Models
Wind Forecast
What We Do
We take the highest-resolution wind model available for Maui and apply AI corrections trained on 19 local weather stations. The result: forecasts that account for Maui’s complex terrain, not just the broad trade wind pattern.
What We Do
We use the highest-resolution wind model available for Maui — the UH WRF at 2 km — to produce hourly wind forecasts for 5 coastal regions. The model simulates atmospheric physics on a fine grid, capturing Maui’s trade wind patterns and terrain effects.
Why Corrections Matter
Even the best wind model for Maui (UH WRF at 2 km) systematically overpredicts wind by 4–6 knots at sheltered regions like South Maui, West Maui, and East Maui. A forecast that says “15 knots” when it’s actually 8 isn’t useful. Our AI models learn these terrain biases from a year of observations and correct for them automatically.
How Accurate
Tested against held-out observations from 19 stations across 4 corrected regions.
Wind speed accuracy by region
Accuracy is the typical (RMS) error on held-out test data. Individual forecasts may vary.
At sheltered sites, the physics model overpredicts by 4–6 knots on average. Our correction reduces this systematic bias to near zero while cutting overall forecast error by 50–70%. On the exposed North Shore, the physics model is already accurate (within 4 kt) so no correction is applied.
19 stations, 804,000+ paired observations over 12 months (March 2025–February 2026)
Tested on 2 months of held-out data the model has never seen.
What We Display
- Wind maps – Base physics model output, useful for seeing island-wide patterns and trends at a glance
- Regional forecasts – AI-corrected wind speeds for the first 2 days, then base physics model output for days 3–5. When a correction is applied, you’ll see an annotation like “↓35%” — meaning the corrected speed is 35% lower than what the physics model predicted
- North Shore – Always shows physics model output — the model is already accurate on the exposed trade wind coast
What We Display
- Wind maps – Color-coded wind speeds across the island with animated playback through the day
- Regional forecasts – Hourly wind speed, direction, and gusts for each of Maui’s 5 coastal regions, out to 5 days
How It Works
Two layers:
- Physics model (WRF 2 km) – The UH/PacIOOS WRF atmospheric model simulates wind physics on a 2 km grid, producing hourly forecasts out to 5 days. We extract winds at each of Maui’s 5 coastal regions from nearshore over-water grid points.
- AI terrain correction – Per-station models trained against local observations learn how the physics model’s spatial patterns relate to its systematic errors at each location. The correction uses only model data — no dependence on live station observations — so accuracy is the same whether stations are reporting or not.
- Water points only – Grid points over land are excluded
- Nearshore focus – Only points within 3 km of the coastline
- Averaged readings – Each region samples 13–15 grid points
How It Works
- Physics model (WRF 2 km) – The UH/PacIOOS WRF atmospheric model simulates wind physics on a 2 km grid, producing hourly forecasts out to 5 days. We extract winds at each of Maui’s 5 coastal regions from nearshore over-water grid points.
- Water points only – Grid points over land are excluded
- Nearshore focus – Only points within 3 km of the coastline
- Averaged readings – Each region samples 13–15 grid points
The Base Model
Most weather apps rely on global models (GFS, ECMWF) where grid cells are larger than the terrain features that shape Maui’s wind — valleys, ridgelines, headlands. These models capture broad patterns (“strong trades all week”) but can’t distinguish a windy North Shore from a calm South Shore on the same afternoon. We use the 2 km WRF run by UH specifically for Maui and Oahu — the highest-resolution public wind model available for this area.
| Model | Resolution | Maui Detail | Typical Use |
|---|---|---|---|
| UH WRF 2km (ours) | 2 km, hourly | Resolves valleys, channels, coastal jets | Purpose-built for Maui–Oahu |
| WRF 6km (Hawaii-wide) | 6 km, hourly | Islands resolved but gaps/headlands blurred | Regional Hawaii context |
| NAM 3km (NCEP) | 3 km, hourly | Channels resolved but valleys/coastal jets smoothed | NWS operational forecasts |
| GFS (global) | 25 km, 3-hourly | Maui is ~3 grid cells; terrain lost | Synoptic patterns, wave model forcing |
| ECMWF / ICON | 9–13 km | Under-resolved terrain and channels | Global forecasts, many apps |
Sources
- PacIOOS WRF Maui–Oahu University of Hawaii — 2 km WRF atmospheric model
- UH SOEST WRF Metadata Technical documentation and model configuration
- MesoWest / Synoptic Data Weather station observations used for AI model training
Swell Forecast
What We Use
We built an AI model trained on 13+ years of wave data to forecast waves at Maui. It predicts not just how big the waves will be, but the full breakdown — how much energy is in long-period ground swell vs. short-period wind chop, and which direction each is coming from.
Why
The global WaveWatch III (WW3) ocean model predicts waves across the entire Pacific, but it doesn't fully account for what happens as waves approach Maui. Islands block swells, underwater terrain bends them, and local winds reshape conditions near shore. Our model learns these patterns from years of data — comparing what WW3 predicted offshore vs. what buoys actually measured at Maui.
How It Works
We blend three data sources in a priority cascade. For each forecast hour, the system selects from the highest-available tier:
Tier 1: Nearshore Buoys
What's happening now — Direct measurements from buoys close to Maui. Used for past hours only.
Tier 2: AI-Corrected Forecast
Our best forecast — Our AI model takes WW3's open-ocean forecast and adjusts it for local conditions, predicting both swell and wind chop separately. 0–5 days ahead.
Tier 3: Raw WW3 Fallback
Safety net — Uncorrected WW3 output when the AI model is unavailable.
What the Model Looks At
- Deep-ocean buoys — 4 buoys far offshore track incoming swells hours before they reach Maui
- Swell trends — is the swell building, peaking, or fading?
- WW3 ocean model — open-ocean wave forecast for the waters around Maui
- Wind model — local wind speed, direction, and trends
- Time of year — seasonal swell patterns, especially south shore summer swells
Pauwela Buoy: 206,000 hourly observations (13 years, 2011–2024)
Kaumalapau Buoy: 177,000 hourly observations (18 years, 2007–2025)
Tested on data from 2024 onward that the model has never seen.
How Accurate
Tested against more than 117,000 buoy observations spanning 2+ years that the model has never seen.
Swell height accuracy
Direction and period accuracy
Accuracy is the typical (RMS) error on held-out test data. Individual forecasts may vary.
Our model beats WW3 at both locations. At the Kaumalapau (Lanai) Buoy, where WW3’s coarse grid can’t resolve wave refraction around Lanai, our model is twice as accurate. At the Pauwela Buoy, it’s 35% closer. It also predicts direction and period — a 4 ft swell at 16 seconds from the north is a very different session than 4 ft of chop at 8 seconds from the east.
Sources
- NDBC Buoy Data NOAA — Deep-ocean and nearshore buoy observations
- CDIP THREDDS Server Coastal Data Information Program — Nearshore spectral data
- PacIOOS WaveWatch III Global ocean wave model used as baseline
Swell Exposure
What We Use
Each of Maui's five forecast regions faces a different slice of the ocean. Swells from the north can't reach south-facing beaches — the island itself blocks them. We use directional exposure windows to define which wave directions can physically reach each coastline.
| Region | Faces | Swell Window | Blocked By |
|---|---|---|---|
| North Shore | Open ocean north | 280°–90° | Island to south |
| East Maui | Trades, east swells | 20°–135° | West Maui Mountains |
| South Maui | Southern hemisphere | 150°–250° | Island to north |
| W Maui (South) | South–southwest | 185°–275° | Lanai, Kahoolawe |
| W Maui (North) | North–northwest | 280°–350° | Molokai |
Interactive Explorer
Click or drag on the map below to set a swell direction. Regions that receive swell from that direction light up; blocked regions are dimmed.
In reality, swell bends around islands and headlands through a process called refraction. Large, long-period swells can wrap around obstacles and reach coastlines that a straight-line shadow model would not predict. The exposure windows are a useful simplification, not an exact boundary.
When our swell model predicts a swell from a direction outside a region's window, that swell is filtered out — it can't physically reach that coast.
Sources
- GP's Maui Surf Report Local knowledge — Shadow line degree estimates for each Maui region
Swell Propagation
What We Use
We use group velocity physics to estimate when distant swells will arrive at Maui. Longer-period swells travel faster — a 20-second ground swell moves at 31 knots, while a 6-second wind swell crawls at 9 knots.
How We Use Propagation Physics
- Buoy page arrival times — On the Buoys page, we compute when each swell detected at a deep-ocean buoy will arrive at Maui, based on its period and distance. This gives surfers an early heads-up: “a 14-second NW swell was just detected 370 nm away — it should arrive in about 17 hours.”
- AI model input — Our swell forecast model uses the propagation physics estimate as one of its input features. The model learns when the simple physics gets it right and when island effects (shadowing, refraction) cause the calculation to be off.
Our swell forecast extends 5 days ahead using the WW3 ocean model corrected by machine learning (see Swell Forecast). Propagation from deep-ocean buoys provides a complementary 12–24 hour window of direct observation-based prediction.
| Swell Type | Period | Speed | From NW Hawaii (370 nm) |
|---|---|---|---|
| Wind chop | 6s | 9 kt | ~40 hours |
| Short swell | 10s | 16 kt | ~24 hours |
| Medium swell | 14s | 22 kt | ~17 hours |
| Ground swell | 20s | 31 kt | ~12 hours |
What Happens En Route
- Distance decay — Waves lose energy as they spread. A swell from 370 nm away loses about 11% of its height.
- Direction filtering — Only swells arriving within a region's exposure window are kept (see Swell Exposure).
- Empirical corrections — 18 years of paired buoy observations fine-tune these estimates, accounting for island shadowing and bathymetry that simple physics can't capture.
Sources
- NDBC Buoy Network NOAA — Deep-ocean and nearshore buoy data
- StormSurf: Wave Basics Surf forecasting reference — swell speed, travel times, and the T × 1.5 knots rule
How We Compare
| Maui Wind Swell | Surfline | Windy | WindAlert | WindGuru | |
|---|---|---|---|---|---|
| AI wind correction | ✓ 4 regions | — | — | — | — |
| AI swell correction | ✓ | ✓ | — | — | — |
| Wind model resolution | 2 km | 25 km | 2.5 km | 2 km | 1 km |
| Forecast horizon | 5 days | 10 days | 3 days | 3 days | ~1 day 3 days with 3 km model |
| Live wind stations | ✓ 21 NWS/mesonet + WindyTron | — Airports only | — Airports only | ✓ 13 WeatherFlow | — |
| Live surf cams | — | ✓ | — | — | — |
| Private weather stations | — | — | — | ✓ $45/yr | — |
Wind Accuracy
Most apps show physics model output directly. We start with the highest-resolution public wind model (UH WRF at 2 km), then apply AI corrections trained on 19 Maui weather stations. At sheltered sites, this cuts forecast error by 50–70%.
Wind speed accuracy (sheltered regions)
Accuracy is the typical (RMS) error on held-out test data. Individual forecasts may vary.
Wind Accuracy
We use the UH WRF at 2 km, the highest-resolution public wind model available for Maui. It captures trade wind patterns and terrain effects across the island, producing hourly forecasts out to 5 days.
Swell Accuracy
Global wave models don’t account for island blocking, refraction, or local wind effects. Our AI model, trained on 13+ years of buoy data, corrects for what raw WaveWatch III gets wrong — delivering tighter height, direction, and period predictions at both shores.
Swell height accuracy
Direction and period accuracy
Accuracy is the typical (RMS) error on held-out test data. Individual forecasts may vary.
What Others Do Well
We’re focused on Maui wind and swell. Other services do things we don’t.
Surfline
Live surf cams at Kahului Harbor and The Cove, per-break ratings, and a proprietary nearshore swell model.
WindAlert / iKitesurf
Private WeatherFlow weather stations at locations like Kanaha and Molokini where public data isn’t available.
Windy
Map-based interface with side-by-side comparison of global models (ECMWF, GFS, ICON). Great for tracking Pacific storm systems.
WindGuru
Dense tabular format with multiple models stacked on one page. Runs a 1 km WRF for Maui — higher resolution than ours, but limited to ~1 day at 3-hour intervals.