IN THIS ISSUE:
- New Proof That Urban Heat Islands Bias Surface Temperature Measurements
- Contra Climate Model Projections, Large Swath of Eurasia Is Cooling
New Proof That Urban Heat Islands Bias Surface Temperature Measurements
Much of the warming measured at the Earth’s surface over the past 125 years stems from temperature measurements from locations with growing urban populations resulting in the “urban heat island” effect biasing the recorded temperatures, a study by a top-flight team of scientists from the Earth System Science Center (ESSC) at the University of Alabama in Huntsville recently published in the American Meteorological Society’s peer-reviewed Journal of Applied Meteorology and Climatology concludes. The study links increasing population density around and near surface station locations with quickly rising temperatures that bias the average temperature measure as a whole.
We at The Heartland Institute have long pointed out that reported surface temperatures have a significant warming bias. This is demonstrated when temperature comparisons are made between the surface measurements, temperatures measured by weather balloons, and those measured by global satellites.
At Climate Change Weekly over the years I have detailed how various official weather recording and reporting agencies in countries around the world have manipulated, adjusted, or “homogenized” surface temperature measurements, supposedly to correct for errors introduced by the technologies. Oddly, these “homogenization” efforts seemingly go in only one direction, with past temperatures adjusted downward and present temperatures adjusted upward. That makes the record show a steep warming trend, a steeper trend than has actually been recorded and which plays right into claims that humans are causing a dangerous global warming.
In 2017 I also detailed how in 2015, prior to the Paris climate treaty negotiations, researchers at the National Oceanic and Atmospheric Administration (NOAA) blended contaminated ocean temperature data from ships with relatively pristine data recorded by the Argo network of 3,600 floats distributed almost uniformly across the global oceans to provide temperature and salinity profiles from the surface to a depth of 2,000m, reporting an alarming increase in the rate of ocean temperature rise—supposedly refuting an observed long-term pause in rising temperatures. The shenanigans with ocean temperature data were revealed by the award-winning scientist involved in actually ensuring data quality for the agency.
Then, in 2019, scientists were forced to admit a mathematical error that undermined claims of fast-rising ocean temperatures. The scientists’ extraordinary claims had slipped right through the peer-review process at Nature.
The Heartland Institute produced two groundbreaking studies by award-winning meteorologist Anthony Watts that showed surface stations across the United States are woefully compromised by the urban heat island effect, the phenomenon where urban areas experience higher temperatures, especially at night, than surrounding rural areas, due to the replacement of natural surfaces with heat-absorbing materials such as concrete and asphalt, and being located near artificial sources of heat such as furnaces, air conditioning units, outdoor grills, and areas of high automobile and/or air traffic.
In the first report, from 2009, Watts reported 89 percent of the stations surveyed—nearly nine of every 10—failed to meet the National Weather Service’s own siting requirements for producing unbiased, reliable data. By 2022, when the surface station report was updated, Watts found the situation had gotten worse instead of having improved with insights from his first report. When the report was issued in 2022, Watts and his team of site auditors found and photographically confirmed approximately 96 percent of U.S. temperature stations used to measure temperatures failed to meet NOAA’s and the NWS’s standards for “acceptable” and uncorrupted placement. UHI-biased stations skew the reported average temperature and temperature trends upward.
Perhaps worse still, in 2024 CCW reported on the fact that investigative journalists in the United States and in the United Kingdom discovered many of the “record” or unusually high temperatures reported by official agencies came from surface station locations which had been shut down or moved years earlier. In fact, in both cases approximately 30 percent of the stations sampled, accounting for thousands of stations in the United States and hundreds in England, were “ghost” stations, locations where no station currently exists, with the reported temperatures being completely made up by the agencies, extrapolated from temperatures recorded at nearby stations. Made-up measurements aren’t measurements at all, and they certainly don’t qualify as quality-controlled data.
In the latest contribution to the growing body of literature debunking the quality of official U.S. temperature recording and reporting, ESSC scientists Roy Spencer, Ph.D., John Christy, Ph.D., and William D. Braswell, Ph.D. used a novel method to quantify the average UHI warming for summer temperatures across the contiguous United States from 1895 through 2023:
The method quantifies the sensitivity of Global Historical Climatology Network (GHCN) station raw temperature to station-centered population density (PD). Specifically, closely spaced station pair differences in monthly raw (non-homogenized) TAVG (the average of daily maximum and minimum temperature) and PD are sorted by station pair average PD into six PD classes, and linear regression estimates of the temperature sensitivity to population density change … are made for each class for historical periods ranging from 1 to 21 years in length. Every one of the resulting six sensitivity relationships in each of 22 historical periods from 1880 to 2020 are found to be positive, and their magnitudes allow construction of station-average urban heat island temperature (TUHI) curves as a function of population density.
The analysis found that between 1895 and 2023, the UHI accounted for approximately 8 percent of the measured temperature increase in stations categorized as rural, and about 65 percent of measured warming at suburban and urban stations. The overall result is that UHI accounts for at least 22 percent of the raw temperature increase measured across the GHCN as a whole.
Interestingly, the researchers found the highest rate of warming occurs when population begins increasing beyond wilderness conditions. The UHI is most impactful then, and it mostly stabilizes when the population reaches a very high density.
In addition to quantifying the impact of the UHI on U.S. surface temperature measurements in the lower 48 states, the method developed by Spencer, Christy, and Braswell provides a way to compute the UHI impact on temperatures over time, related to the increase in population density.
The reported temperatures for the United States and for most of the globe come from surface stations. By any measure, these stations and the temperatures they record are compromised by a variety of factors, including UHI introduced by poor siting and/or population density, homogenization changes that lack transparency, and the fact that some “reported data” comes from stations that simply don’t exist or that have been moved, meaning the data or its continuous trend has simply been made up. That’s certainly not how sound science should be undertaken or reported.
Far-reaching, liberty-constraining, economy-impacting public policies should not be based on such a flawed foundation. That’s not sound public policy, especially as climate policies’ champions proclaim themselves to speak for “the science” and demand policymakers follow “the science,” with no questioning or dissent allowed.
Sources: Journal of Applied Meteorology and Climatology; Dr. Roy Spencer
Contra Climate Model Projections, Large Swath of Eurasia Is Cooling
Research recently published in the journal Environmental Research Letters shows some arguably surprising findings. If the findings are correct, central Eurasia cooled significantly from 2004 through 2020, contrary to climate-model projections.
The cooling seems to be a result of increased snowfall over the region in the autumn—snowfall, by the way, which a number of scientists, media outlets, and alarmist climate pundits have forecast over the past two decades would disappear, with children no longer knowing what snow was.
The scientists involved in the study write,
In the context of global warming, autumn air temperatures in central Eurasia have exhibited a cooling trend over the past two decades.
This study reveals that . . . the autumn snow cover percentage over central Eurasia has increased by 5.38% per decade in the past two decades. Quantitative assessments indicate that the contribution of this increase in snow cover to the observed cooling was 21.5%.
The average temperatures in the central Eurasian region of study fell by two degrees Celsius, a rate of 1.425°C per decade, largely due to the 5.38 percent per decade increase in snow coverage.
Climate models fail to project global trends accurately, with their projections of the temperature increase being much higher than measured global trends. The differences between measured temperatures and the trends projected by models fall outside the error bars of the models, and the range of uncertainty for temperature projections is significant in comparison with the projected and measured increases.
This study and others suggest climate-model projections of regional climate changes, and the pronouncements of those researchers and agencies that treat model outputs as the gold standard of climate knowledge, are weaker even than the projections of global trends. Regional projections are even less certain than the projections of global temperatures.
When data and theory (or models) collide, trust the data.
Sources: No Tricks Zone; Environmental Research Letters
