What Hurricane Model Does NOAA Use? Unpacking The Science Behind Forecasts

Lura Schiller 02 Aug 2025

When a storm starts brewing far out at sea, you know, the first thing many of us wonder is just how bad it might get, right? We look to forecasts for answers, and those forecasts, pretty much, come from some really smart computer models. These models are the backbone of how we get ready for what's coming, helping us understand where a storm might go and how strong it could become. It's a bit like having a crystal ball, but one that's built with a whole lot of science and data, so.

The National Oceanic and Atmospheric Administration, or NOAA for short, plays a huge part in keeping us informed about these powerful weather events. They are the folks responsible for putting out those crucial hurricane predictions we all rely on. But have you ever stopped to think about what goes on behind the scenes? What kind of sophisticated tools do they actually use to figure out a storm's path and its strength? It's a fair question, and the answer, as you'll see, involves some pretty impressive scientific work, you know.

So, if you've been curious about the technology helping to protect communities from tropical cyclones, you're in the right spot. We're going to take a look at the main hurricane models NOAA uses, especially their newest and most advanced one. It's really quite fascinating to see how they bring all that information together to help us stay safe, you know, when the weather gets a bit wild.

The New Generation: HAFS Takes the Lead
A Suite of Powerful Tools: Beyond Just One Model
Fueling the Forecasts: Data and Supercomputing
How Models Evolve and Improve
- Measuring Model Performance
- The Ongoing Quest for Better Predictions
Frequently Asked Questions

The New Generation: HAFS Takes the Lead

For a long time, NOAA has been working to make hurricane forecasts even better, and that effort has led to some pretty big steps forward. The latest and most significant development in their forecasting toolkit is, arguably, the Hurricane Analysis and Forecast System, or HAFS. This model is a real cornerstone of their current operations, you know, for predicting these intense storms.

What is HAFS?

HAFS, which stands for Hurricane Analysis and Forecast System, is NOAA's newest hurricane model, and it's also their flagship model for tropical cyclone predictions. It was put into operations on June 27, 2023, so it's relatively new to the operational scene. The goal for HAFS is to give very dependable and skilled guidance on both the path a tropical cyclone will take and how strong it will get, which is really important, you know, for public safety.

This model is seen as the starting point for the next generation of hurricane forecast modeling. Its initial operational capability was expected to replace the Hurricane Weather Research and Forecast (HWRF) model, which was a significant model in its own right for many years. HAFS, pretty much, represents a big leap forward in how NOAA approaches hurricane prediction, so.

Why HAFS Matters for Forecasts

The introduction of HAFS has already shown some very positive results. For example, NOAA’s newest hurricane model, the Hurricane Analysis and Forecast System (HAFS), advanced the accuracy of hurricane forecasts and supported community preparedness actions during the 2024 Atlantic season. This means that with HAFS, forecasters have better information to warn people, and communities can get ready more effectively, you know, for what's coming.

When a storm like Hurricane Milton poses an extremely dangerous threat, say, to Florida, including storm surge, destructive winds, and flooding rainfall, having a model like HAFS can make a real difference. It helps officials track winds, understand the forecast cone of uncertainty, and issue alerts. This is all about safeguarding communities in harm’s way, which is, you know, a very important job.

The Journey to HAFS

The development of HAFS wasn't an overnight thing; it was a result of diligent efforts and unparalleled support from NOAA’s Hurricane Forecast Improvement Project (HFIP), along with close collaborative research work. Sundararaman “Gopal” Gopalakrishnan, Ph.D., is the senior meteorologist and leader of the modeling team that developed this new system. It's a big team effort, really, to bring such a powerful tool to life.

As we kicked off the new year, it was a good time to look back on how HAFS advanced the accuracy of hurricane forecasts and supported community preparedness. It ran alongside existing models for the 2023 season, and the plan was for it to eventually replace them as NOAA’s main operational model. This gradual transition helps ensure everything works smoothly, you know, before it takes over completely.

A Suite of Powerful Tools: Beyond Just One Model

While HAFS is the new flagship, it's important to remember that the National Hurricane Center (NHC) and other hurricane offices don't just use one model. They rely on a wide variety of data and numerical models to get the most complete picture possible. It's like having a whole toolbox of different instruments, each good for a specific task, so.

Other Key Mesoscale Models

Before HAFS, and still running alongside it for a time, were other significant models. The Hurricane Weather Research and Forecasting model (HWRF) is one such specialized model developed by NOAA and other research institutions. The HWRF was designed to simulate the entire life cycle of a hurricane, from its formation to its dissipation, with a high level of detail and accuracy. It uses information about surface winds, clouds, and available energy in the atmosphere to analyze how they affect a storm’s behavior, which is, you know, pretty detailed.

Another important model is the GFDL model. This is a full physics model, developed as a research tool at the Geophysical Fluid Dynamics Laboratory, that has become fully operational. With its fine resolution, about 19km, it provides very detailed insights. So, HAFS, HWRF, and GFDL are examples of mesoscale hurricane models that are run on tropical disturbances and storms, giving forecasters different perspectives, you know, on the same storm.

Broader Climate Models

Beyond the immediate hurricane forecasts, NOAA also uses climate models to look at longer-term trends. Models like the CFSv2, CanSIPS, and NMME provide monthly to seasonal forecasts. These aren't for individual storms, but they help scientists understand the general conditions that might favor or hinder hurricane development over a whole season, which is, you know, pretty helpful for planning.

The Role of the National Hurricane Center (NHC)

The National Hurricane Center (NHC) is responsible for issuing watches, warnings, forecasts, and analyses of hazardous tropical weather, including hurricanes. They are the ones who take all the information from these various models and combine it with observations and their own expert judgment to create the official forecasts. The NHC uses many models as guidance in the preparation of official track and intensity forecasts. The most commonly used models at NHC are summarized in tables they provide, which really shows how much data they're looking at, you know, to make those calls.

It's also worth noting that NHC and other hurricane offices use the data to train predictive models and to test advances in model formulation. For instance, an example is a site that archives historical satellite images of storms. This kind of historical data is pretty important for making sure the models learn and get better over time, so.

Fueling the Forecasts: Data and Supercomputing

These powerful models don't just run on their own; they need a constant stream of information and incredible computing power to do their job. It's like a very hungry engine that needs a lot of fuel and a super-fast processor, you know, to crunch all the numbers.

What Data Powers These Models?

There are many environmental conditions that affect the development of a tropical storm and are used in hurricane modeling. This includes things like surface winds, clouds, and available energy in the atmosphere. The HWRF, for instance, uses physical parameterization schemes that incorporate this information to analyze how they affect a storm’s behavior. New dropsonde will be deployed from hurricane hunter aircraft, too, which provides real-time data from inside the storm, which is pretty valuable, you know.

However, it's also true that models have their limits. For example, some models do not model the impacts of waves on top of the surge, account for normal river flow or rain flooding, nor do they explicitly model the astronomical tide, although operational runs can be run with different water levels. This means forecasters still need to consider other factors when issuing warnings, you know, beyond just what the model shows.

The Supercomputer Advantage

To run these incredibly complex models, NOAA needs some serious hardware. Today, NOAA inaugurated the nation’s newest weather and climate supercomputers with an operational run of the national blend of models. These new supercomputers, first announced in February 2020 with a contract award to General Dynamics Information Technology (GDIT), provide a significant upgrade to computing capacity, storage space, and interconnect speed. This enhanced computing power is pretty much what allows models like HAFS to run quickly and produce detailed forecasts, so.

Accessing Model Information

For those interested in the raw output or even the visual representations, NOAA makes this information available. Output images from the NOAA/NWS models can be found through NCEP's Model Analyses and Guidance (MAG) interface. Raw data from the models can be found through the NOAA Operational Model Archive and Distribution System (NOMADS). This openness allows researchers and the public to look at the same information forecasters are using, which is, you know, pretty cool.

How Models Evolve and Improve

Hurricane forecasting is a field that's always trying to get better. The models themselves are constantly being refined and updated based on how well they perform. It's a continuous process of learning and adjusting, so.

Measuring Model Performance

Scientists regularly look at the skill of various computer model track forecasts for Atlantic named storms, for example, in 2023. This is often compared to a “no skill” model called CLIPER5 that uses only climatology and persistence to make a hurricane track. A "bad model" is one that does worse than the CLP5. The XTRP simply extends the storm’s recent motion out to five days and is always a straight line. This kind of verification provides a general sense of the trends in model performance over time. It's interesting to note how the primary model types have changed over the years; in the early 1970s, statistical (and statistical hybrid) models, along with the simple barotropic SANBAR model, were the primary form of guidance, which is a bit different from today, you know.

The Ongoing Quest for Better Predictions

The field of hurricane modeling is always moving forward. While NOAA's models are central, other entities are also working on advanced forecasting. Google’s AI hurricane forecasting model, for instance, leverages deep learning technology to analyze both historical storm data and current atmospheric conditions. It utilizes neural networks trained on over 50 years of satellite records, ocean temperature datasets, wind speed measurements, and pressure systems. This shows that the pursuit of better hurricane forecasts is a widespread effort, involving many different approaches and technologies, you know, to help keep us safer.

Frequently Asked Questions

What is the newest hurricane model NOAA uses?

NOAA's newest and flagship hurricane model is the Hurricane Analysis and Forecast System (HAFS). It officially became operational on June 27, 2023, and aims to provide more reliable guidance on tropical cyclone track and intensity, so.

How accurate are NOAA's hurricane forecasts?

NOAA continuously works to improve the accuracy of its hurricane forecasts, with HAFS already showing advancements in supporting community preparedness. The National Hurricane Center uses a wide variety of models and data, and they regularly assess model performance against benchmarks to track improvements over time, which is pretty important, you know.

What data does NOAA use for hurricane modeling?

NOAA's hurricane models use a broad range of environmental conditions, including surface winds, clouds, and atmospheric energy. This data comes from various sources, including observations, satellite records, and specialized deployments like dropsondes from hurricane hunter aircraft, to provide a comprehensive picture for the models, you know, to work with.

To learn more about hurricane preparedness on our site, and link to this page understanding storm warnings for more detailed information.

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