Short Answer Questions Flashcards
Past Paper
What are the most important anthropogenic greenhouse gases and what are their most important sources? How is the relative contribution of each gas to global warming characterised?
The most important anthropogenic greenhouse gases are carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and fluorinated gases (such as hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride). Here’s a breakdown of their sources and contributions to global warming:
Carbon Dioxide (CO2):
Main Sources: Burning of fossil fuels (coal, oil, and natural gas) for energy production, transportation, industrial processes, and deforestation.
Contribution to Global Warming: CO2 is the most significant greenhouse gas emitted by human activities. It has a long atmospheric lifetime, contributing to sustained warming over centuries.
Methane (CH4):
Main Sources: Agriculture (enteric fermentation in livestock, rice cultivation, and manure management), fossil fuel production and use, landfill gas, and biomass burning.
Contribution to Global Warming: Methane is a potent greenhouse gas with a shorter atmospheric lifetime compared to CO2, but it has a much stronger warming effect per molecule over a 20-year period.
Nitrous Oxide (N2O):
Main Sources: Agricultural activities (fertilizer use, soil cultivation), fossil fuel combustion, industrial processes, and biomass burning.
Contribution to Global Warming: Nitrous oxide is a long-lived greenhouse gas with a significant warming potential, although it is less abundant in the atmosphere compared to CO2 and methane.
Fluorinated Gases:
Main Sources: Industrial processes, including refrigeration, air conditioning, semiconductor manufacturing, and some consumer products.
Contribution to Global Warming: Fluorinated gases have high global warming potentials (GWPs) and can persist in the atmosphere for a long time. Though they are less abundant than CO2 and methane, their impact per molecule can be thousands of times greater.
The relative contribution of each greenhouse gas to global warming is often characterized by its Global Warming Potential (GWP), which compares the warming effect of each gas to that of carbon dioxide over a specified time period (usually 100 years). GWPs allow for the comparison of the warming effects of different gases on a common scale. For instance, methane has a much higher GWP than CO2 over a 20-year period, but its GWP decreases over longer timescales due to its shorter atmospheric lifetime. Therefore, the choice of the time horizon used for GWP calculations can influence the perceived importance of different greenhouse gases.
What are the main signs of how climate is changing? Why did the
IPCC conclude in its Sixth Assessment Report that the impact of human activities on global climate was ‘unequivocal’?
The main signs of how climate is changing include:
Temperature Increase: Global surface temperatures have risen, with the last few decades being the warmest on record.
Melting Ice: Glaciers and ice sheets are melting at an accelerated rate, leading to rising sea levels.
Rising Sea Levels: Sea levels are rising due to thermal expansion of ocean water and the melting of land-based ice.
Extreme Weather Events: There’s an increase in the frequency and intensity of extreme weather events such as heatwaves, droughts, floods, and storms.
Ocean Acidification: Increased absorption of CO2 by oceans leads to ocean acidification, affecting marine ecosystems.
Changes in Precipitation Patterns: Shifts in precipitation patterns, leading to changes in rainfall intensity, frequency, and distribution.
Ocean Warming: Oceans are absorbing more heat, resulting in ocean warming, which impacts marine life and weather patterns.
Shifts in Ecosystems: Changes in ecosystems and biodiversity due to changing temperatures, precipitation patterns, and other factors.
The IPCC concluded in its Sixth Assessment Report that the impact of human activities on global climate is ‘unequivocal’ due to several reasons:
Comprehensive Scientific Evidence: The report is based on an extensive body of scientific evidence, including observations, models, and analyses from thousands of peer-reviewed studies.
Consistency Across Multiple Lines of Evidence: Various indicators of climate change, such as temperature records, ice melt, sea level rise, and ecosystem changes, all point to a consistent pattern of human-induced climate change.
Attribution Studies: Advances in attribution science have allowed researchers to confidently attribute observed changes in climate to human activities, particularly the increase in greenhouse gas concentrations from burning fossil fuels and other industrial processes.
Understanding of Climate Processes: Scientific understanding of climate processes has improved, enabling more accurate modeling of past, present, and future climate scenarios.
Consensus Among Climate Scientists: There is a strong consensus among climate scientists that human activities are the dominant driver of recent global warming and other climate changes.
Overall, the IPCC’s conclusion of the unequivocal impact of human activities on global climate is based on the weight of evidence from multiple scientific disciplines and methodologies.
Global climate models are used to simulate how climate might change in the future. How can we be confident that the models are reliable? What are the main uncertainties in projections of the amount of climate change by the end of the century?
Confidence in the reliability of global climate models (GCMs) stems from several factors:
Physical Understanding: GCMs are built upon fundamental principles of physics, chemistry, and biology that govern Earth’s climate system. They simulate processes such as atmospheric circulation, ocean currents, cloud formation, and the carbon cycle, among others, based on well-established scientific understanding.
Historical Performance: GCMs have been validated against historical climate data from observations, including temperature records, sea ice extent, and atmospheric composition. Models that accurately simulate past climate conditions provide greater confidence in their ability to project future changes.
Intermodel Consistency: Despite differences in their specific formulations, multiple independent GCMs from different research groups around the world generally produce similar results when simulating past and present climate conditions. Consistency among different models increases confidence in their projections.
Skillful Projections: GCMs have demonstrated skill in reproducing observed trends and variability in various climate variables when compared to historical data. This includes simulating regional climate patterns, such as monsoon systems and temperature trends, with reasonable accuracy.
Process Representation: Models incorporate detailed representations of key physical processes and feedback mechanisms, such as the interactions between clouds and radiation, feedbacks from changes in ice and snow cover, and the role of vegetation in the carbon cycle. Improved process representations lead to more realistic simulations of climate behavior.
However, despite the advancements and confidence in GCMs, there are still uncertainties in projections of future climate change. Some of the main uncertainties include:
Emissions Scenarios: Future greenhouse gas emissions depend on various factors, including population growth, technological advancements, economic development, and policy decisions. Different emission scenarios lead to different levels of climate forcing and, consequently, different projected outcomes.
Climate Sensitivity: The exact sensitivity of the climate system to increases in greenhouse gas concentrations is uncertain. Climate sensitivity refers to the amount of warming that occurs in response to a doubling of atmospheric CO2 concentrations. Estimates of climate sensitivity vary among different models and studies.
Feedback Processes: Climate feedbacks, such as changes in clouds, water vapor, and ice-albedo feedbacks, can either amplify or dampen the effects of greenhouse gas emissions. The exact strength and behavior of these feedbacks are uncertain and contribute to uncertainty in future climate projections.
Natural Variability: Natural variability in the climate system, such as volcanic eruptions, solar variability, and internal variability of the oceans and atmosphere, can influence short-term climate trends and introduce uncertainty into long-term projections.
Regional Variability: GCMs have limitations in accurately simulating regional climate characteristics, including local-scale weather patterns and extreme events. Uncertainties in regional projections can impact assessments of local climate impacts and adaptation strategies.
Addressing these uncertainties requires ongoing research efforts to improve the representation of key processes in models, refine emission scenarios, and enhance our understanding of the climate system’s response to external forcings. Additionally, ensemble approaches, which involve running multiple simulations with variations in model parameters and initial conditions, can help quantify and reduce uncertainty in future climate projections.
Each year we appear to see more frequent weather events causing extreme loss and damage. Are these all caused by climate change, and what other factors might be relevant? How can we estimate the role of climate change in recent extreme events
While climate change can contribute to the increased frequency and intensity of some types of extreme weather events, not all extreme weather events can be directly attributed to climate change. Other factors can also influence the occurrence and severity of extreme events. Some relevant factors include:
Natural Variability: The climate system exhibits natural variability on various timescales, from seasonal to decadal and longer. Natural climate patterns such as El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO) can influence weather patterns and contribute to the occurrence of extreme events.
Land Use Changes: Changes in land use, such as urbanization, deforestation, and agricultural practices, can alter local and regional climate conditions, affecting factors like temperature, precipitation patterns, and runoff characteristics. These changes can exacerbate the impacts of extreme events such as floods, heatwaves, and droughts.
Human Activities: Human activities unrelated to greenhouse gas emissions, such as water management practices, infrastructure development, and land degradation, can influence the vulnerability and exposure of communities to extreme weather events. Poorly designed infrastructure and inadequate land-use planning can increase the risk of flooding, landslides, and other hazards.
Meteorological Factors: Extreme weather events can arise from complex interactions between atmospheric dynamics, thermodynamics, and other meteorological processes. Factors such as atmospheric instability, moisture availability, and synoptic weather patterns can contribute to the occurrence and intensity of extreme events.
Climate Change: Climate change can exacerbate the impacts of certain types of extreme weather events, such as heatwaves, heavy precipitation events, and coastal flooding. Warming temperatures can increase the frequency and severity of heatwaves, while changes in atmospheric circulation patterns can influence precipitation extremes and storm tracks.
Estimating the role of climate change in recent extreme events involves a process known as event attribution, which aims to assess the likelihood and magnitude of an event’s occurrence in the presence and absence of anthropogenic climate change. Event attribution studies typically involve comparing observations of an extreme event to simulations from climate models that include and exclude the effects of human-induced climate change.
Key steps in the event attribution process include:
Event Definition: Clearly defining the extreme event of interest, including its spatial extent, duration, intensity, and relevant meteorological variables (e.g., temperature, precipitation, wind speed).
Observational Analysis: Analyzing observational data to quantify the characteristics of the extreme event and assess its historical frequency and severity.
Model Simulations: Conducting climate model simulations to reproduce the extreme event under different scenarios, including simulations with and without anthropogenic greenhouse gas emissions.
Statistical Analysis: Using statistical methods to compare the likelihood of the extreme event occurring in the presence and absence of climate change, taking into account natural variability and other factors.
Event attribution studies provide valuable insights into the role of climate change in shaping the risk of extreme events and can inform adaptation and mitigation efforts to reduce their impacts. However, uncertainties in both observations and climate models can affect the robustness of attribution assessments, highlighting the need for ongoing research and improved methodologies.
