For decades, the conversation around climate change has revolved around alarming projections, sweeping policy proposals, and increasingly urgent calls to action--higher taxes, more stringent regulations, reduced personal freedom, and a lower standard of living.

At the heart of this discussion are powerful government organizations like NASA, NOAA (National Oceanic and Atmospheric Administration), and GISS (Goddard Institute for Space Studies), whose data and models drive scientific consensus and public policy.

However, many critical questions remain—especially from independent researchers and skeptical observers—about the reliability of historical temperature records, the accuracy of climate models, and the health of open scientific debate.

Have Government Agencies Adjusted Historical Temperature Records?

Yes, historical temperature data has undergone adjustments over time. NOAA, NASA, and GISS all maintain temperature datasets subject to revision. These adjustments are not secret and are often explained as “necessary” corrections for known issues, such as changes in instrumentation, station relocations, urban heat island effects, and observation times.

However, critics argue that these “homogenization” adjustments often result in past temperatures being revised downward and recent temperatures upward, amplifying the apparent warming trend. This has led to transparency and potential bias concerns, even if the stated methodological goals are scientifically suspect. Adjustments can indeed introduce uncertainties, and these should be openly scrutinized.

What Happened to the Original Raw Data?

Much of the early raw observational temperature data, stored on reels of computer tape, was erased and reused as a cost-saving measure.  Data that was not destroyed is often inaccessible in its original format. NOAA and NASA typically archive raw and adjusted datasets, but they are not always prominently featured or easy to compare. The process of adjustment lacks independent oversight or external audit.

One infamous controversy surrounded the Climatic Research Unit (CRU) at the University of East Anglia, where email leaks (dubbed “Climategate”) led to accusations of data manipulation, and these incidents have left lingering doubts among some members of the public and scientific community.

Why Do Older Climate Projections Often Miss the Mark?

Many climate models from the 1980s and 1990s projected higher global temperatures than have actually been observed. For example, James Hansen’s 1988 projections, often cited as an early alarm, overshot actual warming trends, especially under scenarios that assumed high emissions.

The Intergovernmental Panel on Climate Change (IPCC) and modeling institutions acknowledge these discrepancies and continually refine models with better physics, inputs, and observational data. Nevertheless, the failure of some early models has fueled skepticism about the reliability of projections, particularly when they are used to justify significant economic and social policies.

The Role of Clouds: A Missing Piece in Climate Models?

Clouds are one of the most complex climate feedback mechanisms and uncertainty factors in climate modeling. They influence both warming (by trapping heat) and cooling (by reflecting sunlight), and the net effect depends on altitude, type, and regional patterns.

Despite decades of research, models still struggle to simulate cloud behavior accurately. This introduces a significant source of uncertainty into projections of future warming. This uncertainty is underemphasized when models are used to support strict environmental regulations and energy policy shifts.

Why Are Climate Models Still Used for Policy Despite Flaws?

We are told that climate models are the best tools for simulating long-term climate behavior, and most scientists argue that their general trends, especially hypothesized warming due to greenhouse gas emissions, remain robust. However, even within the climate science community, relying on worst-case scenarios (such as the often-criticized RCP8.5) for policy justification has come under fire.

Politicians and policymakers tend to emphasize extreme outcomes to motivate action, even if the probability of those scenarios is low. While it’s reasonable to prepare for risk, there’s also a need for honest communication about uncertainties and confidence intervals.

What Is The Value of a Global Mean Temperature?

When people talk about climate change, one number dominates the conversation: the global mean temperature. We’re told that a rise of 1.5°C or 2°C spells catastrophe. But how meaningful is a global average in a system as wildly variable and regionally diverse as Earth’s climate?

From the equator to the poles, temperature differences can exceed 100°C. The Sahara can scorch at over 50°C while Antarctica remains locked at −50°C. So, what does it really tell us to say the average is 14.9°C or 15.2°C?

It’s like averaging the phone numbers in your contacts list — you get a number, but it doesn’t mean much.

More critically, regional changes matter far more than global averages. A slight average increase could mean significant warming in the Arctic while leaving the tropics virtually unchanged.

Policy is often driven by this single number, despite it smoothing over local realities like rainfall shifts, drought zones, or ocean current changes. , all apparently connected with long-term cycles. The global average is sensitive to data coverage and processing methods. If Arctic stations are sparse or if sea surface temperatures are estimated differently, the “average” can shift.

So why is it used? Because it’s simple, communicable, and politically powerful. But that simplicity is deceptive. The climate system isn’t a uniform blanket warming evenly. It’s a chaotic, regionally driven, multi-variable system with feedbacks, cycles, and surprises.

Focusing solely on the global mean temperature risks missing the real picture, what’s happening where, how it affects people and ecosystems locally, and whether models accurately capture those dynamics.

In short, global mean temperature is a crude metric for a complex system, and decisions based solely on its fluctuations may be scientifically shallow and strategically flawed.

Suppressing Scientific Dissent: A Real Concern?

A recurring criticism is that scientists who question prevailing narratives often face professional repercussions. This includes difficulty publishing in major journals, exclusion from funding opportunities, and even personal attacks. Prominent, well-credentialed, and well-experienced researchers such as Judith Curry, Roger Pielke Jr., and John Christy have spoken about the challenges they’ve faced for expressing skepticism, not of climate change itself, but of its projected severity and the policy responses to it.

Scientific progress depends on open debate and the testing of ideas. When dissenting voices are silenced rather than debated, science risks becoming dogma. Upholding rigorous standards and peer review is crucial—but so is ensuring that alternate hypotheses and critical analyses are allowed a fair hearing.

No Consensus in Science: One Finding Can Invalidate Everything

Despite what headlines or political soundbites may claim, science is not a democracy and is undoubtedly not about consensus. It’s not the number of people who agree that determines truth — it’s the strength of the evidence. A single well-substantiated paper or discovery has the power to overturn decades of established thinking.

This is not just theoretical. History is full of examples:

• Ulcers were once blamed on stress, until two scientists discovered Helicobacter pylori, radically changing gastrointestinal medicine. Initially mocked, they won the Nobel Prize.
• Einstein upended Newtonian physics with just a few pages of equations.
• Plate tectonics, now fundamental to geology, was once considered a fringe theory.

In climate science, however, dissenting voices and disruptive findings are often met not with curiosity but with condemnation. Instead of being welcomed, challenges to prevailing models are too frequently labeled as “denialism” or “anti-science.”

But this mindset is dangerous. When science begins defending a consensus instead of testing it, it stops being science and becomes ideology.

Real science requires that models be falsifiable, data be transparent, and disagreement be encouraged, not silenced. If climate models consistently fail to match observed temperatures, key assumptions (like cloud feedbacks) remain poorly understood, or new findings challenge core predictions. Those issues should spark debate, not suppression.

After all, the hallmark of actual science isn’t certainty — it’s the willingness to be wrong.

The Climate Industry is Built on Incentives, Not Integrity

It’s no secret that science follows funding. In the climate research industry, billions of dollars in government grants, institutional budgets, and international aid flow into projects that align with prevailing climate narratives. But what happens when the funding system rewards alarmism, not accuracy?

The modern climate industry—yes, industry—is primarily driven by government funding, funneled into universities, agencies, NGOs, and private consultants. Much of this money goes to studies, models, and “solutions” that assume worst-case scenarios and promise catastrophic futures unless immediate policy action is taken.

Here’s the uncomfortable truth: 

• Researchers who produce findings that amplify concern over climate impacts often find themselves with easier access to grants, media exposure, and institutional support.
• Those who question dominant assumptions—whether about CO₂ sensitivity, model reliability, or natural variability risk being blacklisted, denied funding, or professionally marginalized.
• The peer-review process, supposedly a firewall for integrity, can become a gatekeeping mechanism to filter out dissenting views, especially when like-minded insiders staff review panels and editorial boards.
• Worse, there have been documented cases of data being selectively presented, models being tuned to desired outcomes, and results being exaggerated for political or media effect. While not every researcher engages in deception, the system often rewards sensationalism over sober analysis.
• When careers, reputations, and billion-dollar climate contracts are on the line, the incentive to conform can override the duty to be objective. As with any industry, money shapes the message.

This doesn’t mean all climate science is fraudulent—but it does mean we must be skeptical of a system where the conclusions often seem preordained, and where challenging the orthodoxy can be professionally fatal.

Bottom line…

If science is to serve the public good, it must be free from political coercion, financial distortion, and ideological gatekeeping. Anything less is not science, it’s marketing.

Climate science is enormously complex and critically important. While the core observation, that Earth is apparently warming and human activity may contribute to the phenomenon, is broadly accepted, many details remain uncertain and hotly debated. The credibility of climate science will only be strengthened by greater transparency in data handling, humility in modeling projections, and openness to diverse scientific perspectives.

When public trust in science erodes, so does the effectiveness of policies that depend on it. Ensuring that dissent is engaged rather than suppressed is not only a matter of fairness, it’s essential for the integrity of science itself.

We are so screwed.

-- Steve