Weather Forecasts & Meteorological Models
An in-depth guide to numerical weather prediction, the differences between global and high-resolution models, the app's real-time Blended Forecast engine, and every atmospheric and wave parameter used in the Windguru+ app.
1 How Weather Forecasts Work
Modern weather forecasting is powered by Numerical Weather Prediction (NWP). Rather than relying on simple extrapolation or empirical rules of thumb, NWP models simulate the Earth's atmosphere using fundamental mathematical laws: fluid dynamics, thermodynamics, radiation, and moisture conservation (the Navier-Stokes equations and ideal gas laws).
Because the atmosphere is a continuous fluid, supercomputers divide the planet and atmosphere into a three-dimensional grid of cells:
- Horizontal Grid Spacing: Measured in kilometers (e.g., 1 km, 2.5 km, 9 km, 13 km). This defines the smallest geographic feature the model can resolve. A 13 km model sees coastal bays and valleys as a broad, smoothed slope, whereas a 1 km model captures localized cliffs, headlands, and thermal channels.
- Vertical Atmospheric Levels: The column of air from ground level to the stratosphere is sliced into tens or hundreds of pressure and altitude layers.
- Simulation Time Steps: The equations are integrated forward in discrete time intervals of seconds to minutes. At each step, wind velocity, temperature, atmospheric pressure, and moisture are computed before stepping forward to the next timestamp.
Forecast models do not run continuously in real time. They are initialized in periodic runs (cycles), typically starting at 00, 06, 12, and 18 UTC (or every 3 hours for rapid-refresh regional models). Before a run starts, meteorological agencies assimilate millions of real-world observations from satellites, weather radar, weather balloons (radiosondes), maritime buoys, commercial aircraft, and ground stations. Processing this data and running the supercomputer simulations takes several hours before the forecast data reaches the Windguru+ app.
Forecast Horizons & Chaos Theory (The "Butterfly Effect")
The atmosphere is a mathematically chaotic system. Minute errors or gaps in initial observations grow exponentially over time. This dictates what you can realistically expect across different forecast horizons:
High-resolution local models shine here. They accurately capture diurnal thermal effects (afternoon sea breezes, valley winds), localized thunderstorm squalls, and venturi acceleration in coastal straits.
Global models reliably forecast large-scale weather systems (depressions, anticyclones, broad frontal passages). However, the exact timing of a wind change or front arrival may shift by 4 to 12 hours.
Beyond 7 to 10 days, forecasts are indicative of general weather regimes (e.g. persistent high-pressure ridge vs. unsettled westerly flow). Expecting exact hourly wind speeds 12 days in advance is scientifically impossible due to atmospheric chaos.
2 Meteorological Forecast Models: Global vs. Regional
Windguru aggregates model output from leading national meteorological services worldwide, supplemented by custom high-resolution simulations run directly by Windguru. Models fall into two primary families:
Simulate the entire planet without artificial geographic boundaries. Essential for tracking intercontinental storms, jet streams, and 7–16 day outlooks. Because they must calculate the whole globe, their resolution is coarser and terrain is smoothed.
Focused on specific countries or coasts. Driven at their boundaries by global parent models, they capture intricate coastal topography, islands, thermal breezes, and localized convection. Their horizon is typically shorter (24h to 72h).
Faced with multiple conflicting forecasts, outdoor enthusiasts often find themselves second-guessing: should you rely on the fine coastal resolution of a local model or the macroscopic stability of a world-leading global model? And what happens when two models disagree entirely?
To help navigate these differences, Windguru+ introduces two complementary tools: the real-time Blended Forecast and the Multi-Model Consensus Indicator, presented in the following sections before diving into the catalog of individual models.
3 The Blended Forecast Engine
On the website, Windguru offers a server-side "Model Mix". The Windguru+ app does not use Model Mix. Instead, the app features its own modern, transparent, client-side Blended Forecast engine (ForecastBlend).
Rather than forcing you to guess which individual model is right today, the Blended Forecast averages every model fetched for your spot into a single consolidated, highly resilient forecast timeline.
No single model wins every day. A 1 km model captures local afternoon sea breeze accelerations, but a 9 km ECMWF IFS model often predicts the arrival time of a major cold front with higher skill. The Blended Forecast combines the local precision of fine-mesh models with the broader stability of global models.
How the Blended Forecast Calculates Values
Every forecast hour across all active models is grouped by its absolute UTC timestamp. For each timestamp, the blended value is computed via a mathematical weighted average:
-
Resolution Quality Weight (1 / √km):
A 1 km model has a quality weight of
1.0, a 2.5 km model has~0.63, a 9 km model has~0.33, and a 13 km model has~0.28. This gives a 1 km micro-grid about 3.5× the influence of a 13 km global model—enough to lead the forecast with local terrain details, while preventing a single rogue model from creating a false alarm. -
Freshness Half-Life (24 Hours):
The age of each model's run is determined from its run initialization timestamp. A run fresh off the supercomputer (2 hours old) carries full weight; a 12-hour-old run still retains
0.67×weight. This avoids abrupt dropouts if an agency experiences a brief upload delay, while gradually fading out stale data. - Smooth Range Horizon Transitions: High-resolution local models typically end at 48 to 72 hours. In the Blended Forecast, when a fine model's range ends, its weight simply stops contributing. The forecast curve transitions smoothly into medium-range global models without an artificial step or sudden jump in wind speed.
-
Trigonometric Circular Averaging for Directions:
Degrees wrap around 360°. A simple arithmetic average of 350° (NNW) and 10° (NNE) would erroneously yield 180° (South). The Blended Forecast uses weighted circular unit vectors (
sin θandcos θ) to ensure directions always point true to the wind. -
Gust Integrity Clamp:
Blended wind speed and gust are averaged over non-null reporting models. The engine strictly clamps the blended gust so that it is always greater than or equal to the blended wind speed (
gust ≥ windSpeed).
4 Model Consensus & The Agreement Dot
When planning a session, checking multiple weather models can sometimes be challenging when forecasts show differing speeds or timings across sources.
Windguru+ offers an intuitive Multi-Model Consensus Indicator. Rather than navigating separate tables, the app evaluates agreement across all available global and regional models for your spot. Right beside each hourly forecast across the Timeline, Classic table, and Meteogram, a single glanceable Consensus Dot provides an immediate, helpful read on forecast consistency.
A Helpful Guide for Your Sessions
The Consensus Dot provides a clear, balanced reading of conditions by taking into account key meteorological factors:
Windguru+ evaluates both wind speed and compass bearing together. A stable forecast means models agree on both how hard the wind will blow and which direction it will come from.
In light airs, small absolute differences in speed are treated naturally as calm conditions, keeping color indicators focused on meaningful shifts in wind behavior.
The indicator balances independent meteorological centers (ECMWF, NOAA, DWD, Météo-France) so that diverse modeling approaches contribute harmoniously to the overall picture.
The most recent model cycles carry the highest influence in the computation, while earlier runs transition smoothly as new updates arrive.
Reading the Consensus Dot at a Glance
At a glance, the Consensus Dot helps you see whether the models agree or require closer monitoring:
All available models show good agreement on both wind strength and direction. Conditions look consistent across sources to help you plan your session.
Models agree on the overall pattern and wind direction, but show slight differences in timing (e.g. a front arriving 2 hours earlier) or peak strength. Worth monitoring before heading out.
Models suggest different scenarios—for example, a fine-mesh model anticipating a localized thermal breeze while a global model expects lighter gradient wind, or a slight shift in a weather front. It simply indicates conditions that may evolve as newer model runs arrive.
The Consensus Dot is transparent and easy to explore. Tap any consensus dot anywhere in the app to open the live Model Breakdown Sheet. You can see every active model's forecast side-by-side, ordered from the most influential to the least influential contributor in the computation, with stale runs and duplicate family members cleanly filtered out.
5 Available Weather Models in Windguru+
Both the Blended Forecast and Consensus calculations draw upon a wide selection of recognized atmospheric models. The table below details the active meteorological models integrated into the Windguru+ app registry, their spatial resolution, cycle intervals, and geographical focus:
| Model | Grid | Cycle | Provider / Source | Coverage & Specialty |
|---|---|---|---|---|
| IFS-HRES | 9 km | 6h / 12h | ECMWF (Europe) | Global benchmark. Universally regarded by meteorologists as the most accurate global atmospheric model in the world. |
| GFS | 13 km | 6h | NOAA / NCEP (USA) | Global reference model. 16-day horizon, updated 4 times daily (00, 06, 12, 18 UTC). Open data staple. |
| ICON 13 km | 13 km | 6h | DWD (Germany) | Global icosahedral non-hydrostatic model. Highly stable dynamic core with excellent mid-latitude performance. |
| GDPS | 15 km | 12h | Environment Canada | Global Deterministic Prediction System. Strong handling of polar and northern hemispheric airmasses. |
| RAP / NAM | 12–13 km | 3h / 6h | NOAA / NCEP (USA) | North American regional models. RAP updates rapidly every 3 hours for near-term synoptic tracking. |
| AROME | 1.3 – 2.5 km | 3h / 6h | Météo-France & GeoSphere Austria | Top-tier European convective-scale model. AROME 1.3 km covers France; 2.5 km covers Austria, French Caribbean, Polynesia, New Caledonia. |
| ICON High-Res | 1.0 – 7 km | 3h / 6h | DWD & MeteoSwiss | ICON 7 km (Europe), ICON 2.2 km (Germany), ICON-2I 2.2 km (Italy), and ICON-CH 1 km (Switzerland & Alpine lakes). Ultra-precise terrain modeling. |
| HARMONIE | 2.0 – 5 km | 3h / 6h | KNMI, DMI, FMI (Consortium) | HARM-NL 2 km (Netherlands), HARM-DK 2 km (NW Europe & Denmark), HARM-FI 2.5 km (Finland/Scandinavia), HARMONIE 5 km (Europe). |
| ALADIN | 1.0 – 2.3 km | 6h | CHMI (Czech Republic) | ALADIN 2.3 km (Central Europe) and ALADIN 1 km (Czech Republic). Highly calibrated for inland European weather. |
| UKV | 2.0 km | 3h | UK Met Office | High-resolution model over the British Isles, updated every 3 hours. Exceptional coastal wind fidelity. |
| MET Nordic | 1.0 km | 6h | MET Norway | Resolves intricate Scandinavian fjords, archipelagos, and northern coastal topography. |
| HRDPS & HRRR | 2.5 – 3 km | 3h / 6h | ECCC (Canada) / NOAA (US) | HRDPS 2.5 km covers Canada. HRRR 3 km provides hourly rapid-refresh updates over the continental United States. |
| WRF (Windguru) | 3.0 – 9 km | 6h | Windguru In-House | Custom WRF simulations run directly by Windguru for wind sports hubs: Europe 9 km, Canary Islands 9/3 km, Egypt 9 km, Gibraltar 3 km, Aegean Sea 3 km, South Africa 9 km. |
| WRF* 1 km Spots | 1.0 km | 6h | Windguru In-House | Dedicated spot micro-grids for premier windsports spots: Tarifa, Canary Islands, Greek Cyclades (Paros/Naxos, Rhodes/Kos), South Portugal (Algarve), Cape Town, Maui/Oahu, Croatia. |
6 Marine & Ocean Wave Models
Waves are physical phenomena distinct from atmospheric wind. An atmospheric model calculates air pressure and wind velocity; it cannot predict ocean swell propagation or shallow-water bathymetric shoaling. Dedicated wave models take 10-meter surface wind fields from atmospheric models and compute:
- Wave Generation: Transfer of kinetic energy from surface wind friction to water over open fetch.
- Swell Dispersion: Waves grouping and traveling thousands of kilometers across open ocean basins with minimal energy loss.
- Decoupled Sea States: Breaking the surface into distinct energy spectra: local wind waves (short period) vs. distant ocean swells (long period).
| Wave Model | Grid | Cycle | Provider | Scope & Usage |
|---|---|---|---|---|
| IFS-WAM | 9 km | 6h / 12h | ECMWF | Global ocean wave benchmark. Directly coupled to the IFS atmospheric model for premier swell forecasting worldwide. |
| GFS-Wave | 9, 16, 25 km | 6h | NOAA / NCEP | Coupled multi-scale global wave model based on WAVEWATCH III®. Global ocean coverage with nested coastal grids. |
| EWAM | 5 km | 12h | DWD (Germany) | European Wave Model. Fine 5 km resolution focusing on the North Sea, Baltic Sea, Mediterranean, and European coastal waters. |
| GDWPS | 25 km | 12h | Environment Canada | Global Deterministic Wave Prediction System, specializing in North Atlantic, Pacific, and Arctic oceans. |
7 Forecast Parameters Used in Windguru+
The Windguru+ app presents essential meteorological and oceanographic data tailored specifically for wind and water sports. Only the parameters actually utilized in the app's views (Timeline, Meteogram, Map, Classic, and Android Auto) are explained below:
The sustained average horizontal wind speed at 10 meters above flat ground. Color-coded using the app's speed palette (from light green/cyan for light breezes to bold yellow, red, magenta, and dark purple for gale/storm winds).
The peak instantaneous wind speed expected during that forecast interval. Gusts reflect atmospheric turbulence, thermal updrafts, or squalls. In Windguru+, gusts are always clamped to be at least equal to the sustained wind speed.
The meteorological direction from which the wind blows (e.g., a North wind blows from North toward South). Rendered in Windguru+ with high-visibility vector navigation arrows that rotate to the exact degree, cardinal labels (e.g. NW, WSW), and exact compass degrees.
Air temperature at 2 meters above the ground.
*Altitude-Corrected Temperature: Numerical models use a smoothed digital elevation grid. A spot situated in a deep valley or high on a coastal headland may differ significantly in altitude from the model's grid cell average. Windguru+ uses high-resolution topography datasets (SRTM & GTOPO30) and vertical temperature lapse rates to correct the forecast temperature to the spot's real altitude.
The apparent temperature felt on human skin, accounting for ambient temperature, convective wind cooling, and relative humidity. Displayed in Windguru+'s Favorites summary chips and spot overview.
Fraction of the sky covered by clouds. Can be viewed as total cloud cover or broken down into three vertical atmospheric layers:
- High Clouds (> 6,000 m): Cirrus and thin veil clouds. Often allow bright sunshine through; minimal impact on solar heating or thermal winds.
- Medium Clouds (2,000 – 6,000 m): Altocumulus and altostratus. Filter out direct sunlight and may weaken thermal breezes.
- Low Clouds (< 2,000 m): Stratus, stratocumulus, or fog. Heavy overcast, blocking sun and often associated with drizzle or marine moisture.
Predicted liquid water accumulation over the period (1 mm = 1 liter per square meter). High-resolution hourly models provide 1-hour accumulation; 3-hourly models provide 3-hour totals.
Snowfall Indication: When predicted temperatures and the freezing level dictate snow instead of rain, precipitation values are highlighted in bold blue text. As a practical rule of thumb, 1 mm of rain corresponds to roughly 1 cm of fresh snow.
The altitude at which the ambient air temperature drops to exactly 0°C. Essential for mountain spots, snowkiting, and assessing winter freezing risk on gear.
Atmospheric pressure adjusted to mean sea level. In classic table notation, pressures above 1000 hPa are displayed in compact shorthand as x - 1000 (for example, 1024 hPa is displayed as 24). Rapidly falling pressure warns of an approaching low-pressure system and strengthening wind.
The amount of water vapor present in the air at 2 meters, expressed as a percentage of the maximum moisture the air can hold at that temperature.
The combined significant wave height of all wave systems (wind chop + swell). Statistically defined as the average height of the highest one-third of all waves observed. Closely matches what a trained observer on the beach judges as the primary wave height.
The time elapsed between the crests of two consecutive waves passing a fixed point. Period is the defining metric for wave power:
- Short Period (4 – 8 s): Locally generated wind chop. Less energy, disorganized surf, steep faces that crumble easily.
- Long Period (10 – 18+ s): Powerful open-ocean groundswell. Originating thousands of miles away, these waves travel fast, carry immense kinetic energy, and wrap cleanly into points and reefs.
The compass direction from which waves approach the coast. Essential for evaluating whether a spot's headlands or reef bathymetry will block, focus, or refract the swell.
When fine-grained wave data is available, Windguru+ breaks down the total sea into its individual physical components:
- Primary Swell (Swell 1): The dominant open-ocean swell train generated by distant storms.
- Secondary Swell (Swell 2): A crossing swell train originating from a second distant weather system.
- Wind Wave: The short-period choppy sea kicked up directly by the local wind currently blowing at the spot.