North America

Remapping the Great Lakes from a Hydrological Perspective

As noted in the two previous GeoCurrents posts, Lake Huron and Lake Michigan are a single body of water, forming the world’s largest freshwater lake (by surface area) by a considerable margin. The Wikipedia article on this greatest of the Great Lakes explains the situation:

Lake Michigan–Huron (also Huron–Michigan) is the body of water combining Lake Michigan and Lake Huron, which are joined through the 5-mile-wide (8.0 km), 295-foot-deep (90 m), open-water Straits of Mackinac. Huron and Michigan are hydrologically a single lake because the flow of water through the straits keeps their water levels in overall equilibrium. Although the flow is generally eastward, the water moves in either direction depending on local conditions. Combined, Lake Michigan–Huron is the largest freshwater lake by area in the world.

 

For casual purposes, there are no problems with regarding this single body of water as divided into two discrete lakes. For both scientific and comparative purposes, however, it is more useful – and accurate – to treat Michigan-Huron as a single lake. Not surprisingly, a National Oceanic and Atmospheric Administration (NOAA) hydrological diagram of the Great Lakes follows this model. But it also divides this massive lake into three basins: Michigan, Huron, and Georgian Bay. Georgian Bay is conventionally regarded as part of Lake Huron, but it hydrologically functions as a separate basin.

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Given these complications, it seems worthwhile to experiment with remapping the Great Lakes. The first map posted below shows the standard five-lake model. The second map depicts Michigan-Huron as a single lake, while adding the much smaller but still substantial (430 sq mi) Lake Saint Clair, which is an essential component of the Great Lakes system. The third map divides Lake Michigan-Huron into its three separate basins. The final map shows how the Great Lakes would be depicted if we were to regard all deep embayments as separate lakes.

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Remapping the Great Lakes from a Hydrological Perspective Read More »

Mapping the Greater Great Lakes of North America

It is difficult to deny the greatness of the Great Lakes, which together form the largest aggregation of large lakes on the planet.  Although almost all sources include five lakes in this collection – Superior, Huron, Michigan, Erie, and Ontario – controversies persist. By geological criteria, Michigan and Huron form a single lake, reducing the number of Great Lakes to four. Yet some observers insist that there are actually six Great Lakes, adding Lake Champlain to the list. In 1998, the United States Congress went so far as to pass a bill giving Lake Champlain official Great Lakes status, thereby allowing the use of targeted Federal funding for the lake and its basin. The bill, however, generated considerable controversy, as Lake Champlain is much smaller than the “other” Great Lakes and is located at some distance from them. Co-chair of the Congressional Great Lakes Task Force Steven C. LaTourette denounced the maneuver, stating that ‘‘If Lake Champlain ends up as a Great Lake, I propose we rename it ‘Lake Plain Sham.” Soon afterward, Congress revised the designation, demoting Lake Champlain while retaining the funding opportunities.

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From a scientific perspective, however, there are good reasons to add a few other lakes to the list, all of which are located along the same great arc and all of which were created by similar geological processes. This idea is admirably explored in a YouTube video by Signore Galilei entitled “North America’s OTHER Forgotten ‘Great Lakes.’” Some of the lakes on Galilei’s list are large indeed: Canada’s Great Bear Lake and Great Slave Lake are both larger than Lake Erie and Lake Ontario and it’s lake Winnipeg is larger than Lake Ontario.

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I have depicted this great arc of lakes – the Greater Great Lakes of North America, if you will – on the map posted below.  Political boundaries have been removed to highlight the lakes themselves. To further defamiliarize the Great Lakes concept, I have rotated the frame, putting northeast at the top. As can easily be seen, this is indeed a great chain of lakes. It is also much more a feature of Canada than of the United States. Only one of lakes – Michigan – is wholly located in the United States. Five are shared between the two countries (Superior, Huron, Erie, Ontario, and Lake of the Woods). All the rest are entirely within Canada.

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Mapping the Greater Great Lakes of North America Read More »

Alcohol & Religiosity in the United States, and the West Virginia Exception

Maps of alcohol consumption in the United States reveal several regions with very low drinking rates. The most prominent is the LDS (Mormon) cultural region focused on Utah and eastern Idaho. The so-called Bible Belt of the southeastern and south-central states is also clearly visible, although most of its coastal counties are excluded. More surprising are several heavily Native American counties in the northern Great Plains and Southwest. Many tribal governments restrict alcohol sales, but actual consumption rates may be higher than the map indicates. Comparing the maps posted here, several indigenous-dominated counties in South Dakota are shown as having low rates of alcohol drinking but relatively high rates of heaving drinking.

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In general, high rates of adherence to religious demoninations that oppose alcohol consumption are associated with low rates of drinking. Lyman Stone, in a fantastic, map-rich post called “Mapping American Churches,” makes this point by juxtaposing a map of “anti-alcohol religious attendance rate” with one showing the prevalence of heavy drinking. As he bluntly notes, “Turns out religious opposition to drinking reduces drinking. Surprise.”

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But although this correlation is striking if unsurprising, interesting – and surprising – exceptions can be found. The most prominent is the central Appalachian region, focused on West Virginia. West Virginia reports very low rates of alcohol consumption and abuse – lower than those of any other state except Utah according to some sources. Yet West Virginia has only a middling level of membership in anti-alcohol churches. It also has a very low rate of overall religious adherence (according to data from 2000).

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Several explanations have been offered for West Virginia’s official rate of alcohol consumption. One is the state’s high level of opioid abuse, as revealed by a 2015 map of overdose deaths.  Another is the prevalence of illicit and untaxed alcohol (“moonshine”) that escapes tabulation.

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A 2019 article in the Exponent Telegram (Clarksburg, WV) expressed some doubt about the state’s reported level of alcohol use. While acknowledging that West Virginia “ranks the lowest in the nation for adult prevalence of both heavy drinking and binge drinking …[and] has been either the lowest or second lowest for many years,” the article went on to note that:

In the period from 2003 to 2012, the most recent data available, 1,092 people died in West Virginia due to crashes involving a driver with a blood alcohol content of 0.08 or higher. That rate, 12.9 per 100,000 population, is well above the national average rate of 6.7 for the same time period.

Although I doubt that West Virginia has one of the lowest alcohol-consumption rates in the United States, it would seem to be lower than one might expect given the state’s history, economic conditions, and relatively low rates of membership in anti-alcohol churches.

Alcohol & Religiosity in the United States, and the West Virginia Exception Read More »

Mapping the Current State of Cannabis Legality in the U.S.

Cannabis legalization at the state level in the U.S. continues to gain ground, even though federal law still classifies “marijuana” as a Schedule One drug, meaning that it is absolutely banned and has “no currently accepted medical use in treatment in the United States.” The resulting discrepancy between state and federal law presents a highly curious situation. It makes a mockery of the supposedly fundamental principle that federal law trumps the state law, with ultimate sovereignty vested in the United States rather than in the individual states. How could a substance possibly have “no currently accepted medical use in treatment in the United States” if 76 percent of those states have declared by law that is does?

The two best maps that I have found of the legal status of cannabis in the United States at the beginning of 2024 are reproduced below, one of which is from Wikipedia and the other from the political journal The Hill.  As can be seen, they portray the situation of quite differently, finding agreement only regarding states in which cannabis is fully legal (mapped as “legal for recreational use” on the Wikipedia map and “recreational and medical” on the one from The Hill.)

The discrepancies between the two maps indicates the complexities of the “gray zone” of partial legalization. In Nebraska and North Carolina, for example, cannabis is fully illegal but decriminalized, meaning that no one will go to jail for possessing it, at least on first offence. Several states allow “medical marijuana” only if its THC content is so low that one cannot experience an altered state of consciousness by ingesting it. In Texas, for example, only CDB oil can be used, and it cannot contain more than one percent THC. Yet as the Wikipedia article on the legal status of cannabis in the United States notes, it is “de facto legal” in Austin, the capital of Texas, as the municipal police will not arrest anyone in possession of less than four ounces, a considerable quantity. Utah, in contrast, allows the ingestion of potent cannabis, but only if one is terminally ill. On all the maps posted here, Oklahoma is placed in the same category as Utah, that of allowing medical but not general use, but the contrast between the two could hardly be more extreme. Medical dispensation is easy to get in Oklahoma, and the state’s cultivation regulations are extraordinarily relaxed. As the New York Times noted in a 2021 article entitled “How Oklahoma Became a Marijuana Boom State”:

Ever since the state legalized medical marijuana three years ago, Oklahoma has become one of the easiest places in the United States to launch a weed business. The state now boasts more retail cannabis stores than Colorado, Oregon and Washington combined. In October, it eclipsed California as the state with the largest number of licensed cannabis farms, which now number more than 9,000, despite a population only a tenth of California’s.

Tribal sovereignty adds another layer of complexity. Cannabis may be completely illegal North Carolina, but it is fully legal in its lands that fall under the authority Eastern Band of the Cherokee Indians. South Dakota allows only medical sales, but on two of its Native American reservations cannabis fully legal.

The complexities of cannabis legality in the U.S. are too large to be captured in any single map. The two maps posted above do a reasonably good job, but the categories that they use might be confusing for some readers. I have therefore remapped the data that they use to try to convey the situation in a more straightforward manner. In both cases, I employ a demographic cartogram, in which each state is sized according to its population, rather than a conventional map. (Unfortunately, the base map that I used excludes Alaska and Hawaii). Using a such a cartogram allows one to visualize the number of people affected by the different legal regimes.

The first of these maps (above)  follows the depiction by The Hill but reduces the categories to three: complete legality, complete illegality, and partial legality. As can be seen, cannabis is fully legal for most people living the northern half and western quarter of the United States. But the only three states that follow U.S. federal law by completely banning cannabis use – Idaho, Nebraska, and Kansas – are located in this same general region of the country. Such clear regional differences, however, are not so apparent in my remapping of the Wikipedia data, which uses five categories and focuses not on cannabis per se but rather on cannabis that contains enough THC to be psychoactive (below). This map better captures the diversity of legal regimes found in the South and across the Great Plains.

Mapping the Current State of Cannabis Legality in the U.S. Read More »

Surprising Findings in a Study of Post-COVID Urban Recovery Rates in the United States and Canada

I recently came across a brief report by the University of Toronto’s School of Cities on the recovery of urban cores in the U.S. and Canada since the COVID-19 pandemic. The study’s methodology is intriguing:

The recovery metrics on these charts are based on a sample of mobile phone data. The recovery metrics on the charts and maps are computed by counting the number of unique visitors in a city’s downtown area in the specified time period (standardized by region), and then dividing it by the standardized number of unique visitors during the equivalent time period in 2019. Specifically, the rankings below compare the period from the beginning of March to mid-June in 2023 relative to the same period in 2019. A recovery metric greater than 100% means that for the selected inputs, the mobile device activity increased relative to the 2019 comparison period. A value less than 100% means the opposite, that the city’s downtown has not recovered to pre-COVID activity levels.

As the results were given in tabular form, I thought that it would be useful to map them to more easily see if there are any distinct regional patterns or anomalies. The resulting map, posted below, has some expected features. Recovery has generally been faster in low-density sunbelt cities, with only Las Vegas showing an increase in downtown activity since 2019.

But there were also some unexpected findings. Columbus, Ohio, for example, has many characteristics of a sunbelt city, despite its cloudy winters, yet it has one of the worst downtown recovery rates. Minneapolis and Seattle also have unexpectedly low rankings. To understand what is going on in these cities one would have to examine exactly how “downtown” is defined in each case. In Columbus, for example, the old central business district has been declining over the past few decades, but a new vibrant urban core has emerged nearby, in a neighborhood dubbed “Short North.” I doubt that it was included in area deemed downtown Columbus.

A few other interesting findings deserve comment. It seems that Canadian downtowns have recovered more quickly on average than those of the northern United States. Is this because they tended to be more alive to begin with? The relatively quick recovery of Oakland, California that is indicated by the study makes little sense. From what I have read of Oakland, and from what I have seen in a few quick visits, the city’s downtown is in a desperate situation, with closing businesses and surging crime. In late September, 2023, Oakland saw an unprecedented strike of business owners. As reported by a local news source:

It’s not business as usual in downtown Oakland on Tuesday morning as store and restaurant owners go on strike over rising crime.

Business owners say the goal of this strike is to send a larger message to City Hall. They want better protection and support so they can safely operate their businesses and make a living.

Many of the participating businesses gathered in front of Le Cheval for a news conference on Tuesday to voice their concerns. The restaurant is closing at the end of the month because of the crime and slow sales post-pandemic.

Participating merchants say, just like Le Cheval, they’re losing customers and foot traffic because of car break-ins, carjackings, robberies and assaults.

In conclusion, I can only fall back of the most tiresome of all academic clichés: more research is needed.

 

Surprising Findings in a Study of Post-COVID Urban Recovery Rates in the United States and Canada Read More »

Small But Densely Populated American Cities & the Transformation of Cudahy, CA

The list of the most densely populated incorporated cities in the United States has some interesting features. The top four entries are all small cities (less than 1.5 mi sq; fewer than 70,000 inhabitants) located just to the west of Manhattan in Hudson County, New Jersey. Three of the top 11 – Kaser, New Square, and Kiryas Joel – are relatively new towns in the New York metropolitan area that are entirely or primarily inhabited by Hasidic Jews. All three have high fertility rates and low levels of per capita income. According to Wikipedia, “Kiryas Joel has the highest poverty rate in the nation” while New Square is “the poorest town (measured by median income) in New York, and the eighth poorest in the United States.”

One surprising revelation in the city-density list is the large number of thickly populated cities that were originally established as low-density suburbs of Los Angeles. Of the 140 U.S. cities with more than 10,000 people per square mile, 28 are in the Los Angeles region. Although still conventionally imagined as a low-density, suburban environment, the L.A. region has been densifying for decades. The sprawling city of Los Angeles itself, covering some 469 mi sq, is now moderately dense by U.S. standards. As the density map of southern Los Angeles County posted below shows, central L.A. is now heavily inhabited, with many census tracts reporting more than 30,000 people per mi sq. Quite a few outlying tracts also post high figures. Many of these areas do not appear at first glance to be densely populated, as they are dominated by low-rise buildings and include many detached, single-family houses. But the number of persons living in each dwelling unit can be high, particularly in areas with large numbers of recent migrants.

Several of small, densely populated cities in the Los Angeles metropolitan area in the northwestern quadrant of a cluster of municipalities known as the “Gateway Cities.” I have enclosed the northern portion of this “Gateway” area on maps posted above and below, excluding the relatively large city of Long Beach. The crowded little cities in this region are relatively poor and have large immigrant populations. In 2019, Business Insider placed Huntington Park in the lowest position in California on its “misery index” and in the tenth lowest nationally. The Wikipedia article on Maywood estimates that one-third of [its] residents live in the U.S. without documentation.” Maywood is also notable for being “the first municipality in California to outsource all of its city services, dismantling its police department, laying off all city employees except for the city manager, city attorney and elected officials, and contracting with outside agencies for the provision of all municipal services.”

The evolution of tiny but densely packed Cudahy, with almost 23,000 residents living in 1.18 mi sq, is particularly interesting. Cudahy was originally designed as a semi-rural garden city. Its founder and namesake, the wealthy meat-packing entrepreneur Michael Cudahy, purchased a large ranch in 1908, which he subdivided and sold off in one-acre lots. As explained in the Wikipedia article on the city:

These “Cudahy lots” were notable for their size—in most cases, 50 to 100 feet (15 to 30 m) in width and 600 to 800 feet (183 to 244 m) in depth, at least equivalent to a city block in most American towns. Such parcels, often referred to as “railroad lots,” were intended to allow the new town’s residents to keep a large vegetable garden, a grove of fruit trees (usually citrus), and a chicken coop or horse stable.

Although gardens, orchards, and farm animals are long gone, the old “Cudahy lots” may still be visible in satellite images (see the image below; I was not, however, able to find a map of the original city lots). At any rate, Cudahy gradually morphed into a crowded industrial town, giving it a legacy of environmental contamination. As noted by the Wikipedia article cited above:

On January 14, 2020, delta Airlines flight 89 dumped jet fuel  Cudahy, while making an emergency landing at Los Angeles International airport. Park Avenue Elementary School suffered the brunt of this dumping. This incident sparked outrage because of the city’s previous history of environmental damage, including the construction of the same school on top of an old dump site that contained contaminated soil with toxic sludge, and pollution from the Exide battery plant.

As a final note, it is intriguing that the two main clusters of small, high-density cities in the United States are located immediately adjacent to the country’s two largest cities, New York and Los Angeles. Populous though they are, these two cities have markedly different built environments and settlement histories. New York is well known for its high population density, but Los Angeles is more commonly regarded as a low-density city anchoring an even lower-density metropolitan area. That vision is longer justifiable.

Small But Densely Populated American Cities & the Transformation of Cudahy, CA Read More »

Capturing the Size and Density of New York City and Environs on a Map of Major U.S. Cities

As mentioned in the previous post, depictions of the population density of major U.S. cities tend to under-emphasize the significance of New York City. New York is clearly the most densely inhabited major city in the United States, with 29,303 people per mi sq (in 2020), a figure that far overshadows that of second-place San Francisco (18,631). San Francisco, moreover, makes a poor comparison, as its total population is more than an order of magnitude less than that of New York (808,437 vs. 8,335,897 in 2022).

The population concentration found in the core areas of New York City is also masked by the relatively low density of some of its outlying areas, particularly of Staten Island. With a population of 8,618 per mi sq (in 2020), Staten Island is comparable in this regard to Los Angeles (8,304.22 per mi sq). In contrast, Brooklyn – which would be the country’s second most populous city if the boroughs of New York had never amalgamated – had a population density of 39,438 per mi sq in 2020, a far higher figure than that of San Francisco. But it is Manhattan that really stands out. Its 1,694,251 residents (2020) are crowded into a mere 22.83 square miles, giving it a density of 74,781 people per sq mi. A century earlier, Manhattan had been even more densely populated. When its population peaked at 2,331,542 in 1910, its density exceeded 100,000 people per mi sq, a figure that makes San Francisco seem sparsely settled in comparison.

In short, when it comes to both urban population size and density in the United States, New York City is in a league of its own, with no real competition. To illustrate this situation, I have redrafted two of the maps that were used to illustrate the previous GeoCurrents post. In the new versions (below), New York is broken down into its five constituent boroughs. A new density scheme was required as well, as four of New York’s five boroughs monopolize the top three categories in the new 2022 map. As the redrafted 1950 map shows, Queens and especially Staten Island were much less densely inhabited than the other boroughs at the time. This map highlights the significance of Brooklyn, the Bronx, and especially Manhattan as the country’s most densely populated urban places in the mid-twentieth century.

But even this redrafted map does not adequately capture the elevated population densities found in the greater New York City region. As the table of the most densely populated incorporated cities in the United States (posted below) reveals, New York City itself ranks in only the sixth position. The four cities with the highest density are all in Hudson County, New Jersey, immediately to the west of Manhattan. The largest city in Hudson County – Jersey City – is not on this list. But if cities that cover very small areas (below five square miles) are excluded, Jersey City ranks in the second position. Yonkers, which is immediately north of the Bronx, also makes this list of the most densely populated sizable U.S. cities. To reflect this concentration of dense urbanism in the New York metro area, I have edited the map once more, this time including Hudson County and Yonkers.

 

One more GeoCurrents post will examine population density in American cities. After that, this blog will turn to the recent elections in New Zealand and Poland before returning to the historical development of the urban system of the United States.

Capturing the Size and Density of New York City and Environs on a Map of Major U.S. Cities Read More »

U.S. City Size, Density, & Population Change, 1950 to 2022 – and the Dream of the “15-Minute City”

Many environmentalists now advocate the development of “15-minute cities,” urban areas dense enough to allow residents “to access most of the places [they] need to go within a 15-minute walk or bike.” This vision has much to recommend it. Many people find neighborhoods of this sort deeply attractive, both as places to live and visit. I count myself among them. My ideal living arrangement would be to divide my time between an apartment in such a city and a house in a remote rural area. Instead, like most Americans, I live in a medium-density suburban environment – which sometimes seems to offer the worst of both worlds.

But although I understand the appeal of 15-minute cities, I also recognize that creating them would be extraordinarily difficult if not impossible in the United States. Evidence from both polling and actual residential choice indicates that most Americans dislike dense cities and prefer suburban living. Ironically, moreover, environmentalists themselves are one of the main obstacles to the urban intensification that such a vision requires. Construction projects of all sorts, after all, often face environmental lawsuits, which can bring them to a quick halt.

An equally severe problem is the fact that the few cities in the United States that approach the required degree of walkability have been deintensifying, shedding residents over the past several years. From 2020 to 2022, New York City lost 3.5 percent of its population, Philadelphia 2.3, Chicago 3.0, and San Francisco a shocking 7.5. This decline was at first mostly a matter of people fleeing crowded conditions during the COVID pandemic, but it is now being driven primarily by safety and property-security concerns. For the same reasons, many of the mass-transit systems that are required for urban intensification are losing ridership and find themselves financially troubled. As a result, it is difficult to avoid the conclusion that, at least in the United States, the 15-minute city is little more than a fond dream.

Some of the maps that I have been making for my prospective historical atlas of urban development in the United States might prove useful in examining the urban growth and density issues surrounding the 15-minute city idea. These maps, to be sure, are unusual, as they depict no geographical features beyond city size and density. The spatial patterns that they show are also wildly distorted. As a result, they might more properly be regarded as graphic visualizations. But I still view them as maps, as all GeoCurrents posts focus on map explication.

The first map shows the size, density, and rough relative locations of the twenty most populous cities, as formally defined, in the United States in 2022. The numbers in the bottom corners of each urban polygon indicate the population growth rate, in percentage terms, of that city from 2010 to 2020 (left) and from 2020 to 2022 (righ). As can be seen, most large American cities lost population in the latter period. More important, such losses were concentrated in more densely inhabited cities. Several of the more sparsely settled cities, in contrast, gained population during this period. But as can also be seen, all these cities added residents from 2010 to 2020, some of them to a significant degree. This was true even in the country’s most densely inhabited urban areas. New York grew in this period by 7.7 percent and San Francisco by 8.5 percent. But with the exceptions of Seattle and Denver, all cities expanding by more than ten percent from 2010 to 2020 are characterized by low population density.

The overall impression conveyed by this map is one of low population density in America’s largest cities. Some of them have annexed such extensive suburban and rural hinterlands that they do not really count as cities in the informal sense. Jacksonville, Florida, for example, consolidated with Duval County in 1968, and as a result, its 971,319 residents live in a “city” that sprawls over 874.46 sq mi. This gives Jacksonville a population density of 1,270.73/sq mi, a figure lower than that of the typical American inner suburb. The contrast between Jacksonville and San Francisco is instructive. Although the city of San Francisco is also consolidated with its county, its population density is of an entirely different magnitude. In 2022, San Francisco’s 808,437 residents inhabited an area of 46.9 sq mi, giving it a density of 17,237.5/sq mi. But if San Francisco is thickly populated by U.S. standards, it is not by that of New York City. In 2020, Manhattan had 1,694,251 residents living in an area of 22.83 sq mi, giving it a density of 74,780.7/sq mi.

As the next map shows, in 1950 the 20 largest cities in the United States were considerably denser that those of 2022. 1950 was arguably the heyday of American urbanism. Driven in part by the war-economy of the first half of the decade, all large U.S. cities grew during the preceding census interval, some by considerable margins. Extremely rapid growth occurred both in sparsely inhabited cities (see Houston on the map below) and in densely settled ones such as San Francisco and Washington, DC.

Seven cities are found on the lists of the 20 largest U.S. cities in both 1950 and 2022. As can be seen on the map posted below, the country’s two densest major cities, New York and San Francisco, experienced relatively little change in either population size or density in the intervening 72 years. Two relatively densely settled cities, Chicago and Philadelphia, saw significant populations losses in the same period, reducing their densities. In contrast, two West Coast cities, Seattle and Los Angeles, experienced major increases in both population and density. Houston, in contrast, saw a huge population increase but did not more into a higher population-density category, as it also expanded in area.

The next map, indicating population size but not density, shows which cities dropped out of the top-20 list between 1950 and 2022 and which ones were added to it. The geographical pattern seen here is stark but not surprising. Except for New Orleans, all the “drop-out” cities are in the northeastern quadrant of the country. In contrast, with the exceptions of Indianapolis and Columbus, all the additions are in the southern half of the country. Interestingly, Columbus has many attributes of a sunbelt city, although it experiences very little sunshine from November through March. The concentration of emergent, low-density, large cities in Texas is also noteworthy.

The final map addresses a question that probably crossed the minds of some readers: where are such major cities as Atlanta or Miami? With just under half a million residents, Atlanta is not a particularly large city, although its metropolitan area certainly is. The same patterns holds for Miami. The map below thus shows the locations (but not the populations) of cities that anchor metropolitan areas in the top 30 by population in 2022, but did not themselves place in the top-20 city lists of either 1950 or 2022. It is not coincidental that three of the eight are in booming Florida.

The first two maps in this post are somewhat misleading, as they do not adequately convey the population density of New York. To do so properly, the city must be broken down into its five constituent boroughs. This will be done for the next GeoCurrents post.

U.S. City Size, Density, & Population Change, 1950 to 2022 – and the Dream of the “15-Minute City” Read More »

Mapping the Development of the Urban Framework of the United States, 1790-1830

I am currently working on an online historical atlas of the development of the urban framework of the United States. The maps and commentaries that will constitute this atlas will be posted gradually over the next few weeks or months, interspersed with regular GeoCurrents posts. The first of these installments, showing the situation in 1840 and outlining the “Philadelphia problem,” appeared on October 13, 2023. Today’s post examines the development of the network of cities in the United States from 1790 to 1830. The population figures in today’s post, like that of October 13, are derived from a Wikipedia article called “List of Most Populous Cities in the United States by Decade.” In subsequent posts, covering the period after 1840, a more comprehensive data source will be used.

The United States had few cities of any size in 1790. New York City tops the conventional list, with 33,131 inhabitants, and Philadelphia comes in second, with 28,522. But Philadelphia at the time was limited to what is now called Center City. If one includes what were then the separate cities of Southwark and Northern Liberties District, which were annexed in 1854, Philadelphia ranks first, with a population of 44,096, and is mapped accordingly.  As can be seen on the map posted below, the country’s main cities – or towns, in one prefers – of the time were all ports, located on the coast or along estuaries. Except for Charleston, South Carolina, all of them were in the greater northeast. The prominence of New England on this map, with more than half of the cities depicted, will not persist into the 1800s as the urban center of gravity shifts south into the Mid-Atlantic states.

The largest cities on the 1790 list significantly expanded from 1790 to 1800, with New York growing from 33,131 to 60,514, Baltimore from 13,503 to 26,514, and Boston from 18,320 to 24,937. Philadelphia, in the larger sense, still vies with New York for top position. Norfolk, Virginia appears on this map, but the year 1800 marks its only inclusion in the top-ten list.

The rapid expansion of the country’s largest cities is a persistent feature of these maps. By 1810, the population of New York City approached 100,000. By this time, New York was clearly the country’s largest city, a position that it will retain and amplify in the following decades. The 1810 map includes the first truly inland city, Albany, New York. Located on the Hudson River, Albany’s appearance reflects the growing importance of trade with the interior. More important is the inclusion of New Orleans on the southern Mississippi, which became part of the United States with the Louisiana Purchase of 1803.

In 1820, Albany drops of the map, replaced by Washington DC, which had 13,247 inhabitants in that year. But as the nation’s capital experienced relatively slow growth after this period, it falls off the top-ten list in 1830 and does not reappear until 1950. In the early nineteenth century, Washington was derisively called “the city of magnificent distances” due to its small number of residents living in an urban framework designed for a larger population. In 1842, Charles Dickens claimed that “Its streets begin in nothing and lead nowhere.” The fact that capital of the United States was such a small city reflects the limited extent of the federal government before the Civil War. As its constituent states were arguably more important than the country itself, the common locution at the time was “The United States are…,” rather than “the United States is… .”

The major changes on the map of 1830 reflect the opening of the Erie Canal (the dotted blue line on the map) in 1825. The Erie Canal facilitated the emergence of an extensive water-based transportation network, linking the Hudson River to the Great Lakes, and, by extension, to the Ohio and Mississippi rivers. Not surprisingly, Albany reappears on the 1930 map. More important, Cincinnati emerges as the first significant Midwestern city. Cincinnati will remain in the top-ten list until 1910. Today, with a population of 309,51, it ranks in the 64th position, surpassed by a few suburbs of little historical significance. In the early and mid-1800s, however, Cincinnati was a major and rapidly growing city, due in part to its role in butchering and processing hogs for the national market. This industry was so important that the city was deemed “Porkopolis.” As is explained in a 2016 Cincinnati Magazine article:

“Porkopolis” is one of the names by which Cincinnati is known, and its origin is explained in the following manner: About 1825 George W. Jones, president of the United States branch-bank, and known as “Bank Jones,” was very enthusiastic about the fact that 25,000 to 30,000 hogs were being killed in this city every year; and in his letters to the bank’s Liverpool correspondent he never failed to mention the fact, and express his hope of Cincinnati’s future greatness as a provision-market. The correspondent, after receiving a number of these letters, had a unique pair of model hogs made of papier mache, and sent them to George W. Jones as the worthy representative of ‘Porkopolis.’”

… Frances “Fanny” Trollope is infamous for publishing a scathing indictment of Cincinnati in her 1832 book “Domestic Manners of the Americans”. A great deal of her bile is directed at our pigs:

“If I determined upon a walk up Main-street, the chances were five hundred to one against my reaching the shady side without brushing by a snout fresh dipping from the kennel; when we had screwed our courage to the enterprise of mounting a certain noble-looking sugar-loaf hill, that promised pure air and a fine view, we found the brook we had to cross, at its foot, red with the stream from a pig slaughterhouse while our noses, instead of meeting ‘the thyme that loves the green hill’s breast,’ were greeted by odours that I will not describe, and which I heartily hope my readers cannot imagine.”

It is not coincidental that the Procter & Gamble Company is headquartered in Cincinnati. As explained in Encyclopedia Britannica:

The company was formed in 1837 when William Procter, a British candlemaker, and James Gamble, an Irish soapmaker, merged their businesses in Cincinnati. The chief ingredient for both products was animal fat, which was readily available in the hog-butchering centre of Cincinnati. The company supplied soap and candles to the Union Army during the American Civil War and sold even more of these products to the public when the war was over.

Although candles are now usually made of wax, historically they were mostly made from animal fat. In earlier times, only prosperous people could afford wax candles.

Mapping the Development of the Urban Framework of the United States, 1790-1830 Read More »

Non-Metropolitan Patterns of Population Change in the United States, 2020-2022

Earlier this year Axios published a revealing map of population change in all counties in the United States from 2020 through 2022. This map, unlike the ones that I made and posted earlier this week, allows one to assess population change in non-metropolitan as well as metropolitan areas. As can be easily seen for the United States as a whole, rapid growth was concentrated in three areas: western and central Florida; the suburban and exurban fringes ringing the largest cities of Texas; and a western belt encompassing Utah, Idaho, and western Montana. Other interesting patterns can also be discerned. To clarify them, the rest of this post will examine state-and regional-level map-details extracted from this national map.  

Let us begin with Appalachia. Several recent articles (for example, this one by Aaron M. Renn) have noted that southern Appalachia is doing much better than northern Appalachia on almost every metric. It is therefore no surprise that most counties in southern Appalachia grew during this period while many if not most in the north shrank (that is, if “north” is defined as all areas north of the northern borders of North Carolina and Tennessee).

Appalachia is often placed in the same cultural and socio-economic category as the Ozark Plateau, located mostly in southern Missouri and northern Arkansas. Both areas are characterized by steep terrain, heavy forests, and a backwoods folk culture that is both widely denigrated and romanticized. In terms of recent population change, the Ozark Plateau clearly groups with southern Appalachia. But as can be seen on the paired maps below, most counties in this region lost population, or remained relatively static, during the 2010 to 2020 period. The only substantial growth then was in its two metropolitan areas, Springfield in southwestern Missouri and Fayetteville-Springdale-Rogers (home of Walmart and several other major corporations) in northwestern Arkansas. When the COVID pandemic hit, however, people began to relocate to the region’s rural counties. I was intrigued by the very rapid growth shown for Wright County. A quick Internet search, however, returned almost nothing other than a single highly misleading post from World Population Review, which claimed that the county’s population dropped during this period. But as the table and graph posted below indicate, this information was improperly extrapolated from a tiny snippet of information from an earlier period. I find it amusing that this reputable website claims that Wright County lost exactly 63 people every single year between 2011 and 2023! Such are the dangers of automated demographic interpretation.

Recent population growth in the Ozark Plateau is reflected in the expansion experienced in other lightly populated, scenic parts of the country. Most of Maine, the northern lower peninsula of Michigan, and northern Wisconsin also saw rural population growth in this period. An interesting place to examine this phenomenon is in the Dakotas. As the maps posted below show, most counties in far western South Dakota saw major population gains from 2020 to 2022 whereas most of those of western North Dakota saw significant declines. This pattern is easily explained. Western North Dakota experienced massive growth from 2010 to 2020 due to the oil boom in the Bakken Formation. That boom came and went (although it may return), and as a result the region’s population dropped sharply after the 2020 census. Western South Dakota, in contrast, contains the Black Hills, a scenic region with high amenity values. It is therefore no surprised that it saw a boom during the COVID period. It is important to note, however, that many counties in the western Dakotas have so few people that the gain or loss of a small number can make a dramatic difference on this map.

Differences between states are also apparent on the national COVID-era population-change map. Consider, for example, the neighboring states of Illinois and Indiana. Although Indiana and Illinois are politically very distinct, their non-metropolitan counties are quite similar. But recent population change at the county level differs greatly across the state border. Only five counties in Indiana had more than a one-percent population loss during this period, whereas only three counties in Illinois had more than a one-percent gain. The financial woes of Illinois are probably a significant factor here.

Idaho and western & south-central Montana show stark difference between the 2010-2020 and the 2020-2022 population-change maps. In the earlier period, quite a few primarily rural counties lost population. In the latter, only tiny Wheatland County, Montana (population 2,069 in 2020) lost more than one percent of its residents. From 2020 to 2022, many counties in this region, both metropolitan and rural, saw population gains of more than five percent.

California makes an interesting contrast with Idaho and Montana. Population loss from 2020 to 2022 was concentrated in the affluent coastal region, with San Francisco County exhibiting a drop of 7 percent, the largest in the country. But quite a few low-population, peripheral counties also experienced big drops, with Lassen declining by more than five percent. Intriguingly, some of these scenic counties with high outdoor-amenity values had experienced demographic booms in the final decades of the twentieth century. But as can be seen in the tables posted with the map below, this growth had essentially come to an end by 2010. Both Tuolumne and Mono counties, adjacent to Yosemite National Park, lost more than one percent of their population between 2020 and 2022. Evidently, state boundaries matter considerably in relocation decisions, and California is no longer a very attractive state.

 

 

 

 

Non-Metropolitan Patterns of Population Change in the United States, 2020-2022 Read More »

Striking Patterns of Population Change in U.S. Metropolitan Areas, 2020-2022

The 2020 to 2022 COVID period saw major population changes in the metropolitan areas of the United States, with some experiencing rapid gains and others rapid losses. Wildwood-The Villages, Florida, for example, saw a staggering 11.75 percent population increase, whereas Lake Charles, Louisiana witnessed a sobering decline of 6.01 percent. Mapping these changes reveals some interesting patterns.

The first map, showing population change in major metropolitan areas (defined here as those with more than 1.5 million people in 2002) exhibits clear regional differences. A stark north/south divide is evident in the region east of the Mississippi River. Here, every major metro area in the South saw population gains, some significant. So too did three out four in the lower Midwest (Columbus, OH, Cincinnati, OH, and Indianapolis, IN), although by smaller margins. By contrast, every major metropolitan area in the Northeast and upper Midwest lost population. In the western two-thirds of the country, population declines were restricted to the Pacific Coastal region. Here every major metropolitan area except Seattle saw a decline. Texas, in contrast, is notable for its rapid metropolitan expansion, with Dallas, Houston, Austin, and San Antonio all registering major gains in this period.

Somewhat different patterns are seen on the map of secondary metropolitan areas, defined here as those with populations between 700,000 and 1.5 million in 2022. As can be seen, fewer of these smaller metro areas lost population, indicating a shift from larger to smaller cities. Intriguingly, most of those that did decline are in or near the Mississippi River and the eastern Great Lakes, the main transportation corridor of the central part of the U.S. before the coming of railroads. New Orleans (official, the New Orleans–Metairie metropolitan statistical area) saw a drop of over 3.5 percent. I was surprised to see that New Orleans is no longer populous enough to qualify for the higher categories on this map, as its population has apparently dropped below one million. A major statistical discrepancy, however, complicates this analysis. According to the Wikipedia table that I used to make this map, New Orleans–Metairie had a population of only 972,913 in 2022, having declined from 1,007,275 in 2020. The Wikipedia article on the New Orleans–Metairie metro area, however, gives it a population of 1,271,845 in 2020. But no matter how one looks at it, New Orleans has hemorrhaged population, with the city itself dropping from 627,525 residents in 1960 to 383,997 in 2020.

The secondary metro areas that saw population growth in this period also exhibit some interesting patterns. Those in the Atlantic Northeast all saw minor population gains, presumably due to people fleeing the region’s larger and more expensive major metro areas. Much more rapid expansion, however, was experienced in the secondary metro areas of the southeast, particularly in Florida and the Carolinas. Secondary metro areas in the interior West also saw substantial growth.

Even more distinct patterns are visible on the map showing the fastest growing and fastest shrinking metro areas of all sizes during this period. (Many official metropolitan areas, it is important to note, are not large; Eagle Pass, TX, for example, has fewer than 60,000 inhabitants.) As can easily be seen, most of the fastest growing metro areas are in the southeastern coastal region, stretching from the Gulf Coast of Alabama through the Atlantic Coast of the Carolinas. Florida really stands out on this map. Several smaller metro areas in the non-coastal West also saw extremely rapid growth. St. George UT, for example, went from 180,279 to 197,680 inhabitants, a gain of almost 10 percent. After having witnessed the boomtown atmosphere of Bozeman MT, which does not even qualify for this map with a growth rate of just under 5%, I have a difficult time understanding how the infrastructure of Saint George could keep up with such rapid population expansion.

In contrast, three states stand out for the rapid population decline of many of their metropolitan areas: California, Louisiana, and West Virginia (metro area #16 on this map is Weirton–Steubenville, located in both West Virginia and Ohio). Although metropolitan growth from 2020 to 2022 was concentrated in Republican-voting states, Louisiana and West Virginia form clear exceptions.

The final map shows population loss-and-gain patterns in California’s metropolitan areas during the same 2020-2022 period. Here again the pattern is clear: all coastal metro areas,  which have equable climates but are very expensive, lost population, whereas most less-expensive metro areas in the Central Valley, a region noted for its scorching summers, gained population, as did the similarly toasty San Bernardino-Riverside metro area in Southern California, the so-called Inland Empire. The college town of Chico in Butte County in the northern Central Valley (or Sacramento Valley) however, saw a significant population drop.

Tomorrow’s post will examine the geography of population change in this period in rural counties.

Striking Patterns of Population Change in U.S. Metropolitan Areas, 2020-2022 Read More »

Air-Conditioning Needs and Cartographic Failure at the Washington Post

The Washington Post recently ran an article entitled “Addicted to Cool: How the Dream of Air Conditioning Turned into the Dark Future of Climate Change,” which features three maps of “Summer Days Requiring AC” in the U.S. at different periods of time (1981-200, 2001-2002, and 2060). As expected, the region needing air conditioning is projected to expand. Determining how many days actually “require” air conditioning is, however, an impossible task, as different people vary significantly in their cooling desires and demands, while housing design and shade considerations make big differences as well. Understandably bypassing such complexities, the newspaper used the heat index, a measurement of temperature and humidity, as a proxy. Unsurprisingly, their maps show that a large area of the country already needs summer air conditioning, and that in the decades to come the need for cooling will geographically expand.

The maps included in the article, however, are not impressive, to put it mildly. Their problems are particularly severe regarding California. As can be seen on the map detail of Southern California posted below, the Post’s mapping accurately shows the eastern deserts and the inland western regions as needing air conditioning on most if not all summer days. It also accurately depicts the highest elevation areas as rarely requiring it. But the same map also portrays the coastal zone as AC-dependent. This is not true. Downtown San Diego, for example, has an average July high temperature of 75 degrees Fahrenheit and an average July low of 66 (over the 1991-2020 period). Further north, in Rancho Palos Verdes, similar conditions prevail. According to Weather Spark, “The hottest month of the year in Rancho Palos Verdes is August, with an average high of 76°F and low of 64°F.” The same site also notes that “Over the course of the year, the temperature typically varies from 51°F to 76°F and is rarely below 46°F or above 84°F.” This is climate that very rarely calls for cooling.

The map is equally inaccurate in its depiction of Northern California. As can be seen on the map detail posted below, it does capture the cool summers characteristic of the coastal regions in and around San Francisco and Monterey bays. It completely misses the fact, however, that other coastal regions also have mild summers. The average July high and low temperatures in Point Arena, Santa Cruz, and Carmel are, respectively 65 and 50 degrees F.; 74 and 54; and 70 and 53 (all based on the climatological data found in the Wikipedia articles on these towns). In Point Arena, one is more likely to want heating than air conditioning in June and July, yet the map indicates that cooling is needed on most summer days.

Other odd features mar the map. As can be seen, the city of San Francisco is mislocated in the bay and on its eastern shore.  The national map also features a faint white line that traces part of San Francisco Bay and would appear to indicate the actual coastline, at least in some areas.  Was one map imprecisely overlaid on another?

Although these problems are serious enough, it is the map of projected air-conditioning needs in the year 2060 that truly fails. This can be seen easily on the paired maps showing current and projected AC requirements in California. Here much of the currently cool Big Sur coastal zone is projected to have much reduced air-conditioning needs by 2060. This region of projected cooling is bizarrely shown as extending over the Santa Lucia Range into the southern Salinas Valley, an area that now experiences warm summers (King City has an average July high of 85 degrees F.). Similarly, the currently warm inland area north of Santa Barbara is shown as being expected to have much cooler summers in 2060 than it does today, while with the rest of Southern California is projected to warm.

One can only wonder whether the cartographers in question actually examined these maps before publication, or, if they did, whether they have much of an understanding of the geography of climate. It often seems that journalists use maps as mere ornaments or, alternatively, to have the appearance of spatial precision without the substance. The maps in this article do little more than make the trite point that “more of us will need air conditioning as the climate warms.” Readers deserve better, especially from a once-great paper that is owned by the third richest person in the world.

Air-Conditioning Needs and Cartographic Failure at the Washington Post Read More »

Geographical Patterns of Income Inequality in the U.S. at the State and County Levels

I have long been intrigued by the geography of income inequality in the United States. As maps of the GINI coefficient show, income inequality is highest some of the country’s richest states (New York, Connecticut) and in some of its poorest (Louisiana, Mississippi). Similarly, some of the country’s most Democratic-voting states and some of its most Republican-voting ones are characterized by pronounced income inequality. Relatively low levels of income inequality are concentrated in an area that might crudely be described as the center-north-west, with four contiguous states occupying the lowest category on the map (Utah, Idaho, Wyoming, South Dakota). Low population density characterizes states with low income inequality. All of the states in the bottom two categories on this map except Hawaii have a lower-than-average population density. Politically, these states show the same mixed pattern that characterized the most economically polarized states. Although all the states in the lowest GINI category are bright red on electoral maps, two that fall into the next lowest category (Vermont, Hawaii) are bright blue.

A county-level GINI map clarifies the geography of U.S. income inequality and reveals some interesting patterns (unfortunately, the best map that I could find on this topic is somewhat dated). As can be seen, the elevated levels of income inequality found in northeastern states is largely an urban phenomenon. In the southeast, in contrast, some counties with high GINI coefficients are metropolitan (in southeastern Florida, for example), but others are markedly rural. In Western and Great Plains states characterized by relatively low income inequality, quite a few of their rural counties have high GINI scores.

In North Dakota, South Dakota, and Montana, some rural counties characterized by high income inequality also have a high percentage of Native American residents. To illustrate this correlation, I have placed a GINI map of the Dakotas next to one of indigenous population percentage. But there are a few striking exceptions to this pattern, two of which are noted on the map. As can be seen, Divide County, North Dakota has a small Native American population and a high GINI coefficient. Pete Morris’s agricultural explanation of income inequality, outlined in his comment on yesterday’s post, is probably relevant here as well. In contrast, Buffalo County, South Dakota has a large Native American population and a low GINI coefficient. Both of these counties have very small populations. Buffalo County is noteworthy for having the least populous county seat in the United States (Gann Valley, with a population of 14).

In the south-central region of the country, most counties with high levels of income inequality have large black populations. But again, interesting exceptions can be found. As can be seen, Jefferson County, Arkansas has a high percentage of Black residents and a mid-level GINI ranking. In contrast, Marshall County, Alabama has a very low percentage of Black residents and a high level of inequality. Jefferson County, intriguingly, is known for its concentration of “correctional facilities,” mostly located in and around Pine Bluff. Marshall County, Alabama, in contrast, is part of the Huntsville-Decatur Combined Statistical Area, a region noted for its many well-paid technical workers, owing largely to that presence of NASA’s Marshall Space Flight Center, the United States Army Aviation and Missile Command, and the FBI ‘s Operational Support Headquarters. Marshall’s largest city, Albertville, is mostly noted, however, as the home of the fire-hydrant-manufacturing Mueller Company. As noted by the Wikipedia article on the city, “Albertville holds the title of “Fire Hydrant Capital of the World.” To commemorate the one millionth fire hydrant, a chrome fire hydrant was placed outside the Albertville Chamber of Commerce.”

The next GeoCurrents post will examine the geography of income  inequality in the country’s largest metropolitan areas.

Geographical Patterns of Income Inequality in the U.S. at the State and County Levels Read More »

Explaining Seeming Discrepancies on County-Level Income Maps of the United States

When working on a recent GeoCurrents post that involved maps of income in the United States, I noticed a few unusual patterns. A number of counties, for example, are mapped as having relatively high per capita personal income and relatively low median household income, whereas in others the opposite pattern obtains. In part this is a matter of household size, an explanation that works particularly well for Utah. Consider, for example Utah County, Utah which is characterized by relatively low per capita personal income, relatively high median household income, and a large number of people per household. In contrast, Grand County is characterized by relatively high per capita personal income, relatively low median household income, and a small number of people per household.

In Utah, the number of people per household correlates closely with religion. Members of the LDS church (Mormons) often have high fertility rates, leading to large households. Utah County, Utah, home of Brigham Young University, is usually considered the cultural center of the LDS faith. As can be seen on the second map below, Utah County has one of the highest fertility rates in the country. In contrast, Grand County has a relatively low fertility level (which is not shown in the map due to its small population) and the lowest LDS percentage in the state. Whereas Utah as a whole is roughly 62% Mormon, in Grand County the figure is only 26%.

These easy correlations, however, collapse when one examines North Dakota. As can be seen on the map below, Cavalier County has the highest per capita personal income in the state, which is why it is outlined with a heavy white line on the map posted here. But Cavalier County is also characterized by relatively low median household income and relatively few people per household. This seeming anomaly can be explained by taking into account the different way that the two income measurements are determined. Median household income is calculated by taking the income of all households in a county and finding the middle point; per capita personal income, on the other hand, is calculated by dividing the total income of all persons in the county by the population. If a county has a small population with a few very high-income individuals, the per capita personal income figure is inflated, whereas the median household income figure will remain low if most households have lower incomes.

If this explanation is correct, one would expect Cavalier County to have a relatively high Gini Coefficient, which measures the degree of inequality. The most recent GINI map of all U.S. counties that I was able to find (posted below) indicates that this is indeed the case. Overall, North Dakota is characterized by very wide range in GINI figures, which is probably largely an attribute of the small populations of most of its counties.

 Regardless of its income level, Cavalier has not exactly been a thriving county over the past century. It had more than 15,000 people in 1920 and fewer than 4,000 in 2020.

Explaining Seeming Discrepancies on County-Level Income Maps of the United States Read More »

The Very Wet and Very Dry Summer of 2023 in the United States (and Its Consequences for the U.S. Corn Crop)

The 2023 meteorological summer (June-August) in the United States was both very dry and very wet, with extreme precipitation variation. As the map posted below shows, this was the driest summer since (at least) 1895 over several widely scattered parts of the country, including western Oregon, southern Arizona, western New Mexico, southern Louisiana, southeastern Texas, and the southeastern corner of Minnesota. The map also shows a small area near California’s Bay Area as having experienced its driest summer since 1895, but this particular depiction is misleading. Like most of the rest of the state, this region experiences negligible summer precipitation, getting a little over a tenth of an inch on average (see the table posted below for Antioch, CA). The difference between 0.01 inches and 0.15 inches may be large in percentage terms, but it means next to nothing in regard to actual conditions.

The 2023 summer drought in southern Minnesota, Iowa, and adjacent areas is concerning, as this area forms the heart of the U.S. corn belt. The official Drought Monitor Map shows severe to extreme drought over much of the same area. Curiously, this map also shows extreme long-term drought in parts of Kansas and Nebraska that experienced well above average summer precipitation this year. Some critics complain that the U.S. Drought Monitor is too slow to revise its mapping as conditions change.

Given such dry conditions over much of the corn belt, one might expect a reduced U.S. corn harvest in 2023. But according to an August 8 Reuters headline, “U.S. Farmers Expect Corn Harvest Could Be Second-Biggest Ever,” with the article explaining that “rains during July shepherded the crop through its critical development phase, offsetting dry conditions early in the season and hot summer temperatures.” A Successful Farming article outlines the problems faced by Minnesota farmers due to a three-year drought, while noting that technical improvements have mitigated the damage:

Bob Worth, president of the Minnesota Soybean Growers Association and a corn and soybean farmer in Lincoln County, Minnesota, said that improvements in seed technology is saving his farm from complete disaster despite the dry conditions: “If we had the same hybrids that we had in my early farming years,” Worth said, “we wouldn’t have a crop with as little rain as we’ve gotten.”

Despite its relatively healthy 2023 corn crop, the United States just lost its position as the world’s top corn exporter. The title was handed over to Brazil, as was that for soybeans a few years ago. According to a recent Bloomberg report (cited in Farm Policy News):

For more than half a century, US farmers dominated the international market for corn, shipping more of the critical crop than any other country to feed the world’s livestock, fill its stockpiles and manufacture its processed foods. No more. In the agricultural year ending Aug. 31, the US handed the corn-exporting crown to Brazil. And it might never get it back.

Other parts of the United States saw record-breaking precipitation in the summer of 2023. As the first map in this post shows, much of northern New England, eastern Michigan, southern California, central Wyoming, eastern Colorado, and south-central Montana experienced their wettest summer since 1985. Tropical Storm Hilary was responsible for most of this precipitation in southern California, and for some of it in central Wyoming and south-central Montana.

If the summer 2023 precipitation map had included the first three days of September, its depiction of the southwestern quadrant of the United States would have been quite different, showing much higher figures for eastern Arizona, Nevada, and parts of northern California (see the map below). A rare early-September cut-off low-pressure system rotated off the cost of far northern California during this period, bring unprecedented precipitation to many areas, as well as widely mocked misery to campers at the Burning Man Festival in northwestern Nevada.

Note on this map the extraordinarily steep gradient on the seven-day late-August to early-September rainfall map in northern California. Here areas getting less than five percent of average precipitation in this period are almost adjacent to those getting over 600 percent. This seeming anomaly was partly the result of a sharp precipitation cut-off in the recent storm, with entrained bands of rainfall hitting some areas repeatedly while leaving nearby areas completely dry. But it is also, again, a consequence of the extremely dry average conditions in this region at this time of the year.

The Very Wet and Very Dry Summer of 2023 in the United States (and Its Consequences for the U.S. Corn Crop) Read More »