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In order to contrast temperature patterns in the tropics with those in the middle latitudes, allow me to briefly employ an analogy. It might sound a little bizarre, but I'm going to liken temperatures in the tropics and middle latitudes to human personality types. One theory of human personality defines two types -- Type A and Type B (opens in a new window). In a nutshell, people with a "Type A" personality are "high-strung," obsessed with details and organization, and somewhat rigid. "Type B" personalities on the other hand, are more laid back, "go-with-the-flow" types. They're less stressed out about organization and details.

If I could label the middle latitudes with a human personality, I would probably rate them "Type A". Recall that the middle latitudes mark the region where advancing warm and cold air masses invariably collide. Like a typical "Type A" personality, the middle latitudes seem to be obsessed with organization, dutifully structuring the lower troposphere into narrow zones of relatively large temperature gradients (cold, warm, and stationary fronts). The middle latitudes are constantly trying to manage their temperature gradients in an attempt to be as "organized" as possible.

In contrast, the tropics have a "Type B" personality. As a general rule, horizontal temperature gradients are weak and much more "laid back". To understand why, let's start with the short background video below. In case you're wondering, the values of absorbed solar and emitted infrared radiation plotted in the video represent latitudinal (sometimes called "zonal") averages.

The Tropics and Earth's Energy Budget (2:18)

We can confirm the great emission of infrared radiation from the tropics discussed in the video by viewing plots of outgoing longwave radiation (OLR). For the record, OLR is most intense where surface temperatures are the greatest, such as hot subtropical deserts (the Sahara, for example) during summer. In contrast, OLR is the least intense where it's colder, either because the ground is cold or because deep convection is present. That's because cloud tops in areas of deep convection are high and cold and thus weakly emit longwave (infrared) radiation.

If we look at the long-term average of OLR across the globe (below), we can see the general pattern described in the video. The blazing hot Sahara Desert in northern Africa is clearly an area of high OLR values (some of the highest on Earth, denoted by dark purples), while other tropical areas frequently characterized by deep convection (like the Amazon River Basin in northern South America) have lower values. OLR charts have lots of other practical applications for studying trends in cloudiness and rainfall over the tropics (if you're interested in checking out the variety of OLR products available, check out the Earth System Research Laboratory page of OLR plots (opens in a new window)).

Credit: Earth System Research Laboratory

The relatively large losses of infrared energy to space over the tropics only partially offset major-league solar heating, resulting in a broad surplus of energy (shaded in red in the graph in the video) that varies little with latitude between 30 degrees north and south. This relatively even distribution of surplus energy across the tropics accounts, in part, for the general lack of moderate to strong horizontal temperature gradients in the tropical troposphere.

One other reason for the generally weak temperature gradients at low latitudes is that the water covers approximately 75 percent of the tropics. That means that the uniform surplus of energy in the tropics gets distributed over large expanses of water, thus further limiting opportunities for strong temperature gradients to form (cold air traveling over relatively warm ocean waters gets rapidly modified).

The image below represents the long-term average of annual surface air temperatures across the globe. I point out that there are indeed temperature gradients between tropical land masses and surrounding oceans, but the overall pattern of temperature gradients in the tropics is weak compared to those at higher latitudes. Now I readily admit that any annual average in temperature tends to "wash out" strong signals of gradients in winter, so if you toggle the image slider below, you can see global surface temperatures for a single day in late January.

On this winter day, sharp temperature gradients existed over eastern North America, for example, on the fringe of a continental Arctic air mass. Now, compare them to the flabby gradients over the tropics. No contest, wouldn't you agree? Notice that there are some sharper gradients along the outer fringes of the tropics near 30 degrees north. These larger gradients near 30 degrees are not unusual, given that Arctic air masses drive farther south in winter (occasionally into the fringes of the tropics). In the heart of the tropics, however, gradients are weak by almost any standard.

The lack of large temperature gradients does not stop at the surface, of course. At 500 mb, for example, the lack of strong temperature gradients over the tropics is striking compared to the middle latitudes (check out the annual climatology of 500-mb temperatures across the globe below). So, with regard to temperature gradients, the tropical troposphere has a completely different personality than the middle latitudes.

Credit: Earth System Research Laboratory

I hope the analogy to personality types helps you to understand the different nature of temperature patterns in the tropics and middle latitudes, but now it's time to get a bit more formal. How do we formally describe these different "personalities" of the middle latitudes and the tropics? Meteorologists formally refer to the "Type A" middle latitudes as baroclinic and the "Type B" tropics as barotropic. In the broadest terms, a baroclinic atmosphere is one where horizontal temperature gradients prevail. The middle latitudes, for example, are highly baroclinic during winter, when large horizontal temperature gradients often set the stage for strong temperature advection (opens in a new window). A barotropic atmosphere, on the other hand, is one in which temperature advection is pathetically weak. In the presence of wind, that means that horizontal temperature gradients must be very small. For all practical purposes, the tropics are bereft of horizontal temperature gradients, so "barotropic" best describes the tropical atmosphere.

Recall from the video discussing absorbed solar and emitted infrared radiation versus latitude that, while the tropics run a surplus in energy, the middle and polar latitudes run a deficit. Thus, to balance the ledger of the earth-atmosphere system, it is pretty obvious that there must be a transfer of heat energy poleward from the tropics. This transfer is accomplished by the meridional transport (opens in a new window) of heat energy by the atmosphere and the oceans. You may already be familiar with some mechanisms for this transport, such as the Gulf Stream (opens in a new window) (an ocean current that conveys heat energy northward from low latitudes).

As far as atmospheric transport of heat energy goes, there are several mechanisms working to export heat energy out of the tropics, which we'll explore in later lessons. For now, though, recall that large mid-latitude cyclones are very effective at transporting warm air northward and cold air southward with their broad circulations. Given the large north-south temperature gradients that prevail in the middle latitudes during the cold season, the large impacts on regional temperatures from strong advection qualify mid-latitude cyclones as "big business" in the world of heat transport. Is the same true for tropical cyclones? Not really. Tropical cyclones transport some heat energy and moisture from the tropics to higher latitudes, but their overall contribution pales in comparison to other transport mechanisms. If you're interested, check out the Explore Further section below for more on this topic and another peculiarity that arises from the barotropic nature of the tropics. Otherwise, check your knowledge of the basics of tropical temperatures in the Quiz Yourself section below before you begin exploring another aspect of the "Type B" behavior of the tropics on the next page.

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Just as the tropics display a "Type B" personality with respect to temperatures, they generally maintain that same personality when it comes to pressure. In the tropics, pressure gradients tend to be much more relaxed than they do in the "Type-A" middle latitudes (resuming our analogy from the previous page). 

Indeed, the relatively small temperature gradients over the tropics go hand in hand with relatively small pressure gradients, just as the larger temperature gradients in the mid-latitudes go along with larger pressure gradients there. To get a feel for the relaxed pressure gradients and other key aspects of pressure patterns in the tropics compared to the mid-latitudes, check out the short video below.

Tropical Pressure Patterns (2:32)

The overwhelming message from the video is that pressure gradients are typically weak across the tropics, while the main "flies in the ointment" seem to be tropical cyclones. Indeed, tropical cyclones do something that is unheard of in the middle latitudes: They form in an environment bereft of large temperature gradients yet somehow develop very large pressure gradients around their center. We'll explore this conundrum a little later in the lesson.

Of course, the small pressure gradients throughout the tropics also mean that changes in surface pressure with time at any given location are usually puny compared to the larger increases and decreases that regularly accompany the approach and passage of mid-latitude high- and low-pressure systems. In the equable tropics, pressure patterns can persist for very long periods (weeks and even months). Yet, almost mysteriously, there is a regular daily rhythm of changes in surface pressure that meteorologists detect in the tropics. If you're intrigued, check out the "Explore Further" section at the end of the page.

The relaxed gradients in the tropics don't stop at the surface. The height patterns on constant pressure surfaces over the tropics are similarly relaxed. Consistent with the general lack of temperature gradients at 500 mb over the tropics that we covered previously, note the absence of strong gradients between 30 degrees latitude (north and south) on the chart of long-term mean 500-mb heights below. Height contours on the other mandatory pressure levels in the tropical troposphere show a similarly relaxed pattern.

Credit: Earth System Research Laboratory

Since the pressure gradient force is a primary driver of wind speed, you might think that the winds are almost always weak in the tropics (outside of tropical cyclones, that is), with the weak pressure gradients at the surface and aloft. But, that's far from the truth! To help you visualize the fact that many places in the tropics are quite breezy, despite weak surface pressure gradients, I'm going to introduce a new type of plot -- the wind rose. Wind roses display the observed frequency of wind directions (and sometimes speeds) at a particular location. On the left below is a histogram displaying frequencies of observed wind speeds (in meters per second) at an ocean buoy moored at 8 degrees South, 95 degrees West (opens in a new window) during a single year. On the right is the corresponding wind rose for the buoy, which shows the frequency of observed wind directions during the same year.

Credit: David Babb @ Penn State is licensed under CC BY-NC 4.0 (opens in a new window)

From these two images, we can quickly get two important messages. First, wind speeds at the buoy were between five and nine meters per second (roughly 10 to 20 mph) the vast majority of the time, which hardly constitutes "weak" winds. Second, the direction from which the wind blew during the year was remarkably consistent. To get your bearings with the wind rose, note that each concentric ring represents a ten-percentage point increase in the relative frequency of the observed wind direction. Thus, the daily mean wind direction of 130 degrees (from the southeast) occurred on nearly 45% of the days, and the daily mean wind direction of 140 degrees occurred on about 28% of the days! The wind rose clearly demonstrates that winds retained their overall southeasterly direction for almost the entire year (and didn't deviate much from 130 degrees). Small variations in wind direction and breezy conditions are fairly typical in tropical locations because of the famous belt of "trade winds," (opens in a new window) which we'll cover formally in a later lesson.

Many wind roses that you'll encounter also include wind-speed data right on the wind rose plot. The short video below walks through an example of how to interpret such wind roses (a Key Skill from this section). The wind rose in the video is from a mid-latitude location; note how much more variable wind directions are compared to our example from the tropics above.

Wind Roses (3:08)

I strongly recommend taking some time to practice extracting information from wind roses (you can start with the "Key Skill" section below). Wind roses can provide lots of practical information. For example, consulting meteorologists use wind roses when they work on the design of airports (runways should be built to avoid strong crosswinds), and skilled forecasters regularly use wind roses when studying the climatology of a particular location. After you're comfortable with interpreting wind roses (and check out the "Explore Further" section, if you wish), you'll be ready to examine another difference between the tropics and the middle latitudes -- the structure of mid-latitude cyclones versus the structure of tropical cyclones.

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Up to this point, you've seen the generic phrase "tropical cyclone" used to describe the low-pressure systems that form over warm tropical seas. However, as you're about to find out, naming and classifying tropical cyclones is somewhat complicated. Before we get into how tropical cyclones are named, let's look at the areas where tropical cyclones tend to form. Do they form just anywhere in the tropics? Not really. As you can see from the image below, the breeding grounds and regions where tropical cyclones typically track can be boiled down to seven areas:

1. Atlantic Basin (the northern Atlantic Ocean, the Gulf of Mexico, and the Caribbean Sea)
2. Northeast Pacific Basin (from Mexico to the International Dateline)
3. Northwest Pacific Basin (from the International Dateline to Asia, including the South China Sea)
4. North Indian Basin (includes the Bay of Bengal and the Arabian Sea)
5. Southwest Indian Basin (from Africa to about 100 degrees east longitude)
6. Southeast Indian/Australian Basin (100 degrees east longitude to 142 degrees east longitude)
7. Australian/Southwest Pacific Basin (142 degrees longitude to about 120 degrees west longitude)

Of these seven areas, the Northwest Pacific and Northeast Pacific basins tend to be the busiest, as this map of global tropical cyclone tracks (opens in a new window) over a 30-year period suggests. Meanwhile, some areas in the tropics are nearly entirely free of tropical cyclones. While tropical cyclones can form outside of the seven areas listed above, it happens relatively infrequently. For example, the southern Atlantic Ocean (south of the equator) is rarely home to tropical cyclones.

With tropical cyclones in any basin possibly impacting multiple countries, how do forecasters keep tabs on all of them? The World Meteorology Organization created a branch called the Tropical Cyclone Programme (TCP) to ensure that all countries bordering and within each basin are adequately prepared for the threat posed by tropical cyclones. To accomplish this goal, the TCP's primary responsibility is to establish a nationally and regionally coordinated network of forecasting centers. To define areas of responsibility, they partitioned the tropical-cyclone basins and assigned Regional Specialized Meteorological Centers (RSMCs), which issue the official forecasts and advisories for their respective basins (see figure below).

Although each RSMC is responsible for issuing the official forecasts and advisories for their jurisdiction, there can be multiple cities which issue warnings for various countries under the umbrella of a single RSMC. For example, the official advisories and forecasts for the Atlantic Basin come from the National Hurricane Center in Miami, but the Canadian Hurricane Centre in Dartmouth, Nova Scotia issues warnings when tropical cyclones threaten Canada, using the National Hurricane Center's products as their basis. Keep in mind that Atlantic hurricanes and tropical storms moving northward along the East Coast can pose a significant threat to the Canadian Maritimes (the provinces of New Foundland, Nova Scotia, New Brunswick, and Prince Edward Island).

Credit: World Meteorological Organization

In addition to the Regional Specialized Meteorological Centers and Tropical Cyclone Warning Centers on the map above, the Joint Typhoon Warning Center (JTWC) is an additional warning center and serves as a joint effort between the United States Navy and Air Force. JTWC was founded in 1959 in Guam, but has since moved to Pearl Harbor, Hawaii. While JTWC does not issue official public forecasts, they keep tabs on tropical cyclones globally for U.S. Department of Defense interests. I realize that the acronyms for all these forecast centers might seem a bit like alphabet soup, but if you're interested in exploring them more, the links in the Explore Further section toward the end of the page may be of interest.

Now that we know who's keeping track of tropical cyclones around the globe, we can delve into how they keep track of them. As you're about to see, standards vary around the globe. For starters, forecasters often have their eyes on clusters of showers and thunderstorms across the tropics (often called "tropical disturbances"). Tropical disturbances do not have closed circulations and are not formally tropical cyclones; however, by convention in the U.S., tropical disturbances that have the potential to develop into tropical cyclones are dubbed "invests." Each invest is tagged with a number from 90-99 along with a capital letter, which corresponds to the tropical basin where it's located (see the table below for the letters that correspond to each basin). Forecasters start with the number 90 and sequentially progress to 99, and then start over again at 90. So, for example, Invest 99L in the Atlantic Basin would be followed by Invest 90L, and so on.

If the tropical disturbance with organized convection develops a closed cyclonic circulation in its surface wind field, it becomes a tropical depression as long as its maximum sustained wind speeds (opens in a new window) are less than 34 knots (39 miles per hour). Note that different definitions of "sustained" (as described in the link) can lead to different storm classifications in different basins. Tropical depressions are formally considered tropical cyclones, and at this point The Joint Typhoon Warning Center, Central Pacific Hurricane Center, and the National Hurricane Center routinely assign a new number to go along with the letter referring to the basin of origin. For each season in each basin, the digits start at "01" and then increase by one for each successive depression that forms. Since the capital letter refers to the basin of origin, the letters are not changed if tropical cyclones cross 140 or 180 degrees longitude. I should note, however, that depressions in the Atlantic Basin are an exception. When a depression is classified in the Atlantic, the National Hurricane Center simply refers to it by its number ("One", "Two", etc.) and the letter "L" gets dropped from the designation.

Once a tropical cyclone reaches sustained wind speeds of at least 34 knots (39 miles per hour), it becomes a tropical storm and receives a name (more on the naming of tropical cyclones in a bit). Tropical cyclones retain their tropical storm status as long as their maximum sustained winds remain between 34 knots and 63 knots. Once a tropical cyclone reaches maximum sustained winds of at least 64 knots (74 miles per hour), it loses its "tropical storm" label, and earns one of the classifications in the table below, depending on the basin in which the storm is located. At times, I may generically refer to "hurricanes" in the text, but keep in mind that such references also include strong tropical cyclones that go by various labels in basins around the world.

Of course, all "strong" tropical cyclones (hurricanes, typhoons, etc.) are not created equal. Some are much more intense than others. In the Atlantic and Northeast Pacific basins, forecasters use the Saffir-Simpson Hurricane Wind Scale (opens in a new window) to further classify a given hurricane. Hurricanes classified as "Cat 3", "Cat 4", or "Cat 5" (all hurricanes with maximum sustained winds of at least 96 knots, or 111 mph) qualify as major hurricanes. Although major hurricanes make-up only 21% of the hurricanes that hit the United States, these fierce storms account for over 83% of all the damage from landfalling hurricanes. For the record, Australian forecasters, rank tropical cyclones a bit differently (opens in a new window).

Other basins also have different descriptors for extremely intense tropical cyclones. In the Northwest Pacific Basin, for example, the particularly descriptive classification of "super typhoon" is used once a typhoon's maximum sustained wind speed reaches at least 130 knots (more than twice the minimum typhoon wind speed). For some interesting tidbits on a few memorable super typhoons, check out the Explore Further section below. In the North Indian Ocean, meanwhile, severe tropical cyclones that attain maximum sustained winds of at least 130 knots graduate to super cyclonic storm. Before you finish up this section, try your hand at the Quiz Yourself tool toward the end of the page to make sure you've got the basics of classification conventions.

The Name Game

There's a checkerboard history behind the naming of tropical cyclones in the various basins around the world. If you're interested in the history of naming tropical cyclones, I encourage you to check out the corresponding section within Explore Further below. The reason why tropical cyclones get named, however, is pretty straightforward. The practice of naming tropical cyclones ensures clear, unambiguous communication between forecasters and the general public when forecasts, watches, and warnings are issued. At any given time across the globe (or even within a single tropical basin) there can be multiple tropical cyclones present at any one time. As an extreme example, the satellite image from September 14, 2020 (below) shows a whopping five named storms present in the Atlantic Basin!

Credit: NOAA

Without the practice of naming tropical storms, deciphering forecasts for multiple active storms in a basin could be a real mess -- sifting through coordinates or other technical descriptions of a storm's location. In the end, using names is much simpler for the general public, so let's get to the (not so simple) business of how storms are named. In the Atlantic and eastern Pacific, the World Meteorological Organization and National Weather Service (NWS) have used lists of alternating male and female names in alphabetical order to christen storms since 1979.

I should point out that any year that the alphabetical list of male and female names is not long enough to accommodate all the named storms in a season, the National Hurricane Center turns to a supplemental list of names; however, prior to 2021, the standard was to use letters of the Greek Alphabet (Alpha, Beta, Gamma, Delta, etc.) to name storms once the original list of names had been exhausted. Use of the Greek Alphabet to name storms only occurred twice (2005 and 2020).

For Central Pacific storms, the Central Pacific Hurricane Center uses its own list of names of Hawaiian origin. Because not many tropical cyclones form in the Central Pacific, they don't restart the list from the beginning each year, and instead they just keep using the same list until all the names have been used. When they reach the end of one list, they simply begin with the first name on the next list.

Meanwhile, in the northwest Pacific Basin, since the year 2000, the World Meteorological Organization has used names which are, for the most part, not male or female names. Instead, most names on the list refer to flowers, animals, birds, trees, or even foods, etc. Others are simply descriptive adjectives. Each name on the list is contributed by a participating nation within the basin. The names are not used in alphabetical order like in the Atlantic and eastern Pacific, however. Instead, the contributing nations are listed in alphabetical order and this ranking determines the order that the names are assigned.

It's important to note, however, that the established lists from the World Meteorological Organization are not universally used for storms in the northwest Pacific. The Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA) assigns Filipino words as storm names when storms threaten the Philippines so that locals can easily remember them and communicate about the storm. For example, when Super Typhoon Haiyan (opens in a new window) made landfall in the Philippines as one of the strongest tropical cyclones on record at the time, Haiyan (which is from the Chinese for "petrel" -- a type of seabird) was known as "Yolanda" in the Philippines. So, be aware that you may come across two names for some storms in the northwest Pacific Basin.

Finally, in the North Indian Ocean, tropical cyclones weren't named from a traditional list until 2004. Prior to that year, conventions for identifying storms and keeping historical records were somewhat awkward (more in Explore Further). With regard to name selection, eight countries belonging to the WMO Tropical Cyclone panel for the North Indian basin contributed eight names each, which were tabulated into eight columns. In each column, one name from each country appeared, with the names listed in the order determined by the alphabetized contributing nations (the same convention as in the Northwest Pacific basin). You can see the lists of names for tropical cyclones in the North Indian Ocean and all other tropical basins (including basins not covered in-depth here) on the World Meteorological Organization's page of tropical cyclone names (opens in a new window), if you're interested.

An average of approximately 85 named tropical cyclones form each year worldwide -- a small number compared to the hundreds and hundreds of cyclones that parade across the middle and high latitudes each year. Yet, the attention that meteorologists focus on tropical cyclones sometimes seems disproportionately great. That's because strong tropical cyclones can cause staggering losses of life and property. Next up, we'll compare tropical cyclones with mid-latitude cyclones. Not surprisingly, there's a world of difference between them!

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With the great potential for loss of life and property posed by tropical cyclones, they certainly garner great attention from weather forecasters and the public at large. But, why do powerful tropical cyclones more frequently steal national and international headlines, while mid-latitude cyclones rarely do? The first reason is likely that mid-latitude cyclones are more numerous. Hundreds of them trek across the globe each year. Meanwhile, only about 85 tropical cyclones develop each year.

Secondly, a tropical cyclone can attain a much greater intensity in terms of both sea-level pressure and wind speed (some even call hurricanes the "kings" of all low-pressure systems). For example, the most intense tropical cyclones can have sea-level pressures below 900 mb. Typhoon Tip (1979) had the all-time lowest at 870 mb, but other storms such as Hurricane Wilma (2005) and Hurricane Melissa (2025) have had central pressures below 900 mb. On the other hand, the sea-level pressure at the center of a mid-latitude cyclone rarely drops below 950 mb. For example, the famous Superstorm of 1993 (aka the "Storm of the Century") (opens in a new window), had a central pressure of 963 mb at its peak.

With these observations in mind, a natural question might be, "Why do strong tropical cyclones often attain sea-level pressures that are notably lower than those associated with mid-latitude cyclones?" While both types of cyclones are low-pressure systems, the answer to that question can found by examining the differences in structure and strengthening mechanisms characteristic of each type of low-pressure system. For starters, let's review the process of self-development that mid-latitude cyclones undergo in the short video below.

Self-Development of Mid-Latitude Cyclones (1:49)

The positive feedback loop described in the video continues uninterrupted until the late stages of occlusion, when the low moves back into the cold air (away from the baroclinic zone) and upper-level divergence over the low weakens (the low starts to "fill" -- surface pressure rises). But, in a nutshell, the whole process hinges on temperature gradients, the resulting temperature advections, and their connection to the magnitude of the divergence aloft. The divergence aloft (which is greater than the magnitude of the convergence at lower altitudes) drives the intensity of the mid-latitude cyclone. Also note, however, that the divergence aloft along with low-level convergence drives upward motion over the center of the low. You'll occasionally read or hear explanations that suggest that rising air causes lower surface pressures, but that's just not true. In fact, just the opposite is true. Rising air actually works against the overall reduction in surface pressure.

Recall that rising air cools via expansion, and once clouds and precipitation develop, can also yield evaporational cooling (assuming the atmosphere is not already at saturation). In turn, cooling by forced ascent increases the mean density in the column of air that extends from the ground to the tropopause (low-level convergence and upper-level divergence are still at work). Assuming a nearly hydrostatic atmosphere (opens in a new window), in which the force of gravity is balanced by the upward pressure gradient force, this increase in mean column density serves to add column weight. During the development stage of a mid-latitude cyclone, dominant weight-loss processes, such as net column divergence and warm advection near 200 mb overwhelmingly offset the tendency for air columns to gain weight from adiabatic and moist adiabatic cooling. But my point should now be clear: Rising air tends to make surface pressures higher, not lower. In other words, rising air actually works against the deepening of a mid-latitude cyclone; it serves as a "check and balance" on the overall intensity of the system.

Strong tropical cyclones, on the other hand, don't have this "check and balance" over their centers. Indeed, the predominant vertical motion over the center of a hurricane is downward. It's that downward motion that creates the eye of the storm, as shown in the visible satellite image of Hurricane Melissa from October 27, 2025 below. For the record, the eye is a roughly circular, fair-weather zone at the center of a hurricane. By "fair weather", I mean that little or no precipitation occurs in the eye and an observer looking upward in the eye can often see some blue sky or stars. 

Credit: CSU/CIRA & NOAA

The diameter of the typical eye ranges from approximately 30 to 60 kilometers (about 16 to 32 nautical miles across), but eye diameters as small as four kilometers (approximately two nautical miles) and as large as 200 kilometers (approximately 110 nautical miles) have been observed. For the record, Hurricane Wilma's "pinhole eye" (opens in a new window) was the smallest recollected by forecasters at the National Hurricane Center (two nautical miles) as the storm deepened to 882 mb (the lowest on record in the Atlantic Basin) in 2005.

The "fair weather" in the eye can largely be attributed to the sinking air over the center of the storm. The downward motion in the eye is only on the order of a few centimeters per second, which suggests that the central core of strong tropical cyclones is approximately hydrostatic. Given that the compressional warming in the eye decreases the mean density of the central column of air in the eye (and thus its weight), we can deduce that subsidence contributes to the low central pressures observed in hurricanes. Of course, as the sinking air warms, relative humidity decreases within the sinking parcels, which promotes the clearing observed within the eye.

I should point out however, that the air does not uniformly sink within the eye of a hurricane. Observations taken from the eye of a hurricane often reveal an inversion at an altitude of about one to three kilometers like the one shown on this temperature and dew-point soundings (opens in a new window) retrieved from measurements taken in the eye of a hurricane. The subsidence inversion (opens in a new window) near 850 mb is the telltale sign of downward motion in the eye of a hurricane, but the presence of this inversion means that air does not sink all the way to the ocean surface. The fact that air does not sink all the way to the surface explains why low clouds frequently exist in the eyes of hurricanes (although skies may not be completely overcast).

Regardless of the fact that air does not uniformly sink throughout the entire eye, the compressional warming associated with the subsidence in the eye is one contributor to the "warm core" of a hurricane (by "warm core" I mean that the air columns at the center of the low are warmer than those at the periphery). Meanwhile, deep, moist convection outside of the eye (in the eyewall--the partial or complete ring of powerful thunderstorms around the eye, and spiral bands--relatively long and thin bands of convective rains) also contributes to the warm core.

Credit: National Weather Service

The image above gives you an overall view of the basic structure of a hurricane on radar. Note the spiral bands (yellow, orange, and red shadings) curving in toward the center of the storm, and the innermost spiral band wrapped around most of the eye (the roughly circular area marked by lower reflectivity in greens and blues) to form the eyewall on the northern and western sides. How does the deep, moist convection in the eyewall and spiral bands contribute to the warm core of the storm? Simply put, the air parcels rising in thunderstorm updrafts are initially very warm and moist (due to evaporation from warm tropical seas). As these parcels rise in thunderstorm updrafts, huge amounts of latent heat of condensation are released. Yes, air parcels cool as they rise, but the release of latent heat keeps them warmer than they otherwise would be, which keeps the air within a hurricane warmer than air at the same altitudes outside of the influence of the hurricane. Weaker tropical cyclones are also warm core systems because of the release of abundant latent heat (even though weaker systems don't have eyes--there's no organized compressional warming in the center of the storm).

All in all, within a strong tropical cyclone, the warm core generated by latent heat release and compressional warming can be quite substantial. For example, check out the cross-section of satellite-detected temperature anomalies from Super Typhoon Haiyan at 1726Z on November 7, 2013 (below).

The core of the warm anomaly approximately coincides with the eye of Haiyan, and at its peak in the middle and upper troposphere, temperatures were as much as 7 degrees Celsius greater than the environment surrounding the storm. Outside of the eye, the warm anomaly is weaker, but still spans hundreds of miles across the storm. Given the maximized warm core near the center of the storm, it becomes clear that hurricanes create large horizontal temperature gradients internally (especially at the interface of the eye and eyewall) during their development, even though they initially form in the weak horizontal temperature gradients that characterize the tropics. As you've learned, mid-latitude cyclones are just the opposite: They form in areas with large horizontal temperature gradients, and their circulations ultimately act to reduce horizontal temperature gradients over time.

Sustaining Tropical Cyclones

Now that we've established a key difference between tropical cyclones (which have a warm core) and mid-latitude cyclones (which do not, since they are characterized by rising motion over their centers and typically lack deep, moist convection near their cores), let's turn our attention to another key factor in the intensification of both mid-latitude and tropical cyclones--divergence aloft. You're already familiar with the role of divergence aloft in mid-latitude cyclones, supplied primarily by 500-mb shortwave troughs and 300-mb jet streaks, but divergence aloft plays an important role in tropical cyclones, too.

In order to help you visualize divergence aloft in tropical cyclones, allow me to introduce the secondary circulation of a tropical cyclone. As the name implies, tropical cyclones have two distinct circulations. The primary circulation, as you might expect, refers to rotation of air around the center of the storm. But, there's another circulation going on at the same time. In a basic sense, low-level air flows in toward the center of the storm, rises in thunderstorms within the eyewall and spiral bands, and flows (mostly) outward aloft, sinking around the periphery of the storm. This general circulation (in at the bottom of the storm, up, out at the top, and down around the storm's periphery) is the secondary circulation. To visualize this "in, up, and, out" process in the context of a strengthening hurricane, check out the short video below.

Hurricane Intensification (1:28)

As the video shows, divergence aloft helps to reduce surface pressure over the center of a hurricane by removing mass from air columns near the center of the storm (and the divergence tends to increase as thunderstorms intensify). Meanwhile compressional warming over the center (which also tends to increase as thunderstorms intensify) also acts to reduce surface pressure. Ultimately, hurricanes intensify as a result of a positive feedback loop, albeit a completely different one than the self development process for mid-latitude cyclones. The key to maintaining the whole process of hurricane intensification is sustaining organized deep convection around the core of the storm. One of the salient features in the positive feedback loop for hurricanes is "scale interaction." In a nutshell, processes on the spatial scale of convection (thunderstorms, for example) work to amplify changes on a larger spatial scale (such as lowering surface air pressure in the eye of a hurricane). In turn, amplification on the larger spatial scale amplifies convection (thunderstorms), and the feedback loop is off to the races. We'll delve much deeper into the details later in the course, but for now you should have a basic idea of how hurricanes intensify.

As you now know, tropical cyclones operate quite a bit differently from mid-latitude cyclone, so make sure that you understand the main contrasts between the two types of storms. To help you keep track of the major differences, below is a quick summary, highlighting the key differences between mid-latitude and tropical cyclones.

By now, I hope you're beginning to appreciate the differences between the mid-latitudes and the tropics. But, we're not done quite yet. Even the tools that tropical forecasters use are different! We'll start with map projections next. You'll quickly see that the map projections commonly used in the mid-latitudes don't work so well in the tropics!

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The fact that Earth is a sphere presents some hurdles for map-makers (and weather forecasters). Trying to accurately depict our spherical Earth on flat maps brings some real challenges, and the resulting process is always imperfect. Because of these imperfections, many types of map projections exist. Depending on the type of map projection, it is possible to minimize (or, in some cases, eliminate altogether) distortions in shapes, areas, distances and directions (the "Big Four" that map-makers worry about). But, no single map projection accurately preserves them all. Indeed, minimizing or eliminating distortions in one or two of the "Big Four" often results in gross distortions in the others.

Because a number of different projections exist, weather forecasters must always be aware of the benefits and limitations of viewing data displayed on various map projections. From your previous studies, you should be familiar with the polar stereographic projection, which is commonly centered on the North Pole. The benefit of such polar stereographic projections is that it allows forecasters to track the movement of weather systems in the middle and high latitudes over long distances. It is, however, important for forecasters to get their bearings when looking at polar stereographic projections because compass directions are not preserved. For example, in the polar stereographic map below, the arrow off the Pacific Coast of the United States represents a wind blowing from due west (270 degrees). An arrow representing a due west wind off the East Coast of the U.S. would be oriented quite differently, though, because it still would need to parallel the nearest latitude circle.

Polar stereographic map projections are commonly used by forecasters when tracking weather features in the middle and high latitudes, but not in the tropics. Why are polar stereographic projections not favored by tropical forecasters? For a clue, check out Texas and Alaska on the map above. They look to be nearly the same size, but in reality, Alaska is more than twice the size of Texas. Indeed, polar stereographic projections like this one suffer from gross size distortions farther away from the North Pole, and that's a problem when analyzing tropical weather patterns.

Tropical forecasters, therefore, turn to Mercator projections like the one below to track tropical weather systems. Distance distortions in the tropics are very limited on Mercator maps; however, they have major distance distortion problems at higher latitudes, as the image below indicates. As a result, Alaska completely dwarfs Texas (far more than in reality). At even higher latitudes, Greenland looks to be almost the size of Africa, but in reality, Africa is more than 13 times larger than Greenland. At the extreme, the North and South Poles (single points, in reality) appear as straight lines at the top and bottom of Mercator maps. Now that's distortion!

The limited distortion in the low latitudes is one reason why the Mercator projection is the map of choice for tropical forecasters. Another reason for its favored-map status is the relative ease in plotting and interpreting the tracks of tropical cyclones. That's because any line drawn between two points on a Mercator map preserves compass direction. For this reason, tracking tropical storms and hurricanes on Mercator maps is standard practice at the National Hurricane Center. For example, check out this five-day forecast for Hurricane Erin (opens in a new window), issued at 11 AM EDT on August 15, 2025. The fact that Erin was moving toward the west-northwest, and was predicted to take a turn toward the north

 in the next five days is easy to discern because of the use of a Mercator map. The cost of preserving compass directions, however, is the large distortions at higher latitudes.

To understand why distances are accurately represented in the tropics (and not at higher latitudes), you need to have a general understanding of the technique for creating Mercator projections. The common Mercator map is a cylindrical projection (opens in a new window) that accurately represents east-west distances along the equator (in other words, the distance scale is true). Nonetheless, distances are reasonably accurate within 15-20 degrees of the equator, making the Mercator projection ideal for the tropics. I should point out that Mercator projections can be constructed so that east-west distances are accurate along two standard latitudes equidistant from the equator.

Because horizontal distances in the tropics are depicted with reasonable accuracy, it is possible to look at satellite loops or a series of static satellite images of hurricanes and do a quick rough calculation of the storm's westward speed across the Atlantic. The key to these calculations is realizing that at the equator, Earth's circumference is 24,901 statute miles, and we have 360 degrees longitude in total. Simple division tells us that one degree longitude at the equator is equivalent to 69 statute miles (or 60 nautical miles). As we move away from the equator, this distance changes, but in the tropics, it serves as a good approximation (especially within 15-20 degrees latitude of the Equator). If you're wondering, one degree latitude is always equivalent to these values.

Based on this calculation, we can apply an old-fashioned, but simple and effective method to estimate a tropical cyclone's westward speed. You can literally put one finger on the center of the hurricane in the first image of a satellite loop or series of static images and then your thumb on the storm's center in the last image. Then, simply estimate the number of longitude degrees between your finger and thumb, multiply by 69 statute miles (or 60 nautical miles), and divide by the time (in hours) in order to calculate the forward speed in statute miles per hour (which most folks would just call "miles per hour.") or nautical miles per hour (which most folks would just call "knots"). For example, check out the image slider below. The first image shows infrared satellite imagery on a Mercator projection with Hurricane Erin located at about 19 degrees North, 59 degrees West. If you toggle the slider, you'll see the infrared satellite image from 24 hours later, with Erin now located around 19 degrees North, 65 degrees West.

During this time, Erin moved roughly westward near 19 degrees North latitude, and moved a total of about 6 degrees longitude. If we wanted the forward speed in knots (nautical miles per hour), multiplying 6 degrees by 60 nautical miles per degree gives a total of 360 nautical miles in a 24-hour time period, for an average speed of about 15 knots (17 miles per hour). Of course, we now have sophisticated computer models that predict positions and movement of tropical cyclones, but for short-term forecasts (say, less than 12 hours), extrapolating the storm's current motion can sometimes be quite useful (possibly even yielding superior results to computer model guidance).

Extrapolating current tropical cyclone movement can be helpful when the storm's environment doesn't change much, but tropical cyclones often change directions as their steering environments change. Furthermore, tropical cyclones don't always move from east to west, nor do they always stay in the tropics! Many tropical cyclones eventually curve toward the poles. As they do so, Mercator maps become less useful because of the increasingly large distortions at higher latitudes. For example, check out this five-day forecast for Hurricane Erin later in its life (opens in a new window) from the National Hurricane Center plotted on a Mercator projection. At the latitudes where Erin was predicted to travel, it's pretty difficult to get a feel for the storm's predicted forward speed because the distances on the map are so highly distorted. Note that the latitude/longitude "boxes" toward the top of the map are much, much larger than those at the bottom.

So, what do forecasters do as storms enter the middle latitudes? They turn to the Lambert conformal projection, which is a conical map projection that preserves distances along two standard latitudes (typically 30 and 60 degrees north -- note that the standard latitudes lie on the same side of the equator). Moreover, distortion is minimized in a narrow band along the two standard latitudes, but it increases with distance from these standard parallels. As its name suggests, the map projection is conformal, meaning that it preserves the proper angles between intersecting lines and curves and thus tends to preserve the shapes of relatively small areas better than other kinds of projections. Even though Lambert conformal projections preserve the shapes of small areas, it distorts their sizes, particularly those areas that lie relatively far from the standard latitudes.

In most of the mid-latitudes, however, distortion is relatively low on Lambert conformal projections (it's not nearly as significant as it is in the deep tropics). For this reason, meteorologists frequently take advantage of the shape-preserving nature of the Lambert conformal projection as tropical cyclones move out of the tropics into the mid-latitudes. Preserving the shapes of tropical cyclones as they travel to higher latitudes (on satellite images, for example) is important to forecasters because they continually look for physical changes in these weather systems to help them get a better handle on their current and future states.

Before we move on, I encourage you to check your knowledge of some basics from this page in the Quiz Yourself section below. Up next, I want to now talk briefly about the computer models used in tropical forecasting. If you pay close attention, you'll note the frequent use of Mercator maps to display model data in the tropics. Keep reading!

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Although we covered an "old-school" approach for short-term tropical cyclone track forecasts on the previous page, we have many sophisticated tools for predicting the track and intensity of tropical cyclones. Indeed, the advent of computer model guidance revolutionized weather forecasting, and tropical forecasting is no exception. Thanks to developments in computer guidance, reasonably accurate forecasts for tracks of tropical cyclones are now the norm several days in advance.

You're already familiar with how computer models work and what some of their main flaws are from your previous studies, and you should be familiar with some commonly used computer models and forecast variables used for forecasting in the middle latitudes. That basic knowledge is still applicable to the tropics, but tropical forecasters have some other computer guidance tools to work with, too. I'll break the discussion down into three parts -- global models, specialized tropical cyclone models, and ensembles.

Global Models

Since tropical cyclones are a global phenomena, forecasters often turn to the "global models" (that is, models that have a domain covering the entire globe that you should already be familiar with from your previous studies) to keep tabs on tropical cyclones in any basin. This includes both the "traditional" numerical weather prediction models run by the major modeling centers around the world (such as the GFS in the United States, ECMWF from Europe, CMC GDPS from Canada, the UKMET from the United Kingdom, and the JMA from Japan, among others), as well as artificial intelligence-based models that these centers have developed, such as the AI-GFS or the EC-AIFS (which stands for the European Centre Artificial Intelligence/Integrated Forecast System). 

As a quick reminder, traditional numerical weather prediction models and artificial intelligence (AI) models produce their predictions in different ways. Traditional numerical weather prediction models start with a representation of the current state of the atmosphere and then solve numerous mathematical equations that describe the dynamics and thermodynamics of atmospheric behavior to predict future states of the atmosphere. AI models are trained on decades of past weather reanalysis data, and using what they learn about how atmospheric patterns evolve from their training dataset, they can predict future states of the atmosphere after starting with a representation of its current state (often without incorporating physics at all). As you may recall from your previous studies, both modeling approaches have their strengths and limitations.

For an example of what a tropical cyclone looks like in the broad domain of a global model, check out the GFS forecast below. The "footprints" of four tropical cyclones (circled) are apparent as regions of relatively low sea-level pressure. As we've already discussed in this lesson, we can quickly get the idea that tropical cyclones are relatively small features in the scheme of things (certainly compared to the larger mid-latitude cyclones located at higher latitudes). Just a few decades ago, global models had resolutions that were so coarse that they weren't of much use in providing detailed looks at the core and wind field of a tropical cyclone, but resolution has increased so that global models can provide these details to some degree. Still, other models have been developed specifically to provide more detailed guidance for existing tropical cyclones.

Specialized Tropical Cyclone Models

Because global models aren't always the best at simulating the finer details of tropical cyclones, forecasters also turn to models specifically designed to forecast tropical cyclones. These models generally do not have a global domain, and only cover specific tropical basins. NOAA's flagship model developed specifically for tropical-cyclone forecasting is the Hurricane Analysis and Forecast System (HAFS), which became operational in 2023. Some benefits of the HAFS include the fact that it is "ocean coupled," which means that changes in the ocean and atmosphere respond to each other in the model, which is not the case in some global models. Ocean coupling in a model can be a big advantage because as you'll learn later, strong hurricanes can dramatically alter the characteristics of the ocean beneath them, which can then in turn alter the intensity of the storm.

The HAFS is also run at a relatively high resolution, with "nests" that follow individual storms along in time. Its high resolution means that it is capable of predicting small-scale structures within a storm. Of course, there's no guarantee that these small-scale details will be accurate for any given storm, but the ability to realistically simulate deep convective cells can be very helpful in simulating processes in the cores of tropical cyclones, which can improve intensity prediction, on average. As an example of the detail provided by these forecasts, check out the 6-hour forecast (below) of composite radar reflectivity and mean sea-level pressure for Super Typhoon Doksuri (2023), as it approached northern Luzon in the Philippines (opens in a new window).
 

The core of Doksuri was depicted with great detail as it approached northern Luzon, and the HAFS predicted a central pressure of 917 mb. But, as I just mentioned, while the HAFS can make highly-detailed predictions, there's no guarantee that they'll be accurate (the lowest estimated central pressure during Doksuri's life was 926 mb, so this was a pretty substantial error for a six-hour forecast).

The HAFS is actually run in two configurations -- HAFS-A and HAFS-B (note that the forecast prog above is from the HAFS-A). While the HAFS is not a global model, the HAFS-A configuration is run in all tropical basins. The HAFS-B configuration is only run on tropical basins under the responsibility of the National Hurricane Center and the Central Pacific Hurricane Center. The HAFS-A and HAFS-B also have some differences in their ocean coupling schemes and how they simulate some small-scale physical processes. Furthermore, tropical cyclones in the HAFS-B domain that have Doppler radar and other data collected during aircraft reconnaisance flights (opens in a new window) have some extra initialization data compared to storms in other basins.

Lest you think that NOAA didn't run tropical-cyclone specific models until the HAFS debuted in 2023, there's actually a history of such models going back to the early 1990s with the GHM (Geophysical Fluid Dynamics Lab Hurricane Model). Earlier generations of tropical-cyclone specific models also consisted of the HMON (Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic model), which became operational in 2017, and the HWRF (Hurricane Weather Research and Forecasting) model, which became operational in 2007. The HWRF in particular was ground breaking because it was first operational model to be able to assimilate Doppler radar data collected during aircraft reconnaissance flights in its initialization. The HMON and the HWRF are still being run, but are planned to be phased out.

Traditional numerical weather prediction models like the HAFS aren't the only specialized approach to tropical cyclone modeling, however. Specialized AI models focused on tropical cyclone forecasting also exist. These models are trained specifically on past tropical cyclone cases to produce forecasts for tropical cyclones (track, intensity, size, structure, etc.). But, these specialized models don't produce forecasts for the entire atmosphere as global AI models do. Some private sector companies like Google have been major developers of AI-based tropical cyclone models, which play a big role in our next modeling topic -- ensembles.

Ensembles

As you know, both traditional numerical weather prediction models and AI models are fallible, and often, various models have differing solutions. Indeed, check out the average cyclone forecast track errors (opens in a new window) of various computer models. Given that no models are perfect, and their solutions are often different, do forecasters have any tools at their disposal for helping them navigate the sea of uncertainty? Ensemble forecasts, to the rescue! Ensemble forecasting embraces the tendency toward differing forecast solutions by allowing forecasters to see a range of possible forecast outcomes, which allows forecasters to gauge uncertainty.

You've already been exposed to the basics of ensemble forecasting, but allow me to quickly review. Recall from your previous studies that the data used to initialize a computer model is always imperfect (we're nowhere close to being able to perfectly measure variables in the atmosphere everywhere at all times). So, the model initialization always contains errors. Ensemble forecasts are created by slightly altering the initial conditions fed into the model and / or altering the model physics (recall that a model's ability to mimic the atmosphere is not quite perfect). Each slight altering of the initial conditions or model physics generates an ensemble member. When there's very little spread in the solutions from all ensemble members, then the forecast isn't particularly sensitive to small errors in initialization or differences in model physics, and confidence in the operational model solution is high. But, when lots of spread exists among the individual member solutions, then the forecast is very sensitive to those differences, and confidence is lower.

Ensembles comprised of traditional numerical weather prediction models require a lot of computing power to run, and individual ensemble members are often run at reduced spatial resolution to conserve computing resources. But, ensembles for AI models exist, too, and while AI models require an immense amount of training data to develop, actually running the models on a daily basis is far less resource intensive than traditional numerical weather prediction models. So, AI ensembles can have many more members and can run much faster than ensembles from traditional numerical weather prediction models. To see an example of each in action, check out the image slider below, which shows track forecasts from the ECMWF ensemble for Super Typhoon Sinlaku (2026). The thick black line represents the actual storm track, while the multi-colored lines represent the ensemble member forecasts from the 00Z run on April 9.

It's clear that the ECMWF had a huge spread in track forecasts for Sinlaku, but if you toggle the image slider to see the corresponding ensemble run from Google DeepMind's AI model, it had a much tighter clustering of track solutions in this case, which could have helped forecasters narrow the scope of likely possibilities. Both sets of ensembles, however, carried the striking message that confidence steadily lowered with increasing forecast time as the spread in forecast tracks grew (it's simply the nature of the beast that errors associated with computer guidance grow with increasing time).

Ensembles can also give forecasters an idea of the range of possibilities for tropical cyclone intensity forecasts. For Sinlaku, this comparison of the ECMWF and Google DeepMind ensembles (opens in a new window) shows a wide range of possibilities. The black lines represent the storm's actual intensity, and we can quickly take away a few key messages. First, the vast majority of ensemble members underestimated Sinlaku's peak intensity (the black line peaks at the high end of the wind speed forecasts and "bottoms out" on the low end of the sea-level pressure forecasts). However, members of the Google DeepMind ensemble did a good job with timing its rapid intensification to a Category 5 storm. On the other hand, the ECMWF ensemble had a few members that better depicted Sinlaku's maximum intensity (below 900 mb), though they intensified the storm too slowly. Ultimately, forecasters utilize both "physics-based" and AI-based ensembles for key messages about forecast uncertainty. That's very helpful information, and it's much better to take into account the range of possibilities as opposed to locking in on a couple of operational model runs.

Other approaches to ensemble forecasting also exist (combining multiple ensembles into "super ensembles" or simply comparing many completely different models as an ensemble, for example). With many modeling options available (and I only covered the major ones on this page), it's important to remember from your previous studies that forecasters look for consensus among the models and diligently comb over real-time observations that might offer clues about which models have a better handle on a particular weather system. The same approach rings true for predicting tropical cyclones. If you're curious about where you can access model guidance from the global models and other models specifically created for predicting tropical cyclones, check out the list of resources in the Explore Further section below (the section also covers other models that I didn't touch on).

Yes, there's a wide variety of model guidance available to tropical forecasters. But, because tropical cyclones operate differently than mid-latitude cyclones, some unique forecast variables are of interest to tropical forecasters. We'll take a look at these variables next.

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Since we know that tropical cyclones behave differently than mid-latitude cyclones, it stands to reason that forecasters tasked with predicting tropical cyclones look at some different computer model products than the ones we've focused on in your previous studies. Therefore, I want to give you an idea of the major forecast variables and model products that tropical forecasters look at when predicting tropical cyclones. There's a lot of nuance and detail involved with these variables that we'll get into later in the course, but my hope is that this initial exposure will reinforce what makes tropical cyclones "tick" (i.e. factors that favor organized deep convection around the core of the storm) and allow you to start using model products effectively when tracking tropical cyclones.

At the most basic level, forecasters are interested in knowing whether a tropical cyclone will form (if one is potentially just getting started), what its future track will be, and how its intensity will change in time. So, what do forecasters look at in model guidance to get a handle on these issues? The list below is not exhaustive, but it covers the major variables that forecasters keep tabs on. Click on each one to expand the item and see a short explanation (with important forecasting thresholds, where appropriate).

Low-level vorticity and height/pressure patterns

Tropical cyclones require low-level cyclonic vorticity to develop (and stronger tropical cyclones display stronger low-level vorticity maxima with their circulations). Therefore, forecasters often look to 925-mb or 850-mb vorticity to help them diagnose tropical cyclone development.The pattern of mean sea-level pressure or heights at 925 mb or 850 mb can also help forecasters identify troughs and developing areas of low pressure.

500-mb heights/winds

Steering forces for tropical cyclones are somewhat complex as we'll learn later, but the pattern of 500 mb heights and winds provides a proxy for the large-scale steering forces for strong tropical cyclones.

Vertical wind shear through a deep layer of the troposphere

Vertical wind shear is the change in wind speed and/or wind direction with increasing altitude. Why do tropical forecasters care about vertical wind shear? In a nutshell, when vertical wind shear is too strong, tropical cyclones can't maintain organized thunderstorms around their cores. Thus, vertical wind shear between 850 mb and 250 mb (or a similar layer) must be relatively weak for tropical cyclones to form and develop. Basically, tropical forecasters look for wind shear values to be less than 10 meters per second (about 20 knots) as an indication of favorable conditions for genesis and development of tropical cyclones.

Middle tropospheric relative humidity

Relatively moist air in the middle troposphere is favorable for the genesis and development of tropical cyclones, while very low relative humidity values in the middle troposphere are unfavorable. While there are no firm thresholds, values of 70% or higher would be considered highly favorable. Values around 30% or lower would be highly unfavorable for a tropical cyclone (because they hinder sustained, organized deep convection). 

Sea-surface temperatures (SSTs)

In general, higher SSTs tend to promote evaporation into the boundary layer. A warm, moist boundary layer is more favorable for deep convection. SSTs greater than 26 degrees Celsius tend to favor development.

These variables give you a good idea of the types of model products that forecasters tasked with predicting tropical cyclones tend to focus on. To see how a forecaster would evaluate these variables when forecasting a real tropical cyclone, check out the video below.

Model Guidance for Tropical Cyclone Forecasting (7:25)

One big take away from the video is that a tropical cyclone's circulation can affect the interpretation of its steering environment, vertical wind shear, and its local relative humidity environment on computer model progs, so make sure to take note of those discussions in the video. Recognizing how a storm's circulation affects those interpretations is really important for making sound judgments about various aspects of the forecast.

Finally, much like with all the model guidance you've studied previously, plotting conventions (contour intervals, units, color schemes, specific layers for calculating wind shear or mean relative humidity, etc.), can all vary from website to website, so it's always critical that you take the time to get your bearings and recognize what's actually being shown on a given prog. For example, if a prog on one site shows vertical wind shear expressed in meters per second, and another shows it expressed in knots, you can easily make a mistake in assessing the strength of the shear around a tropical cyclone if you're not paying attention to the units!

Now that we've covered some basic tools that forecasters use to predict tropical cyclones, let's wrap up the lesson by looking at forecast products developed by the professionals at the National Hurricane Center. Read on.

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With a wide array of model data available online, it's easy for newer forecasters to get lost in a sea of forecast data. Not to worry, though! Professional tropical forecasters around the globe are constantly watching over the tropics, and issuing forecast products when tropical cyclones form. These products from RSMCs like the National Hurricane Center (NHC) in Miami, Florida, are a great help as you track current tropical cyclones. In addition, they also allow you to virtually shadow professional forecasters to get a sense for how they're thinking about a particular forecast. Indeed, professional forecasters can be an invaluable knowledge resource, even if you don't have "personal connections" to any of them.

In general, tropical forecasters have access to numerous types of observations (some of which you'll learn about later), as well as the same suite of models we've covered. That's a lot of information to manage! The solution? The Automated Tropical Cyclone Forecasting system (opens in a new window) (ATCF) was developed to streamline the forecasting of tropical cyclones at operational forecasting centers run by the U.S. Department of Defense (like JTWC) and the National Weather Service (like NHC). All of the data are organized in files called "decks" which become the data sources for many graphics used by professional forecasters (many of which are available online). If you're interested in reading more about the various "decks", the Tropical Cyclone Guidance Project provides a brief discussion of these ATCF files in their description of real-time guidance (opens in a new window).

Professional forecasters at NHC process and analyze the available data to develop forecast products in line with their mission statement, which is to "save lives, mitigate property loss, and improve economic efficiency by issuing the best watches, warnings, forecasts, and analyses of hazardous tropical weather, and by increasing understanding of these hazards." From its headquarters on the campus of Florida International University, NHC has responsibilities covering 24 countries in the Americas and the Caribbean Islands, as well as maritime interests in the North Atlantic Ocean, Gulf of Mexico, Caribbean Sea, and Eastern Pacific (north of the Equator).

Even when no active tropical cyclones are present within their jurisdiction during hurricane season (June 1 - November 30 for the Atlantic Basin, May 15 - November 30 for the Eastern Pacific), forecasters at NHC are still watching for areas of potential development, which you can follow with their daily tropical weather discussions (Atlantic Discussion (opens in a new window); Eastern Pacific Discussion (opens in a new window)). However, when a tropical cyclone forms within their jurisdiction, that's when NHC's Web page (opens in a new window) becomes more active with an abundance of compelling information and images. I won't cover all of NHC's tropical cyclone forecasting products in this section, but I do want to briefly cover the major products so that you know what's available and you can seek professional guidance when tropical cyclones are active in the Atlantic or Eastern Pacific. For the sake of simplicity, I'll separate NHC's products into text products and graphical products. For the record, the same set of products is also available from the Central Pacific Hurricane Center (CPHC) in Honolulu when storms enter their domain.

NHC Text Forecast Products

For a comprehensive overview of all of NHC's text products, you can check out NHC's text products description page (opens in a new window). For brevity's sake, I'm only going to highlight and summarize three of the most commonly encountered text products:

• Public Advisories are issued by NHC every six hours (03Z, 09Z, 15Z, 21Z) once a tropical cyclone forms, and are meant to do just what their name implies - advise the public of a tropical cyclone's current status and potential impacts. Check out this sample public advisory for Hurricane Sandy (opens in a new window) issued at 11 A.M. EDT on October 29, 2012. Note that the critical current facts about the storm (location, maximum sustained winds, central pressure, and current movement) are listed right at the top of the advisory. Following the current status of the storm are sections discussing watches and warnings, a brief outlook, and impacts. When a tropical cyclone threatens land, NHC quickens the pace, issuing public advisories as frequently as every two or three hours depending on the situation.
• Forecast Advisories are a bit more technical than public advisories (see the corresponding forecast advisory for Hurricane Sandy (opens in a new window) as an example). They're issued by NHC on the same schedule as public advisories, and include much of the same critical information as the public advisories. In addition, forecast advisories also include an estimate for the diameter of the eye in nautical miles, and maximum distances that tropical-storm-force winds (34 knots), storm-force winds (50 knots) and hurricane-force winds (64 knots) extend from the storm's center ("wind radii"). For maritime interests, forecast advisories routinely include distances that waves at least 12-feet high extend from the storm's center ("12-foot wave height radii"). If you need help deciphering a forecast advisory, NHC provides a handy online guide (opens in a new window) that you can reference (it's very helpful for decoding the forecast information). An added feature of the forecasts beyond 72 hours is that they offer a statement about previous errors in forecasting the storm's track and intensity.
• Forecast Discussions are also issued on the same six-hour schedule as public advisories, and allow you to eavesdrop on how NHC forecasters are thinking about a storm behind the scenes. Given the valuable experience of NHC forecasters, reading forecast discussions can be a tremendous way to learn about forecasting tropical cyclones. Regularly, forecast discussions contain comments on interesting storm features, forecasters' concerns about their current estimate of storm position or strength, model uncertainty and performance, explanations of the decisions forecasters have made, and more. Sometimes, forecasters even liken what they see in certain storms to past storms (an example of "analog forecasting"). The corresponding forecast discussion for Hurricane Sandy (opens in a new window) shows that forecasters were thinking about Sandy's status as a tropical cyclone as it headed toward landfall (toward the bottom of the discussion).

NHC Graphical Forecast Products

In addition to text forecast products, NHC also issues a number of graphical forecast products, some of which you may already be familiar with because they're so commonly seen on television weathercasts or online. First is NHC's forecast cone of uncertainty. The track forecasts produced by NHC (or any other forecasting outlet, for that matter) aren't perfect, so only providing a single solution would inevitably be fraught with error (check out the average errors (opens in a new window) for NHC 24, 48, 72, 96, and 120-hour track forecasts). While NHC's track forecasts continue to steadily improve, even three-day forecasts average almost 100 nautical miles of error. Thus, forecast cones of uncertainty, such as the one for Hurricane Irma at 5 A.M. EDT on September 7, 2017 (below), help reflect that the path of the center of the storm is uncertain.

The position of Irma's center at the time the graphic was issued is marked by the black "X." The series of black dots indicate the successive predicted positions of Irma's center (they're just a plot of the coordinates from the forecast advisory). The letters within each dot indicate Irma's predicted intensity at each forecast time ("H" = Hurricane; "M" = Major Hurricane). The white shaded area reflects the cone of uncertainty through Day 3, while the cone for Days 4 and 5 is marked by the white-stippled area. Note how the cone of uncertainty widens with time, reflecting the growing uncertainty as forecast lead time increases.

The width of the cone is based on NHC's historical forecast errors for the previous five years, so the actual width of the cone changes a bit every year. NHC data suggest that the five-day path of a tropical cyclone's center will remain entirely within the five-day forecast cone approximately 60-70% of the time. It should be noted, however, that hurricanes are not "points". They are storms with horizontal breadth. As a result, tropical-storm and hurricane conditions may occur outside the cone, even if the center of the storm remains within the forecast cone of uncertainty. To help make that point, NHC includes a depiction of the current wind extent around the center of the storm (brown and orange shading show the extent of hurricane and tropical-storm force winds, respectively).

Tropical cyclone intensity forecasts can also be quite uncertain, as suggested by this plot the average error (opens in a new window) for NHC 24, 48, 72, 96, and 120-hour forecasts. Improvements in intensity forecasting have generally been more modest (suggesting that much work remains to be done toward improving intensity forecasts), and have been most notable for four and five day forecasts. Given the challenges associated with intensity forecasting, NHC produces some probabilistic forecast graphics for tropical cyclone intensity. In an effort to produce products that are simple to comprehend and focus on potential impacts, NHC created graphics showing probabilities of wind speeds reaching or exceeding 34 knots (tropical-storm force), 50 knots (storm force), and 64 knots (hurricane force) within a five day period. The image below represents the probabilities that sustained wind speeds would exceed 34 knots (tropical storm-force) from 2 A.M. (EDT) on September 7 to 2 A.M. (EDT) on September 12, 2017.

Note that sustained tropical-storm force winds were nearly certain across parts of south Florida during this period. Given that Irma was still a far from Florida, however, tropical-storm force winds weren't a sure thing farther north. The probabilities of hurricane force winds (opens in a new window) in south Florida were lower during this time period (no better than a 50/50 chance in any given location) because of the uncertainties in the storm's future intensity and track, as well as the fact that hurricane-force winds occur over a much smaller area of the storm. If you'd like to see where tropical storm and hurricane-force winds actually ended up occurring from Irma, check out the "Wind History" product in the Explore Further section below.

Of course, timing the arrival of windy conditions with a landfalling tropical cyclone is important, too. For all practical purposes, most preparations need to be completed before tropical-storm force winds arrive in a given location, so NHC also issues products showing the most likely arrival time, as well as the "earliest reasonable" arrival time of tropical-storm force winds ("earliest reasonable" is defined as the time at which there's only a 1 in 10 chance that they'll arrive earlier). For Hurricane Irma, on the morning of Thursday September 7, 2017, NHC predicted that tropical-storm force winds were most likely to arrive in Florida on Saturday evening (opens in a new window), but they could arrive as early as Saturday morning (opens in a new window).

Other Useful Products

In addition to the forecast products outlined above, I want you to be aware of a few other aspects of NHC's page. First, their site includes links to a wide variety of satellite imagery (opens in a new window) from across the globe (some making use of techniques we'll cover later), including some "Floater Imagery." These satellite "floaters" provide a "storm-centric" perspective that follows the storm along in time. They're a great way to get a close-up view of a storm as it moves through the tropics.

After each hurricane season ends, NHC also posts a "Tropical Cyclone Report (opens in a new window)" for each storm in the Atlantic and Eastern Pacific. These reports contain a wealth of information about the storm, including its origins and history, relevant meteorological statistics, casualty and damage statistics, and a discussion / critique of how the storm was handled by forecasters as it happened. NHC even occasionally makes changes to a storm's intensity in their post analysis if they believe that a more thorough analysis revealed that mistakes were made in real time. The final estimates are contained in a table of "Best Track" data in the report.

That wraps up our look at the forecasting products from NHC. This wasn't a thorough treatment by any means, though. For now, I just wanted you to get a feel for the commonly-used products that are available. NHC produces some other products that we'll cover later. In the meantime if you're interested in NHC and its history, or want to see a few other operational products, I encourage you to check out the Explore Further section below.