PBS Terra investigates 1.5°C warming, climate modeling, and US regional risk

Overview

In this PBS Terra episode, Maya Mae investigates the persistent 1.5°C warming threshold, the role of greenhouse gases, and what advanced climate models say about future weather. The program travels from ice cores to a top supercomputer to connect measurements of past atmospheres with projections of the near future, including the ongoing coal plant transition in the United States and the rapid rise of renewable energy.

Key insights

• Ice cores reveal abrupt CO2 changes in the past and how today’s CO2 rise compares to prehistoric events.
• Macro climate models use ensembles on powerful supercomputers to estimate regional impacts and uncertainties.
• Renewable energy costs and policy shifts are reshaping the energy landscape faster than earlier doom scenarios suggested.
• A risk map highlights which US regions, especially urban areas with high exposure and vulnerability, are most at risk from heat, precipitation, and sea level rise.

Overview

PBS Terra delves into the urgent question of how warm the world will get and what that means for everyday weather. The episode frames a global context in which 2023 was the warmest year on record, and 2024 continued that trajectory. The show explains that the 1.5 degree Celsius target from the Paris Agreement has already been exceeded for more than 12 months in modern history, prompting a closer look at the models, data, and trajectories that will shape policy and daily life in the near term.

Understanding the science

The program explains the familiar greenhouse gas blanket concept and shows why the rate of CO2 increase matters as much as the absolute level. It highlights the past, using 55,000 year old ice trapped in Antarctica to illustrate how concentrations of CO2 rose during glacial cycles. A key point is that the fastest natural rise in CO2 observed in the last 100,000 years was still an order of magnitude slower than the current human-driven rise, underscoring the urgency of reductions in emissions.

Climate models are introduced as complex systems of equations that simulate physics, chemistry, and the carbon cycle. Because the real world involves uncertain variables such as cloud feedbacks, ice-albedo effects, and how much carbon the oceans and biosphere will absorb in a warmer world, ensembles of simulations are used to estimate probabilistic outcomes. The episode emphasizes that even with a precise emission pathway, a wide range of temperatures remains possible due to these uncertainties.

From ice cores to supercomputers

A central thread is the use of one of the world’s most powerful supercomputers to project weather extremes across the United States. The machine runs hundreds of simulations, generating probabilistic forecasts that show how different regions may experience heat, heavy rainfall, drought, and more intense storms as the climate warms. The discussion stresses two major sources of uncertainty: climate sensitivity to greenhouse gas concentrations and carbon cycle feedbacks, including how much the ocean and biosphere will continue to absorb CO2 as the system warms.

Despite the uncertainties, the consensus among scientists is that the 1.5°C target will be exceeded on current trajectories, and to stay well below 2°C, net zero emissions should be achieved by mid-century. The episode notes that many models still rely on older emission scenarios, and the world has since moved into a different policy and technology landscape that makes the old “business as usual” narrative less likely, though not without challenges.

Energy transition and economic dynamics

The program recounts a dramatic energy transition underway in the United States and worldwide. A coal plant near Detroit, once a century-old symbol of fossil fuel power, is being retired, and the site will host a large energy storage project. The narrative emphasizes that about half of U.S. coal plants are expected to shut down by 2026, reflecting a broader shift toward renewables. It also discusses the cost dynamics of solar, wind, and batteries, noting that the learning rate for solar is about 20 percent per doubling of capacity, which has driven down costs for decades and helped undercut fossil fuels even for people less motivated by climate concerns.

Human dimensions and risk mapping

The episode introduces a climate risk map created by Dr. Marshall Shepherd and colleagues, which merges hazards with exposure and vulnerability to identify communities most at risk. The map highlights Florida, the Gulf Coast, parts of the Southwest, and densely populated areas like Los Angeles. It emphasizes that vulnerability is closely tied to social factors, including the intersection of race, age, income, and infrastructure. The discussion underscores that adaptation and resiliency measures are essential as warming continues to intensify heat waves, droughts, heavy precipitation, and sea level rise.

What the findings mean for the future

Ultimately the program frames a race between rapid adoption of clean energy and the impacts of climate change. It argues that clean energy is increasingly cost-effective and that renewables are proliferating faster than some early forecasts predicted. The episode closes with a sense of cautious optimism rooted in the tangible progress seen over the last decade, while reaffirming that the world must aggressively pursue net-zero emissions to limit warming and reduce climate risk, especially in the most vulnerable communities.

Implications for viewers

Viewers are encouraged to understand not just the science of warming but the practical pathways through which policy, technology adoption, and adaptation influence regional weather and long-term resilience. The episode connects global data with local risk, showing how the same forces driving planetary change affect cities, power systems, and everyday life.