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Administrators Say They Will Not Include Local-Area Parks

On a regular Saturday-morning Zoom meeting of hams a few months ago, a participant in Los Angeles asked the group, “Why can’t I activate one of my local parks and have it count in POTA?” Some of those in attendance echoed the sentiment. Based on that question, I asked myself what does POTA as a program look like? I recently published a snapshot of POTA sites, activations, and activators on this blog. There were several findings that we did not know before I published these results.

As I concluded in that article, “There are a small number of POTA sites that account for at least half of all activations since the program began. Not surprisingly on the heels of this finding, there are a small number of extreme activators who account for a significant share of last year’s POTA activations. These extreme activators are scattered throughout the same regions as the most activated parks.” It may be this element that drives the increasing social media presence of the portable park activations.

Another surprising finding is that only two percent of all activators in 2025 were Technician class licensees. While Techs do have some HF privileges, this very small presence as POTA activators is still quite surprising.

What do we know about POTA entities, their use, and accessibility to hams?

The decisions by POTA to start with the National (Federal) Parks used in NPOTA was an obvious baseline. They apparently added what they reasoned were state-owned parks during this rollout over the years since 2017. Now, if one does not understand the federal-state-local data systems very well, it is easy to assume that “all” state-owned parks would be managed through a single state agency for parks, right?

Well, recall that it’s government, which has multiple layers, too. There are usually add-ons to authorizations, unanticipated programs initiated by state legislatures, multi-jurisdictional agreements, and so on. This assumption by POTA likely led to an inconsistent set of “state” parks added later. That is, most state parks are administered by State agencies (see their national association for State Parks Directors). This doesn’t include, except idiosyncratically, parks governed by state agencies under “special jurisdiction” agreements. I have one near my home. It took two years for me to convince my State Mapping Coordinator (who actually lives in Tennessee) that it is indeed a “state” park but governed by a special water district established by the Legislature. That was when a reservoir was created in the 1960s to provide water for the City of Jackson (MS). It is not under the Mississippi Department of Wildlife, Fisheries, and Parks agency! This is merely one example that was clearly unknown by my Mapping Coordinator. There are likely many, many other examples.

Over time, there is somewhat of a hodge-podge of park entities at the sub-national level on the POTA entity list, now totalling some 11,966 parks in the continental U.S. as of December 2025. That sounds like a lot, no? There should clearly be enough for everyone to activate one almost any time, right?

Well, in a word: no. There is a significant shortchanging of hams who live in urban centers. For instance, in Los Angeles where Ivan WC2S lives, it takes an hour to drive one-way across the city! Hmm. With so many licensed hams with HF privileges in LA, how many POTA sites do they have to choose from? Nine. It’s worse in Silicon Valley (one) and Dallas-Fort Worth (two). It’s 38 minutes on average to drive across San Jose. Kevin KW6E says that the one POTA site in Silicon Valley gets congested, preventing the myriad of other hams in that high tech region from using them very much without something akin to an informal repeater frequency coordination taking place. Well, that’s a bit of an overstatement but you get the point. There are some 6,907 licensed General or Extra Class hams in the San Jose urban area. In fact, KW6E uses a POTA activation alert just to tell him when the only POTA site in the area is activated so he won’t bother packing his portable gear and driving to it for nothing! It’s as bad in the Dallas-Fort Worth Metroplex where it can take 1-2 hours to drive from one side to the other. In that urban area, there are 11,050 Generals or Extras, almost twice the number in the San Jose urban area.

Considering the traffic congestion and the paucity of POTA sites in most urban centers, I posted on the amateur radio and parksontheair Reddit threads asking about the need for a local parks program. There were well over a thousand views with a hundred plus responses and climbing. Many quickly agreed about the need for activatable local parks but many just expressed loyalty to the POTA program by stating that things are fine as they are now. The flippant answer by some to “just go out doors and drive to a POTA site” as a solution doesn’t begin to consider the full situation for urban hams. That’s one motivation for me to bring data to bear on better understanding it. If one has a half day to do POTA activations, then that’s what it may well take for urban hams to activate various sites. But time isn’t abundant for many amateurs who want to play radio outdoors, especially if they are also employed. An hour might be the largest chunk of recreation time available all week for the vast number of hams in urban areas.

The problem is a classic question of spatial mismatch: how well matched are the spatial distributions of POTA sites, HF-privileged hams, and “local” parks? Are urban-located hams significantly kept away from reasonable access to POTA sites? How many urban hams are there anyway? How would this change if POTA did include local parks (they have stated in writing that they aren’t) or if an independent program included them? I’ve found some rather stark answers to these questions which I’ll summarize below. It’s not consistent at all for most urban centers with off-the-cuff responses to my Reddit thread.

Some Census Geography Concepts

Readers all use city, metropolitan area, and the like in everyday conversation. But most do not fully understand how the Census Bureau defines and designates areas in the U.S. as urban, metropolitan or non-metropolitan areas. I’ll give a brief synopsis with illustrations to help the reader better understand the results for activating parks. The definitive reference guide is the Census Geographic Areas Reference Manual (or GARM). If the reader skips this section, the results following it may become confusing.

Shown below is a map of the Continental U.S. (CONUS) with states and Census Divisions illustrated. The red “blobs” are urban areas, largely representing cities in the country. Those areas in blue are metropolitan areas as designated by the Office of Management and Budget (OMB) every few years. The of green areas are micropolitan areas, largely thought of as smaller cities unto themselves. The light tan areas are counties outside of metropolitan areas, called non-metropolitan counties. They are highly visible, for instance, in the Midwestern states and elsewhere. They are what most would call rural areas. These are the officially defined geographical designations from the Bureau of the Census I used in this study.

This is a high-level visualization, of course, so we need something more specific to better understand the spatial mismatch of POTA sites, hams, and local parks. The graphic below further illustrates and officially defines several of these geographic concepts. (I used to give PhD students in my spatial analysis course an exam on all this geography.) I’ve used Los Angeles as an example with the Death Valley area as a supplement.

We can think of Urban Areas as the central urbanized portion of metropolitan areas. Not all of the space within metros consists of “concrete-and-steel” as Dr. Jeremy Porter and I demonstrated a few years ago using nationwide remote sensing imagery with these Census Bureau boundaries. Urban Areas do nonetheless reflect the most developed geography within large cities. In fact, they help define the specific metro area itself (see definitions). Metropolitan Areas consists of a core (“big”) county with adjacent counties with strong commuting ties to the core county. Micropolitan Areas, by contract, are smaller urban centers with a smaller core county and adjacent ones. We often think of them as middle sized cities situated distinctly apart from larger metro centers. The Core-Based Statistical Area (CBSA) is a combination of Metropolitan and Micropolitan Areas which give a larger geographic unit characterizing a set of adjacent and economically integrated units. Finally, a Combined Statistical Area (CSA) puts together two or more adjacent Metro or Micro areas with strong economic and social ties (“bedroom communities,” satellite cities, edge cities, and so forth). The Bureau usually considers the non-metropolitan counties not included in the above categories as rural areas.

Parks, Hams and Analysis Procedures

These geographic concepts are used to compare the locations of POTA sites to licensed hams with HF privileges, the ones most likely to participate in field activitions. I did restrict these hams to those with General or Extra license classes. Technicians have limited HF privileges but comprised only two percent of all activators in 2025. I used the Trust for Public Lands ParkServe_(tm) database which contains all known parks in the U.S. to identify “local” parks. There are several classes of parks owned or managed at the sub-State level. For simplicity, I only use the municipal (or city) parks here. These are most identified with local government jurisdictions.

The TPL works with local, state, federal, private, and multi-jurisdictional entities each year to identify and track protected lands. Parks are an essential part of these lands. This is a far superior resource for the identification of parks, especially and the state and local levels, than is the approach taken by POTA Inc. The fact that a large team with state representatives monitors these protected lands annually ensures that the parks included meet specific criteria with yearly updates in any relevant changes. I believe that the POTA organization leaves this up to the local Mapping Coordinator who may not actually reside in the state of reference and who may well not annually verify each POTA entity.

To be included in the ParkServe database, a park or ‘park-like’ place must meet the following criteria:

• Be located outdoors
• Be a named destination (e.g. not an unnamed median or drainageway)
• Encourage informal public use (e.g., the public is encouraged to walk through and stay awhile)
• Encourage at least one ‘park-like’ activity such as socializing, enjoying nature, or play/exercise

The TPL performs many more analyzes to evaluate parks for access, amenities, climate, and so forth. This results in both a ParkServe Index score as well as prioritization of areas needing access to more parks for the population surrounding the local areas.

Municipal-owned parks from the ParkServe database in the 48 Continental States (CONUS) totalled some 101,301 park entities. By accessing the POTA.app website, I downloaded the list of POTA sites as of late December 2025 with their assigned latitude and longitude coordinates and activation summaries, reflecting point data for their list of official entities for activation. To profile the ham population, I used all licensed General and Extra amateur license-holders in the FCC ULS database for circa 2025 (downloaded January 1, 2025 to reflect the end of FCC transactions for the previous year). Those whose license had technically expired but remaining in the database (a known practice to preserve the ability to renew an expired license within two years) were excluded (see Snapshot article). For this study, I included only hams in the Continental U.S. (excluding AK, HI and territories).

This included 191,282 Generals and 159,522 Extras for a total of 350,804 HF-privileged hams in the continental U.S. These are called GE hams throughout the study. Yes, I realize that Technicians do have some limited HF privileges and note that in the narrative as only two percent of POTA activators in 2025 were Technicians. I omitted legacy Novices (5,028) and Advanced licensees (29,327) from this analysis for convenience. Should the reader think that these omissions would change the results, I’ve described the methods sufficiently to replicate them with Novices and Advanced licensees included if so desired. Technicians (381,563), long the largest share of amateur licensees (49.8%), were also extracted for use in a later part of the study. Again, these numbers only reflect those in the Continental U.S.

What are the Issues Addressed in this Study?

The questions guiding me are these:

• Where are POTA sites collectively located and how does this compare to the urban concentrations of HF-privileged hams (Generals & Extras)?
• Are local municipally-owned parks substantially more or less accessible than POTA sites to GE hams in urban areas?
• Is there an imbalance in the access to POTA sites for urban hams and how large of a share of GE hams are affected?
• Does there appear to be a significant market of hams to warrant a new program that organizes local parks into an online system facilitating their activation?

POTA Sites and Municipal Parks in the U.S.

Here is a repeat map from the Snapshot article of the POTA locations extracted from the official POTA.app website. Each one is shown as a red dot over a map of the U.S. with metropolitan and urban areas shown in varying shades of gray underneath on the basemap.

By way of general reference, the map below is very similar to the one above for POTA sites. It displays municipal parks shown as blue dots. Obviously, they are clustered in cities where local governments own or manage them. While there are many more local municipal parks than POTA sites, their pattern clearly emphasizes city locations, many more in urban areas than in the non-urban population areas. While the spatial scale is national, we will see below how the accessibility varies with POTA sites for GE hams.

A well-known GIS issue of spatial scale is why both maps appear to show parks everywhere hams might be located. We need to examine smaller areas to determine whether there is reasonable access to POTA sites and, if not, whether local parks might resolve that issue for most urban located GE hams. A large area might appear inundated with parks until one has to actually drive to one. Let’s take a closer look.

Spatial Access Profiles of POTA and Municipal Parks

Before jumping into the results, here is an example of how spatial access is measured. Shown below are excerpts of two maps illustrating an area east of Atlanta GA. The center point of each hub is the location of a POTA site with all of the GE hams for which it is the nearest POTA site (first map, in red). I created a polygon around the furthest points for related ham operator locations, reflecting the minimal “friction of distance” to activate their nearest POTA park. This polygon is called a convex hull in math and is a common spatial tool in GIS. I have done the same thing for the second map (in blue) depicting the nearest municipal park for the same set of GE hams. To compare how accessible each park is, we compare the relative convex hull size of each POTA and municipal park. A numerical number that is useful for this is the area in square miles within each convex hull polygon. The larger the polygon, the longer the average distance it is from GE hams to the nearest park.

In the profiles for the cities below, I will omit the hub-and-spoke elements for clarity and overlay only the POTA and municipal convex hulls on the base map. This will give the reader an explicit visualization as to how accessible each type of park is to GE hams in the region.

Profiles for Several Major Cities on Park Access

This is a summary of accessibility for five metropolitan areas and cities across the U.S.: Atlanta, Chicago, Dallas-Fort Worth, Los Angeles and Seattle. All have significant average drive-times in their respective traffic patterns. In the maps below, the pink polygons are the convex hulls for POTA parks, depicted as red dots. The blue-purple polygons are similar convex hulls for municipal sites. These are noted in the legend. In general, the reader will see a far greater pattern of accessibility to municipal parks in these large U.S. cities than for POTA sites. Let’s go through each one.

The Atlanta core urban area (above) contains a high concentration of GE hams, some 7,734, although the growth of the northern suburbs has exploded over the past few decades. But there are only two POTA sites in the core urban area (see center pink polygon). The travel distance is much, much longer than to the many, many municipal parks. As the reader examines those burgeoning suburbs, the same pattern is present: far more accessibility to municipal parks than to the sparse POTA sites. This is only visible using the appropriate spatial scale.

Chicago (above) is a major urban center in the Midwest, a long-time growth location in the history of the United States. It, too, is a suburban-growth metropolitan area. There are 10,058 GE hams in the Chicago urban area. Chicago has no POTA entities in the urban area. There are a small number outside in the southern and western suburbs. But, as with other urban centers, there are numerous municipal parks available with short travel distances for GE hams.

The Metroplex (above), as the Dallas-Ft Worth metropolitan area calls itself, is a surprising case. It is a spread-out urban development in many ways. So one might expect more POTA sites than in, say, Atlanta or Chicago. But there are only two: one in northeast Dallas and one in southeast Fort Worth! With the drive time associated with the Metroplex, these two POTA sites require a significant period of time to activate. The many municipal parks, by contrast, do give many GE hams access for the figurative hour-long activation. There are 11,050 GE hams in the Dallas-Fort Worth urban area, slightly more by comparison than in Chicago.

The drive times in Los Angeles (above) are famous. Famously long, that is. This can place a clear burden on hams who want to engage in POTA activations. The map above illustrates the relatively few POTA sites in the greater Los Angeles metropolitan area. The convex hull depiction of POTA site distance illustrates this in a city where there are 22,276 hams with General or Extra licenses as of December 2025. The number of municipal parks are far more accessible than are POTA entities in LA. This gives a birds-eye view to why Ivan WC2S asked why can’t I activate a local park in POTA? There are so many more of them!

Seattle (above) is a city culturally focused on outdoor activity with mountains, water and other recreation pursuits nearby. There are several POTA sites in the Seattle urban area. In the Seattle-Tacoma urban core, there are 13,171 GE hams living there. But even in an outdoor-driven locale, the accessibility of municipal parks is far superior to POTA sites in the region. The blue-purple polygons characterizing the “service area” for each municipal park for the GE hams nearby is rather clear even in the metropolitan urban core with several POTA sites in the general area. The traffic congestion in the Sea-Tac area, focused on the I-5 interstate, is just below what it infamously is in Los Angeles. This added element to POTA activation makes getting to an activatable park site a greater time sink.

These major cities illustrate clearly how relatively sparse POTA sites are in their urban centers. The question remains: How do these major cities compare to the nation as a whole? And does this POTA site scarcity in urban areas keep a significant share of HF-privileged hams from activating those parks? I present summary data on national patterns now. They provide rather clear answers.

National Patterns for POTA and Local Municipal Park Accessibility

I have summarized the national results of this type of analysis in tables below. They provide a clear, focused picture of the relative distances for hams holding General and Extra tickets to POTA sites versus local municipal ones. The gap in accessibility to POTA vs municipal parks by urbanization is fairly stark. To my knowledge, I have never seen the identification of licensed amateurs across the rural-to-urban classifications used by the Census Bureau so this too is a new set of findings in the ham radio literature.

This table shows the number of hams, their percent composition, POTA sites and their respective share, and the imbalance of POTA sites by urban and metropolitan areas. The number of cumulative (lifetime) activations for POTA sites and their share are also included. Finally, the local municipal park number and share (percentage) round out this summary of parks, activations and how they vary by urbanization zones across the U.S.

I also illustrate parts of this table through bar charts below but let me emphasize the spatial mismatch indicators at the outset. Well over one-half of the GE hams in the U.S. CONUS, some 8 out of 10, are in metropolitan areas, largely similar to the general population. They are concentrated in urban zones within the metro area (62.3%). This provides a great imbalance in the locations of POTA sites here. Over a third of these sites (38%) are in the non-urban metro areas with only a very small share (6.5%) in urbanized areas. This imbalance is rather stark relative to the ham population residing in those areas. I include an imbalance ratio of the share of POTA sites to the share of GE hams as a summary figure.

The two bar charts help crystalize this spatial mismatch. POTA sites, largely due to their National Park origins, are mostly outside of urban centers in Metro areas (see left). There are many in rural (non-metro) counties. The mismatch comes with the spatial concentrations of GE hams (see right). Most are located in urban centers of metropolitan areas. Only small shares of GE hams are in non-metro counties or in Micropolitan areas near the third concentration of POTA sites.

How busy these POTA sites are with activations tends to reflect this imbalance. The great inequality of lifetime activations noted in the Snapshot article for the nation as a whole can be partly explained through their location. As shown in the table, half of all activations are in those POTA sites in non-urban metro areas (49.1%). Only 17.6 percent occur in urban portions of metropolitan centers. This is very similar to those in non-urban, non-metro (“rural”) areas. Small cities (micropolitan) have a slightly smaller share (14%). The rest are very nominal in size. Thus, activations in the whole tend to not be where the vast majority of GE hams live. Does this restrict the number of activations by a majority of POTA activators, leaving it to the smaller share of extreme activators? (See my Snapshot article on this.)

In general, consumers obey the “friction of distance” in their shopping behaviors. The closer options tend to receive more shoppers. To give an overall picture of the pattern of distances from where GE hams live to POTA and local municipal parks, I’ve created two simple histograms of these distances in miles. To increase clarity, I truncated the chart to 30 miles but the full range is used to compute descriptive statistics. The average distance for POTA sites is about 7.53 miles. For municipal parks, it is 3.69 miles, an approximate four-mile difference on the average. There are a very small share of hams who live much larger distances than the 30 miles shown to a POTA site as well as the nearest municipal site.

To give a further summary of the accessibility to POTA sites for urban and non-urban areas, I computed the number of GE hams per POTA site within each metro and urban category. This metric is a rough indication of the potential demand for access by these license holders. (This is not unlike corporate site-selection metrics.) The category where most POTA sites are located (shown above) is in the non-urban areas of metropolitan areas. There are 14.9 GE hams per site there. For the inner city urban area of metros, there are many more GE hams, some 280.5 per POTA site! This shows the tremendous potential contention for those sites as Ivan WC2S and Kevin KW6E described in our Zoom conference. It also illustrates the tremendous market for park availability for them to activate should local parks be available.

Smaller isolated micropolitan areas also have a much smaller market, but it depends on the urban status of POTA sites and GE hams. There are 122.1 hams per POTA site in Micropolitan urban areas but only 8.8 in the non-urban regions within them. This reflects another spatial location for park contention and a market for potential expansion to local parks.

The non-metropolitan counties, commonly called America’s rural areas, have another substantial urban gap. In urban areas in non-metro counties, generally thought of as small towns, have ten-fold more hams-per-site (64.3) as those in the non-urbannon-metro areas (6.0). These data show the stark lack of accessibility by urban-based GE hams regardless of whether they are in metro, micro or non-metropolitan zones.

What is the Overall Accessibility to Parks for GE Hams?

While these results make a strong case that urban hams with GE credentials are not well-served by the POTA program, questions remain. How far are they from POTA sites versus local municipal parks? The two histograms above do show a prominent disparity favoring local parks. Moreover, are there cases where POTA sites are closer to GE hams than municipal parks? Remember, it is about the relative spatial proximity of sites to hams.

In the earlier section on major city profiles, I used the convex hull polygon to illustrate how large or small the spatial distance was for each GE ham in the area to POTA versus municipal parks. The area in square miles within those polygons represents the closeness that each type of park is to GE hams for which it is the closest entity. The table below is a summary of that nationwide analysis.

It should not be surprising that the average area in the convex hull representing the nearest park service zone, whether using to the mean or median, is much smaller for municipal parks than POTA sites. This shows how the “friction of distance” is far less for municipal parks because that is where most GE hams are located! The average area for POTA sites is 118 square miles while for municipal parks it is one-fifth that at only 20 square miles. The median, where one-half of the parks are above and below the figure, is 52 for POTA sites and 0.3 for municipal parks. These patterns are rather dramatic by comparison. However, the minimum and maximum illustrate that there are also very large municipal parks (max = 6,652 vs 4,031 for POTA).

Compare the area of the convex hull above to the average distance from the same set of GE hams to POTA vs municipal parks in the line chart below. The urban area effect is clear by comparing the red and blue lines in each chart. The lines depict the difference between urban and non-urban areas in the average distance to the nearest POTA and municipal parks. The three charts pertain respectively to metropolitan areas, micropolitan areas and non-metropolitan counties with urban areas within them. This summary of average (crow flies) travel distance illustrates the three-part elements of the locations of POTA sites, municipal parks and GE hams. It takes all three components to best understand accessibility.

In urban metro areas, for example, the average distance to a municipal park is under two miles. It is over seven miles to the nearest POTA site. All of the urban average distances are about the same regardless of metropolitan classification as for non-urban distances across these metropolitan categories. Thus, for the continental U.S., municipal parks are closer to GE hams than area POTA sites by several miles on the average. The sole exception occurs in the most rural locations, non-urban non-metro areas, where POTA sites tend to be located themselves and are therefore closer.

Are there any POTA sites that are closer to GE hams than municipal parks? Well, yes there are. But not that many in the scope of the full set of licensed hams. Here is why I say that.

The pie charts above show the results for comparisons where POTA sites are closer to individual GE hams than their closest municipal parks. The results are further indications of the spatial mismatch of GE hams and POTA sites with municipal parks being situated in urban areas. Few POTA sites are closer in urban metro areas (8.6%) but more so in non-urban ones (16.1%). Most all municipal parks are closer in for urban metro hams (91.4%). This reverses in Micropolitan areas as almost a third (33.1%) of POTA sites are closer in the non-urban areas there. This drops to about one-fifth for urban micropolitan cities (19.3%). Finally, for non-metropolitan counties, a similar pattern occurs with a fourth (28%) having hams with POTA sites closer than municipal ones. This is not the case in rural areas with urban centers (small towns). Some 93 percent (92.8%) have municipal parks nearby with only some 7 percent (7.2%) with POTA sites being closer. I hasten to remind the reader that the greatest concentration of GE hams is not in rural or suburban areas but in the urban zones of metropolitan areas.

What Have We Learned About the Location of Hams and POTA Sites?

The rather elaborate results show that urban General and Extra Class hams are significantly under-served in access to the POTA program’s current park entities. These parks are just not where the hams live. Booking a longer period of time for portable ham operations is required for GE hams in the largest metropolitan urban centers. I’ll hasten to add that some 62 percent of GE hams live in those areas. There is also time contention for sparse urban sites where there are many hams who want to activate them. Ask Kevin K6WE who lives in Silicon Valley. He has an alert set just to let him spot activators in the single POTA site in his general area. Why? So he won’t pack his gear and drive to one of them only to find RF contention for his transceiver from other hams doing an activation. This scenario is due to the spatial locations of POTA sites, the concentrations of GE hams in urban centers, and the much longer drive times in the transportation networks in those areas.

A classic spatial mismatch interpretation fits these results. By and large, POTA sites are not where the most General and Extra amateur operators live. Thus, POTA sites are activated mostly by a small group of extreme activators and in a small group of POTA sites. The majority of activators in 2025 reported 5 or less such successful trips (median number). (This is from the Snapshot article.) This mismatch is not purely a result of POTA Inc. making intentional choices. Indeed, the National Parks program in the U.S. represents some of our earliest protected lands (thank President Theodore Roosevelt). They were intentionally located in what was then more isolated areas away from urban centers. Adding a mix of state-owned and managed park sites by POTA Inc. merely increased the mixture of official POTA sites that are outside of the larger urban metro centers where most GE hams live.

Even though unintentional, the official list of POTA sites does fly in the face of consumer behavior by ham operators. The well-established “friction of distance” does guide consumer choice, such as choosing a park to activate in POTA (or perhaps, not activate at all). But is it a problem? Can’t urban-based hams just drive to a POTA site and enjoy the countryside? Yes, they can. Obviously, some do. But it does come at a price for the majority of POTA-activating ham operators. For those hams who participated in POTA activations during 2025, my statistical modeling results show that for every mile further the nearest POTA site is, hams activated one-half fewer times during the year (i.e., a reduction of 0.5 activations per mile). This suggests more study in future articles but suffice it to say here, where hams are located does affect the choice of parks and the number of times they activate them.

One large issue not directly addressed here are Technician Class licensees. They account for about half of all licensed amateurs in the Continental U.S. (49.1%). Yet, only two percent of them reported POTA activations in all of 2025. This is a topic for further study in future articles.

What can be done? Some ardent POTA fans would (and have on Reddit) say, “Shut up and operate.” Wow. That attitude leads to consternation, frustration and, likely, a movement to solve the problem through competitive means in the marketplace. What do I mean by this? POTA Inc. has said in writing to Ivan WC2S that adding local parks to their system is not going to happen. That is certainly their corporate choice and I for one am not asking them to by implication of these research results. Perhaps it is beyond their technical capability to handle these many more parks. For whatever the underlying reason, they have spoken and they are not going to undertake this.

Is it worth a grassroots movement to launch an independent “park activation” program for local parks? It might be but that coming to fruition remains to be seen. I hope this article has provided some data-driven facts for consideration to those interested in portable operation in parks across the U.S. It’s a great activity space that should be more accessible to all.

Administrators Say They Will Not Include Local-Area Parks

On a regular Saturday-morning Zoom meeting of hams a few months ago, a participant in Los Angeles asked the group, “Why can’t I activate one of my local parks and have it count in POTA?” Some of those in attendance echoed the sentiment. Based on that question, I asked myself what does POTA as a program look like? I recently published a snapshot of POTA sites, activations, and activators on this blog. There were several findings that we did not know before I published these results.

As I concluded in that article, “There are a small number of POTA sites that account for at least half of all activations since the program began. Not surprisingly on the heels of this finding, there are a small number of extreme activators who account for a significant share of last year’s POTA activations. These extreme activators are scattered throughout the same regions as the most activated parks.” It may be this element that drives the increasing social media presence of the portable park activations.

Another surprising finding is that only two percent of all activators in 2025 were Technician class licensees. While Techs do have some HF privileges, this very small presence as POTA activators is still quite surprising.

What do we know about POTA entities, their use, and accessibility to hams?

The decisions by POTA to start with the National (Federal) Parks used in NPOTA was an obvious baseline. They apparently added what they reasoned were state-owned parks during this rollout over the years since 2017. Now, if one does not understand the federal-state-local data systems very well, it is easy to assume that “all” state-owned parks would be managed through a single state agency for parks, right?

Well, recall that it’s government, which has multiple layers, too. There are usually add-ons to authorizations, unanticipated programs initiated by state legislatures, multi-jurisdictional agreements, and so on. This assumption by POTA likely led to an inconsistent set of “state” parks added later. That is, most state parks are administered by State agencies (see their national association for State Parks Directors). This doesn’t include, except idiosyncratically, parks governed by state agencies under “special jurisdiction” agreements. I have one near my home. It took two years for me to convince my State Mapping Coordinator (who actually lives in Tennessee) that it is indeed a “state” park but governed by a special water district established by the Legislature. That was when a reservoir was created in the 1960s to provide water for the City of Jackson (MS). It is not under the Mississippi Department of Wildlife, Fisheries, and Parks agency! This is merely one example that was clearly unknown by my Mapping Coordinator. There are likely many, many other examples.

Over time, there is somewhat of a hodge-podge of park entities at the sub-national level on the POTA entity list, now totalling some 11,966 parks in the continental U.S. as of December 2025. That sounds like a lot, no? There should clearly be enough for everyone to activate one almost any time, right?

Well, in a word: no. There is a significant shortchanging of hams who live in urban centers. For instance, in Los Angeles where Ivan WC2S lives, it takes an hour to drive one-way across the city! Hmm. With so many licensed hams with HF privileges in LA, how many POTA sites do they have to choose from? Nine. It’s worse in Silicon Valley (one) and Dallas-Fort Worth (two). It’s 38 minutes on average to drive across San Jose. Kevin KW6E says that the one POTA site in Silicon Valley gets congested, preventing the myriad of other hams in that high tech region from using them very much without something akin to an informal repeater frequency coordination taking place. Well, that’s a bit of an overstatement but you get the point. There are some 6,907 licensed General or Extra Class hams in the San Jose urban area. In fact, KW6E uses a POTA activation alert just to tell him when the only POTA site in the area is activated so he won’t bother packing his portable gear and driving to it for nothing! It’s as bad in the Dallas-Fort Worth Metroplex where it can take 1-2 hours to drive from one side to the other. In that urban area, there are 11,050 Generals or Extras, almost twice the number in the San Jose urban area.

Considering the traffic congestion and the paucity of POTA sites in most urban centers, I posted on the amateur radio and parksontheair Reddit threads asking about the need for a local parks program. There were well over a thousand views with a hundred plus responses and climbing. Many quickly agreed about the need for activatable local parks but many just expressed loyalty to the POTA program by stating that things are fine as they are now. The flippant answer by some to “just go out doors and drive to a POTA site” as a solution doesn’t begin to consider the full situation for urban hams. That’s one motivation for me to bring data to bear on better understanding it. If one has a half day to do POTA activations, then that’s what it may well take for urban hams to activate various sites. But time isn’t abundant for many amateurs who want to play radio outdoors, especially if they are also employed. An hour might be the largest chunk of recreation time available all week for the vast number of hams in urban areas.

The problem is a classic question of spatial mismatch: how well matched are the spatial distributions of POTA sites, HF-privileged hams, and “local” parks? Are urban-located hams significantly kept away from reasonable access to POTA sites? How many urban hams are there anyway? How would this change if POTA did include local parks (they have stated in writing that they aren’t) or if an independent program included them? I’ve found some rather stark answers to these questions which I’ll summarize below. It’s not consistent at all for most urban centers with off-the-cuff responses to my Reddit thread.

Some Census Geography Concepts

Readers all use city, metropolitan area, and the like in everyday conversation. But most do not fully understand how the Census Bureau defines and designates areas in the U.S. as urban, metropolitan or non-metropolitan areas. I’ll give a brief synopsis with illustrations to help the reader better understand the results for activating parks. The definitive reference guide is the Census Geographic Areas Reference Manual (or GARM). If the reader skips this section, the results following it may become confusing.

Shown below is a map of the Continental U.S. (CONUS) with states and Census Divisions illustrated. The red “blobs” are urban areas, largely representing cities in the country. Those areas in blue are metropolitan areas as designated by the Office of Management and Budget (OMB) every few years. The of green areas are micropolitan areas, largely thought of as smaller cities unto themselves. The light tan areas are counties outside of metropolitan areas, called non-metropolitan counties. They are highly visible, for instance, in the Midwestern states and elsewhere. They are what most would call rural areas. These are the officially defined geographical designations from the Bureau of the Census I used in this study.

This is a high-level visualization, of course, so we need something more specific to better understand the spatial mismatch of POTA sites, hams, and local parks. The graphic below further illustrates and officially defines several of these geographic concepts. (I used to give PhD students in my spatial analysis course an exam on all this geography.) I’ve used Los Angeles as an example with the Death Valley area as a supplement.

We can think of Urban Areas as the central urbanized portion of metropolitan areas. Not all of the space within metros consists of “concrete-and-steel” as Dr. Jeremy Porter and I demonstrated a few years ago using nationwide remote sensing imagery with these Census Bureau boundaries. Urban Areas do nonetheless reflect the most developed geography within large cities. In fact, they help define the specific metro area itself (see definitions). Metropolitan Areas consists of a core (“big”) county with adjacent counties with strong commuting ties to the core county. Micropolitan Areas, by contract, are smaller urban centers with a smaller core county and adjacent ones. We often think of them as middle sized cities situated distinctly apart from larger metro centers. The Core-Based Statistical Area (CBSA) is a combination of Metropolitan and Micropolitan Areas which give a larger geographic unit characterizing a set of adjacent and economically integrated units. Finally, a Combined Statistical Area (CSA) puts together two or more adjacent Metro or Micro areas with strong economic and social ties (“bedroom communities,” satellite cities, edge cities, and so forth). The Bureau usually considers the non-metropolitan counties not included in the above categories as rural areas.

Parks, Hams and Analysis Procedures

These geographic concepts are used to compare the locations of POTA sites to licensed hams with HF privileges, the ones most likely to participate in field activitions. I did restrict these hams to those with General or Extra license classes. Technicians have limited HF privileges but comprised only two percent of all activators in 2025. I used the Trust for Public Lands ParkServe_(tm) database which contains all known parks in the U.S. to identify “local” parks. There are several classes of parks owned or managed at the sub-State level. For simplicity, I only use the municipal (or city) parks here. These are most identified with local government jurisdictions.

The TPL works with local, state, federal, private, and multi-jurisdictional entities each year to identify and track protected lands. Parks are an essential part of these lands. This is a far superior resource for the identification of parks, especially and the state and local levels, than is the approach taken by POTA Inc. The fact that a large team with state representatives monitors these protected lands annually ensures that the parks included meet specific criteria with yearly updates in any relevant changes. I believe that the POTA organization leaves this up to the local Mapping Coordinator who may not actually reside in the state of reference and who may well not annually verify each POTA entity.

To be included in the ParkServe database, a park or ‘park-like’ place must meet the following criteria:

• Be located outdoors
• Be a named destination (e.g. not an unnamed median or drainageway)
• Encourage informal public use (e.g., the public is encouraged to walk through and stay awhile)
• Encourage at least one ‘park-like’ activity such as socializing, enjoying nature, or play/exercise

The TPL performs many more analyzes to evaluate parks for access, amenities, climate, and so forth. This results in both a ParkServe Index score as well as prioritization of areas needing access to more parks for the population surrounding the local areas.

Municipal-owned parks from the ParkServe database in the 48 Continental States (CONUS) totalled some 101,301 park entities. By accessing the POTA.app website, I downloaded the list of POTA sites as of late December 2025 with their assigned latitude and longitude coordinates and activation summaries, reflecting point data for their list of official entities for activation. To profile the ham population, I used all licensed General and Extra amateur license-holders in the FCC ULS database for circa 2025 (downloaded January 1, 2025 to reflect the end of FCC transactions for the previous year). Those whose license had technically expired but remaining in the database (a known practice to preserve the ability to renew an expired license within two years) were excluded (see Snapshot article). For this study, I included only hams in the Continental U.S. (excluding AK, HI and territories).

This included 191,282 Generals and 159,522 Extras for a total of 350,804 HF-privileged hams in the continental U.S. These are called GE hams throughout the study. Yes, I realize that Technicians do have some limited HF privileges and note that in the narrative as only two percent of POTA activators in 2025 were Technicians. I omitted legacy Novices (5,028) and Advanced licensees (29,327) from this analysis for convenience. Should the reader think that these omissions would change the results, I’ve described the methods sufficiently to replicate them with Novices and Advanced licensees included if so desired. Technicians (381,563), long the largest share of amateur licensees (49.8%), were also extracted for use in a later part of the study. Again, these numbers only reflect those in the Continental U.S.

What are the Issues Addressed in this Study?

The questions guiding me are these:

• Where are POTA sites collectively located and how does this compare to the urban concentrations of HF-privileged hams (Generals & Extras)?
• Are local municipally-owned parks substantially more or less accessible than POTA sites to GE hams in urban areas?
• Is there an imbalance in the access to POTA sites for urban hams and how large of a share of GE hams are affected?
• Does there appear to be a significant market of hams to warrant a new program that organizes local parks into an online system facilitating their activation?

POTA Sites and Municipal Parks in the U.S.

Here is a repeat map from the Snapshot article of the POTA locations extracted from the official POTA.app website. Each one is shown as a red dot over a map of the U.S. with metropolitan and urban areas shown in varying shades of gray underneath on the basemap.

By way of general reference, the map below is very similar to the one above for POTA sites. It displays municipal parks shown as blue dots. Obviously, they are clustered in cities where local governments own or manage them. While there are many more local municipal parks than POTA sites, their pattern clearly emphasizes city locations, many more in urban areas than in the non-urban population areas. While the spatial scale is national, we will see below how the accessibility varies with POTA sites for GE hams.

A well-known GIS issue of spatial scale is why both maps appear to show parks everywhere hams might be located. We need to examine smaller areas to determine whether there is reasonable access to POTA sites and, if not, whether local parks might resolve that issue for most urban located GE hams. A large area might appear inundated with parks until one has to actually drive to one. Let’s take a closer look.

Spatial Access Profiles of POTA and Municipal Parks

Before jumping into the results, here is an example of how spatial access is measured. Shown below are excerpts of two maps illustrating an area east of Atlanta GA. The center point of each hub is the location of a POTA site with all of the GE hams for which it is the nearest POTA site (first map, in red). I created a polygon around the furthest points for related ham operator locations, reflecting the minimal “friction of distance” to activate their nearest POTA park. This polygon is called a convex hull in math and is a common spatial tool in GIS. I have done the same thing for the second map (in blue) depicting the nearest municipal park for the same set of GE hams. To compare how accessible each park is, we compare the relative convex hull size of each POTA and municipal park. A numerical number that is useful for this is the area in square miles within each convex hull polygon. The larger the polygon, the longer the average distance it is from GE hams to the nearest park.

In the profiles for the cities below, I will omit the hub-and-spoke elements for clarity and overlay only the POTA and municipal convex hulls on the base map. This will give the reader an explicit visualization as to how accessible each type of park is to GE hams in the region.

Profiles for Several Major Cities on Park Access

This is a summary of accessibility for five metropolitan areas and cities across the U.S.: Atlanta, Chicago, Dallas-Fort Worth, Los Angeles and Seattle. All have significant average drive-times in their respective traffic patterns. In the maps below, the pink polygons are the convex hulls for POTA parks, depicted as red dots. The blue-purple polygons are similar convex hulls for municipal sites. These are noted in the legend. In general, the reader will see a far greater pattern of accessibility to municipal parks in these large U.S. cities than for POTA sites. Let’s go through each one.

The Atlanta core urban area (above) contains a high concentration of GE hams, some 7,734, although the growth of the northern suburbs has exploded over the past few decades. But there are only two POTA sites in the core urban area (see center pink polygon). The travel distance is much, much longer than to the many, many municipal parks. As the reader examines those burgeoning suburbs, the same pattern is present: far more accessibility to municipal parks than to the sparse POTA sites. This is only visible using the appropriate spatial scale.

Chicago (above) is a major urban center in the Midwest, a long-time growth location in the history of the United States. It, too, is a suburban-growth metropolitan area. There are 10,058 GE hams in the Chicago urban area. Chicago has no POTA entities in the urban area. There are a small number outside in the southern and western suburbs. But, as with other urban centers, there are numerous municipal parks available with short travel distances for GE hams.

The Metroplex (above), as the Dallas-Ft Worth metropolitan area calls itself, is a surprising case. It is a spread-out urban development in many ways. So one might expect more POTA sites than in, say, Atlanta or Chicago. But there are only two: one in northeast Dallas and one in southeast Fort Worth! With the drive time associated with the Metroplex, these two POTA sites require a significant period of time to activate. The many municipal parks, by contrast, do give many GE hams access for the figurative hour-long activation. There are 11,050 GE hams in the Dallas-Fort Worth urban area, slightly more by comparison than in Chicago.

The drive times in Los Angeles (above) are famous. Famously long, that is. This can place a clear burden on hams who want to engage in POTA activations. The map above illustrates the relatively few POTA sites in the greater Los Angeles metropolitan area. The convex hull depiction of POTA site distance illustrates this in a city where there are 22,276 hams with General or Extra licenses as of December 2025. The number of municipal parks are far more accessible than are POTA entities in LA. This gives a birds-eye view to why Ivan WC2S asked why can’t I activate a local park in POTA? There are so many more of them!

Seattle (above) is a city culturally focused on outdoor activity with mountains, water and other recreation pursuits nearby. There are several POTA sites in the Seattle urban area. In the Seattle-Tacoma urban core, there are 13,171 GE hams living there. But even in an outdoor-driven locale, the accessibility of municipal parks is far superior to POTA sites in the region. The blue-purple polygons characterizing the “service area” for each municipal park for the GE hams nearby is rather clear even in the metropolitan urban core with several POTA sites in the general area. The traffic congestion in the Sea-Tac area, focused on the I-5 interstate, is just below what it infamously is in Los Angeles. This added element to POTA activation makes getting to an activatable park site a greater time sink.

These major cities illustrate clearly how relatively sparse POTA sites are in their urban centers. The question remains: How do these major cities compare to the nation as a whole? And does this POTA site scarcity in urban areas keep a significant share of HF-privileged hams from activating those parks? I present summary data on national patterns now. They provide rather clear answers.

National Patterns for POTA and Local Municipal Park Accessibility

I have summarized the national results of this type of analysis in tables below. They provide a clear, focused picture of the relative distances for hams holding General and Extra tickets to POTA sites versus local municipal ones. The gap in accessibility to POTA vs municipal parks by urbanization is fairly stark. To my knowledge, I have never seen the identification of licensed amateurs across the rural-to-urban classifications used by the Census Bureau so this too is a new set of findings in the ham radio literature.

This table shows the number of hams, their percent composition, POTA sites and their respective share, and the imbalance of POTA sites by urban and metropolitan areas. The number of cumulative (lifetime) activations for POTA sites and their share are also included. Finally, the local municipal park number and share (percentage) round out this summary of parks, activations and how they vary by urbanization zones across the U.S.

I also illustrate parts of this table through bar charts below but let me emphasize the spatial mismatch indicators at the outset. Well over one-half of the GE hams in the U.S. CONUS, some 8 out of 10, are in metropolitan areas, largely similar to the general population. They are concentrated in urban zones within the metro area (62.3%). This provides a great imbalance in the locations of POTA sites here. Over a third of these sites (38%) are in the non-urban metro areas with only a very small share (6.5%) in urbanized areas. This imbalance is rather stark relative to the ham population residing in those areas. I include an imbalance ratio of the share of POTA sites to the share of GE hams as a summary figure.

The two bar charts help crystalize this spatial mismatch. POTA sites, largely due to their National Park origins, are mostly outside of urban centers in Metro areas (see left). There are many in rural (non-metro) counties. The mismatch comes with the spatial concentrations of GE hams (see right). Most are located in urban centers of metropolitan areas. Only small shares of GE hams are in non-metro counties or in Micropolitan areas near the third concentration of POTA sites.

How busy these POTA sites are with activations tends to reflect this imbalance. The great inequality of lifetime activations noted in the Snapshot article for the nation as a whole can be partly explained through their location. As shown in the table, half of all activations are in those POTA sites in non-urban metro areas (49.1%). Only 17.6 percent occur in urban portions of metropolitan centers. This is very similar to those in non-urban, non-metro (“rural”) areas. Small cities (micropolitan) have a slightly smaller share (14%). The rest are very nominal in size. Thus, activations in the whole tend to not be where the vast majority of GE hams live. Does this restrict the number of activations by a majority of POTA activators, leaving it to the smaller share of extreme activators? (See my Snapshot article on this.)

In general, consumers obey the “friction of distance” in their shopping behaviors. The closer options tend to receive more shoppers. To give an overall picture of the pattern of distances from where GE hams live to POTA and local municipal parks, I’ve created two simple histograms of these distances in miles. To increase clarity, I truncated the chart to 30 miles but the full range is used to compute descriptive statistics. The average distance for POTA sites is about 7.53 miles. For municipal parks, it is 3.69 miles, an approximate four-mile difference on the average. There are a very small share of hams who live much larger distances than the 30 miles shown to a POTA site as well as the nearest municipal site.

To give a further summary of the accessibility to POTA sites for urban and non-urban areas, I computed the number of GE hams per POTA site within each metro and urban category. This metric is a rough indication of the potential demand for access by these license holders. (This is not unlike corporate site-selection metrics.) The category where most POTA sites are located (shown above) is in the non-urban areas of metropolitan areas. There are 14.9 GE hams per site there. For the inner city urban area of metros, there are many more GE hams, some 280.5 per POTA site! This shows the tremendous potential contention for those sites as Ivan WC2S and Kevin KW6E described in our Zoom conference. It also illustrates the tremendous market for park availability for them to activate should local parks be available.

Smaller isolated micropolitan areas also have a much smaller market, but it depends on the urban status of POTA sites and GE hams. There are 122.1 hams per POTA site in Micropolitan urban areas but only 8.8 in the non-urban regions within them. This reflects another spatial location for park contention and a market for potential expansion to local parks.

The non-metropolitan counties, commonly called America’s rural areas, have another substantial urban gap. In urban areas in non-metro counties, generally thought of as small towns, have ten-fold more hams-per-site (64.3) as those in the non-urbannon-metro areas (6.0). These data show the stark lack of accessibility by urban-based GE hams regardless of whether they are in metro, micro or non-metropolitan zones.

What is the Overall Accessibility to Parks for GE Hams?

While these results make a strong case that urban hams with GE credentials are not well-served by the POTA program, questions remain. How far are they from POTA sites versus local municipal parks? The two histograms above do show a prominent disparity favoring local parks. Moreover, are there cases where POTA sites are closer to GE hams than municipal parks? Remember, it is about the relative spatial proximity of sites to hams.

In the earlier section on major city profiles, I used the convex hull polygon to illustrate how large or small the spatial distance was for each GE ham in the area to POTA versus municipal parks. The area in square miles within those polygons represents the closeness that each type of park is to GE hams for which it is the closest entity. The table below is a summary of that nationwide analysis.

It should not be surprising that the average area in the convex hull representing the nearest park service zone, whether using to the mean or median, is much smaller for municipal parks than POTA sites. This shows how the “friction of distance” is far less for municipal parks because that is where most GE hams are located! The average area for POTA sites is 118 square miles while for municipal parks it is one-fifth that at only 20 square miles. The median, where one-half of the parks are above and below the figure, is 52 for POTA sites and 0.3 for municipal parks. These patterns are rather dramatic by comparison. However, the minimum and maximum illustrate that there are also very large municipal parks (max = 6,652 vs 4,031 for POTA).

Compare the area of the convex hull above to the average distance from the same set of GE hams to POTA vs municipal parks in the line chart below. The urban area effect is clear by comparing the red and blue lines in each chart. The lines depict the difference between urban and non-urban areas in the average distance to the nearest POTA and municipal parks. The three charts pertain respectively to metropolitan areas, micropolitan areas and non-metropolitan counties with urban areas within them. This summary of average (crow flies) travel distance illustrates the three-part elements of the locations of POTA sites, municipal parks and GE hams. It takes all three components to best understand accessibility.

In urban metro areas, for example, the average distance to a municipal park is under two miles. It is over seven miles to the nearest POTA site. All of the urban average distances are about the same regardless of metropolitan classification as for non-urban distances across these metropolitan categories. Thus, for the continental U.S., municipal parks are closer to GE hams than area POTA sites by several miles on the average. The sole exception occurs in the most rural locations, non-urban non-metro areas, where POTA sites tend to be located themselves and are therefore closer.

Are there any POTA sites that are closer to GE hams than municipal parks? Well, yes there are. But not that many in the scope of the full set of licensed hams. Here is why I say that.

The pie charts above show the results for comparisons where POTA sites are closer to individual GE hams than their closest municipal parks. The results are further indications of the spatial mismatch of GE hams and POTA sites with municipal parks being situated in urban areas. Few POTA sites are closer in urban metro areas (8.6%) but more so in non-urban ones (16.1%). Most all municipal parks are closer in for urban metro hams (91.4%). This reverses in Micropolitan areas as almost a third (33.1%) of POTA sites are closer in the non-urban areas there. This drops to about one-fifth for urban micropolitan cities (19.3%). Finally, for non-metropolitan counties, a similar pattern occurs with a fourth (28%) having hams with POTA sites closer than municipal ones. This is not the case in rural areas with urban centers (small towns). Some 93 percent (92.8%) have municipal parks nearby with only some 7 percent (7.2%) with POTA sites being closer. I hasten to remind the reader that the greatest concentration of GE hams is not in rural or suburban areas but in the urban zones of metropolitan areas.

What Have We Learned About the Location of Hams and POTA Sites?

The rather elaborate results show that urban General and Extra Class hams are significantly under-served in access to the POTA program’s current park entities. These parks are just not where the hams live. Booking a longer period of time for portable ham operations is required for GE hams in the largest metropolitan urban centers. I’ll hasten to add that some 62 percent of GE hams live in those areas. There is also time contention for sparse urban sites where there are many hams who want to activate them. Ask Kevin K6WE who lives in Silicon Valley. He has an alert set just to let him spot activators in the single POTA site in his general area. Why? So he won’t pack his gear and drive to one of them only to find RF contention for his transceiver from other hams doing an activation. This scenario is due to the spatial locations of POTA sites, the concentrations of GE hams in urban centers, and the much longer drive times in the transportation networks in those areas.

A classic spatial mismatch interpretation fits these results. By and large, POTA sites are not where the most General and Extra amateur operators live. Thus, POTA sites are activated mostly by a small group of extreme activators and in a small group of POTA sites. The majority of activators in 2025 reported 5 or less such successful trips (median number). (This is from the Snapshot article.) This mismatch is not purely a result of POTA Inc. making intentional choices. Indeed, the National Parks program in the U.S. represents some of our earliest protected lands (thank President Theodore Roosevelt). They were intentionally located in what was then more isolated areas away from urban centers. Adding a mix of state-owned and managed park sites by POTA Inc. merely increased the mixture of official POTA sites that are outside of the larger urban metro centers where most GE hams live.

Even though unintentional, the official list of POTA sites does fly in the face of consumer behavior by ham operators. The well-established “friction of distance” does guide consumer choice, such as choosing a park to activate in POTA (or perhaps, not activate at all). But is it a problem? Can’t urban-based hams just drive to a POTA site and enjoy the countryside? Yes, they can. Obviously, some do. But it does come at a price for the majority of POTA-activating ham operators. For those hams who participated in POTA activations during 2025, my statistical modeling results show that for every mile further the nearest POTA site is, hams activated one-half fewer times during the year (i.e., a reduction of 0.5 activations per mile). This suggests more study in future articles but suffice it to say here, where hams are located does affect the choice of parks and the number of times they activate them.

One large issue not directly addressed here are Technician Class licensees. They account for about half of all licensed amateurs in the Continental U.S. (49.1%). Yet, only two percent of them reported POTA activations in all of 2025. This is a topic for further study in future articles.

What can be done? Some ardent POTA fans would (and have on Reddit) say, “Shut up and operate.” Wow. That attitude leads to consternation, frustration and, likely, a movement to solve the problem through competitive means in the marketplace. What do I mean by this? POTA Inc. has said in writing to Ivan WC2S that adding local parks to their system is not going to happen. That is certainly their corporate choice and I for one am not asking them to by implication of these research results. Perhaps it is beyond their technical capability to handle these many more parks. For whatever the underlying reason, they have spoken and they are not going to undertake this.

Is it worth a grassroots movement to launch an independent “park activation” program for local parks? It might be but that coming to fruition remains to be seen. I hope this article has provided some data-driven facts for consideration to those interested in portable operation in parks across the U.S. It’s a great activity space that should be more accessible to all.

We often read that POTA is the “fastest-growing activity in U.S. amateur radio.” I’ve said it, too. Several times. I think satellite operations are a distant second growth activity. But do we actually know much about POTA activity growth through empirical data? My impressions are based on guesstimates from data on Canada where I analyzed a national survey of hams conducted originally by RAC. In 2001, some 37% of those Canadian hams said they engaged in portable operations, including POTA, SOTA and the like. It ranked 9th among 37 common ham activities in the survey. They reported to the tune of 15.7% participating in satellite operations. Alas, we do not have parallel data on U.S. hams so these are inferences made from comparative data. But data nonetheless.

It is not unusual at all for most of us to gain our impressions of ham radio activity through social media. Heck, there are Youtubers who say they make their living from their channel(s) and associated activities! Those who do not work at it full time or don’t even monetize their outlets add significantly to the mix of media impressions. So if POTA activity gets a very large share of social media output, our best guesses are shaped by those impressions in the absence of empirical data themselves. This applies to things other than amateur radio, like politics. You get the point. In a vacuum of data, we get captured by social media.

To illustrate, here’s a Google Trends result from using both “Parks on the Air” and “POTA” as search terms with a five-year window ending circa January 25, 2025. In the dual trend lines, POTA wins as a search term but both show a marked, continuing, and slightly growing interest through search terms on Google. The brand “POTA” seems to have currency in Google Searches as a frequently-used proxy for all social media output. Thus, social media impressions are strong in this one!

We need data to complement what we see through social media. In this article, I present a brief snapshot on POTA activity among U.S. hams. I use data actually reported to the POTA website to describe where all of the current U.S. POTA sites are located. I also examine 2025 annual data for all activators as well as all activations reported to their website. I have not seen any research like this reported by the POTA administration or other hams. If readers do see what I’ve missed, I’d appreciate receiving the link. I’m good on QRZed.

Here’s a snapshot of key POTA elements using these data. I use maps and basic statistical tools to help describe patterns in POTA activity. The results are organized into POTA sites, activations and activators in 2025. I think the reader will gain much greater insight into the POTA program activity since inception in 2017 through these data.

POTA Sites Across the U.S.

Owing to the origination of the POTA program as a continuing expansion of the National POTA program by the ARRL, these official sites include national parks. These favor undeveloped areas (and cannot be developed without permission) outside of urban centers. POTA adds many, though not all, state-controlled parks and similar preserved entities. They add or remove POTA entities on an ongoing basis. As of December 2025, the map below illustrates the locations of all POTA sites in the U.S.

The map shows definite visual clusters of sites in the Northeast. Although not shown, this region also has a high density of licensed hams. Florida, Missouri and Utah also have clear and distinct concentrations of POTA sites. These are followed by Michigan, Washington, Arkansas and California. These states have internal clusters within the state characterizing POTA site distributions. Note that these are both Federal and state-controlled parks and related sites (wildlife management areas, etc.).

The data show that POTA sites are far from uniformly distributed across the U.S. Given the basis for founding the POTA program on the sunset of NPOTA by the ARRL, we would not expect them to be for U.S. Parks alone were founded to be undeveloped protected areas away from urban centers. This map puts a finer point to where official POTA sites are located. In future articles, I’ll show more details at finer spatial scales on the characteristics of POTA site locations.

POTA Activations

While POTA sites are all over the U.S. and not uniformly distributed, how frequently each one is activated by hams is far, far less uniform in nature! I took each POTA site’s lifetime activation numbers and put them on the map below. After examining a histogram of the distribution (not shown here), these intervals were placed on the number of times each park was activated: 0-1, 1-1000, 1,500-2,500, and 2,500-5,381 (highest). They seemed to reflect the observed cut-points in the activation data.

While most parks have been activated at least once—although difficult to see on this scale—I emphasized parks by size of the circle, colorizing each category. Those with the largest circle shown in red are the most highly activated POTA sites in the U.S. Where are they? Mostly along the Appalachian Trail, near the popular vacation spot of Orlando FL, in the Midwest, and one in the Northwest in Washington. Those one step down in size shaded in blue tend to follow this same pattern with the exception of one in Colorado.

These results show that there is some linkage of POTA park activation frequency to distance from the market of hams for activation. In consumer economics, the “friction” that distance to any consumer choice will generally favor shorter choices over longer ones, especially over time. This tends to affect the frequency of consumer choice such as which POTA park to activate. The map of most popular activations in the POTA program is consistent with this long-standing consumer behavior paradigm.

Friction of distance in consumer behavior represents the time, effort, and financial costs required to access goods or services, causing a reduction in interaction as distance increases. This concept drives consumers to minimize travel, favoring closer options, which impacts store choice, purchase frequency, and online engagement by reducing cognitive and physical load. 

The reader might look at this map and think that this is not clearly reflecting this phenomenon. While it does depend on the market of hams and that subset who participated in POTA since the 2017 inception, it is a fair question. I’ve put another visualization of how unequal the distribution of activations across parks in this program is from 2017-2025. The curve in the graphic below reflects the following. The number of activations for each park was sorted from highest-to-lowest with the cumulative percentage computed for each. The ranks from 1 (most activated) to 11,996 (least activated) came from the original sort. The cumulative percentage of the total activations that each park represents is plotted against the rank. (In statistics and economics, this is a type of Lorenz Curve.) This curve tells us just how much of the total lifetime activations are reflected by each park. If each one had an equal share, the line would be flat and straight from zero percent, rank 1 to 100 percent, rank 11,966 (number of POTA parks).

I have placed three lines noting the share that the top 100 parks (green), 500 parks (blue) and 1,000 parks (red) are of all activations ever reported to the POTA program. The green line intersects the 20 percent line of all activations. In other words, 100 parks account for one-fifth of all activations. The top 500 parks account for some 40 percent. Finally, the 1,000 top parks out of the almost 12,000 POTA sites account for one-half (52%) of all POTA activations since the program began in 2017. This is a highly unequal distribution demonstrating the dominance of a small portion of POTA sites in total activations.

POTA Activators in 2025

Who are POTA activators? This is in intriguing question as social media profiles suggest they are significantly comprised of hams who face housing restrictions on home antennas outdoors. Not all of them, but enough to make a clear inclination toward portable operations in the activity space of Parks on the Air^(tm). I’ve shown two pie charts below to illustrate the composition of POTA activators in terms of license class. On the left are all amateur licensees in States (no territories) as of December 2025. On the right are POTA activators in 2025 using U.S. call signs, individual licenses (no clubs).

Note: I always remove those licenses that have reached their expiration date. The FCC ULS data system does not. This is for their convenience since an expired license is dormant but can be recalled for activation by the operator within two years. The FCC database management team simply keeps this license record in the database in case of that recall. This is for their operational convenience. This often confuses hams who just download the ARS data from the FCC ULS system and compute totals without fully understanding the curation protocols in the data themselves!

As has been made widely known, Technicians are the largest operator class in the U.S., here over 49 percent. Generals are next at about one-quarter with Extras comprising about one-fifth. The dormant Advanced Class (about 4 percent) and Novice Class (less than one percent) round out the distribution of operator classes at the end of 2025.

POTA activation is dominated by Extra and General Class licensees. Over half (57%) hold Extra Class licenses with almost forty percent being Generals (39%). Only two percent (or 257 hams) reported activations in the POTA program. Another two percent (rounded to the percent) of Advanced tickets participated in POTA park activation. These data show that it’s an HF-privilege game, largely, as only 257 Technicians used the meager HF privileges they have to activate a POTA park, unless they were using other modes facilitated by their band privileges. It’s almost an all-General/Extra affair in POTA at this point.

Some POTA activators are far more active than others. To illustrate this, consider the box plot shown here. The average number of activations in 2025 was just over 23 (mean = 23.4) but ranged from 1, the minimum, to 3,396! The median number is 5 with the mode just being a single park activation (the mode being the single most occurring number). The distribution of individual ham POTA activations, not unlike what we saw for parks, is highly skewed. This suggests that the social media haze of the fastest growing activity might be based on the extreme number of activations by a small number of hams.

This box plot represents the percentile distribution of the number of total activations by each POTA activator reporting in 2025. As the bottom text details, out of the activations last year, one-quarter reported 2 activations (Q1, or lowest quartile). One half reported 5 activations (median). Some three-quarters activated 19 or fewer POTA parks (Q3 or third quartile). Those activators reporting 20 to 3,396 are classified as extreme values. I’ve put a black rectangle around the hams whose number of activations reflect statistically extreme values in this distribution. They are shaded in blue. These extreme activators contribute a lot to the POTA program while the vast majority of portable operators reporting to the POTA program reported less than 20 last year. Do the extreme activators garner the bulk of the social media presence regarding POTA activity?

To flesh out where these extreme POTA activators are located, I’ve created the map below. There are light green and dark green points. Together, they represent all 2025 POTA activators reporting to the program. The dark green points are the license locations of these extreme POTA activators. They are concentrated along the Appalachian Mountain trail and environs in the subregion. They are scattered throughout the rest of the U.S. in small clusters within states we have mentioned before. I’ll demonstrate more below. But I want to emphasize that the dark green points reflect hams who repeatedly activate POTA sites in extremely higher numbers than the vast majority of POTA participants.

To help the reader see the connection, I have put all POTA activators on a map with the most activated POTA sites as shown above. This map also has urban and metropolitan areas designed on the base map. This will become more important in future articles on the POTA program. But for this snapshot, it confirms the role that distance to POTA sites plays in the frequency of activating any POTA sites.

In an analysis not shown here, I estimated a spatial regression model (spatial lag specification) predicting the number of activations by the distance in miles to the nearest POTA site for the ham operator. These are for those hams who participated in POTA during 2025. The results show that for every mile further the nearest POTA site is, the ham activated one-half fewer times during the year (i.e., a reduction of 0.5 activations per mile). I’ll study this more in future articles but suffice it to say here, where hams are located does affect the choice of parks and the number of times they activate them.

Thoughts

This snapshot provides the first look at the POTA program from a national scale using data rather than social media impressions or conversational anecdotes. What do we see?

There are a small number of POTA sites that account for at least half of all activations since the program began. Not surprisingly on the heels of this finding, there are a small number of extreme activators who account for a significant share of last year’s POTA activations. These extreme activators are scattered throughout the same regions as the most activated parks. Perhaps I will examine those patterns in a future article but the empirical fact remains: POTA is dominated by a small share of extremely active operators, almost all of whom hold General or Extra Class licenses. The largest license class, Technicians, are just not part of the game in this activity space in 2025.

As in most consumer behaviors, distance to the “product,” here a POTA site, shapes the frequency of consumption. My initial regression model showed a one-half activation reduction over the year for every mile that the nearest POTA site it to hams who reported activity during 2025. This result begs for further analysis. Has it been this way since the beginning of the POTA program (2017)? Does the ham’s location in the rural-to-urban residential continuum affect this “friction” of distance? Perhaps we will find out in future articles.

This descriptive snapshot gives the reader a clearer picture of where POTA sites are and which ones are most popular for activators. But the majority of activators pale in comparison to the extreme activators. The median for 2025 was just 5 activations, illustrating that one-half reported less than five with the other half more than five. The mode was a single activation. Are the social media reports indicative of these “small timers” or of the extreme activators? Well, watch social media portraying POTA for yourself. There could be a lot of experimentation by hams in 2025 who just did a POTA activation to see if it was for them, then decided it was not. Or they just did it as a social activity with ham friends and the schedule precluded more activations than just one or a few last year. We don’t know. But it appears that longer trip distance to activate a POTA site might largely eat away up to a half day, something that many amateurs would not have very frequently available for this activity. These data are consistent with that pattern.

Clearly the initial finding that 2025 POTA activators activated less as the nearest official site was further away begs for additional analysis. Distance requires an increased time commitment. Those on social media who both frequently activate POTA sites, especially serially in a “rove,” devote a significant amount of time, money and preparation in doing so. Nothing wrong with this. But how common is it within the market of amateurs interested in POTA operations? Not very, these data suggest. It begs the question of where are most ham operators located relative to existing POTA sites? Are they too far away to be practical for their sphere of obligations to activate official POTA sites very much?

I’ll explore this avenue in future articles because it is important to gain our impressions from data rather than the pantheon of what we see on social media, particularly where the outlet is monetized on the content creation surrounding their POTA activity. We reported results suggesting that it may just be a small group of all activators who live in some favorable propinquity to POTA sites themselves or who monetize their time expenditure for POTA content creation (i.e., they are “working”). This leaves out many hams because of the choice of sites by the POTA program and the legacy of National Parks as the foundational base for the program itself relative to where they live.

I’ll close with the observation that Technicians are only two percent of the reported activators in 2025. It seems a shame that these licensees don’t have more of a place in this activity space. Getting 2 meter simplex working, for instance, would be very challenging for many POTA sites. Are there other viable options to engage the largest group of hams in the U.S. license classes into more portable activations in parks? Yes, SOTA is one. It takes SOTA sites with significant prominence to facilitate such contacts that could count as a two-fer (SOTA and POTA). SOTA sites are not uniformly distributed to offer universal access either. It seems a wasted opportunity to have POTA sites that do not overtly engage Technicians to participate at a higher rate than merely two percent of all activations in the most recent year. I’ll look into this in future articles.

Listeners to the ICQ Podcast where I appear monthly as a Presenter probably heard me say that I was successfully treated for a highly aggressive prostate cancer (adenocarcinoma, Gleason 8) almost two years ago at the Mayo Clinic. While in Rochester for two weeks, I had a lot of time in bed recovering from the surgery before being released for home back in Mississippi. For me, I tried to keep my mind on things besides the cancer treatment as I had the top prostate cancer hospital in the U.S. treating me and the top robotic surgeon, Dr. Igor Frank, at the helm. So what does a ham think about in this circumstance? Let me tell you…

Antennas! I worked out plans for a half dozen portable antenna designs that had been smoldering in my brain before the unexpected diagnosis and biopsy. Don Field, Editor of Practical Wireless, expressed an interest in first dibs on each manuscript resulting from my experiments with portable HF antennas. Here are a few that are published or in-press as of this writing. And more to come.

Eiffeltenna

Based on the almost whimsical Youtube video by Jim Heath W6LG (now sk), I considered the photography lighting tripod, ubiquitous in the camera industry. Jim put together a quick-and-dirty (unusual for him) vertical antenna based on a type of tripod construction that electrically isolates the three legs from the telescoping vertical part. Brilliant! They are inexpensive so I bought a few from Amazon or eBay to experiment with. I paired the tripod with a 17′ telescoping whip and an inductor coil, finishing off the “fine French dining” concept with a tablecloth underneath of Faraday Cloth. Following my focus on making each section having a low resistance electrical connection when extended, it works very well. Very quick to set up, take down, and pack. It appeared in the October 2025 issue of PW. Bon appetit!

Delta Vee AutoLoop

Loop antennas of all designs have fascinated me since I was a teen building classic ones for AM BCB DXing. I have a sort-of horizontal loop around the edges of my roof due to HOA restrictions. )I have also written about that in PW-see March 2023 issue.) When Chameleon released their Tactical Delta Loop, I took a look at my friend, Steve KM9G’s take on it (see Temporarily Offline on Youtube). He found it was very flat across most HF bands. Hmm. Lawrence Cebik’s earlier models of loops, including the Delta geometry, showed that it has harmonics based on the design band and that height above ground places a significant part in the feedpoint impedance. What antenna magic have the Chameleon engineers come up with? Whatever it was, it priced out at over $400 USD.

From watching TO’s channel and the brief review of Michael KB9VBR, it appears that they use a fixed 5:1 balun to get the impedance down to the 50 ohm ballpark. I don’t understand TO’s flat SWR but antennas nearly on the ground can do funny things. So my take on the problem here was we can choose to optimize the balun wind for a certain band with some higher band harmonics working against a tuner for a reasonable match or just have a single band antenna. But wait. Why not use an ATU at the feedpoint to optimize the match across most HF bands? This only becomes practical with a light-weight battery-powered, RF-sensing ATU mounted directly at the “bare wires” from the loop’s geometry. That’s what I did here to create what I call the Delta Vee AutoLoop. I use a $40 used surveyor’s tripod without the head made by Manfrotto. It was purchased at a local electronic recycling center but I bought another on eBay for the same price. The head is what surveyors want so one without it is far cheaper. It has a standard bolt that I connect to an adaptor for the mount point as explained in the PW article.

Randy K7AGE says he’s building one to use on his parked truck when out doing POTA or other portable operations. This antenna appeared in the January 2026 issue of Practical Wireless.

Random Copper Stick

I had been puzzling over these carbon fiber masts since they came out. My friend George KJ6VU cautioned to me that they wouldn’t load up and they played havoc with his Packtenna wire antennas if they come in contact with them. So, bah humbug! Then I ran across Ben VE6SFX’s Youtube video on an experiment with on using Faraday tape on the outside of the carbon fiber mast. He said it worked as a random wire type of antenna! So, after working my brain for months on an angle for this, Ben’s experiment gave me a direction.

The Random Copper Stick was built by using a carbon fiber telescoping mast and copper tape—both 1 inch and 1/8″ widths—applied from the bottom to the top for each section of the disassembled mast. The very top section was removed as it was way too small to hold the tape. This gave me a reasonable length for a random wire antenna. My experimental measurements with a 17′ wire (20 meter measurement) showed a fairly clear phenomenon that Ben didn’t get into in his Youtube video. As shown below in a slide from a talk that I give to clubs on these experimental antennas, the carbon fibers disturb the relationship between the physical and electrical lengths of the wire as they are closely connected to the mast. (Score one for George KJ6VU’s observations!) Thus, using a 9:1 Unun with the mast works very well with an ATU at the transceiver. To quote my lawyer friend, Mike N5DU, I was shocked and amazed at how an antenna that I was convinced would not work turned out so well.

If you fancy taking a walking stick to operate portably, consider the RCS. It’s very easy to build, back and put up. I built one for my friend Scott K0MD to take with him on his trips to pair with his Icom 705. My article on the Random Copper Stick appears in the February 2026 issue of Practical Wireless.

Wave Caster Vertical

It is scheduled to appear in the April issue of PW but that should coincide with Spring Break weather at the beach. You can build the Wave Caster to Hang Ten while working some HF bands, lol. This one is also very easy to setup if you have anything in the portable site environment to clamp the mount. in the Wave Caster, I use an idea that Chuck KK6USY published on his Youtube channel in a coujple of videos. Particularly, he solved the problem of winding an antenna wire around a spool without it getting too much stress and eventually breaking. Chuck used a small resin reel with a ring terminal to solve this problem. Well, that solved a problem I wrestled with on ways to multiply antenna designs using these inexpensive carbon fiber masts with wire that wouldn’t take much time for the portable operators. (Not all have a half day to go to a POTA site that can be far, far away with a lengthy setup.)

With a Super-C photography clamp, almost any sturdy surface can be used to “brace” the vertical so it stays up while the temporary operation plays out. Just don’t forget it when you leave because I can tell you it is easy to do! This one is scheduled as of this writing to appear in the April issue of Practical Wireless magazine.

I have a couple of other designs that I am finalizing as the wild weather in the South permits. They may appear in PW but I’ll post a notice here if they do.

My time at Mayo Clinic was well spent. I cannot overstate how positive the medical treatment there was. Mayo treats 26,000 prostate cancer patients per year and have been rated #1 for many years. There was never a moment where I felt like I was a number on a lengthy list. I was fortunate to get connected with Dr. Igor Frank there as the “top gun” on robotic prostate cancer removal. I gave him a small momento as an expression of my appreciation as I was discharged. I understand that it may have made an appearance at the Department Christmas Party.

Change has pulls and tugs toward the past and forward into the future

We hear the word culture bandied about all the time. It means different things to different people. Social scientists define it as follows:

As a sociologist and statistician, one thing I’ve observed about amateur radio in the U.S. is that culture has a strong pull towards the past. We often hear this coming out when hams begin some comment with their “tenure” in the hobby: “Well, I’ve been licensed X years and I know…” Substitute your own number of years for X in this sentence. The listener is supposed to genuflect toward this tenure in the hobby as containing superior knowledge and wisdom. Social linguists call this “indexicality” to indicate what reference is being used in the argument. (For bench testers, think “reference plane” in VNA calibration.) So many amateurs “index” their understanding of the hobby relative to when they were first licensed, especially if it was during their teen years. That understanding “indexes” everything that comes afterwards and results in much of the verbal conflict on the air and on social media. Or, in person, to the astute observer at hamfests, lol.

The power that such indexicality has on the hobby is related to the demographic composition of amateur radio at this time. The demographer Ron Lesethage documented how the age composition of a population is related to the values for having children, a predicate for population replacement. In most all developed countries, child-bearing age women no longer see giving birth as an important part of their future. This is a clear historical change with respect to how they define what is important in their lives as women, unlike their mothers and women in most previous age cohorts. This “index” by women in developed countries is an example of the power that these belief benchmarks have on society. With the dominance of Baby Boomers in the hobby, is it any wonder why so the view of many hams in terms of technology is much closer to the Spark Gap than it is, say, using digital modes like FT8?

What does this have to do with a Spark Gap transmitter?

It is a metaphorical reference point to the technological origins of the wireless which, by definition, was amateur in nature. If we consider an automobile as the ham collectivity passing through time, at what point should the Spark Gap transmitter leave our rearview mirror as a guidepost? Is that vision a stifling tug against our speed toward what is visible through our front windshield? Many historians and innovators say yes it is. Here’s an AI-assisted image to illustrate what I mean.

So many new innovations are before us. But so many index our progress against the earlier periods more adjacent to the ancient Spark Gap transmitter. This is a continuum, of course, but listen to the naysayer commentaries on recent innovation. Why are they “bad” for the hobby? Are they “killing” amateur radio? I’ve noted previously that change is often labeled as pending death to those whose indexed standards are in decline. Right now, it’s those of the Baby Boomers as they hold positions of power and influence in the hobby while they progress toward Silent Key status.

Remembering the cultural origins of an activity like ham radio should become history at some point. That is, every new initiate shouldn’t be held to norms of beginning at the beginning. It is thought that an overemphasis on history can stifle innovation. This doesn’t mean that history should be forgotten. This is not a binary argument. Quite the contrary, there is a balance and a place for history. New initiates into the hobby shouldn’t be pushed toward the historical beginning but acquire it as part of the present and immediate future’s innovation. The latter is often what draws newcomers to the hobby space.

What does an emphasis on the past do for progress?

There are several elements to the detriment of an over-reliance of early history as a main part of the culture of a group like amateur radio. An article on this by the Thought Lab says the following about it.

How an overemphasis on history reduces innovation

• Risk aversion: When experienced professionals rely too heavily on “how we’ve always done it,” they become hesitant to venture into the unknown. The fear of failure can stop the pursuit of unconventional, and potentially groundbreaking, ideas.
• Limiting frames of reference: Extensive experience and historical precedent can create a mental model of what is possible, making it difficult to conceive of entirely new possibilities. In this environment, alternatives and fresh perspectives are often overlooked.
• False confidence in expertise: A deep knowledge of the past can create an “illusion of expertise” that leads to overconfidence. This mindset can close people off to new information and different approaches, stunting creative growth.
• Subconscious bias against novelty: Research has shown that many leaders have an unconscious bias toward familiar, established solutions, especially when motivated to reduce uncertainty. This bias can cause them to reject new ideas, even if they outwardly claim to want creative thinking.
• Misguided strategic choices: As seen in Soviet technology policy, an incorrect assumption about the historical trajectory of innovation can lead to big, irreversible bets on the wrong path. Instead of building on existing strengths, leaders may shift their focus toward an ineffective strategy, weakening their own sector. 

How a balanced understanding of history promotes innovation

• Learning from past successes and failures: By studying the history of an industry, innovators can see what has worked and what has not. This prevents the repetition of past mistakes and allows for the identification of successful strategies that can be applied in new contexts.
• Understanding complex origins: History reveals that modern innovations are often built upon a long lineage of prior technologies and discoveries. This understanding gives innovators context for where to focus their efforts and avoids a simplistic or misleading view of progress.
• Questioning assumptions: Historical perspective allows innovators to question entrenched narratives and conventional wisdom. It helps them re-evaluate their beliefs by comparing them to a wide range of past scenarios, which can lead to new insights.
• Gaining resilience: Studying how past innovators and companies overcame challenges can inspire a more resilient approach to obstacles. Instead of seeing setbacks as reasons to give up, they are viewed as a necessary part of the journey.
• Revealing long-term impacts: History helps put the ethical ambiguities of new technologies into perspective. By observing the unintended consequences of past innovations, creators can better consider the potential long-term risks and societal impacts of their work. 

Readers can identify these issues within the hobby by just reading and listening for a bit. National and local organizations are legion for this “we have always done it this way.” Witness the ARRL Sections which arose when one of the Founders (Maxim) was organizing regional bodies to pass messages. Is this not a Spark Gap in the rearview mirror today? This geography to serve amateur radio in the United States is almost ludicrous. See also Onno’s article on changing the current culture in amateur radio. I could go on but this is a family-rated blog, lol.

What can we do about this demographic transition in our culture?

How can amateur radio more effectively deal with the shackles of a fossilized culture where tradition rules innovation? Do we need the Spark Gap in our rearview mirror as a guidepost? Let’s just acknowledge that no amateur could sit down at a workbench and design and build a modern transceiver! Take a Kenwood TS-590SG. It’s far from the leading edge. But could you design one? Then build that design? I couldn’t. Why would we? As Rob Sherwood has written (and I have analyzed), we have the best receivers that we have ever had in the current market. Even though purchasing semi-homebrew radios, like the BitX variety (and I have), push hams toward tinkering, they are not “production” quality for many ham radio activities—like contesting, DXing, and so forth. Yes, some do spend most of their time in tinker-mode rather than production-mode. What we know from Canada is that we have strong segments in “production mode” activities as well as segments in experimentation where homebrew radios have a better use-case for the population. Should we pressure all newbies toward the past when getting them interested in the present and future? My friend, Dan KB6NU, just wrote about this same topic.

Yes, I built a crystal radio as a young teen, using the Fox Hole model with a pencil lead, razor, toilet paper roll for the coil, and so forth. Led the building of an FM and AM station as well. Learned a lot. I still build a lot of things. These activities are highly useful as educational tools. But we must face that we are appliance operators today due to the sophistication of the technology. At best, we are appliance enhancers by homebrewing accessories, modifying “appliance” radios, and so forth. Yes, some do build and operate fully homebrew rigs. Bill Meara N2CQR of Solder Smoke comes quickly to mind. Nothing detrimental with that per se but should we have a norm that every ham should follow suit? When we get the Spark Gap out of our rearview mirror as a guidepost for the future, we will make much more progress with post-Baby Boomers for reasons I’ve outlined above.

My bespoke portable HF antenna, called the EiffelTenna, is featured in the October issue of Practical Wireless. I was inspired by a video of Jim W6LG on his Youtube Channel as well as the further work of Jason VE5REV via Twitter (X). It’s a fun build, inexpensive, is very portable, and works 40, 20, 15 and 10 meters. I use Faraday Cloth for the counterpoise and place the tripod directly on it.

The 40 meter operation works as a center-loaded vertical, something I posted on regarding the inductor coils recently. If you intend to build the EiffelTenna, check out that article too. The EiffelTenna base alone would be good for Technicians since it works on 10 meters without a whip or coil. A stainless steel whip on top of the tripod makes for a solid vertical with its own mounting base. For windy conditions, I use some 1lb ankle weights attached to each tripod leg using the built-in velcro straps.

Shown below is the EiffelTenna deployed for testing on my driveway. (Click for full image) It is setup for 40 meters using a JPC-12 inductor coil. Others work as well or better so this was just the option used here because it’s adjustable. The RF sweep has the coil bypassed using KB9VBR’s trick for use on 20 meters. Nearly 50 ohms with SWR of 1.06 at 14.154 MHz. Note how relatively small the counterpoise cloth is in this picture.

This full antenna system packs down into an inexpensive camera tripod bag ($16 via Amazon). A RigExpert antenna analyzer is underneath the Faraday Cloth for matching in the field. Coax from RG-316 with a ferrite bead choke is wound on a wire winder printed by my public library for the cost of resin ($4). Blue ankle weights were purchased at Academy Sports while on sale.

The EiffelTenna uses traditional vertical antenna concepts with unexpected objects serving as both a ground mount and a radiating element. Thanks Jim W6LG and Jason VE5REV for the inspiration!

Blog Author Note: This is a paper written with Dr. Scott McIntosh of Lynker Space. A PDF of this article is available by clicking here. Reproduction with attribution is permitted.

Sunspots to amateur radio operators are central to daily operations, especially on the HF bands. Ever since Schwabe began counting and plotting daily observed sunspots in 1826, the leading perspective has been that sunspots follow a given, time-ordered, sinusoidal pattern of rise and fall, largely around an eleven-year cycle. The pattern of differences among cycles has been the topic of much speculation, generally without any actual empirical observation of those factors. Until recently, the sunspot cycle is virtually just a given construct based largely on daily sunspot counts, summarized to each month.

There is almost no theoretical discussion of sunspot cycle antecedents, only their effects on propagation. For instance, Nichols (2015) exclaimed, the “top experts” are unable to identify the peak or trough of the solar cycle or the timing of the transition from one cycle to another. Previous work, especially in amateur radio, has focused almost wholly on atheoretical “curve-fitting” style models of the sunspot cycle with observed sunspots gathered for almost two centuries being just a given phenomenon (see Howell and McIntosh 2022a).

With the open acknowledgement that previous predictions have not been very accurate, it is puzzling as to why better theoretical explanations have not been sought by amateur radio experts on propagation patterns (e.g. Luetzelschwab n.d.). This devotion to the theoretically unexplained eleven-year sine wave function as a sterile paradigm in the face of the empirical anomalies reduces scientific progress in understanding the sunspot cycle. Here is why.

Philosophers of science have long debated the role of prediction and explanation in scientific progress. Douglass (2009) summarizes the debate as follows. “Prediction is important because we can be surer that the scientist generating the theory has not fudged or somehow subtly made his theory inconsistent or less clearly applicable to certain contexts by virtue of some torturous, ad hoc accommodation. Prediction also allows for the generation of new (hopefully supporting) evidence. Explanation is important because it helps us think our way through to new predictions.” To make progress in the scientific understanding of the sunspot cycle, we need both theoretical understanding coupled with better predictive capability.

This was the thrust of our 2022 article series in RadCom. We published papers in the July and August issues outlining the long prevailing scientific paradigm on the sunspot cycle, noting that it was largely devoid of a formal theory predicting its rise and fall. We outlined a major challenging theoretical paradigm, led in its creation by the second author, on not only predicting Cycle 25 but offering the beginnings of why the amplitude and modulation of such cycles behave the way they do. In essence, this marked a change from mere prediction toward explanation, a cardinal sign of growth in any area of science. As we have reached the midpoint of Cycle 25, it is time to see how this argument is faring.

Competing Sunspot Cycle Paradigms

The expert panels convened by the NASA/NOAA/ISED organizations (hereafter, NNI) over the past several sunspot cycles have published their own forecasts of the next one. They have done this without any disclosure of the specific model used or the specific substantive theoretical perspective driving them. They do not disclose their methodology but state that it is the consensus opinion of an expert panel reviewing more than fifty various models submitted to them for consideration. Unlike most all peer-reviewed scientific work, the official sunspot cycle forecasts are a theoretically unexplained given resulting from an expert opinion panel whose deliberations are not open to public inspection. Their forecasts have largely failed to be very accurate when later compared to the observed sunspot numbers in the predicted cycle (see Howell and McIntosh 2022a,b for a full discussion).

The second author’s team, hereafter called the McIntosh team, developed both a theoretical foundation and empirical forecast of Cycle 25, publishing the methods they utilized and what substantive concepts shaped them. Unlike the official NNI forecasts, the McIntosh team’s work is public for all to read. We strongly encourage the readers of this paper to review our 2022 articles for details as they are indeed nuanced arguments.

Suffice it to say that the competing McIntosh paradigm emphasizes not the mere curve-fitting exercise that so many amateur radio prognosticators subscribe to in their forecasts (e.g., Cohen 2020) but two new key conceptual elements of the Sun’s dynamo. This was new ground. As we illustrate below, much of the scientific community resisted an open consideration of these ideas at the beginning.

One concept is the Terminator, a landmark event in the sunspot cycle delineating the start, end, and overlap of sunspot and magnetic activity cycles. This event does not correspond to the statistical minimum or maximum in the number of sunspots but to an underlying shift in part of the sun’s dynamo that shapes the entire cycle’s behavior. It arises from the famous Hale Magneto Cycle (Howell and McIntosh 2022a).

A second concept is the timing of the Terminator within the approximate eleven-year period. Taken from our earlier paper:

“This variability, when viewed through the lens of an insular sunspot cycle, lends itself to the anomalies noted by prominent amateur radio propagation enthusiasts. The delay in Termination frequently leads to the forecast of a poor cycle approaching, even another Maunder Minimum, by hams. More critically, the longer the time between terminators, the weaker the next cycle would be. Conversely, the shorter the time between terminator events, the stronger the next Solar Cycle would be. This is the cornerstone thesis in the new competing paradigm which successfully addresses several anomalies observed by Nichols (2015), Nichols (2016) and Luetzelschwab et al. (2021).” (Howell and McIntosh 2022a: 40).

We suggested in 2022 that the key question is whether we are indeed in a crisis stage of a paradigm shift, using the perspective of the well-established Kuhnian model of scientific revolutions (Kuhn 1962). The evidence of such a crisis state would include the following two elements. Firstly, if the competing McIntosh team’s model produces a better empirical forecast than the official NNI’s forecast does, then the theoretically-based paradigm that is a better forecast pushes toward a crisis state. Secondly, what further shapes a crisis state is if other scientists flock to the empirically-superior, theoretically-explicated one. This pattern of behavior, measured largely through citations of the competing paradigm’s exemplars, propagates the new paradigm to the field. If scientists use the competing paradigm’s exemplary papers to shape their own work, then the revolution is taking shape through the collective behavior of other scientists (Kuhn 1962).

We offer a narrated illustration in Figure 1 of the stages and processes of Kuhn’s classic explanatory model applied to these two competing paradigms. We begin on the right side of the wheel of paradigm change. Effectively, the initial “boundary maintenance,” or resistance by adherents to shift from the traditional paradigm embedded in the NASA/NOAA/ISED predictions, eventually gave way to peer reviewers’ objectivity. This occurred through reviewers and editors evaluating the increasingly massive empirical evidence based upon all sunspot cycles for which there were data constructed by the McIntosh team as they revised their initial 2012 work. This was not accomplished very quickly or very easily. As Kuhn (1962) stipulated, this is not at all unusual for a competing set of ideas which threaten the “normal science” embedded in a reigning paradigm.

Nevertheless, the existing normal science “puzzle solving” produced many anomalies in the prediction of both the amplitude and the timing of adjacent sunspot cycles. This acknowledgement that we just do not have a sufficient understanding to produce very accurate forecasts created increasing doubt in adherents to the current paradigm after facing the massive amount of evidence from the original McIntosh team’s paper.

The “boundary maintenance” from 2012 when Science Magazine rejected the initial paper on the new theory began to give way some years later. This occurred through the McIntosh team’s surprising Cycle 25 prediction of a far higher peak in sunspots than the NASA/NOAA/ISED (NNI) official predictions and why they made this forecast. Remember, the official sunspot forecast for Cycle 25 contained no explanations of how they were derived, only that a panel of experts came up with them. This “exemplar” article was published in 2020, some eight years after the initial “boundary maintenance” rejection in 2012. As these results are compared to the errors in previous expert panel forecasts by more and more scientists, this set in motion increasing collective doubt being attached to NNI’s undisclosed methods. This behavior is shown as “model drift” in Figure 1.

Once this model drift occurred after the McIntosh team’s Cycle 25 forecasts were published (2020), the empirical race was on to see which forecast would be more accurate. Modern website technology made this a monthly comparison with the release of each new count of sunspots (shown in Figure 2 below). When the second “exemplar” paper on the timing of the Terminator event appeared in 2023, this undoubtedly significantly enhanced the motivation of other scientists to read and consider the competing paradigm’s exemplars to use as a basis of their own work.

Modern technology speeds up scientific awareness of new works as compared to periodic print journal publication. So, this social network technology makes the process identified by Kuhn back in the 1960s as a “revolution” in paradigm-change an even more valid metaphor today. Should a growing number of other scientists base their published work on the exemplars of the McIntosh team, then direct “model competition” sets in. These collective acts by others in the scientific community are behaviorally manifested through increasing citations of the exemplars in the competing paradigm. If the competing paradigm’s empirical superiority continues, it is only a matter of time before the full model revolution occurs, quickly resulting in a rapid change to a new accepted paradigm. It is our assessment, as illustrated in Figure 1, that we are clearly in the model competition stage as we stand today.

Where Is Paradigm Competition at the Peak of Cycle 25?

In this paper, we evaluate the status of this potential revolution in our shared understanding of the important sunspot cycle. This is based on the two elements described above:

1. Empirical superiority of the McIntosh team exemplars which introduced their paradigm to this field of science. Is the McIntosh team forecast for Cycle 25 demonstrably more accurate than those offered by the NASA/NOAA/ISED Panel of experts?
2. Does the pattern of citations of the two exemplar articles published by the McIntosh team show that other scientists are adopting them? If this adoption is considerable, then the evidence compounds in favor of their new paradigm.

We now provide evidence on both elements of the issue at the approximate middle of Cycle 25. It will show that the results underscore our assessment of where things are in Figure 1.

Statistical Comparisons of the Two Cycle 25 Forecasts

Using the Austrian Space Weather Office website, we produce in Figure 2 the smoothed monthly sunspot numbers for Cycle 25 and for the two competing forecasts. We use the approximate peak time in Cycle 25 to delineate our comparisons. In other words, if this were an athletic competition, what is the score at the end of the first half of play?

In Figure 2, the vertical line is this demarcation as of August 2024 in the time series. Note that the NASA/NOAA/ISED (hereafter NNI) forecast had somewhat of a “false start,” to borrow a track-and-field metaphor, in that after their first set of numbers went public (light blue line), they released another revised forecast. This one shifted their forecast start back some six months (dark blue line). No public explanation was given by the NNI group. We use this revised NNI forecast in our analysis. The McIntosh team forecast is in the red line.

For comparative illustration, there are four other data series. The average monthly sunspot cycle number since 1750 is in green. The three observed sunspot numbers include the daily sunspots (light green line) and the key smoothed monthly sunspots in black. (There is a short series of estimated daily numbers in orange, shown after the final monthly figure.) This represents a visualization of the forecast and observed monthly sunspot numbers. The series includes 32 months of data, our approximation of the first half of Cycle 25.

In this graph, the NNI forecast does appear consistently lower than the observed monthly sunspot data after the summer months of 2022 while the McIntosh team numbers appear generally higher. The exception is near mid-cycle where the observed sunspots spike above both projections. Neither set anticipated this sharp rise in monthly sunspots. But are these two forecasts just a random walk around the observed monthly sunspots? Statisticians have addressed questions like this for some time because time series graphs are somewhat subject to various interpretations. We make statistical comparisons using standard methods for this in Figures 2 and 3.

In our 2022 RadCom paper series, we presented the McIntosh team forecast for a complementary index of solar propagation influence, the Solar Flux Index (SFI, abbreviated as f10.7). We use the NNI forecast for SFI to further compare the statistical accuracy of an atheoretical expert opinion forecast versus the theoretically-driven McIntosh team model.

We use the standard text by Theil (1966) for the analysis of forecast comparisons. One measure of the statistical accuracy of two time series is the mean absolute error (MAE) represented by the formula of

where yⁱ and xⁱ are the respective data values for each time series compared at the i^th time interval. That sum is divided by the number of points in the time series (or n) to yield this average absolute error in numbers of monthly sunspots.

Another test that is metric-free is the mean absolute percentage error (MAPE) which is the percent version of MAE. It is the sum of the actual minus forecast divided by the actual which is averaged over the number of temporal observations:

The third consideration we make is to test for the equivalence of the two forecasts (i.e., are the different forecast series just random walks?). In this part, we use the Diebold-Mariano test or D-M (Diebold and Mariano 1995) which compares the mean difference in the squared-error or absolute error of each forecast to the observed data. This S₁ test is applied to both the MAE and the MAPE (Theil 1966). The D-M S₁ test can use alternate kernel densities in this computation. To safeguard our comparisons, we compute tests using both a uniform and a Bartlett kernel for the standard error estimation. Each produced similar results so the uniform kernel is presented in our results. See Diebold and Mariano (1995) for details. We used Stata 17 software for our computations using the dmariano script (StataCorp 2017).

As shown in Figure 3, the McIntosh team series results in an average monthly forecast error of 26.8 sunspots. For the NNI forecast, the average monthly error is 45.3 sunspots. The McIntosh team forecast is 18.73 sunspots more accurate on average each month. The D-M test shows that this is statistically significant: the McIntosh forecast is significantly more accurate than the NNI prediction for the first half of Cycle 25. The most recent surge in monthly sunspots during 2024 was predicted by both forecasts but the McIntosh predictions were more on track in the graph with those observations.

The second panel of Figure 3 contains the percent form (MAPE) of the forecast errors for each group’s projections. The McIntosh forecast averaged a 25.4% monthly error, lower than the NNI expert panel’s 38.3% error each month. This is a 12.9% difference between the two, reflecting a statistically more accurate forecast (p=.0000).

The Solar Flux Index (SFI) is also a critical index for propagation. It rivals the SSN in importance for daily HF operations. We use this forecast to complement the ones for monthly sunspots. The SFI graph is in Figure 4. For NNI, all monthly errors are on the high side whereas the McIntosh team’s hover on the low side of zero (i.e., matching the observed SFI). Both anticipated the rise upward during the summer months of 2024 but were off in their respective predictions. Over the first-half of Cycle 25, the McIntosh forecast averaged 25.65 Index points closer to the observed SFI (17.2 vs. 42.9). The D-M test suggests that this is a significant edge in favor of the McIntosh prediction (p= .0000).

Putting the SFI forecast errors in percent form, the lower panel illustrates a consistent over-prediction of the monthly Solar Flux Index by both. The NNI’s numbers are visibly off-base by 20 percent or greater in the graph. Some segments of the McIntosh predictions are also off by 10 to 20 percent. Overall, however, the average percent error is 27.8% for the NNI forecast and some 16.6% less for McIntosh at 11.2%. As with the MAE metric, this difference in percent form is statistically in favor of the McIntosh series (p = .0000).

In short, the McIntosh team has empirically superior forecasts for both monthly sunspots and the Solar Flux Index, two leading indices for propagation used by amateur radio and many other spheres of radio transmission practice. They are uniformly statistically significant in favor of the McIntosh theory-driven approach as compared to the expert panel forecasts from NNI.

Evidence of Paradigm Change Through Bibliometric Analysis

To examine evidence on other scientists adopting the new McIntosh team paradigm, we used methods of bibliometric citation analysis (De Bellis 2009: Chapter 8; Prabhakaran et al. 2018). This is a set of methods used to measure the impact and influence of scholarly works through the patterns and frequency of citations in various contexts (Andres 2009; Alphasoft.com n.d.). This set of metrics measures the behavior of the scientific community toward the competing paradigm which Kuhn (1962) shows is the key to paradigm change.

Traditional citation counts from the print medium tend to be much slower than scientific discovery is actually produced because of the circulation of print media (De Bellis 2009: Chapter 8). Because of this, alternative metrics were developed to measure how Internet-based tools enhance the sharing of scholarship. These tools include paper pre-print servers, online exchange of papers, and other discussion networks that are in daily use to stay abreast of the latest emerging knowledge. These “alternative metrics” including social media and online publishing are used in this part of our analysis through the Altmetric system (see Astrophysics Data System).

Following Kuhn’s approach to paradigm-change, we studied the two papers that the second author identified as the exemplars (Kuhn 1962) introducing and illustrating his team’s competing paradigm. The Astrophysics Data System (or ADS) maintained by Harvard University on behalf of the Smithsonian Astrophysical Observatory (SAO) under a NASA grant was the source of our citation analysis. The ADS system (available at (https://ui.adsabs.harvard.edu/) facilitates meta-analysis of papers in astrophysics with both bibliometric computation and visualization of results. We utilize this system to analyze citation and discussion metrics for both exemplar papers as well as all publications for the leader of this scientific team (the second author here). While we do not report a full bibliometric analysis (for example, see Prabhakaran et al. 2018), the compilation of citation metrics does suffice to gauge the initial attention and influence that this competing paradigm is having on the field of solar physics and amateur radio itself.

Figure 5 summarizes these metrics for the two exemplars. The first paper, introducing the overlapping Hale magnetic activity cycles and the relationship they have to sunspot amplitude, has 73 total citations. The bar chart on the upper right shows the trends in citations for this paper (note that 2025 is not yet fully realized). The scientific output analysis by Altmetric gives it an “attention score” of 858. This ranks number one of almost two thousand articles in the journal. Among over one-half million articles published during the same period, it ranks 813. It is in the top 5% of all research ever tracked by Altmetric.

The second exemplar introduced the Terminator timing construct, illustrating it using all the data on sunspot cycles in existence, by associating it to patterns within the 22-year Hale Cycle. This paper extended the first exemplar’s idea of potential causes of the amplitude by adding a conceptual basis for what “kick starts” the next cycle. This paper has 18 citations, moving up quickly in the year after publication as shown in the bar chart. It has an attention score thus far of 654. This article is ranked number one of almost 1,600 articles in this leading journal, Solar Physics. By comparison to about one-half million articles published in the field at the same time, it ranks 999. More importantly, it too ranks in the top 5% of all research articles scored by Altmetric.

Turning to all papers published by this scientific team’s leader, Figure 6 summarizes the same type of citation analysis. Emphasizing the period of 2020-2025 for when the competing paradigm was introduced, there are 457 papers considered in this figure. There are 5,901 citations of these papers, only a thousand of which are self-citations, necessary to build and continue a line of scholarship. The citations by other scholars are the key element for exemplar adoption. There are about two thousand citations, “normalized” to the volume of other articles published around the same time. This puts the citation patterns into the context of the scientific problem as a comparison to numbers of citations per se (see the ADS website for details). The bar chart extends the scope prior to the year 2020 to check the scholarly output by this team’s intellectual leader. The result is a steady increase in citations by other scientists in peer-reviewed papers, an indication of a very productive scholar growing in a career that is being recognized by other scientists in their own work.

The H-index is the most popular one in use for scientific comparisons. A value for H means that the author has that number of papers that are each cited by a minimum of the same number. The H-index number in Figure 6 increases prominently in 2020 to about 45, continuing through 2025. Note that an H-index value of 40 is outstanding and over 60 is exceptional (Hirsch 2005).

The read10-index reflects a decade swath of readership citations of the author’s publications. It shows the works published in 2010 (pre-paradigm introduction) and 2020 (paradigm introduction) as having the highest values, well over 100. This trend line shows the immediate interest in the author’s works over a long period of time (a decade), a sign of prominence in science.

The i100-index, however, might be the most illustrative for our purpose to ascertain how the paradigm is being adopted by others in this field of science. It illustrates the number of publications with at least 100 citations, a challenging hill to climb in science. The growth in the (purple) i100 line shows that a minimum of 100 citations for papers by McIntosh steadily increases after 2015 but especially after 2020, the year of publication for the first exemplar paper. This is also indicative of movement toward paradigm-adoption by others. The tori-index corroborates this trend as his papers become central citations by other scholars. The i10-index began to also spike when the 2020 paper came out and continued after the second exemplar appeared. This index surpasses 130, suggesting that many papers by the author have been each cited by a minimum of 10 other authors.

The bibliometric portion of our analysis shows strong evidence that the peer scientific community is heavily engaged in the competing paradigm. The two exemplars have been substantially growing in peer citations to a level of prominence. They have garnered the top attention in the respective scientific journals where they appeared, no small feat for any scientist. The H-index score shows that the lead scholar producing this new paradigm has reached an outstanding region, further evidence of movement toward direct model competition in Kuhn’s model of paradigm change.

Is There Demonstrable Progress in the Revolution?

Our goal has been to determine if there is Kuhnian movement (Kuhn 1962) toward a revolution in the long-standing paradigm for the sunspot cycle at the midpoint of Cycle 25. We identified two elements of evidence: the empirical superiority of the NNI versus the McIntosh team forecasts and the degree of scientific adoption of the competing paradigm’s exemplary papers.

Using long-established methods in forecast comparisons, our results leave little objective doubt that the theory-driven forecast by the McIntosh team is superior. For smoothed monthly sunspot counts covering the first 32 months of the Cycle, the McIntosh team forecast is 19 spots more accurate, a 13 percent and statistically significant improvement over the NNI numbers. (Note that we used the NNI’s revised forecast after they adjusted to some six months behind their original Panel’s predictions.) We included forecasts for the Solar Flux Index (f10.7) over the same time horizon. The McIntosh team’s SFI forecast is 26 index points or 17 percent more accurate. The empirical superiority, at least at mid-cycle, clearly favors the McIntosh paradigm.

The bibliometric analysis we presented on how the two exemplary papers have been received by the scientific field showed strong evidence of engagement and adoption with the competing paradigm. The overall standing of scholarship by the lead scientist was a second element surrounding this new paradigm. It too demonstrated a clear upturn in citation metrics after the publication of the two exemplar papers.

The citation numbers have been continually increasing since the first (2020) and second papers (2023) appeared in peer-reviewed journals. We noted in Figure 1 the boundary maintenance by keepers of the long-standing paradigm who rejected the original paper in 2012. It took nearly a decade (from 2012 to 2020) of continually increasing the amount of scientific evidence involving the linkages between the Hale Cycle to the sunspot cycle’s behavior to reach a successful peer-reviewed publication. With the observed rapid increase in citations of the two exemplar papers, Kuhn’s concept of a non-linear, revolutionary adoption of a competing paradigm appears indeed to fit the bibliometric results.

To underscore Kuhn’s notion, the more contemporary “attention” metrics for the two exemplars show that each is the number one ranked article in the respective publishing journal. Each is also in the top five percent of all research articles ever tracked by Altmetric. The two exemplars have clearly captured the attention of the field and the associated reporting on it challenging the status quo paradigm.

We find the bibliometric citation results to also be strong evidence that the competing paradigm is indeed now within direct model competition as illustrated in Figure 1. It may well take until the end of Cycle 25 to determine the extent that a paradigm revolution has occurred. It will depend on the continued reception of the McIntosh team’s published results as they continue their research program. This adoption would be spurred along by a continuing forecast superiority during the second half of Cycle 25. Those monthly comparative results are available on the Austrian Space Weather website for all to see.

We likened this study to that of checking the score at half-time of an athletic event. However, we must wait until this cycle is compete to render a full assessment of who wins the scientific competition. We plan to revisit this analysis at the appropriate time. The available evidence at half-time, nonetheless, clearly favors progress in the revolution involving our understanding of the critically important sunspot cycle.

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