NAM vs HRRR. Compare the major regional weather models for North America

NAM and HRRR are the two major regional weather models for the US and North America. This means that when you look at the weather forecast for your favorite spot and activity in this region, you most likely see data from one of these two models. However, there is a logical question: what is the difference between the models, and which one is more accurate? Are there any alternatives? In this article, we will answer it.

NAM vs HRRR: common points

Before talking about the differences, it is important to look at the similarities to understand where we are coming from.

First and most importantly, NAM (North American Mesoscale Forecast System) and HRRR (High Resolution Rapid Refresh) are the two most common regional weather models for the continental United States, Canada, and Mexico. This means that they provide weather forecasts for this country and this continent due to their spatial resolution or grid with a series of points where the weather is predicted, which cover these territories.

The second important similarity is that both models are professional governmental projects, not private or amateurish. This is understandable: to use any major regional models, not speaking about the global ones such as GFS, also American, you need incredibly powerful supercomputers (and knowledge), which private companies and individual meteorologists do not have. Plus, it is very expensive to run a weather model.

This also explains the popularity of these two regional models — being the largest government projects, they have logically become the most widespread.

The source of both models is the National Weather Service (NWS) of the National Oceanic and Atmospheric Administration (NOAA), the main US weather service, with headquarters in Washington, D.C. However, the model is developed in different branches of the organization, so the source of their origin is also one of the differences between them. But we will name them later in the article.

Third, both models produce weather forecasts for all seven main weather elements, namely: general weather conditions (sunny, overcast, and so on), air temperature, precipitation, wind, atmospheric pressure at sea level, relative humidity, and visibility. But each of the models has dozens more advanced elements for the atmosphere, ocean, and other environments. We will name the specific elements later because this is more of a difference between the models.

The fourth thing the two models have in common is that they both produce short-range weather forecasts. This is a type of forecast depending on their duration which equals a period from 12 to 72 hours (from half a day to 3 days). But no more than that.

Fifth, both models are non-hydrostatic, so they use the same equations to predict weather phenomena in the atmosphere. Hydrostatics is a branch of continuum physics that studies fluid equilibrium or the theory of fixed fluid behavior. It also refers to topography. This means that it uses altitude in the forecast, i.e. more accurately takes into account the influence of the terrain on the weather.

In particular, as of June 20, 2006, the NAM model has been running with a non-hydrostatic version of the Weather Research and Forecasting (WRF) model at its core. The same is for HRRR, which has been in operation since 2017.

For comparison, GFS is a hydrostatic model. Instead of altitude, it uses atmospheric pressure (which as we know changes with altitude). This means that compared to non-hydrostatic models they perform worse at the higher resolution of the model grid, i.e. they take the topography into account worse.

This is the end of the main similarities of the models, although you can find other less important ones if you want.

To summarize: NAM and HRRR are two regional weather models from the same part of the world, the United States covering North America. Both models are non-hydrostatic with short-range forecasts for seven major weather elements, including the three main ones: temperature, precipitation, and wind.

NAM weather model forecast for Washington, D. C., US, in the Windy.app for iOS. Maria Oswalt / Unsplash

NAM vs HRRR: differences

NAM and HRRR have a lot in common, but there are even more differences. Let’s look at the main ones in the same way.

Organization of origin and its headquarters

Both models are developed by NOAA but in different divisions. NAM is from the National Centers For Environmental Predictions (NCEP), the US main weather organization, which also makes the GFS global weather model, which is located in Washington, D. C. HRRR is from the Global Systems Laboratory (GSL), one of ten NOAA's research laboratories, which is located in Boulder, Colorado.

With the first everything is more or less clear — there are such major weather services in every country in the world. They are also the sources of the main global and regional models.

With the second one, everything is more interesting. According to NOAA, the idea of GSL is that their "research improves environmental prediction models, develops state-of-the-science decision support tools and visualization systems, and uses high-performance computing technology to support a Weather-Ready Nation."

They are also "committed to increased diversity equity, inclusion, and accessibility as well as a strong foundation for career growth."

GSL's research serves the nation in the following main fields: 1). Public safety, where they "help emergency managers respond to weather threats quickly", 2). Aviation, where they "assist the Federal Aviation Administration (FAA) in reducing air traffic delays and increase safety, 3). Energy, where GSL’s weather models "enable the energy industry to plan for the variable nature of wind and solar energy", and 4). Fire weather, where "the decision support systems and smoke models developed by GSL help with wildfire operations.

The official websites of these organizations are Ncei.noaa.gov, and Gsl.noaa.gov. The weather models pages at the sites are Emc.ncep.noaa.gov and Rapidrefresh.noaa.gov. The main NWS and NOAA sites are Weather.gov, and Noaa.gov.

Spatial resolution

The NAM model's spatial resolution is 12 km (7.4 mi) while the HRRR model has 3 km (1.8 mi). Does it mean that the bigger number means the more accurate forecast? Not at all. More: it means exactly the opposite.

Spatial resolution is the distance between two points of the weather model grid. Hence the smaller the number, the better the resolution, and hence the quality of the forecast. It is like the pixels on your computer monitor, smartphone, or photo camera.

So the spatial resolution, the main parameter of any weather mode, is 4x times better in HRRR than in NAM. That's where the model's name comes from — High-Resolution Rapid Refresh.

However, the word "mesoscale" in the name of the NAM model means more or less the same. Mesoscale (as well as medium or regional meteorology) is one of the four main scales of meteorology, which studies medium-scale weather phenomena from a few kilometers to several hundred and a thousand or two, but usually not more, that last from one day to several days to a week. For example, these are weather fronts.

So both models are mesoscale. Anyway, from this, we can make a preliminary conclusion that the HRRR model is more accurate. But we will talk more about that right away.

Forecast depth

Both models give short-range weather forecasts, but with different durations. The forecast by NAM is available for 61 hours or 2.5 days, and by HRRR — for 36 hours or 1.5 days. By this, the second most important parameter of weather models, NAM, turns out to be the better model, because it gives a longer forecast — almost twice as long.

Forecast step

The forecast step is the period of the weather forecast within one day or how many hours ahead you can see the forecast. With NAM, it is 3 hours, while HRRR has 1 hour. That is you can see the forecast of the first model with a 3-hour frequency: for 6 am, 9 am, 12 am, and so on, and for the second model — with a 1-hour frequency: for 6 am, 7 am, 8 am, and so on.

The forecast for each hour is also more convenient. HRRR also wins here but with a small caveat, which you will also learn below.

Expected update frequency

Weather models produce weather forecasts from one to several times a day. This is called "update frequency" or "expected update". Accordingly, the more often it is updated, the fresher the forecast in your weather application or on your favorite website.

The NAM model is updated four times a day or every 6 hours at 00:00, 06:00, 12:00, and 18:00 UTC. This means, for example, that the 15 o’clock forecast you see was made early in the day and will be updated only once more during the day. The HRRR has a much, much better figure — 24 times a day or every hour. These words mean that it provides a forecast based on 3 km (1.8 mi) weather radar data — the unique advantage of HRRR. It is assimilated every 15 min over a 1 h period, "adding further detail to that provided by the hourly data assimilation from the 13 km radar-enhanced Rapid Refresh (RAP) — the base of the model, which comes from the same National Centers for Environmental Prediction (NCEP), which makes the NAM and GFS weather models.

Hydrostatics is also one of the reasons for the frequency of model updates. Non-hydrostatic models like these two require more computation, while hydrostatic models require less, so NAM is updated half as often as GFS — twice a day vs. four times a day for the latter. (But HRRR is out of this rule.)

So this is another preliminary argument in favor of the HRRR as being more accurate than NAM.

So, those are the main differences between the two models.

To summarize: NAM and HRRR are models from two different weather services — NCEP and GSL (but of the same organization, NOAA). NAM resolution is 4x times smaller than HRRR — 12 km vs. 3 km. The first is updated with the standard frequency for weather models — twice a day, the second has the highest update frequency of all weather models — every hour, due to weather radar's data. So, anyway, you can see the HRRR forecast for every hour — three times as often as GFS, whose forecast step is also standard 3 hours.

But there are other differences. Several additional ones will be better understood by experts in meteorology. Let’s also name the main ones.

In addition to the basic weather elements, the models provide a forecast for dozens of advanced elements that are not found in general weather forecasts. For example, NAM, predicts show depth, one of the most important parameters for skiing and other winter sports and outdoor activities.

Multiple grids

According to NOAA, "NAM generates [not just one but] multiple grids (or domains) of weather forecasts over the North American continent at various horizontal resolutions. HRRR has one general grid.

Advanced weather elements

Each grid in NAM "contains data for dozens of [basic] weather parameters, including temperature, precipitation [and others, as well as advanced ones, such as] lightning, and turbulent kinetic energy. NAM uses additional numerical weather models to generate high-resolution forecasts over fixed regions, and occasionally to follow significant weather events like hurricanes."

However, according to GSL, the "HRRR is the only hourly updating model that can predict individual thunderstorms on a 3 km grid over the U.S." It is also a cloud-resolving and convection-allowing weather model.

Weather radars

As has become clear, the main difference between HRRR and NAM is that it uses the Rapid Refresh (RAP) model system, which according to NOAA, "ingests data from a network of ground and satellite-based sensors, radar, and aircraft. So it is a storm-scale model."

Let’s summarize the additional differences of the weather models as well: although NAM and HRRR both deal with similar advanced weather phenomena, at the expense of their other features, they predict them differently and with different accuracy, including radar in the latter. At the same time, NAM uses multiple weather grids.

HRRR weather model forecast for Boulder City, Colorado, US, in the Windy.app for iOS. Jon Cartagena / Unsplash

NAM vs HRRR: accuracy

From all of the above, could one conclude that the HRRR is more accurate and better overall than NAM? In general, yes. The former surpasses the latter in the main parameter of the accuracy of weather models — the resolution, as much as four times (3 km vs. 12 km). The HRRR is also updated 6x more frequently — every hour (24 times a day) versus once every 6 hours (4 times a day). You can't argue with all these numbers, not to mention the use of the radar, the most accurate weather prediction tool available today, for short periods of minutes and hours.

However, you should consider that the HRRR is a special weather model with a shorter forecast (1.5 days vs. 2.5 days for NAM) for an even more accurate prediction of certain weather events, especially severe weather.

Hence the duration of the forecast is the main advantage of NAM, as well as its resolution, especially in comparison with the main US global model GFS (27 km).

In other words, in general, both models are more accurate for their region compared to the global models, but the HRRR clearly wins over the NAM due to the above parameters, and therefore it can be considered more accurate. This, however, should be confirmed in practice for your particular case — the region of the United States, given that it is a large country, the local terrain, the time of year, the sport you play, and others.

NAM vs HRRR: alternatives

NAM and HRRR are two weather models which cover almost all needs of ordinary weather users and experts in the US and North America, but they are not 100% universal due to their peculiarities and the complexity of weather forecasting in general. From this, it’s logical also to ask about alternative models in case you can’t find the information you need in one of them, or they don’t suit you for other reasons.

The answer: yes, and no. There are alternatives, but with some peculiarities:

GEM (Global Environmental Multiscale Model). In North America, this model is often referred to as the CMC (Canadian Meteorological Centre) model. Due to its resolution and specialization, it is the most accurate model for forecasts in Canada. It has two versions: regional with a 2.5 km resolution for Canada, and global with 25 km. Learn more about it at Collaboration.cmc.ec.gc.ca, and En.m.wikipedia.org.
COAMPS (Coupled Ocean Atmosphere Mesoscale Prediction System). It covers certain regions bordering the United States and it is run by the Naval Research Laboratory (NRL) of the Coast Observing Research and Development Center (CORDC) of the American Navy. It has a 12 km resolution. Learn more about it at Cordc.ucsd.edu, and Journals.ametsoc.org.

As a result, none of the alternative models covers the United States, which occupies most of North America. Therefore, they cannot be regarded as full-fledged alternatives to NAM and HRRR. In other words, these regional models have no full alternatives. But they may be more accurate than NAM and HRRR for other parts of North America, which must also be tested in practice. They also offer a comparable resolution.

NAM vs HRRR: comparison table

So, we have described in detail the two major regional weather models for North America and tried to find alternatives for them. Let’s summarize their main similarities and differences in the table (to get larger image, simply right-click on it and open it in the new tab):

Regional weather models for North America comparison: NAM vs HRRR / Windy.app

Where to get the weather forecast from NAM and HRRR models?

You can find weather forecasts from both major regional models for more than hundreds of thousands of spots for various outdoor activities in the US and North America in the Windy.app application.

To do this, on the app’s Home screen or the Weather Map, find your home, favorite, or nearest spot and go to its page. You can also do it visually by icons on the same map.

Outdoor spots search in the Windy.app for iOS

Visual outdoor spots search by icons on the Weather Map in the Windy.app for iOS

Select one of the models in the slider below the wind rose and get a forecast with a set of basic and advanced weather elements.

NAM weather model on the Spot screen in the Windy.app for IOS

HRRR weather model on the Spot screen in the Windy.app for IOS

To find out which weather parameters are available from each of the models, go to Weather Profiles via the icon to the right of the model slider. Scroll to the Advanced menu section. In particular, in the Windy.app you will get the following parameters:

NAM

Weather condition
Air temperature
Precipitation
Wind direction: cardinal and degrees
Wind speed
Wind gusts
Cloud coverage
Snow depth

HRRR

Weather condition
Air temperature
Precipitation
Wind direction: cardinal and degrees
Wind speed
Wind gusts
Cloud coverage

NAM weather elements in the Windy.app for iOS

HRRR weather elements in the Windy.app for iOS

To get the update time of the models, scroll down the forecast table and open the dedicated field. Note: in the Windy.app both models are updated twice a day.

Weather models update time in the Windy.app for iOS

Another extremely useful function of the application which resonates very much with the theme of this article is to compare the forecasts of these and other models on the same chart. To do this, click on Compare in the slider with the models. The feature is in the Pro version of the app.

Comparing NAM and HRRR, and other models in the Windy.app for iOS

Finally, you can get the forecast for the whole region on the Weather Map, which is logical in the case of regional weather models, because spots don’t give it, covering only some places.