Climate change refers to long-term changes in temperatures and weather patterns. While these changes can occur naturally — such as fluctuations in solar activity — since the 19th century, climate change has primarily been driven by human activities, particularly the burning of fossil fuels like coal, oil, and natural gas.
Before using chillR, there’s a brief overview of climate change, because the upcoming work will mainly focus on predicting how global warming might affect phenology-related metrics.
To understand what’s happening to our planet, it’s important to know the main causes of climate change. This helps us spot false claims that things like the sun, cities, or natural changes in the climate are the main reasons for global warming. The truth is simple: human-made greenhouse gas emissions are heating up our planet, and the only way to stop this is to greatly reduce these emissions.
The video below, titled Climate Change 1 - Drivers of Climate Change, is the first in a series of four videos on the topic of climate change presented by Eike Lüdeling. It provides a comprehensive overview of the primary drivers of global climate change, such as greenhouse gases, aerosols, solar radiation, ozone, and others.
The next video, Climate Change 2 - Recent Warming, explores climatic changes that have already occurred or for which there is substantial evidence. It demonstrates that the planet has experienced significant warming for several decades, almost globally.
When it comes to climate change, the most severe impacts are still ahead. This is largely due to the significantly higher rate of greenhouse gas emissions observed over the past few decades, with no signs of a slowdown in the near future. As a result, the human-induced ‘forcing’ effect on our climate has reached unprecedented levels, making it likely that future changes will occur even more rapidly than those we have already witnessed. The next video Climate Change 3 - Future scenarios introduces the methods that climate scientists employ to forecast future conditions and presents climate scenarios developed by these scientists, which researchers in other fields can use to project the impacts of climate change on ecological and agricultural systems.
Having robust climate scenarios is essential, but they only take us partway toward reliable assessments of climate change impacts. A potentially greater challenge lies in translating these climate scenarios into biological consequences. To achieve this, we need impact models or other methods to derive the impacts of climate change. The last video Climate change 4 - impact projection approaches introduces various methods for projecting climate impacts.
Exercises on climate changeThe main drivers of climate change on a decade-to-century scale include:
Greenhouse Gases (GHGs): GHGs like carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) trap heat in the atmosphere, leading to the greenhouse effect, which raises Earth’s temperature. The increase in these gases is primarily due to human activities, such as burning fossil fuels, industrial processes, and deforestation
Aerosols: Particles in the atmosphere that can cool the climate by reflecting sunlight. They come from both natural sources (e.g. sea salt, dust, volcanic eruptions, fires) and human activities (e.g.power plants, cars, fires and cook stove). They are major climate driver in industrial centers (e.g. China)
Sun: Solar radiation heats the Earth, with minor fluctuations occurring over time due to cycles in solar activity, such as sunspots. Although these variations contribute only a small portion to the current climate changes, they play a significant role in driving climate change over geological timescales
Ozone: Ozone in the stratosphere protects Earth from UV-B radiation, while tropospheric ozone acts as a greenhouse gas and contributes to warming
Surface albedo: The reflectivity of the Earth’s surface affects how much solar energy is absorbed. Light surfaces (like ice) reflect more energy, while dark surfaces (like forests or oceans) absorb more, influencing the planet’s heat balance. Changes in surface reflectivity, such as melting ice and snow, decrease the albedo effect, leading to more heat absorption and further warming
The currently most important driver of climate change is greenhouse gases, particularly CO₂. The mechanism through which CO₂ affects the climate involves the greenhouse effect: CO₂ molecules in the atmosphere absorb long-wave radiation emitted from the Earth’s surface and re-radiate it in all directions, including back toward the surface. This process traps heat and increases global temperatures, driving many of the changes we observe in climate patterns.
In recent decades, global temperatures have been rising at a faster rate than at any other time in human history. This trend is evident from the fact that the hottest years on record have all occurred within the last few decades. One striking example is the extreme heat in Siberia in the spring of 2020, where temperatures were up to 8°C above the recent average. This trend is particularly concerning because it is mainly driven by human activities, especially the emission of greenhouse gases. Unlike previous climate changes, which took place slowly over long periods, today’s fast rise in temperatures increases the risk of triggering dangerous effects, like melting permafrost and losing ice cover, which could make global warming even worse. Even a small increase of 1.5°C could seriously upset the balance of our climate, showing how important it is to take action against these human-caused changes.
RCP stands for Representative Concentration Pathways, which are essential scenarios used in climate modeling to project potential future greenhouse gas emissions and their impacts on the climate. RCPs are defined by the level of radiative forcing — measured in watts per square meter (W/m²) — that is expected by the end of the 21st century. Each pathway corresponds to a specific amount of greenhouse gas concentrations, which can significantly influence global temperatures. The role of RCPs is to serve as inputs for climate models, helping to produce future climate scenarios, which are essential for understanding the potential impacts of climate change and planning appropriate mitigation and adaptation strategies.
The four climate impact projection methods described in the fourth video are:
Statistical models: These models establish relationships between climate parameters and impact measures, such as crop yield. They use historical data to explain past trends and project future climate impacts. Their primary limitation is that the statistical relationships may not remain valid under future climate conditions, and they may overlook important factors
Species Distribution Modeling: Also known as ecological niche modeling, this method predicts the future distribution of species by relating current presence or absence data to climatic parameters. However, these models may assume species are in equilibrium with the climate, which is often not the case
Process based models: These models aim to represent all major system processes using equations, capturing the scientific knowledge of processes like crop growth, phenology or hydrology. However, they are limited by the lack of complete understanding of complex systems, and often require extensive parameterization or assumptions
Climate Analogue models: This method identifies current locations with climates similar to those expected in the future at another site, offering real-world examples that can guide adaptation strategies. However, they may be limited by differences in non-climatic factors and lack of suitable data, making it difficult to draw clear conditions