Statistics House of Cards? – Watt?

Climate scientists have assured us for years that NOAA’s homogeneous temperature datasets, especially the Global Historical Climate Network (GHCN), are the gold standard for tracking global warming. But what if the “correction” applied to these datasets introduces more noise than the signal? A recent study atmosphere Shocking inconsistencies were found in NOAA adjustments, raising serious concerns about the reliability of homogeneous temperature records.

The study, which was soon composed of independent climate researchers, was composed of Peter O'Neill, Ronan Connolly, Michael Connolly and Willie. NOAA's homogenization technology was carefully inspected. Known for their expertise in climate data analysis and critical assessment of mainstream climate methodology, these researchers have collected an extensive archive of NOAA's GHCN datasets for more than a decade. Their research involves tracking 1800 daily updates Analyze how NOAA's adjustment to historical temperature records changes over time.

Their discovery reveals a deep pattern Inconsistent and unexplained changes In temperature adjustments, people have prompted a re-examination of how NOAA handles climate data.

The study analyzed NOAA's GHCN dataset over a decade and found that:

• The adjustment of the same temperature record is different on different dates– Sometimes it's big.
• 64% of the breakpoints determined by NOAA pairwise homogenization algorithm (PHA) are highly inconsistentappears in less than 25% of NOAA dataset runs.
• In more than 75% of cases, only 16% of adjustments are always appliedwhich means that most “corrections” are unpredictable.
• Less than 20% of the breakpoints in NOAA correspond to the actual record station changesindicating that many adjustments were made without supporting metadata.

In layman's words: NOAA repeatedly changes historical temperature records in ways that are inconsistent, insufficient records and error-prone.

What should homogenization do?

Homogenization is a statistical process designed to eliminate non-climatic biases from temperature records such as station location, instrument type, or changes in observation time. NOAA's PHA algorithm adjusts temperature records based on statistical comparisons with adjacent sites – no actual metadata is needed to confirm whether adjustments are needed.

NOAA researchers defended this approach, claiming it effectively eliminated bias. However, new research suggests it may be introducing Arbitrary and inconsistent changes This may distort the temperature trend.

If NOAA adjustments are inconsistent, how can we trust the long-term climate trends derived from them? This is why this is important:

• Garbage, go out of garbage: Climate models and policy decisions rely on adjusted temperature data. If these adjustments are unreliable, the conclusions based on them are questionable.
• Artificial warming or cooling? The study did not explicitly analyze whether these inconsistencies tend toward warming or cooling, but past studies have shown that homogenization tends to Amplify the warming trend.
• Lack of transparency: NOAA's daily homogenized updates mean that the past has been constantly rewrites with little to no accountability or external verification.

The authors of the study believe that homogeneity is It should not be done blindly Do not use actual site metadata. Instead, the adjustment should be:

1. As much as possible, ground pass through the site metadata– Not only based on statistical model assumptions.
2. Make transparent– The user of temperature data should be notified exactly when and why adjustments are made.
3. Reassess bias– Has the warming trend been increased systematically?

If NOAA's temperature records are indeed the best we have, then they should be robust, reproducible and verifiable. Instead, this study shows that they are a moving target, adjusting frequently based on the day There is no clear reason.

The question we have to ask is: Is the global temperature record a reliable data set or a statistical house of cards?

We need transparency, accountability, and scientific rigor in climate science. Prior to this, each NOAA temperature dataset was obtained using a grain of salt.

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