Since 1750, Earth’s average surface temperature has increased by 0.8 degrees Celsius. As carbon dioxide levels in the atmosphere are expected to double by the end of the 21st century, scientists predict a global temperature rise between 1.5 and 4.5 degrees Celsius. If the increase is on the lower side, around 1.5 degrees Celsius, some regions might become drier and less productive, while others could become warmer, wetter, and more productive. However, a rise of 4.5 degrees Celsius would be as significant as the warming since the last ice age 22,000 years ago, when much of North America was covered by ice. Such a change would dramatically alter our climate.
Accurate predictions of temperature changes are essential for planning our future. Currently, the uncertainty range is too broad to determine the best responses to climate change confidently. Despite 35 years of research, the estimate of a 1.5 to 4.5 degrees Celsius increase for doubled carbon dioxide levels remains unchanged. This uncertainty stems from our incomplete understanding of aerosols and clouds.
A new experiment at CERN aims to address this issue. To predict temperature changes, scientists need to understand Earth’s climate sensitivity, which is the temperature change in response to radiative forcing. Radiative forcing occurs when there’s a temporary imbalance between the energy Earth receives from the Sun and the energy it radiates back into space, often due to increased greenhouse gases. Earth adjusts to this imbalance by warming or cooling.
We can estimate Earth’s climate sensitivity by examining data since the industrial age began in 1750. This involves understanding the global temperature rise since then and the current radiative forcing compared to pre-industrial times. Human activities have increased greenhouse gases, causing warming, but have also increased aerosol particles in clouds, which have a cooling effect.
While pre-industrial greenhouse gas levels are well-documented through ice core samples from Greenland and Antarctica, we lack direct measurements of cloudiness from 1750. This gap is a major source of uncertainty in determining Earth’s climate sensitivity. To estimate pre-industrial cloudiness, scientists rely on computer models simulating aerosol formation processes in clouds.
Aerosols are tiny particles suspended in the air, originating from sources like dust, sea spray, or biomass burning. They can also form through gas-to-particle conversion in the atmosphere. Aerosols are crucial because cloud droplets form around them. Without aerosols, there would be no clouds, no fresh water, and a much hotter climate, making life as we know it impossible.
The formation of aerosol particles and their effects on clouds are not well understood, contributing to uncertainty in climate sensitivity. The CERN experiment, known as “Cloud,” has created a large steel vessel with low contamination levels to measure aerosol formation under controlled conditions. In its first five years, Cloud identified key vapors responsible for aerosol formation, such as sulfuric acid, ammonia, amines, and biogenic vapors from trees. Additionally, Cloud is exploring whether galactic cosmic rays, which vary with solar activity, enhance aerosol formation in clouds.
Cloud is tackling two major questions: First, how cloudy was the pre-industrial climate, and how have clouds changed due to human activities? Understanding this will help refine climate projections for the 21st century. Second, could solar climate variability in the pre-industrial era be explained by the influence of galactic cosmic rays on clouds? These ambitious goals aim to deepen our understanding of climate dynamics.
Engage in a seminar where you will discuss the concept of climate sensitivity and its importance in predicting future climate scenarios. Prepare a short presentation on how aerosols and clouds contribute to the uncertainty in climate sensitivity estimates. Use visual aids to illustrate the impact of different levels of radiative forcing on Earth’s temperature.
Participate in a hands-on workshop where you will use computer models to simulate aerosol formation and cloud development. Experiment with different variables such as aerosol concentration and types to observe their effects on cloud properties. Discuss your findings with peers and explore how these simulations help in understanding pre-industrial cloudiness.
Conduct a field study to identify local sources of aerosols, such as dust, sea spray, or biomass burning. Collect samples and analyze them in the lab to understand their composition and potential impact on cloud formation. Share your results in a report, highlighting the significance of aerosols in climate dynamics.
Engage in a structured debate on whether galactic cosmic rays significantly influence cloud formation and climate change. Research both supporting and opposing viewpoints, and present your arguments. This activity will help you critically evaluate the evidence and understand the complexities of climate science.
Analyze the CERN Cloud experiment as a case study. Review the methodologies used, the key findings, and their implications for understanding climate sensitivity. Prepare a detailed report or presentation that evaluates the experiment’s contribution to climate science and suggests potential areas for further research.
**Cloudy Climate Change: How Clouds Affect Earth’s Temperature**
Earth’s average surface temperature has warmed by 0.8 degrees Celsius since 1750. When carbon dioxide concentrations in the atmosphere double, which is expected before the end of the 21st century, researchers project that global temperatures will rise by 1.5 to 4.5 degrees Celsius. If the increase is closer to the low end, 1.5 degrees Celsius, we may be more able to adapt, with some regions becoming drier and less productive, while others become warmer, wetter, and more productive. Conversely, a rise of 4.5 degrees Celsius would be similar in magnitude to the warming that occurred since the last glacial maximum 22,000 years ago, when much of North America was covered by a thick ice sheet. This would represent a dramatic change in climate.
It is crucial for scientists to predict temperature changes with as much precision as possible so that society can plan for the future. The current range of uncertainty is too large to confidently determine the best responses to climate change. However, the estimate of 1.5 to 4.5 degrees Celsius for a doubling of carbon dioxide has remained unchanged for 35 years. Why haven’t we been able to narrow it down? The answer lies in our incomplete understanding of aerosols and clouds.
A new experiment at CERN is addressing this issue. To predict how temperature will change, scientists need to know Earth’s climate sensitivity, which is the temperature change in response to a radiative forcing. Radiative forcing refers to a temporary imbalance between the energy received from the Sun and the energy radiated back into space, such as the imbalance caused by an increase in greenhouse gases. To correct this imbalance, Earth warms up or cools down.
We can determine Earth’s climate sensitivity from experiments conducted since the industrial age began in 1750 and use this information to project future warming based on various radiative forcings in the 21st century. To do this, we need to know two things: first, the global temperature rise since 1750, and second, the current radiative forcing relative to the pre-industrial climate. Human activities have increased greenhouse gases in the atmosphere, contributing to warming, but they have also increased aerosol particles in clouds, which have a cooling effect.
Pre-industrial greenhouse gas concentrations are well measured from bubbles trapped in ice cores from Greenland and Antarctica, providing precise data. However, we lack direct measurements of cloudiness in 1750, which is a significant source of uncertainty in determining Earth’s climate sensitivity. To understand pre-industrial cloudiness, we must rely on computer models that simulate the processes responsible for forming aerosols in clouds.
Aerosols are tiny liquid or solid particles suspended in the air. They can be primary, originating from dust, sea spray, or burning biomass, or secondary, formed by gas-to-particle conversion in the atmosphere. Aerosols are prevalent in the atmosphere and can block sunlight in polluted areas or create a blue haze over distant mountains. Importantly, cloud droplets cannot form without aerosol particle seeds. Without aerosol particles, there would be no clouds, and consequently, no fresh water. The climate would be significantly hotter, and life as we know it would not exist.
Despite their importance, the formation of aerosol particles in the atmosphere and their effects on clouds are not well understood. Even the vapors responsible for aerosol particle formation are not well established, as they exist in very small amounts. This lack of understanding contributes to the significant uncertainty in climate sensitivity and the wide range of future climate projections.
The experiment at CERN, named “Cloud,” has built a large steel vessel with low contamination levels, allowing for the measurement of aerosol formation under tightly controlled atmospheric conditions for the first time. In its initial five years, Cloud has identified the vapors responsible for aerosol particle formation, including sulfuric acid, ammonia, amines, and biogenic vapors from trees. Additionally, using an ionizing particle beam from the CERN proton synchrotron, Cloud is investigating whether galactic cosmic rays enhance aerosol formation in clouds. This has been proposed as a potential natural climate forcing agent, as the flux of cosmic rays varies with solar activity.
Cloud is addressing two significant questions: First, how cloudy was the pre-industrial climate, and how much have clouds changed due to human activities? This knowledge will help refine climate projections for the 21st century. Second, could the observed solar climate variability in the pre-industrial climate be explained by the influence of galactic cosmic rays on clouds? These are ambitious yet realistic goals for understanding our climate.
Climate – The long-term pattern of weather conditions in a particular area, including temperature, precipitation, and wind, over an extended period of time. – The study of climate change focuses on understanding how human activities are altering the Earth’s climate systems.
Temperature – A measure of the warmth or coldness of an environment or substance, typically expressed in degrees Celsius or Fahrenheit. – Scientists monitor the average global temperature to assess the impact of global warming.
Aerosols – Suspended solid or liquid particles in the atmosphere, which can originate from natural sources or human activities and affect climate and air quality. – Aerosols can influence climate by scattering sunlight and modifying cloud properties.
Clouds – Visible masses of condensed water vapor floating in the atmosphere, which play a crucial role in the Earth’s climate system by affecting radiation and precipitation. – The formation and behavior of clouds are critical factors in climate models.
Greenhouse – A structure with walls and roof made chiefly of transparent material, such as glass, used for growing plants; in environmental science, it refers to gases that trap heat in the atmosphere, contributing to the greenhouse effect. – Greenhouse gases like carbon dioxide and methane are significant contributors to global warming.
Sensitivity – The degree to which a system responds to changes in external conditions, such as the climate system’s response to increased greenhouse gas concentrations. – Climate sensitivity is a key parameter in predicting future climate change scenarios.
Radiative – Relating to the emission or transmission of energy in the form of waves or particles, particularly in the context of the Earth’s energy balance. – Radiative forcing is a concept used to quantify the influence of factors like greenhouse gases on the Earth’s climate.
Uncertainty – The degree to which the outcome of a process or the value of a measurement is unknown, often due to limitations in data or understanding. – Uncertainty in climate projections arises from various sources, including model limitations and natural variability.
Projections – Estimates or forecasts of future conditions based on current data and trends, often used in the context of climate change to predict future climate scenarios. – Climate projections indicate that global temperatures could rise significantly by the end of the century.
Dynamics – The study of forces and motion within systems, often used to describe the complex interactions and changes within environmental and climate systems. – Understanding the dynamics of ocean currents is essential for predicting climate patterns.
