July 2026 Sets a CONUS Record for the Warmest Month
A lot is being said about the fact that July 2026 eclipsed July 1936 as the warmest month on record for CONUS temperatures. Objections from contrarians are voluminous, but a post on X from Chris Martz seems to capture the gist of the objections I'm hearing. According to him, "That claim is misleading for two reasons:
- This is due to minimum temperatures only, which skew the 'average.'
- The real, measured thermometer data (area-weighted) don’t support this claim."
Each of these objections are seriously uninformed and misleading, and it won't be hard to demonstrate why. After rebutting Martz's claims, though, I'll point out some ways that this record could be reported in misleading ways, and what I think might do a better job of showing what's happening in the US.
Objection #1: The Record is Due to Minimum Temperatures Only
This is objectively false. The record is for average temperature (Tavg), not minimum temperature (Tmin), and it should be patently obvious that Tavg doesn't skew the average, it is the average. Let's help Martz out and restate his objection to something that is at least mildly intelligent. It's true that since GHG-induced warming prevents thermal energy from escaping to space, we should expect Tmin to increase more rapidly than Tmax, and this is also exactly what we observe. Both Tmax and Tmin are increasing, and Tavg, which is just (Tmax + Tmin)/2, is increasing. This is confirmation that current warming is driven primarily by increases in greenhouse gases like CO2. The Dust Bowl years, by contrast, were driven by a very different mechanism that made daytime highs (Tmax) much warmer while nighttime lows (Tmin) were comparably less affected. It would be fair to say that the 1930s were hot more because of Tmax than Tmin, and the 21st century has been hot more because of Tmin than Tmax. Because of this, it is actually more remarkable that Tavg in July 2026 has eclipsed the previous record from July 1936, since the factors that drove extremely hot summer highs in the 1930s (also made worse by human activity) are no longer at work.
| Tmax in CONUS is Increasing |
The only way to get Tmax to show record highs in the 1930s is to engage in a bit of cherry picking. We have to limit ourselves to CONUS and then limit ourselves to the Summer months.
This lets us zoom in on the area most affected by the Dust Bowl (Summer CONUS particularly in the Midwest) and minimize the fact that outside of this season and general area, the 1930s simply were not that hot. Essentially, Chris Martz wants us to zoom in on an outlier while at the same time complaining that scientists are skewing the average. I find that a bit disingenuous.
| Tmax was Hot in the Midwest. Not so Much Elsewhere |
So yes, if you engage in a sufficient amount of cherry picking, you can see the exceptional heat in Summer Tmax in the midwestern states. But that just makes it even a bit more remarkable that CONUS has so quickly eclipsed that July 1936 record.
Objection #2: "Measured Thermometer Data" Don't support This Claim
The record is recorded in NOAA's nClimDiv dataset which is "measured thermometer data (area weighted)." I think we need to help Martz out here and improve his objection to the data. His real complaint is not that nClimDiv isn't "measured thermometer data." His real complaint is that nClimDiv uses bias correction that removes non-climatic biases that affect CONUS temperature trends. He would rather us use the raw (biased) data before NOAA uses its homogenization algorithms to remove those biases. And his statements about homogenization are at best misleading (see links to further evidence and citations to the relevant literature):
- Homogenization does not technically "cool the past." Homogenization removes biases that artificially warm the past in the US. Globally, bias correction has the overall effect of increasing temperatures prior to 1940 by removing cold biases affecting SSTs. Raw temperatures globally show about 0.12°C more warming than bias corrected datasets.
- Homogenization does not "inflate recent warming by blending urban biases into rural stations." If anything, the exact opposite is the case. The "raw" USCRN dataset shows marginally more warming than the homogenized nClimDiv dataset for the years they overlap (2005 to present). And multiple lines of research confirm that the most rural stations (both in CONUS and globally) are warming at the same rate as all stations, meaning necessarily that there no remaining bias from urbanizing areas adding spurious warming to homogenized datasets. In fact, even Roy Spencer has shown that to find any bias in CONUS temperatures you have to use the raw station data. This bias is removed in homogenized datasets, and this can be seen in maps of temperature anomalies that show cities warming at the same rate as rural areas.
- Time of observation (TOBS) bias is very real, and is well-documented in the literature (Zeke Hausfather has an interactive demo here). Changing TOBS does change the frequency of double-counting either hot days or cool nights. This has been quantified and even simulated in USCRN data. Different datasets correct for this by different means and come to the same conclusions. The bias is well-quantified and therefore can be corrected.
- Martz has no familiarity with the scientific literature on bias correction (including homogenization). His claims come more from the likes of Tony Heller. I've compiled a bibliography of the literature on bias correction and urban heat islands here. Anyone can read this and check up on my claims.
- This is a record for CONUS (2% of the planet), not the globe. It's significance is not as great as record highs in GMST anomalies.
- The record high for July 2026 (76.89°F) eclipsed July 1936 (76.77°F) by 0.12°F. I haven't researched the CIs for each, but it's possible it's still a statistical tie.
- As I've shared elsewhere, record temperatures are less significant for climate than trends and larger scale distributions of temperatures. A stronger case can be made that extreme heat is getting worse in the US by looking at data in different ways. Below I'll show what I think can do a better job. And here I'll stick to CONUS, since that's what the current record is concerning.
As I discuss elsewhere, the frequency of Tmax temperatures greater than 95°F are increasing. Clearly there's a bump frequency during the 1930s, but these occur a bit more frequently now. This comes from Zeke Hausfather at ClimateBrink
I downloaded the nClimDiv monthly Tavg from NOAA and then sorted them by rank. Of the 1579 months in CONUS since 1895, I selected the top 5% (n=79) and plotted the distribution of the top 5% of monthly Tavg temperatures. I then binned these in 5-year increments and plotted the frequency of the top 5% of monthly Tavg values.
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