Which Weather Model Is Most Accurate? The Answer Might Surprise You

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Meteorologists must choose from a multitude of weather models to create a forecast. These models vary in lead time, precision, and skill and each has their place when a meteorologist produces a forecast

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Using the right tool for the job is a mantra that transcends workplaces and career paths. Much like a plumber choosing the right wrench or a surgeon selecting the proper clamp, meteorologists must choose from a multitude of weather models to create a forecast. These models vary in lead time, precision, and skill and each has their place when a meteorologist produces a forecast. However, it is rare that a meteorologist would opt to utilize one model exclusively.

Utilizing multiple models is a vital part of the forecast creation process. This allows for situations where a single model, forecasting a large, land-falling hurricane for example, can be discarded when the vast majority of models are forecasting a swift turn out to sea.  When talking about which model guidance to follow, most of the conversations revolve around the various American weather models  run by the National Weather Service and the European model (Euro) produced by the European Center for Medium Range Weather Forecasts. While those are the most well-known, there are also weather models run by Environment Canada (the Canadian equivalent of the National Weather Service) and the Met Office in England, just to name two. Each of these weather models utilizes a set of equations to predict the atmosphere, however each model’s equations are slightly different, and this can spiral into the difference between the need to prepare evacuations and continuity of business and a quiet, late-summer’s day.

To help refine the forecast, meteorologists typically employ an ensemble approach to get rid of outlying solutions and frame the overall risks. The ensemble approach allows meteorologists to look at a group of weather models, rather than individually. One of these ensemble forecast techniques is to look at multiple different models, seeing how entirely different sets of equations handle the same situation. This initial pass can point to outlying model solutions due to a model’s, sometimes poor, handling of the atmosphere. However, this does nothing to establish if, for instance, a storm is trending east or west. The second pass is typically to use the older runs of the same models to try and establish a trend in the modeling. This can help narrow down a storms track and intensity and can point out if just a single run of a model was ‘off’. Lastly, meteorologists can reference the ensembles of each of the models. With this approach, a model is run multiple times but with slightly different initial conditions. Each of these slightly different initial conditions can produce some deviation in a storms track and intensity, which further helps eliminate outlying solutions and increase confidence where there is a good convergence of track and intensity.

The use of multiple models is critical in the forecast creation process, but is not without its own pitfalls. In 2012, Hurricane Sandy made landfall in New Jersey to devastating effect. Its forecast track, including the left turn, was well forecasted by the European model 7 days out. However, most other model solutions took Sandy out to sea, leaving the European model as an outlying solution. Over numerous runs, other weather models began to forecast a land-falling hurricane and the models taking Sandy out to sea became the outlying solutions. Had forecasts been locked into the European models forecast earlier, additional preparations could have been made. However, if that early land-falling track had been utilized and the storm then turned out to sea, the forecast would have looked alarmist. This is an example of the the challenge meteorologists face when there are multiple solutions for the same storm, in this case one of the most costliest hurricane in U.S history.

As computing power increases, meteorologists look forward to more precise models and models that can accurately forecast systems as large as hurricanes, down to the individual storms within a rain band. Even with those improvements, the use of multiple models will likely remain the first tool a meteorologist leans on to zero in on the most accurate forecast.  

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