What Are Spaghetti Models?

A delicious-sounding term has made its way back into the weather forecasting vocabulary as hurricane season ramps up, but it has nothing to do with food.

Spaghetti weather models, also known as spaghetti plots, are a forecasting tool that helps give a visual of possible storm tracks. Each plot represents a different forecast model, with each model having its own way of predicting the storm.

They are a simplistic way of conveying a lot of tropical information quickly, but there can also be downfalls to relying on these plots.

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Spaghetti Plots Don't Portray Impacts

Although most models show possible impacts, in order to present many models succinctly on a single chart, meteorologists generally produce spaghetti plots that usually only show the “where” and a loose representation of “when” for tropical systems.

To get to this level of brevity, meteorologists must focus only on the center point of a tropical system. These plots don't speak to whether a storm will bring rainfall, hurricane-force winds, surge or other data; they just contain information about the center of a storm's future track.

Each Model Has A Slightly Different Purpose

Most models have the goal to be the very best, but each one has a different way of getting to that result.

Some weather models are built on statistics, some on atmospheric dynamics. Others are built on other models, while some are built entirely on climatology and persistence of the current atmosphere.

One major advantage spaghetti models have is when most of the models overlap. This is a big confidence booster for forecasters because most of the models have the same idea, even if they are getting to it in different ways.

Another confidence booster is consistency between forecast model runs. When numerous runs consistently show similar ideas, it can be helpful for forecasters. When models change from run to run, this means that either the atmosphere is changing or the model does not have a good idea about what's happening, and it is usually the latter.

Looking At Ensembles May Be The Way To Go

There is also a second flavor of models called an "ensemble" that can be especially helpful three to seven days in advance. The most well-known models – the Euro, GFS, Canadian, and others – all have ensembles. An ensemble is a collection of forecasts all valid at the same forecast time.

Ensembles should be leaned on in the medium- to long-term forecast realm to see all of the possibilities for a given period.

Ensemble systems can be helpful in multiple ways.

First, if these ensembles are tightly packed together in three to seven days, the confidence in a forecast is higher, but it still should be checked against other ensembles.

Secondly, if a model's ensemble is tightly packed but still diverges from other models like the Euro or the hurricane models, it could be either very arrogant or likely to be correct. Figuring out which of these possibilities is correct comes with forecaster experience.

Finally, if this ensemble's members are spread apart within two to four days, you know that model has less confidence, or that the overall forecast is highly uncertain.