The NBM models were first introduced to the LuckGrib model suite in mid 2018. Later that year the models were upgraded to v3.1, adding several new parameters and many new models to the blend.
Recently, the National Blend of Models was again updated, to v3.2. There are, again, new parameters available along with many new models being incorporated into the blend.
The four NBM models are:
NBM Conus, Alaska and Hawaii
These three models gain an important new parameter - standard deviation for wind speed and wind gusts. As the blend takes as input many weather models, it has access to the spread among these models for the winds. The NBM now generates the standard deviation for the wind speeds which is a direct representation of how certain the forecast is for these values.
This new ability for these models to be able to express uncertainty is new, and, in my humble opinion, important.
When looking at any long term forecast we know that we should trust the forecast less and less as the forecast time extends out. However, the uncertainty is not spread evenly among the forecast domain. Depending on the weather patterns, some areas will have greater certainty and other areas will have less. The standard deviation is an expression of the forecast certainty and is an important factor when evaluating the forecasts.
The oceanic domain of the NBM has improved wind speed and direction. This model continues to provide probability winds, which are a very interesting way of evaluating the winds in a forecast.
The NBM Oceanic model is one of the most interesting surface wind forecast models available. All sailors should be evaluating this model.
NBM Oceanic covers most of the Pacific and Atlantic oceans, down to 30° south, at a 10km resolution.
The Oceanic model used to be run six times a day. It is now being run four times a day, at the UTC times: 00Z, 07Z, 12Z and 19Z.
All NBM models have additional new inputs
The service change notice describes the changes to the NBM suite of models, in detail.
Thank you to the NBM team for making this data available, and for their work in improving it.
The NBM data represent an important resource for the weather community to consider. Feedack is welcome on how useful you find these models.