10 Reasons Why Thinking People Resist Climate Alarmism9 min read

Climate change is real, but the alarmist narrative surrounding it often exaggerates risks and oversimplifies complex science. The following points explain why I resist climate alarmism, highlighting scientific, methodological, and policy-related concerns.

1.0 Alarmism itself is a red flag

The style of climate communication frequently exhibits hallmarks of political and economic manipulation: exaggerated predictions, suppression of dissent, demonization of skeptics, and appeals to authority. Roger Pielke Jr., a political scientist, observes:

“The normalization of extreme scenarios risks undermining the credibility of climate science.” ¹

Mike Hulme, a sociologist at the University of Cambridge, warns:

“Treating climate change as a single apocalyptic narrative sidelines plural perspectives.” ²

2.0 No One Knows the “Ideal” Global Temperature

Climate policy often assumes that warming beyond 1.5°C or 2°C is inherently catastrophic. Yet no one has identified what the “optimal” mean global temperature should be. Richard Lindzen, MIT climatologist, notes:

“We don’t know what the optimum climate is… It’s certainly not obvious that it’s the present one.” ³

3.0 Failed Catastrophic Predictions for Decades

High-profile climate predictions have repeatedly failed to materialize. In 1989, a UN official warned that entire nations could be “wiped off the face of the Earth” by 2000. ⁴ Al Gore’s An Inconvenient Truth (2006) predicted ice-free Arctic summers by 2013–2015, yet sea ice persists. Judith Curry notes:

“The failure of extreme predictions has damaged the credibility of climate science.” ⁵

4.0 Significant Problems Measuring Global Temperature

Accurately measuring global temperature is difficult due to biases in surface station networks, including poor maintenance, paint degradation, and urban heat islands. Watts et al. found:

“92% of U.S. temperature stations surveyed did not meet siting standards and produced warm biases.” ⁶

Even satellites require adjustments and differ significantly from surface datasets:

“Satellites show significant differences from surface datasets.” ⁷

5.0 Ignoring the Benefits of Warming

The real inconvenient truth, besides the lack of catastrophic sea level rise and weather anomalies is the documented greening affect of higher CO2. Perhaps global warming is good!

Rising CO₂ has contributed to global greening and higher crop yields. NASA reports:

“From a quarter to half of Earth’s vegetated lands has shown significant greening over the last 35 years largely due to rising carbon dioxide levels.” ⁸

CO₂ fertilization also boosts yields of wheat, rice, and other crops. ⁹

6.0 The Dangers of the Rate of Change May Be Overstated

Alarmists often claim the rate of climate change is unprecedented and dangerous. But historical records show rapid climate swings are common, and the planet has repeatedly adapted. H.H. Lamb writes:

“Climatic swings of 1 to 2°C have been common in the past 1000 years.” ¹⁰

Additionally, such climate swings have not created catastrophes in those cases as far as we can tell, and any proposed tipping point that could suddenly usher in a precipitous calamity seems unwarranted.  No tipping point has yet been conclusively observed in the historical record. Changes like ice sheet mass loss, ocean circulation slowdown, or forest dieback are occurring, but these trends are gradual relative to the abrupt shifts predicted in tipping point scenarios. ¹¹

7.0 Climate Models Have Limits

Even the IPCC acknowledges “substantial uncertainties” in climate sensitivity to CO₂ (IPCC AR6, 2021). Despite decades of climate modeling, projections often overestimate warming compared with observed trends. This reflects major gaps in understanding cloud dynamics, aerosol interactions, and oceanic feedbacks—all notoriously difficult to simulate accurately.

Early climate models, developed in the 1970s and 1980s, were rudimentary. They focused mainly on radiative-convective processes and produced very rough estimates of global temperature changes. By the 1990s, more sophisticated coupled atmosphere-ocean models emerged, attempting to simulate interactions between oceans, land, and atmosphere. But even these often required major adjustments after observational data revealed significant mismatches.

One of the most persistent challenges has been cloud feedbacks. Clouds can both amplify and dampen warming, but early models struggled to represent their behavior realistically. As a result, some early model variants predicted extreme warming scenarios that never materialized. Over time, many of these models were either discarded or heavily revised to align more closely with observed climate trends.

7.1 Timeline of Major Corrections

• 1970s–1980s: Simple radiative-convective models. No ocean coupling; cloud effects largely absent.

• 1990s: Introduction of coupled atmosphere-ocean models (AOGCMs). Basic cloud parameterizations added, but often misrepresenting regional precipitation and temperature feedbacks.

• 2000s: Tuning of cloud parameters; some models producing extreme warming outcomes were phased out. Aerosols began to be incorporated more systematically.

• 2010s: High-resolution models allowed better representation of cloud processes and oceanic feedbacks. AI-assisted parameter tuning emerged to correct biases in radiation and cloud cover.

• 2020s: Models like ICON-A integrate machine learning and finer-scale cloud simulations, improving accuracy—but still limited by uncertainties in feedback mechanisms.

7.2 The Risk of Overreliance

While models are useful scientific tools, they remain nascent instruments. Heavy reliance on them can lead to policy and public decisions based on worst-case projections rather than observable trends. Many catastrophic predictions from early models, such as extreme sea level rise within a few decades or immediate ice sheet collapses, have not materialized, underscoring the danger of assuming model outputs are infallible.

As atmospheric scientist Richard Lindzen notes:

“Models are useful tools, but they are not crystal balls.” (Wall Street Journal, 2014)

This history highlights two key points: models evolve iteratively, and predictions are only as reliable as the assumptions and parameters they incorporate. While the potential for tipping points and severe climate outcomes exists, the track record of overly alarmist projections demonstrates the limits of current modeling capability. For informed discussion, it’s essential to differentiate between plausible future scenarios and unrealized catastrophes projected by early, imperfect models.

8.0 Policy Trade-Offs and Conflicts of Interest

Climate policy consumes vast resources, often measured in trillions of dollars, that could otherwise address pressing global challenges such as poverty, disease, education, and access to affordable energy. As Bjørn Lomborg emphasizes:

“Even ambitious climate policies will have a modest impact on global temperatures while costing trillions… resources could save more lives if spent elsewhere.” ¹²

Beyond the economic trade-offs, there are structural issues in global climate governance and research funding that merit attention. Critics have documented that large institutions, including the IPCC, often operate under incentives that favor alarming narratives. Models projecting extreme warming and catastrophic impacts can attract political and media attention, increasing institutional relevance and funding, while research that challenges mainstream projections often receives less support or is marginalized.

• Conflicts of Interest: Some researchers or organizations receive funding from governments, multilateral agencies, or NGOs that have a vested interest in emphasizing the risks of climate change. While funding itself doesn’t invalidate research, it can create subtle pressures to favor dramatic projections over cautious or contrarian perspectives.

• Underfunding of Contrary Science: Studies that question the magnitude of climate sensitivity, examine natural climate variability, or critique model assumptions often struggle to secure grants. For instance, research by Lindzen, Spencer, and others highlighting uncertainties in cloud feedbacks and aerosol effects received less institutional support, despite being peer-reviewed and published.

• Policy Biases and Alarmism: When extreme model predictions are amplified without adequate caveats, they can influence policy disproportionately. This can lead to policies that prioritize carbon reductions at the expense of human development, particularly in poorer nations that still rely on fossil fuels for energy access.

The policy trade-off is clear: allocating massive resources toward climate mitigation, especially when models remain uncertain, may yield modest reductions in warming while forgoing investments in immediate human welfare. Responsible climate policy should therefore balance mitigation efforts with global priorities, transparency about uncertainties, and openness to diverse scientific perspectives.

9.0 Human Contribution Remains Uncertain

The extent of human influence on observed warming is debated. CO₂ levels and temperatures do not always correlate perfectly. Judith Curry notes:

“Attribution of warming to human activities is still highly uncertain, particularly on decadal timescales.” ⁵

10.0 Earth’s Natural Buffering Capacity

The planet has powerful buffering systems that mitigate climatic impacts. Oceans absorb heat and CO₂; vegetation and soil act as carbon sinks; and historical records show the biosphere adapts repeatedly. Lamb notes:

“Climatic swings of 1 to 2°C… and the biosphere has repeatedly adapted.” ¹⁰

Conclusion

Skepticism of climate alarmism is not denial of warming. Extreme claims, one-sided reporting, measurement uncertainties, and Earth’s buffering capacity all suggest that public discourse should focus on balanced risk management rather than apocalyptic fear. As Mike Hulme reminds us:

“Climate change is not a problem waiting for a solution; it is an environmental, cultural and political phenomenon.” ²