“The Great Adjustment Debate: Is Climate Data Really Reliable?” Exploring the discrepancies between raw data and adjusted climate records. By DR. MATTHEW WIELICKI
Many question whether these adjustments are made to exaggerate warming trends, while mainstream climate scientists and NOAA argue that they are necessary to correct known biases in historical measure
The Great Adjustment Debate: Is Climate Data Really Reliable?
Exploring the discrepancies between raw data and adjusted climate records.
SEP 12
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PAID
In recent years, the debate over temperature data adjustments has become increasingly polarized. Many question whether these adjustments are made to exaggerate warming trends, while mainstream climate scientists and NOAA argue that they are necessary to correct known biases in historical measurements. To explore this issue, I will compare some different independent analyses of NOAA temp data adjustments.
NOAA’s Position and Modern Adjustments
The U.S. Climate Reference Network (USCRN) was introduced as a modern dataset with state-of-the-art instrumentation designed to avoid the biases found in older datasets. While the USCRN provides more reliable data, NOAA continues to defend the necessity of adjusting historical data. For instance, NOAA’s methods include homogenizing data from older datasets to align them with modern readings, an effort designed to present a coherent historical record. However, critics argue that these adjustments, while intended to address biases, often reinforce the narrative of accelerated modern warming.
Berkeley Earth: Defending Data Adjustments
In their report, Berkeley Earth justifies the need for adjusting historical temperature data by explaining that such data is prone to various biases that can distort long-term climate trends. These adjustments are intended to correct inconsistencies in the historical record to provide a more accurate representation of temperature changes over time. Two major types of bias that Berkeley Earth addresses are Time of Observation Bias (TOBs) and the Pairwise Homogenization Algorithm (PHA).
Time of Observation Bias (TOBs):
Historically, temperature recordings at weather stations were made at different times of day, and over the years, a systemic shift occurred. Before the 1950s, many stations recorded temperatures in the afternoon, but after the 1950s, the observation time shifted to morning at many stations. This change led to a cooling bias in the recorded temperatures, as morning temperatures are typically cooler than afternoon temperatures. The shift, if unadjusted, would create the false impression that earlier decades were warmer than they were compared to modern records.
By adjusting for TOBs, Berkeley Earth and NOAA argue that this bias can be corrected, by raising past temperatures slightly and aligning historical data with modern observations for a more accurate comparison. This adjustment results in a more consistent and reliable long-term trend of temperature change, free from the distortions caused by inconsistent observation times.
Pairwise Homogenization Algorithm (PHA):
PHA is another technique used to adjust for non-climatic factors influencing temperature measurements. Localized factors such as the relocation of weather stations, changes in instruments, or the influence of urban heat islands can introduce artificial changes in temperature data. For instance, when weather stations move from a rural to an urban location, or when modern instruments replace older ones, the data can reflect changes that have nothing to do with climate and everything to do with local influences.
The PHA works by comparing each station’s data to nearby stations that have similar conditions, allowing it to detect and correct for anomalies that may result from these non-climatic factors. This method ensures that temperature records reflect broad regional climate changes rather than localized disturbances or technical changes. Berkeley Earth emphasizes that such adjustments are crucial for constructing a more accurate global temperature record, arguing that without these corrections, the data would be unreliable.
Geophysical Research Letters Review
The 2015 paper published in Geophysical Research Letters titled “Evaluating the Impact of U.S. Historical Climatology Network Homogenization Using the U.S. Climate Reference Network” argues that NOAA’s adjustments are scientifically sound and necessary. It claims that even with significant adjustments, the warming trend remains consistent with the data. However, this study has been critiqued for pushing a specific climate narrative by validating adjustments that systematically create a warming bias, despite acknowledging the data complexities.
It is important to note that NOAA’s methods validate confirmation bias by adjusting historical records to fit the narrative of modern climate models, which project increasing warming. This approach, while designed to improve data accuracy, may obscure natural climate variability and inflate the urgency of climate action. The emphasis on adjustments that warm the present and cool the past raises concerns about the integrity of the long-term climate record.
This practice raises the possibility of confirmation bias, something I have discussed at great length that is inherent in the IPCC, adjusting historical data to align with modern climate narratives. This paper, while endorsing the quality of modern datasets like USCRN, tends to brush over uncertainties and complexities in historical data corrections, framing the adjustments as unquestionably scientific.
Both the USCRN data and NOAA’s historical adjustments thus reveal a tension between refining data quality and pushing a narrative that supports dramatic climate action. These biases are subtle yet significant, and they underscore why a more critical examination of temperature data, and how it’s presented to the public, is necessary before making drastic policy decisions based on potentially skewed records.
MDPI’s Atmosphere Journal: A More Critical View
In contrast to the above reports, the MDPI paper "Evaluation of the Homogenization Adjustments Applied to European Temperature Records in the Global Historical Climatology Network Dataset" questions whether the temperature adjustments made to climate data might be inflating modern warming trends. The paper argues that the methods used to correct historical temperature records may not be as neutral or scientifically robust as they are claimed to be, raising concerns about the accuracy of long-term climate projections.
Overemphasis on Adjustments
The MDPI paper points out that, while some adjustments to historical data may be necessary due to changes in observation methods, station relocations, or instrument upgrades, the extent of these adjustments, particularly in recent decades, seems excessive and could introduce a warming bias. The paper argues that these corrections may magnify the warming trend beyond what the raw data would suggest. Essentially, it raises the question of whether the adjustments are truly justified by the available data or if they reflect a degree of confirmation bias, a tendency to interpret data in a way that confirms pre-existing beliefs about climate change.
One of the key criticisms is that many of the adjustments result in past temperatures being lowered, while more recent temperatures remain relatively unchanged or even increased, thereby exaggerating the warming trend. The MDPI paper suggests that this pattern may distort the real picture of how the Earth's climate has changed, making the recent warming appear more dramatic than it might be without such adjustments.
Urban Heat Island Effect
A significant concern raised by the MDPI paper is the treatment of the Urban Heat Island (UHI) effect, a phenomenon in which urban areas retain more heat due to human activity, asphalt, and building materials. The paper argues that adjustments for UHI effects do not go far enough in accounting for how urbanization skews temperature data. Since urban areas are typically warmer than rural areas, the failure to adequately adjust for this could result in an overestimation of global warming.
This critique is important because many of the world’s temperature stations are located in or near urban centers. If the UHI effect is not properly accounted for, it may bias the overall dataset, inflating global warming estimates. The MDPI paper suggests that climate scientists might be underestimating this effect, which could be one of the reasons modern temperature records show more warming than historical records when adjusted.
Comparison and Skeptical Critique
All studies agree that temperature data requires adjustments, but the confidence in the neutrality of these adjustments varies. NOAA defends the adjustments as scientifically justified and necessary, while the MDPI paper argues that they may introduce bias and inflate warming trends.
Moreover, the reliance on techniques like PHA, where temperature records are adjusted based on surrounding stations, introduces new uncertainties. Adjustments for urban heat islands, while critical, may still fall short, potentially exaggerating the warming trend. As a result, the process of homogenizing historical temperature data requires closer scrutiny, particularly when it influences drastic climate policies.
The crux of the debate centers on whether these adjustments serve to clarify the historical climate record or whether they reflect confirmation bias in climate science. For instance, if corrections systematically make past temperatures cooler and modern temperatures warmer, it creates a more pronounced warming trend.
Conclusion: Questioning the Neutrality of Adjustments
The debate over temperature adjustments reveals a significant divide in how we interpret climate data. Berkeley Earth and NOAA argue that these adjustments are necessary to correct known biases, but critics like those in the MDPI paper suggest they may introduce a warming bias that distorts the true climate picture.
Given the magnitude of recent adjustments, particularly those that cool the past and warm the present, it’s important to question the neutrality of these corrections. With so much at stake in terms of climate policy, a more critical examination of how data is adjusted is crucial. Should sweeping policy decisions be based on adjusted datasets that introduce their own biases? Policymakers and the public should carefully consider this question before accepting the prevailing climate narrative.