Data quality
Number of papers: 15
Examination of space-based bulk atmospheric temperatures used in climate research — International Journal of Remote Sensing, 2018; Christy, Spencer, et al
These experts in satellite temperature measurement report on the latest data sets in 2018. They find “evidence that MSUs (temperature sensors) on National Oceanic and Atmospheric Administration’s satellites (NOAA-12 and −14) contain spurious warming, especially noticeable in three of the four satellite datasets. Comparisons with radiosonde (balloon) datasets independently adjusted for inhomogeneities suggest the actual tropical (20°S-20°N) trend is +0.10 ± 0.03°C per decade. This tropical result is over a factor of two less than the trend projected from the average of the IPCC climate model simulations for this same period (+0.27°C decade−1).
Systematic Error in Global Temperatures due to Weather Station Ageing — Science of Climate, 2024; Moritz Büsing
“The white paint or white plastic of the housings of weather stations ages, which leads to increased absorption of solar radiation and to increased temperature measurements. This alone would be a small error. However, many different state-of-the-art homogenization algorithms repeatedly add this small value each time a weather station is renovated, renewed, or replaced, which results in a substantial systematic error.”
LiG Metrology, Correlated Error, and the Integrity of the Global Surface Air-Temperature Record — Sensors, 2023; Pat Frank
The entirety of the 19th century thermometer-based temperature record is worthless because of calibration and drift errors. Mercury thermometers are reasonably stable, but liquid thermometers are not. Furthermore, 20th century thermometer data does not convey any information about rate or magnitude of temperature change. The uncertainties are higher than the anomalies.
Systematic Error in Climate Measurements: The Surface Air Temperature Record — International Seminars on Nuclear War and Planetary Emergencies, 2016; Patrick Frank
This paper discusses the errors associated with various types of temperature method, concluding: “At the 95% confidence interval, the rate or magnitude of the global rise in surface air temperature since 1850 is unknowable.” This paper is heavily gated. I can send a copy to anyone interested.
Mid-Tropospheric Layer Temperature Record Derived From Satellite Microwave Sounder Observations With Backward Merging Approach — JGR Atmospheres, 2023; Zou et al.
This group carefully assessed the signal processing of satellite microwave data and finds a troposphere warming trend of 0.14 degrees K, similar to that of Christy and Spencer at UAH. This measurement once again shows that climate models are running far too hot. Commentary by Ross McKittrick.
The Detection and Attribution of Northern Hemisphere Land Surface Warming (1850–2018) in Terms of Human and Natural Factors: Challenges of Inadequate Data — Climate, 2023: Soon, Connolly, et al.
“A statistical analysis was applied to Northern Hemisphere land surface temperatures (1850–2018) to try to identify the main drivers of the observed warming since the mid-19th century. Two different temperature estimates were considered — a rural and urban blend (that matches almost exactly with most current estimates) and a rural-only estimate. The rural and urban blend indicates a long-term warming of 0.89 °C/century since 1850, while the rural-only indicates 0.55 °C/century. This contradicts a common assumption that current thermometer-based global temperature indices are relatively unaffected by urban warming biases.”
Uncertainty in the Global Average Surface Air Temperature Index: A Representative Lower Limit — Energy & Environment; Patrick Frank
The author examines the air-temperature record with thermometers and finds that the error bars on these numbers are so large that “the rate and magnitude of 20th century warming are thus unknowable, and suggestions of an unprecedented trend in 20th century global air temperature are unsustainable.”
Evaluation of the Homogenization Adjustments Applied to European Temperature Records in the Global Historical Climatology Network Dataset — Atmosphere, 2022; O’Neill et al.
From the press release: The findings of the study show that most of the homogenization adjustments carried out by NOAA have been surprisingly inconsistent. Moreover, every day, as the latest updates to the thermometer records arrive, the adjustments NOAA applies to the entire dataset are recalculated and changed. As a result, for any given station, e.g., Cheb, Czech Republic, the official homogenized temperatures for 1951 (as an example) might be very different in Tuesday’s dataset than in Monday’s dataset. … the authors warned that these bizarre inconsistencies in this widely-used climate dataset are scientifically troubling. They also are concerned that most researchers using this important dataset have been unaware of these problems until now.
On the choice of TLS versus OLS in climate signal detection regression — Climate Dynamics, 2022; Ross McKitrick
“Total least squares (TLS) or multivariate orthogonal regression is widely used as a remedy for attenuation bias in climate signal detection or “optimal fingerprinting” regression. But under some circumstances it overcorrects and imparts an upward bias, as well as generating extremely unstable and imprecise coefficient estimates. … TLS can be sufficiently biased to cause false positives when explanatory signals are negatively correlated, and the bias gets worse as the signal-noise ratio on the explanatory variables rises. Additionally TLS should not be used on its own for climate signal detection inferences since if the no-signal null is true, TLS is generally inconsistent, whereas OLS attenuation bias disappears.”
Imposed and Neglected Uncertainty in the Global Average Surface Air Temperature Index — Energy & Environment, 2010; Patrick Frank
While government agencies and journalists like to show temperatures increasing since the 1850s, this author shows that the error bars on these measurements are greater than the trend, concluding “the global average surface air temperature trend is statistically indistinguishable from 0 C.”
Analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends — Journal of Geophysical Research, 2011; Watts et al
This group analyzed hundreds of weather stations and found that fewer than eight percent of stations qualify as stations that have been able to maintain a consistent record. The rest have changed so much that their measurements are biased to some degree. A full 70 percent of sites have been interrupted, miscategorized, or compromised. The authors show that poorly sited sensors show much higher low (overnight) readings and statistically significantly higher high (daytime) readings than can be independently verified. The majority of sites used to measure US temperature have been strongly biased by urbanization and do not show temperature trends accurately.
Objectively Analyzed Air-Sea Heat Fluxes for the Global Ice-Free Oceans (1981–2005) — Bulletin of the American Meteorological Society, 2007; Yu & Weller
This long but well-written paper explains that to-date no one has actually measured energy-in vs energy-out and that, after doing so, they found that water vapor probably plays a much larger role than climate models give it credit for. If true, that would account for making models much hotter and much more dependent on CO2 as a driver. The authors conclude “The trend pattern of latent heat flux (LHF) bears a great similarity to that of SST, suggestive of an atmospheric response to oceanic forcing.” This is the opposite of what we are normally told.
Urbanization Effects on Estimates of Global Trends in Mean and Extreme Air Temperature — American Meteorological Society, 2021; Zhang et al.
“The urbanization effect on the trends of annual mean and extreme temperature indices series in East Asia is generally the strongest, which is consistent with the rapidly urbanization process in the region over the past decades, but it is generally small in Europe during the recent decades.”
Reassessment of the homogenization of daily maximum temperatures in the Netherlands since 1901 — Theoretical and Applied Climatology, 2022; Dijkstra et al.
“The parameters used for the KNMI’s current homogenization of De Bilt result in a very sharp decrease of tropical days, which is not replicated by the majority of the 116 variants. Moreover, after homogenization, De Bilt appears to be an outlier compared to the other meteorological stations. Therefore, the current homogenized estimates of tropical days for De Bilt should be treated with considerable caution.” One of the authors is Marcel Croc, a founder of Clintel.org.
The New Radiosounding HARMonization (RHARM) Data Set of Homogenized Radiosounding Temperature, Humidity, and Wind Profiles With Uncertainties — JGR Atmospheres, 2021; Madonna et al.
This team revisited and normalized balloon instrument data. Their results did not confirm the IPCC’s view that temperatures have been increasing, especially in the upper troposphere, where they were supposed to be increasing.