Het GRAF model, 3km wereldwijd, elk uur een nieuwe run

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IBM Introducing the World’s Highest-Resolution Global Weather Forecasting Model

https://www.wunderground.com/cat6/IBM-Introducing-Worlds-Highest-Resolution-Global-Weather-Forecasting-Model?cm_ven=cat6-widget

Paar stukjes uit het artikel:

IBM announced today that they will be introducing the world’s highest-resolution global weather forecasting model later in 2019--the IBM Global High-Resolution Atmospheric Forecasting System (GRAF). The model will be the first hourly-updating weather model that is able to predict something as small as a thunderstorm virtually anywhere on the planet.

The current top global forecasting models, the European (ECMWF) model and the U.S. GFS model, subdivide the global atmosphere into grid boxes that average 9 kilometers and 13 kilometers on a side, respectively, then solve the mathematical equations of atmospheric flow to generate a forecast for each of those grid cells. The new GRAF model employs a variable-resolution grid, resembling a honeycomb, that can be configured with higher resolution over areas of particular interest (Figure 1). Over land areas, the GRAF grid elements will have average resolutions of 3 km, which is about 3 - 4 times greater than the European and GFS models.

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In addition, GRAF runs hourly, compared to the 6-hourly runs available for the GFS model and the 12-hourly runs of the European model. NOAA’s High-Resolution Rapid Refresh (HRRR) model does run hourly at 3-kilometer resolution, but only covers the U.S. The new GRAF model will be like the HRRR model, but global in coverage.

Initially, the highest-resolution version of the GRAF model will run at least 12 hours into the future; a lower-resolution version now being tested extends out as far as 120 hours.

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Every weather model requires weather observations to initialize the forecast, and GRAF uses the same system as the GFS to get the initial weather conditions. However, GRAF has the capability to crowdsource additional weather data by using pressure sensor readings sent from barometers found within smartphones, if people opt in to share that information. In addition, hundreds of thousands of pesonal weather stations, many operated by amateur weather enthusiasts, will also be able to contribute data to the model. These additional data sources will require some challenging quality assurance algorithms, and it will be very interesting to see by how much this crowd-sourced data improves forecasts.

 

Dat laatste is wel saillant gezien de zaak die LA heeft aangespannen tegen The Weather Company, zie bijvoorbeeld:

https://www.nytimes.com/2019/01/03/technology/weather-channel-app-lawsuit.html