inland Sites:
Safety Overrides (All Sites):
Why the distinction between coastal and inland? Coastal sites benefit from marine boundary layer flow which tends to be smoother and more laminar, allowing slightly higher gust tolerances. Inland sites are more prone to mechanical turbulence and thermal activity, requiring stricter criteria and explicit checks for stable, non-thermal conditions.
Mini Wing Quality Score (0-1.0): The model also provides a confidence score combining:
Practical interpretation: Mini wing conditions are rare and specialized. When the orange line shows high values (70-100%), experienced mini wing pilots will find ideal conditions: strong, smooth, laminar ridge lift without thermals or turbulence. These are typically stable high-pressure days with brisk winds and no convection.
Wind Speed (km/h): Large numbers show wind speed at site elevation, color-coded by safety:
Gust Difference (+X km/h): Shown in orange below the wind speed. Be cautious when gust differences exceed 10-15 km/h, as this indicates turbulent conditions. Higher gust differences suggest unstable air and increased turbulence risk.
Wind Direction Arrow: Small arrow at top shows wind direction:
Flyable Wind Sectors (Blue Arcs) in the windrose: The wind compass shows blue arcs representing ±30 degrees off the main fall line for the hill. Outside of these zones, the vertical component of rising air will be reduced and there is greater chance of rotor spilling across the site.
What does grey wind speed mean? When wind speed is displayed in grey, it indicates that even though the wind direction may be within the flyable range, the vertical wind component is insufficient for ridge soaring.
How is this calculated? The model decomposes the wind vector into components relative to the site's takeoff aspect and slope:
Wind Speed × sin(slope angle) × alignment factorWhy does this matter? This commonly occurs when:
Practical interpretation: Grey wind speed means "the wind direction might technically be OK, but you won't get enough lift to stay up." This is different from a grey arrow (wind outside flyable range) or light green wind (light but adequate vertical component).
Understanding Wind at 500m AGL vs Ground Level:
Wind Speed Delta: Shows the difference between the wind speed at 500m above takeoff vs takeoff (in km/h):
Wind Direction at 500m: The direction arrow shows wind at 500m AGL, colored based on both directional consistency and speed difference with ground wind:
Thermal Quality Stars (0-3): This is a synthesized rating of pure thermal potential, derived from multiple meteorological components. It is differnt to RASP starts and is unique to Flybot. It is also independent of wind, turbulence, or convective hazards.
Time to Release: This parameter is a physically-derived estimate of the thermal duty cycle, representing the time required for the ground to heat a surface-layer air parcel to the point of buoyant release. It's a more sophisticated metric for thermal strength than sensible heat flux alone.
How It's Calculated: The model computes this value by solving a simplified energy balance equation:
Time = Energy Required / Rate of Energy Input
Interpretation: A short release time (<15 min) indicates a rapid thermal cycle with strong and frequent lift. A long release time (>30 min) suggests infrequent, weaker thermals that require more patience to find and utilize. It effectively describes the rhythm of the day.
Colour coded with red: <10 mins (very fast release), orange: 10-20 mins (fast release), green: 20-30 mins (moderate release), blue: 30-60 mins (slow release).
Temperature at 1000m AGL (top row): Shows how cold it will be at altitude, helping you dress accordingly. Color-coded from icy blue (cold) through green (mild).
Temperature at Site Elevation (bottom row): Ground-level temperature at the site:
The temperature spread between ground and altitude is primarily for comfort and clothing planning.
Rainfall (top): Blue raindrop symbols show rainfall intensity:
Total Cloud Fraction (middle): Shows the % of sky covered by cloud (0 = clear skies, 100 = completely overcast). Higher values indicate more cloud cover, which may affect thermal development, visibility, and the ability to find thermals marked by cumulus clouds.
Cloud Base Category (bottom): Text shows cloud base height category:
Cloud base category is calculated from cloud_base_height_2p5_oktas (cloud base at 2.5 oktas coverage).
When XC Potential >0.5 and Flyability >0.5, the flyability track background turns purple. This indicates good cross-country flying conditions.
Note: XC Potential is still a work in progress. It uses a different model trained on conditions where pilots have exceeded 10km flights.
When viewing "Today" forecast, a red dotted vertical line shows the current time, helping you see what conditions are happening right now.
Forecast Model: Met Office UK2km forecast (4-hour delay)
Update Frequency: Hourly
Machine Learning: Our models are trained on historical flight records and site-specific characteristics to predict flyability and XC potential.
We start by assembling two streams of data: high-resolution Met Office UKV (2-km) forecast fields and observed paragliding activity from OGN/PureTrack. The weather stream is collated across many daily CSVs, lightly cleaned (rows with extensive gaps dropped; remaining NaNs imputed), and then enriched with per-site metadata (take-off aspect and elevation) from our Flybot annotations table. Each weather record is joined to the nearest site and hour, and then aligned to flight logs aggregated by site and hour—so for every "site × hour" we know the forecast conditions and whether pilots actually flew (and whether anyone went XC).
On top of the raw meteorology we build a stack of pilot-centric features. These include wind–topography interactions (headwind and crosswind components relative to each site’s take-off aspect), vertical wind shear metrics between standard heights (10–100–250–500–1000 m AGL), gust diagnostics (gust ratio/excess), cloud and visibility categories, precipitation flags, thermal proxies (dew-point spreads, near-surface lapse rates, CAPE variants), and simple stability/turbulence indicators (e.g., Richardson bulk number). The result is a wide, engineered dataset where each row is a forecast snapshot of “how flyable this site-hour looked” in the dimensions pilots actually care about.
Labelling is necessarily noisy in a sport constrained by people’s availability and risk appetite, so we use a positive–unlabelled (PU) learning setup. “Positive” means we observed pilots on site that hour; anything else starts unlabelled. We then mark a subset of obvious “no-go” hours as reliable negatives using conservative heuristics (e.g., very strong wind or gusts, any precipitation, or very poor visibility). We also reduce confounding by matching negatives to positives with similar wind direction at the same site, and we split train/validation by site groups to test on genuinely unseen sites. Features are standardised column-wise. A compact neural network is trained with a PU/PNU-style loss so it learns the boundary between “conditions with observed flying” and everything else without pretending all missing activity is a true negative. In parallel, we train a separate Random Forest classifier for cross-country propensity using flights > 10 km as positives, giving a probability that conditions are supportive of XC.
End-to-end, the pipeline (current code version v_19) ingests forecasts, enriches them with terrain/site context, aligns them to observed behaviour, engineers domain features, constructs PU-appropriate training sets with group-aware splits, scales inputs, and trains the models (flyability and XC) ready for scoring future forecasts. The output is a site- and hour-specific probability that conditions will be flyable, plus a complementary XC-likelihood signal to help pilots plan their day.
Missing your favourite site? We'd love to add it to our forecast coverage! Submit the site details and we'll include it in our list of forecasted locations.
What we need:
Please provide as much detail as possible to help other pilots. The more information you share, the more useful the forecast and site information will be for the community.
Flybot is a passion project built for the UK paragliding community. If you find it useful and want to support continued development, hosting costs, and new features, consider buying me a coffee!
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