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What does PWG / PWE / GFS / ECMWF / SPIRE / UKMO / HRRR/ NAM/ & AROME stand for?
What does PWG / PWE / GFS / ECMWF / SPIRE / UKMO / HRRR/ NAM/ & AROME stand for?
Jon Bilger avatar
Written by Jon Bilger
Updated over a week ago

They are the forecast models we provide.

Our goal is to give you the most accurate forecast data available. A single forecast model will never be the most accurate in all situations, so by having access to the world’s top forecast models you can be assured to get the best possible forecast, to give you greater confidence in your decision-making.

PredictWind has been the market leader for accurate forecasts in the recreational market since 2008. Using the CSIRO CCAM model with 450 high-resolution domains around the world, PredictWind covers most popular recreational marine users in the world.

PWG: Stands for the PredictWind proprietary weather model that uses the NCEP global initial conditions, processed through the CSIRO CCAM model to generate the PWG forecast.

PWE: Stands for the PredictWind proprietary weather model that uses the ECMWF global initial conditions, processed through the CSIRO CCAM model to generate the PWE forecast.

Using the ECMWF and NCEP initial conditions (which are comparable to a 'photographic' snapshot that contains the current state of the Earth's atmosphere) enable us to run our own worldwide weather models, and we are the only private company in the world that has this proprietary technology.

GFS: Stands for Global Forecast System from NCEP. This is used by most other weather websites/apps. We now display the GFS-FV3 model when you see the GFS label in PredictWind. It’s the first significant upgrade to GFS in about 40 years. Unlike the previous GFS model, GFS-FV3 is able to simulate vertical movements such as updrafts, a key component of severe weather, at very high resolution. So far, tests suggest that the FV3 model has more accurate five-day forecasts, as well as better predictions of hurricane tracks and intensification. Although the new FV3 core has shown improvements over GFS it remains ranked 3rd for accuracy behind ECMWF(1st) and UKMO(2nd).

ECMWF: Stands for European Center for Medium-Range Weather Forecasts and is highly regarded by Meteorologists and top Navigators around the world. The ECMWF High RES model consistently rates as the top global weather model from a national weather service with the highest rating scores. In March 2016 ECMWF increased the resolution of their model to a record-breaking 9 km resolution, which is currently the highest resolution global model available. ECMWF data has a very high acquisition cost, and this is why the data is not widely used by many weather websites, and has been traditionally used only by top yacht racing teams and meteorologists.

SPIRE: Is a truly innovative company with the largest nanosatellite network in space. Spire uses a unique technique of measuring the earth’s atmosphere with 3x more radio occultation data than any other commercial entity. This gives an advantage in forecast accuracy for remote locations. The Spire model is #1 for wind speed and direction accuracy using data from offshore weather buoys. It is #2 behind the ECMWF for land-based weather stations.
​You can learn more about Spire by watching this video.

UKMO: Otherwise known as the “Unified Model” by the UK Meteorological Office has a long reputation as a market leader in forecast modelling. UKMO has very similar accuracy to the ECMWF model offshore, and is slightly behind the ECMWF & Spire models for the land based weather stations.

HRRR: Stands for High-Resolution Rapid Refresh and is an NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3 km grids with 3 km radar assimilation. Radar data is assimilated in the HRRR every 15 min over a 1-h period adding further detail to that provided by the hourly data assimilation from the 13 km radar-enhanced Rapid Refresh. To learn more see the video.

NAM: Stands for North American Mesoscale Forecast System and is one of NOAA’s major weather models, which in this case covers most of North America. NAM is a mesoscale model, which means that the numerical analysis is able to model land, and other features, at a higher resolution than in a global model, leading to improved forecast accuracy.

AROME: Is a small scale numerical prediction model, operational at Meteo-France since December 2008. It was designed to improve short-range forecasts of severe events such as intense Mediterranean precipitations (Cévenole events), severe storms, fog, urban heat during heat waves. This model is highly regarded by top racing navigators and beats the ECMWF forecast.


Comparing the PWG/PWE forecasts allows you to gauge the confidence level in the forecast, and adding the GFS/ECMWF/ SPIRE & UKMO forecasts take your confidence to a new level. Generally the unique PredictWind model, and its higher resolution will be more accurate, but with all 9 forecasts you can have greater confidence in your forecast to make the best decision.

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