Why is predicting regional climate extremes more difficult than global temperature?

Predicting regional extremes like heatwaves or floods is more difficult because the internal variability of the atmosphere is much greater, making the signal from CO2 forcing relatively smaller and harder to isolate statistically.

What does the bar on the right side of IPCC Figure 9.8 represent?

The bar represents the spread of absolute global mean temperatures predicted by different climate models for the reference period (1961-1990). It highlights that while model trends align, their absolute temperature simulations still have biases.

What causes the divergence in predictions between different climate models?

Divergence stems primarily from uncertainties in parameterizing sub-grid processes (like cloud formation and ocean eddies) that cannot be resolved by the model's grid spacing, leading to different mathematical representations.

Does the IPCC report provide uncertainty ranges for temperature projections?

The projections in IPCC reports show uncertainty as the spread among different models' outputs. However, individual models may not always run extensive ensembles to explore their own internal uncertainties due to computational limitations.

Why is it crucial to have accurate regional climate models?

Accurate regional models are vital for understanding and preparing for specific impacts like extreme weather events (flooding, cyclones), potential tipping points (like ice sheet melt), and the human body's limits in extreme heat and humidity.

Can future technology like carbon capture negate the need for immediate emissions cuts?

Relying solely on future carbon capture technology is risky. If critical tipping points are crossed before such technology is developed and deployed, irreversible changes may render these efforts ineffective.

Should developed nations invest in climate adaptation in developing countries?

Investing in climate adaptation in developing nations is crucial, both for humanitarian reasons and self-interest. Unchecked climate impacts can drive mass migration, potentially creating widespread instability that affects developed nations.

Key Moments

Did scientists get climate change wrong?

Sabine Hossenfelder

Science & Technology4 min read36 min video

Nov 15, 2019|443,979 views|10,072|6,864

science physics climate change hossenfelder climate models global temperature climate predictions weather climate did scientists get climate change wrong is climate change real how certain are climate predictions

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Key Moments

TL;DR

Climate models accurately predict global temperature but need improvement for regional weather extremes, which are crucial for policy and adaptation.

Key Insights

Climate models have been remarkably accurate in predicting global average temperature rises due to increased CO2.

The New York Times article correctly highlights the need for better simulation of regional weather extremes, which directly impact people's lives.

Simulating regional extremes is more challenging due to greater natural climate variability, requiring more sophisticated statistical techniques and model improvements.

The bar in IPCC Figure 9.8 shows that while models agree on temperature trends, absolute temperature predictions have a wider spread, indicating room for improvement in model physics and parameterizations.

Uncertainty in climate models primarily stems from parameterizing sub-grid processes (like cloud formation and ocean eddies) due to computational limitations.

The urgency of climate change has shifted from a purely scientific endeavor to a critical societal issue, demanding more realistic and accurate models for adaptation planning.

ACCURACY OF GLOBAL TEMPERATURE PREDICTIONS

Climate models have demonstrated remarkable accuracy in predicting the global average temperature increase. This is because the signal of CO2 forcing is strongest and the 'noise' from natural climate variability is weakest at global scales. The focus on global mean temperature is scientifically robust as it represents the most direct impact of increased CO2. Therefore, claims that models have underestimated the effect of carbon dioxide on global warming from this perspective are generally unfounded.

THE CHALLENGE OF PREDICTING EXTREMES

While global temperature trends are well-captured, the prediction of regional weather extremes (heatwaves, floods, intense hurricanes) presents a greater scientific challenge. These phenomena are more influenced by the atmosphere's internal chaotic variability, making the anthropogenic signal relatively weaker and harder to isolate. The New York Times article accurately points to the critical need for improved modeling of these regional impacts, as they directly affect human societies and are of significant public concern.

UNDERSTANDING MODEL UNCERTAINTIES

A key area of discussion revolves around the uncertainties in climate models, particularly illustrated by Figure 9.8 of the IPCC report. While models show good agreement on temperature trends, the spread in their predictions for absolute surface temperatures is significant. This spread is not necessarily an indicator of failed predictions for trends but highlights the complexity in accurately simulating Earth's climate system from first principles, especially concerning oceanic and atmospheric processes like cloud cover.

SOURCES OF MODEL DIVERGENCE

The divergence in predictions among various climate models stems less from chaotic initial conditions and more from the fundamental challenge of representing sub-grid scale processes. Due to computational limitations, complex phenomena like cloud formation, ocean eddies, and topography effects must be parameterized using simplified formulas. Different research groups develop varying parameterization schemes based on available data and assumptions, leading to a range of outcomes and contributing significantly to model uncertainty, especially at regional levels.

THE SHIFTING ROLE OF CLIMATE SCIENCE

Climate science has transitioned from primarily a research endeavor to a critical societal issue. The increasing frequency and intensity of devastating weather events globally necessitate more accurate and realistic climate models. Governments and individuals need reliable predictions to plan for future resilience, including building infrastructure, determining safe living areas, and assessing the habitability of regions under changing climate conditions. This societal demand accelerates the need for model improvements.

IMPROVING MODELS FOR ADAPTATION AND POLICY

To address the pressing societal needs, climate models must become more realistic and accurate, minimizing approximations where possible. This requires significant investment, particularly in supercomputing resources. Higher resolution models, with grid spacings approaching one kilometer, could potentially eliminate many of the most crucial parameterizations for cloud processes and ocean eddies. This improved understanding of regional climate change, especially concerning tipping points and their irreversibility, is vital for effective adaptation strategies and informed policy-making.

EMISSIONS REDUCTION VERSUS ADAPTATION

While current scientific understanding provides sufficient evidence for making decisions on emission reductions, the science is not 'done' regarding climate adaptation. Even with immediate zero emissions, past and ongoing emissions will cause continued climate change. This necessitates a focus on adapting to these changes, particularly in developing nations disproportionately affected. Furthermore, ignoring regional tipping points risks rendering future technologies for carbon capture ineffective, underscoring the need for continued detailed climate research.

THE NEED FOR INVESTMENT IN CLIMATE MODELING

The development of more accurate and reliable climate models, especially for regional extremes and potential tipping points, requires substantial investment. This investment is crucial for providing governments and societies with the information needed to prepare for and mitigate the impacts of climate change. Ignoring this need could lead to significant societal disruption, such as mass migration, driven by increasingly uninhabitable conditions in vulnerable regions, highlighting the long-term self-interest for developed nations to support adaptation efforts globally.

Mentioned in This Episode

●Software & Apps

●Organizations

●Books

●People Referenced

Common Questions

Yes, models from the 20th century to the present have been remarkably accurate in predicting the rise in global mean temperature, which is a robust indicator of the effect of CO2 forcing.

Topics

Technology & Innovation Science & Mathematics Climate Adaptation Carbon Emissions Climate Modeling Environment & Climate Extreme Weather Prediction Tipping Points Climate Science Model Uncertainty

Mentioned in this video

Organizations

The Guardian

Mentioned as the publication source for an article suggesting that scientists have completed their job on climate change and it's up to citizens to push leaders to act.

IPCC

Intergovernmental Panel on Climate Change, whose reports and figures (like 9.8) are discussed in relation to climate model predictions and uncertainties.

UK Met Office

Mentioned as an example of an institution that produces large ensembles of climate change integrations.

People

Tim Palmer

Professor at the University of Oxford discussing climate models, their accuracy, and limitations.

Concepts

Navier-Stokes equations

A set of partial differential equations that describe the motion of viscous fluid substances, mentioned as a fundamental physical law used in climate models.