A spaghetti model is a method to graph information. In the case of hurricane spaghetti models the graph represents the PREDICTED location and path of a hurricane over a 10 day time period. The spaghetti parts comes in when many different predictions and shown at the same time as in the image on the right.
Ever wonder why it’s so hard to predict where and when a hurricane will exactly make landfall or how strong it will be? It’s not from a lack of information available; it’s actually from too much information available.
Hurricane forecasters have many different computer models to aid in predicting a storm’s path and its intensity. All of them are good, but they each take into account many variables and when looking at a five day and beyond forecast, prediction can vary widely. Meteorologists will refer to these as the “spaghetti models” because when laid out on a map, the storm paths resemble strings of spaghetti. When these models are grouped into a consensus the result is a map referred to as the “cone of uncertainty” taking into account (most to all) paths from one extreme to the other. This map is one that is more familiar to television weather reports.
There are many groups that predict tropical cyclone track and intensity models a summary of the top six follows:
ECMWF: The European Center for Medium-Range Weather Forecasting (ECMWF) model is the premier global model in the world for medium range weather forecasting in the mid-latitudes. In 2006, the ECMWF made improvements those starting producing very accurate hurricanes forecasts.
GFS: The Global Forecast System model run by the NWS. Excellent graphics are available on the web from the National Center for Environmental Prediction.
GFDL: The NWS/Geophysical Fluid Dynamics Laboratory model. The GFDL and HWRF models are the only models that provide specific intensity forecasts of hurricanes. More detailed GFDL graphics are available at NOAA/NCEP.
UKMET: The United Kingdom Met Office model. Data from this model is restricted from being redistributed according to international agreement, and graphics from the UKMET are difficult to find on the web.
HWRF: The NWS/Hurricane Weather Research Model. HWRF is a non-hydrostatic a coupled ocean-atmosphere model, will utilize highly advanced physics of the atmosphere, ocean and waves in one prediction system, providing unparalleled understanding of the science of tropical cyclone evolution. Its output gives meteorologists an analysis of the hurricane in three-dimensions from real-time airborne Doppler radar. It will make use of a wide variety of observations from satellites, data buoys, and hurricane hunter aircraft. No other hurricane model accesses this wide of a range of meteorological information. The GFDL and HWRF models are the only models that provide specific intensity forecasts of hurricanes. Detailed HWRF graphics are available at NOAA/NCEP.
NOGAPS: The U.S. Navy's Navy Operational Global Prediction Center System. Graphics are available at the Navy web site. This model has been performing poorly in recent years compared to the other global models, so it has been removed from the consensus models that the National hurricane Center uses as of 2011.
So which model is best? There is no one model that is right all the time, so each storm and the conditions in and around that storm must be taken into account. Some models are known to perform better in certain scenarios and some older models are known to have limited forecasting ability. The most common models are a collection of models that are commonly used and trusted to be more reliable. That does not mean any one model is correct for this storm, as even the best models can be wrong.
We all want to know where and when a hurricane with hit. Prediction technics and storm modeling has come a long way, just a decade ago 120 hour forecasts from the National Hurricane Center were not even made public, today forecasts for 240 hours out (10 days) are used for every tropical storm that nears the US coast.
Meteorologists want to provide the most accurate information and do not want to be left with spaghetti on there face from inaccurate predictions.
Weather links and resources used for blog: