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Days of 90°F or hotter and Heating degree days

Where Days of 90°F or hotter is higher, Heating degree days tends to be lower. The link is very strong: -0.80 across 3,089 counties, on a scale from −1 (opposite) to +1 (in step). That figure compares places with the same population density, income and education, so those differences can't explain it. It holds inside states too. Measured separately within each of 39 states, the middle value of the link is -0.76.

Holds after adjusting

Every place, plotted

One dot for each place reporting both measures. Hover over or tap a dot to see its name and values. The thin line is the straight line that best fits the dots. The bold line, shown for counties, is the link after adjusting for density, income and education. A dot far from the lines is a place that does not follow the pattern.

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What each measure is

Days of 90°F or hotter

The number of days in the year when the high temperature reached 90°F or more. The high is the average over the county of NOAA's daily map of weather station readings, made of squares about 3 miles wide. So a county with hot valleys and cool mountains counts fewer days than its hottest town. A state's figure is the average of its counties, each weighted by its land area. Lower 48 states only, from 1951.

NOAA NCEI nClimGrid-Daily · NOAA NCEI nClimGrid-Daily v1.0.0 county averages (prcp/tmax/tmin, scaled), hot_days; states, counties averaged by land area

Heating degree days

A measure of how cold the year was, as a total over its days. A day whose average temperature is 50°F counts 15 heating degree days, the degrees it fell short of 65°F. A day at 65°F or warmer counts none. Homes often need heat on days below 65°F, so more degree days mean more heating weather. NOAA estimates them from its monthly temperatures for each county. A state's figure is the average of its counties, each weighted by its land area. Alaska and Hawaii are not covered.

NOAA NCEI nClimDiv · NOAA NCEI nClimDiv climdiv-hddccy, sum of the 12 months; states, counties averaged by land area

Highest and lowest

Where each measure is highest and lowest among the places reporting both (2023), with the other measure beside it. This is shown for every size of place where both are published. Metro-area values are added up from their counties. A measure that cannot be added up across counties, such as a middle value (median), has no metro figure. Counts are shown per 1,000 residents, since raw totals would only list the largest places. Cities and towns and ZIP codes are shown where the Census survey or the CDC publishes them; most other sources stop at the county. They are shown for places of 5,000 residents or more, and only where the survey’s margin of error is small enough for the figure to be usable. The CDC publishes its health estimates for cities in a version adjusted for age, so places with older or younger people can be compared fairly, but not for ZIP codes.

Counties

By days of 90°F or hotter

Days of 90°F or hotterHeating degree days
Highest
Starr County, TX196471
Zapata County, TX192528
Hidalgo County, TX189435
Brooks County, TX187558
Jim Hogg County, TX186571
Lowest
Teller County, CO08,987
Summit County, CO010,987
San Juan County, CO011,210
Saguache County, CO09,280
Routt County, CO09,429

By heating degree days

States

By days of 90°F or hotter

Days of 90°F or hotterHeating degree days
Highest
Texas1181,901
Louisiana1141,414
Florida105647
Arizona90.23,511
Mississippi891,888
Lowest
Rhode Island0.3965,071
Vermont0.5667,215
New York0.9476,437
Maine1.167,736
New Hampshire1.696,926

By heating degree days

Days of 90°F or hotterHeating degree days
Highest
North Dakota10.48,901
Wyoming6.968,670
Minnesota8.018,233
Montana11.68,065
Idaho10.38,000
Lowest
Florida105647
Louisiana1141,414
Georgia62.71,879
Mississippi891,888
Texas1181,901
Metro areas

By days of 90°F or hotter

Days of 90°F or hotterHeating degree days
Highest
Rio Grande City-Roma, TX196471
Zapata, TX192528
McAllen-Edinburg-Mission, TX189435
Alice, TX178607
Yuma, AZ1761,207
Lowest
Youngstown-Warren, OH05,327
Wooster, OH05,235
Wheeling, WV-OH04,964
Waynesville, NC04,945
Watertown-Fort Drum, NY06,691

By heating degree days

Days of 90°F or hotterHeating degree days
Highest
Breckenridge, CO011,117
Jackson, WY-ID010,692
Edwards, CO09,543
Evanston, WY-UT09,512
Cody, WY09,355
Lowest
Key West-Key Largo, FL13483
Miami-Fort Lauderdale-West Palm Beach, FL128122
Naples-Marco Island, FL147167
Cape Coral-Fort Myers, FL124218
Port St. Lucie, FL101219

Counties furthest from the pattern

Compared with the straight line that best fits all 3,108 counties: the five with far more heating degree days than their days of 90°F or hotter would suggest, and the five with far less.

Days of 90°F or hotterHeating degree days
Above the line
Lake County, CO011,328
San Juan County, CO011,210
Summit County, CO010,987
Sublette County, WY010,945
Hinsdale County, CO010,865
Below the line
Orange County, CA161,666
Carteret County, NC92,171
Dare County, NC162,342
Brevard County, FL64365
Hyde County, NC192,277

Two series, one county

Both measures over time for a county you pick. The two charts are stacked, so they share only the years along the bottom. You can pick from the thirty largest counties reporting both. This panel covers 2010–2024, and a measure published only once shows as a single dot.

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Every version of the link

Each row measures the same link, from −1 to +1, in a different way. If the rows mostly agree, the link does not depend on one choice of method.

Before adjusting for anything-0.7263,089 counties reporting both
After adjusting for density, income and education-0.803the part of the link that is not just how urban, rich and educated a place is
Also adjusting for population size-0.821size taken out as well as density
Also comparing only within each state-0.656each county is compared only with others in its own state, so this is no longer a comparison between states
Also holding winter sunshine equal-0.526compares counties that get the same sunlight in winter as well. If this is much weaker, part of the link is a difference between sunny and grey regions (more)
Giving bigger counties more weight-0.804the adjusted link for the average resident rather than the average county. With this weighting, the data counts for about 284 equally weighted counties
Middle value inside single states-0.763the link worked out inside each of 39 states with at least 20 counties reporting
Using ranks, after adjusting-0.831uses each county’s rank, not its value, so a few extreme counties cannot create the link

How much to believe it

Could it be chance?

The p-value is the chance of seeing a link this strong if there were really none. A value of 0.05 or less means the link is unlikely to be chance. Very small values are written in short form: 3.1e-16 means 0.00000000000000031, and the bigger the number after “e-”, the smaller the value. Treating every county as a separate case gives p = 0.000. But counties in the same state tend to resemble each other, so the better figure allows for that: p = 7.1e-19. The site tested 32,131 pairs, and testing so many turns up some flukes. The q-value allows for that too. For this pair it is 0.000.

Do nearby places look alike?

Moran’s I measures how much nearby places look alike: 0 means no map pattern, and higher means neighbours are more similar. For the part of each county that the adjustment leaves unexplained, it is +0.68 (p = 0.001). That unexplained part still clusters on the map. So some regional factor shared by both measures is not accounted for.

Did they change together?

The figures above compare counties at one moment. This asks a different question: where days of 90°F or hotter rose most, did heating degree daysmove too? Each county’s change is compared with the average change in its own state. That takes out ups and downs that hit a whole region at once. Each change is the gap between two estimates that both contain some error. That error pulls these links towards zero, so a weak one is weak partly for that reason. The q column shows whether a link could be a fluke, allowing for the many pairs tested: 0.05 or less means it is unlikely to be chance.

PeriodCountiesChange togetherWithin statesq
2014–2019 the main test: each Census survey figure averages five years, and these two do not overlap; before the pandemic3,108-0.51-0.160.143
2019–2023 a repeat check: its two five-year survey figures both include 2019, and it covers the COVID years3,108-0.44-0.060.592

Over the main period, any link between the changes could easily be chance. How change is measured.

At three sizes of place

The same pair measured across counties, metro areas and states. A missing size means the measure cannot be combined up to that level.

LevelPlacesUnadjustedAdjustedNote
county3,089-0.73-0.80
state48-0.73-0.86no same-state comparison at state level: the units do not sit inside states one to one
cbsa917-0.76-0.82not adjusted for median household income: not available at this level; no same-state comparison at cbsa level: the units do not sit inside states one to one

Related pairs

Association only. Nothing here shows that either measure changes the other. This describes counties, not the people in them. Two measures going together across places does not mean the same people have both. How the US county data works · Explore Days of 90°F or hotter and Heating degree days