Ensemble Forecast Model Upgraded by National Weather Service

 In Industry Highlights
ensemble forecast model

In September 2020, the National Weather Service (NWS) deployed an upgraded ensemble forecast model that should provide a boost to emergency preparedness efforts and help save lives.  The beauty of the upgrade is that it will double forecast length, providing an extra 2 weeks of prep time for infrastructure.

Features and Functionality of the New and Improved Ensemble Forecast Model

NWS installed the FV3 dynamic core (Finite Volume Cubed Sphere) in its Global Ensemble Forecast System (GEFS).  This was the first major upgrade to the NWS ensemble forecast model since 2015.  The upgraded model features several improvements:

Increased Ability to Measure Confidence Level

The new forecasting model produces a wide range of potential weather outcomes by running many simulations, each of which has a slightly different starting point than the others.  The greater the similarity between each outcome, the higher the degree of confidence in the accuracy of the overall forecast. 

For example, the number of models that can be run has increased from 21 to 31 with the upgrade.  If all 31 show a similar outcome, the degree of confidence in the forecast is high.  But if only, say, 15 show a similar outcome, then there is more uncertainty and potential variability in the forecast.

Increased Accuracy

Another feature of the new model is that its resolution has improved 24%, providing a higher degree of accuracy.  Overall, the new and improved ensemble forecast model is more accurate because it offers a higher level of precision around hurricane track and intensity, precipitation, and wave heights.

Increased Lead Time

Finally, with the upgrade, the model can now predict the weather 33 days out, doubling the previous maximum lead time of 16 days. 

The bottom line is that with greater accuracy and longer lead times, the new and improved NWS ensemble forecast model will help improve everyone’s ability to be well-prepared.  

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