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.
This can help narrow down a storms track and intensity and can point out if just a single run of a model was ‘off’. With this approach, a model is run multiple times but with slightly different initial conditions.
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 challenge meteorologists face when there are multiple solutions for the same storm, in this case one of the costliest hurricane in U.S. history.
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. … Read More Jim Forster is one of just 239 Certified Consulting Meteorologists (CCM) in the world.
CCS are experts in the application of weather information to a host of practical challenges. He serves as Chief Meteorologist for Dan, the largest business-to-business weather organization in the world where he and his team providing actionable weather forecasts and consulting services in the Aviation, Transportation, Marine, Energy, Agriculture and Safety markets.
This graphic illustrates the huge number of variables that go into weather forecast models. Numerical weather prediction models, or NP, solve a complex set of mathematical equations that are based on the physics that drives how the air moves and how heat and moisture are exchanged throughout the atmosphere.
Generally speaking, the European model has produced the most accurate global weather forecasts. Today we have global sources of data of many types to give the forecast the best possible start.
Nashville’s horrific tornadoes are too strong a reminder that the spring severe weather season is upon all of us. We haven’t had a lot of severe weather in the last few months here in Southeast Texas, so looking at which model is performing best is challenging.
IBM also owns Wei which is a primary vendor for weather graphics (ours and every other TV station in Houston, in fact). The IBM Gray computer is long-awaited and has excellent “resolution” (think how well your new smartphone takes pictures compared to five years ago).
Snapshot taken at 9pm Tuesday RPM, or Rapid Precision Message, also has excellent resolution, goes out 48 hours on a 4-kilometer scale, updates once an hour and is driven by the well-respected Weather Research and Forecast model (created by the Air Force, NOAA and the National Center for Atmospheric Research). IBM, RPM, Breathe upside is that ALL of them have the strongest storms this morning north of I-10.
Exact Track Radar 11pmA severe thunderstorm watch went into effect for our northern counties, not surprising given the model forecasts. We can cherry-pick any event to compare and give out trophies, of course, but it’s great news that all these models were very much in line with each other.
Interestingly, the IBM timing was the best, the RPM was correct with the extension of the front to the south, and the Herr had the bullseye of severe weather in our northern counties. The RPM: it initialized well and was the most aggressive, and I would rather impress upon viewers the potential severity of the situation.
The ECM WF is generally considered to be the most accurate global model, with the US's GFS slightly behind. Weather models are simulations of the future state of the atmosphere out through time.
Millions of observations are used as initial conditions in trillions of calculations, producing a three-dimensional picture of what the atmosphere might look like at some time in the future. Massive computers are used to do these calculations at incredibly fast speeds to enable simulations to cover the entire globe, and extend up to two weeks into the future.
Global models produce forecast output for the whole globe, generally extending a week or two into the future. Because these models cover a wider area, and a longer time span, they’re generally run at a lower resolution, both spatially (fewer forecast points per given area) and temporally (fewer time points get a forecast).
These slight differences multiply out through time because the atmosphere is a chaotic system. This also means any errors that the models make in the near term become exponentially larger with time.
Weather modelling centers attempt to control for the influence of chaos by running ensemble systems that each use slightly different initial conditions. Each ensemble “member” then produces a forecast as if its set of initial conditions were correct.
This fact most glaringly reached the American public when only the European forecast model correctly predicted Hurricane Sandy would turn toward the northeastern United States in 2012 rather than remaining out to sea. For the Northern Hemisphere during the last two months, as measured at the 500mb level of the atmosphere (about 5.5 km above the Earth's surface), the European model scores the highest by far, at .905.
He concluded, “It is not that U.S. global (numerical weather prediction) is getting less skillful, but that other nations are innovating and pushing ahead faster. In his post, Mass calls attention to several steps the National Weather Service and its parent agency, the National Oceanic and Atmospheric Administration, could take to make the GFS model more competitive, including improving the physics of its model and better utilizing the two powerful new supercomputers that Congress recently provided.
Weather forecast models are computer programs that can help predict what the weather will be in the future, any time in the future from an hour to ten days out and even months ahead. These forecast models take current weather observations collected from thousands of locations (such as wind speed, wind direction, air temperature, pressure, etc.
), make an estimate about the current weather for locations where no actual data exists, and then use math and physics equations to predict what will happen in the future. Below is an image from the “GFS” forecast model showing areas of high and low pressure as well as precipitation.
Global Forecasting System Produced by the US Government Covers the entire globe Forecasts out to 384 hours (16 days) Updates 4x per day Model resolution of 13 km Average accuracy score lags the ECM WF (but every storm is different) Cost = freely available to anyone European Center for Medium-Range Weather Forecasts Produced by a group of European Governments Covers the entire globe Forecasts out to 240 hours (10 days) Updates 2x per day Model resolution of 9 km (more detailed than the GFS) Average accuracy score makes it the best model (but every storm is different) Cost = $250,000 for commercial license to host data.
Personal license is available to access data with an individual subscription (see Paid Forecast Model Websites below). Then there are message (fine-scale) models, which hone in on more specific regions and tend to be able to forecast tiny weather features better than the global models, like thunderstorms or snowfall within steep mountains.
Weather models provide gigabytes of forecast data each time that they run. A 16-day snow forecast for the United States and southern Canada from September 24 – October 10, 2019, from the American GFS model.
A 16-day precipitation forecast for the United States and southern Canada from September 24 – October 10, 2019, from the American GFS model. This is for the United States and southern Canada from September 24 – October 10, 2019, from the American GFS model.
First, forecast models differ in how they collect the current weather conditions across the globe. Even with a sophisticated measurement network including satellites, radars, weather balloons, ground-based weather stations, planes and ships, forecast models must make assumptions to fill in the gaps between actual weather observations, in places like oceans, large forests, deserts, etc.
Second, forecast models differ in the math and physics equations that they used to move from the current condition of the atmosphere and turn that into a weather prediction. And third, forecast models have different levels of detail (resolution) and can struggle to properly account for steep terrain like the mountains where we ski and ride.
All of these factors play a roll in creating different forecast outcomes even though the models are starting with mostly the same information about the current state of the atmosphere. To account for both of these shortcomings, models are run many times with slightly different current weather conditions and equations.
For example, the GFS ensemble forecast model is made up of 21 versions, each of which uses slightly different current conditions. The forecasts made by the models are usually most accurate within 1-5 days, and then they lose accuracy the further out in time they go.
This is because of the chaotic nature of weather, in which very small uncertainties in the current state of the atmosphere have a “butterfly effect” on the future. As computer technology and scientific knowledge improve, the models will become more sophisticated continuing to lead towards more accurate forecasts.
Don't forget to download the Open Snow app and stay tuned to our latest forecast updates throughout the season. There are tons of weather sites out there and while a good portion of them are freaky conspiracy websites run by high schoolers with inexplicably large followings, there are some true gems that many weather enthusiasts have yet to discover.
The embodies great because it aggregates and archives almost every text product issued by the National Weather Service in real time. The site also features a mammogram generator (an example is pictured above) that allows you to visualize model data for certain variables such as temperature and rain/snowfall for up to a week in the future.
The site is great for tracking synoptic scale features such as nor'Easters and the jet stream. SimuAWIPS, pictured at the top of this post, is an incredible resource for tracking current weather and predicting what will happen in the short- to medium-range.
The SimuAWIPS interface is interactive, customizable, and allows you to view up to four windows of weather data at once. Its features, layout, and interactivity make it my number one site for weather graphics.