1 Topics from Chapter 1: Framing, context and methods

Report and Chapter Overview

Pete Matthews

IPCC Introduction

The Intergovernmental Panel on Climate Change (IPCC) possesses tremendous responsibility. They play several key roles, including critically assessing scientific, technical, and socio-economic information pertaining to the impacts of human-induced climate change. In addition, the reports that the IPCC generates are comprehensively and transparently reviewed to ensure scientific integrity. The Assessment Reports of the IPCC have been divided into three groupings:

1. Working Group 1:
   1. Assesses the physical science of climate change
2. Working Group 2:
   1. Assesses the associated impacts, vulnerability and adaptation options of climate change
3. Working Group 3:
   1. Assesses the mitigation response to the options presented in Working Group 2

The Sixth Assessment Report (AR6) of the IPCC represents the collation of over 30 years of thorough scientific research and expert assessments, and defines the many challenges presented in the 21st century. This report depicts how far the IPCC has come since its conception in 1988. Not only is this report considered one of the most widely recognized sources in the scientific community, it has had a tremendous impact on education and government.

Goals of Chapter 1 – Framing, Context, Methods

1. Set the scene for the WGI assessment and to place it in the context of ongoing global changes, international policy processes, the history of climate science, and the evolution from previous IPCC assessments
2. Describe key concepts, methods, relevant developments, and modeling framework used in this assessment
3. Provide context and support for the WGII and WGIII contributions to AR6

Where we are now

Thankfully, the conversation pertaining to climate change and limiting negative human environmental impacts has been heating up in recent years. More and more people are realizing the consequences of our actions and are pushing for reform. The IPCC sixth assessment cycle has even been used for international legislation, including the well-known Paris Agreement. This agreement intends to hold the increase in average global temperature to below 2 degrees Celsius above pre-Industrial levels. However, there is much more action and global collaboration needed to realize this goal.

There are a multitude of ways in which the effects of climate change are tracked and measured. The global-averaged warming of the climate system is the most commonly presented data. Changes in the global mean surface temperature are calculated relative to a baseline averaging period from 1850-1900. GMST change until present (2011-2020) is 1.09 degrees Celsius. Reports show that this temperature anomaly is steadily rising. In addition to the warming of the climate system, atmospheric concentrations of greenhouse gases are another effective measuring tool that truly shows how much our planet has changed since the industrial revolution. Carbon dioxide is the strongest driver of anthropogenic climate change. The increase of carbon dioxide concentrations from 1850 to 2019 is staggering. In 1850, concentration levels were 285.5 +/- 2.1 ppm, whereas they are currently at 409 +/- .4 ppm.

There have also been human-induced shifts in the hydrological cycle. The intensity of the water cycle is increasing, along with a higher exchange of water between the surface and the atmosphere. The effects of this shift are different throughout the world. For example, annual mean precipitation over land in the Northern Hemisphere temperate regions has increased, while the sub-tropical dry regions have experienced a decrease in precipitation in recent decades.

How we got here

There is a tremendously long history pertaining to how we got to the stage we are in as a society. Between the rise of the human population, industrial expansion, usage change of land, innovation, etc., there is an abundance of information to include. However, some salient developments are below:

Instrumental Observations

Over the years, there has been a dramatic evolution of instrumental data and tools for measuring quantities important for climate change. These include data at Earth’s land and ocean surfaces, at altitude in the atmosphere, and at depth in the ocean. Instrumental weather observation first occurred in the 1600’s, with the invention of barometers and thermometers. By the 1800’s, national weather surfaces were able to construct built networks of surface stations. In the mid-19th century, naval weather logs recorded winds, currents, precipitation, and other fields. This kickstarted the movement of data collection, which has been critical for comparing current conditions to those of the past. Although this is only one example, there are countless other forms of innovation and technology that have shaped our modern instrumental data and techniques. We are now able to take data accurately and efficiently.

Paleoclimate

The 19th century was a critical time for the investigation of ‘new’ topics such as fossils, geological strata, ice ages, and warm periods. These components came together to form the early forms of paleoclimate studies. The study of paleoclimate refers to the gradual evolution of the Earth’s climate over hundreds to billions of years using pre-instrumental historical archives, indigenous knowledge, and natural archives left through natural processes. In simple terms, this is when the comprehensive and wholistic view of climate change was popularized in the scientific community.

Identifying Natural and Human Drivers

As early as the 1800’s, scientists were identifying factors that contributed to natural climate change. Factors that they outlined are as follows: greenhouse gases, orbital factors, solar irradiance, continental position, volcanic outgassing, silicate rock weathering, and the formation of coal. Anthropogenic drivers, or human drivers, were also hypothesized as early as the 17th century. One of the first studies pertaining to human environmental interference was in the 1890s. Scientists hypothesized that rise in carbon dioxide concentrations was due to the deforestation and rise of large-scale agriculture in the United States. During the same time period, scientists also calculated the effects of increased or decreased carbon dioxide emissions on planetary temperature. Today we of course have much more information, but scientific feats of the past jumpstarted the initiative.

AR6 Foundations and Concepts

AR6 builds upon previous IPCC reports using the latest scientific studies, concepts, and cross-cutting methods.

Baselines, Reference Periods, and Anomalies

Baseline values refer to a period against which differences are calculated. Reference periods are used to indicate a certain time period in which relevant statistics are calculated. Anomalies are variations in observed and simulated climate variables over time.

Variability and Emergence of the Climate Change Signal

Climate varies naturally as well as due to human interference. The relative importance of these factors depends on the climate field and region of interest. The climate change signal is when the change in climate is larger than the natural or internal variations. For example, in the 1930s, scientists noticed the uptick in temperature and overall climate change. Although they were able to detect a difference, they could not pinpoint what was responsible. Was this due to a long-term natural trend or are humans to blame? It is emphasized in the chapter that the ‘signal’ had not differentiated itself from the ‘noise’ of natural variability. With better observations and a larger human-induced signal, scientists are more easily able to differentiate between the two.

Sources of Uncertainty in Climate Change Simulations

When evaluating climate change simulations, it is important to note that there will be uncertainty to some degree. There are three primary sources of uncertainty:

1. Uncertainties in radiative forcing
   • There are uncertainties involving both future and past emissions and radiative forcing. Future radiative forcing is of course uncertain because it is impossible to determine the choices society will make that will determine future human-related emissions. Past radiative forcing and emissions are uncertain because there are unknown factors. For example, it is unclear how many volcanic eruptions there were in the past and the amplitude of changes in solar activity. There were also inadequate observations of aerosol pollution in the past.
2. Uncertainty in the climate change response to particular radiative forcing; internal and natural variations of the climate system
   • Due to the complexity of our planet, it is often extremely difficult to predict what will happen to the climate in response to sporadic natural factors. Therefore, uncertainty is present.
3. Interactions among sources of uncertainty
   • It is more than likely that there are interactions between radiative forcing and climate variations. For example, anthropogenic aerosols may influence decadal modes of variability in the Pacific. However, these interactions are difficult to predict, similarly to the previous sources of uncertainty.

Changes in Global Temperature between 1750 and 1850

As previously stated, the Paris Agreement was intended to hold the increase in average global temperature to well below 2 degrees Celsius above pre-industrial levels.  It is important to now ask, how exactly are we classifying the term “pre-industrial?” Typically, the term refers to the period between 1850 and 1900. However, it is also known that natural and human related environmental impacts occurred before 1850. Is it possible to obtain detailed, accurate information regarding the Earth’s climate prior to 1850?

Temperature change and variability due to humans prior to 1750 is widely disputed between scientists. Although there is some evidence suggesting that humans did in fact alter the natural state of the climate, it is unable to be confirmed. Unsurprisingly, the Industrial Revolution was the first period in time that proved the notion that humans were impacting the natural environment, specifically in terms of increasing temperatures. This was primarily due to coal-powered machinery which was widely used across the United States and parts of Europe. However, it did take several decades for noticeable change to occur. Between 1750 and 1850, carbon dioxide levels increased from 278 ppm to 285 ppm. We can rule out the burning of fossil fuels for a reason why this occurred. The only hypothesis that makes logical sense is that land use changes spurred an increase in carbon dioxide concentration. The concentration of GHGs also increased, and there was a cooling influence from other anthropogenic radiative forcing. In addition, the difference in net radiative forcing from changes in solar activity and volcanic activity in 1850 to 1900 is less than +/- 0.1 Wm, compared to 1750. With these factors in mind, it was estimated that the change in global temperature from 1750 to 1850-1900 was roughly 0.1 degrees Celsius. The anthropogenic component likely ranged from 0.0-0.2 degrees Celsius.

Risk Framing in IPCC AR6:

The definition of risk states that it is the potential for adverse consequences for human or ecological systems, recognizing the diversity of values and objectives associated with such systems. Therefore, both impacts of climate change and human responses to such climate change are the two components to climate change risk. In addition, the severity of the exposure and its consequences must be taken into account. This can be looked at through a social, health related, economic, or cultural lens. The info graphic below breaks down three of the ‘need to know’ risk terminology that will tremendously impact IPCC AR6 comprehension. Exposure, vulnerability and hazard all have their own unique definitions, but are intertwined through a common foundation.

The Second Half of Chapter 1

Blaze Burke

The second half of the IPCC’s AR6 WGI – Chapter 1 discusses many topics that are developments since AR5 as well as foundational information to allow the reader to understand subsequent chapters better. Those topics include attribution, modeling developments and implications, scenario development and integration, and frequently asked questions. This paper aims to consolidate the process the IPCC uses to develop climate models, discussed at length in this chapter, from the formation of working groups to a final assessment report and how AR6 differs from the first IPCC report in 1990. We seek to distill the operational and systematic processes that happen, as an international cross-functional effort, to produce this weighty and extensive assessment of our planet’s climate. By understanding how a computer-generated climate model that predicts future global and regional climates comes into existence and the process which goes into making the model real, relevant, and reproducible, you will be able to appreciate the following chapters’ scientific understanding and how it came to be. Please consider perusing Chapter 1 if you would like further information or deepen your knowledge on any of the topics addressed in this paper.

The IPCC discusses in the following chapters and further details the changes in global and regional climate systems that are becoming more evident, not only through scientific observations but also being lived experiences to millions of people across the globe as they endure increases in frequency and intensity of extreme weather; observe biodiversity loss in their region, and witness rapid changes to landscapes long thought imperturbable. These climate-related effects on natural and human systems are discussed at length throughout AR6; however, Chapter 1 serves as a primer to the rest of the assessment report and is limited in its in-depth discussion of the causal elements of climate change. Consider Chapter 1 to be a chapter that explains how we get to the information found in the rest of the report. So, in that spirit, let’s begin!

Firstly, it is essential to understand that there are many different types of climate computer models that contain many complex processes that span historical data to the most cutting-edge research. These models simulate, compare, contrast, and deepen our understanding of the climate from the distant past to today with the aim of helping to forecast climate patterns decades in the future. Then layering all these findings on top of one another, the models can run scenarios that will help policymakers, scientists, and ordinary people understand the current science. Additionally, these groups will be able to see what predictions the climate community has for the planet’s future and ultimately help inform decisions that help steer humanity and the planet toward a future less impacted by climate change [Section 1.5.3].

One distinction worthy of note is the difference between weather forecasting and climate forecasting. Both are important in modeling; however, climate forecasting deals with finding the average location and intensity of storms (multiple), while weather forecasting deals with finding a storm’s timing, location, and intensity (single). We will be concerning ourselves with climate forecasting when it comes to the modeling contained in AR6.

Secondly, over time, with faster and more powerful supercomputers running climate models, the resolution has increased with each successive assessment report, with the 1990’s FAR (First Assessment Report) having a global resolution of about 500 km improving to 2014’s AR5 having a global resolution of about 110 km. 2021’s AR6 has a global earth systems resolution of 100 km AND a regional model resolution of 25-50 km! [Section 1.5.3.1] The resolution matters because the models can render more accurate predictions and analysis for local effects, especially in the areas of high topography (i.e., mountains) and tropical storms (i.e., hurricanes). It is also worth pointing out that models’ climate sensitivity does not vary much with increases/decreases in resolution.

Ultimately, these models have to be executed, processed models have to be analyzed, and then those interpretations must be consolidated and communicated to the public [Section 1.6.1]. This process follows a framework dividing the work appropriately by topic, scientifically addressing the pressing questions and issues relating to the climate, reviewing the completed work, and then producing an assessment report. The first step is to answer the question, “who, in fact, does the work?”

The work of the IPCC is shared across four main entities: three Working Groups (WGI, WGII, WGIII) and a Task Force on National Greenhouse Gas Inventories (TFI). Each is composed of research committees and smaller groups. Each entity is responsible for different aspects that are compiled in the IPCC’s assessment reports. WGI is accountable for assessing the physical science of climate change and climate systems. WGII evaluates the positive and negative outcomes of climate change and how those impact natural and socio-economic systems while providing options for adapting to climate change. WGIII focuses on mitigating climate change and assessing techniques for reducing and removing greenhouse gas emissions to/from the atmosphere. TFI develops an internationally agreed-upon methodology for calculating and communicating greenhouse gas emissions and removals while also encouraging the use of this methodology by participating countries. The modeling work is then split up among a diverse collection of 28 computer-modeling centers across the globe [Section 1.5.3.3], which run anything from individual scenarios (discussed later), schemes, parameterizations, simple climate models, up to and including very complex general circulation or earth systems models (GCM, ESM) [Section 1.5.3].

Figure 1.27 shows the operation process flow between the working groups to generate scenarios and each group’s given topics. It is interesting to note that the foundation of the working groups and their data is based upon the causes and the effects of climate change, and seeing the topics in that sequential order is all the more fascinating.

FIGURE 1.27 (will be inserted following the final edit of IPCC AR6)

The next step for these working groups is to identify attribution. Attribution in the context of the IPCC is the process of assessing the contribution of one or more casual factors to such observed changes or events [Cross-Working Group Box: Attribution]. A starting point to determine attribution is to ask questions like, “Have human greenhouse gas emissions increased the likelihood of an observed heatwave?” then gather observations, generate a hypothesis for the causes, test the hypothesis, then finally assess the findings for the attribution. Figure 1 in Cross-Working Group Box: Attribution shows this purpose-driven iterative 5-step process that helps direct modeling and future research and finds new connections that weren’t previously known.

FIGURE 1 Cross-Working Group Box: Attribution (will be inserted following the final edit of IPCC AR6)

At the heart of AR6 are modeled scenarios, with the Shared Socioeconomic Pathways (SSP) being the most important since they are used across all chapters and work groups to form a systematic common-thread narrative throughout the following chapters. These scenarios exist to provide a standardized description of how the future may develop, a “what-if?” investigation of causes and effects. Consistent and coherent assumptions are used across the scenarios to inform the modeling on the drivers of climate change, including human-caused greenhouse gas emissions, atmospheric aerosol concentrations, land use patterns, economic processes, innovation in technology, governance, and all the complex interactions between these drivers [Section 1.6.1]. As we saw in Figure 1.27, there is a cause and effect flow that drives the scenario generation process, which not only affects the scientific development of these scenarios but the how the working groups interact with each other to produce the assessment report.

Once the work has been divided up and the scenarios have been modeled, it is now essential to connect and compare the models. That is where CMIP6 comes into play. The 6th phase of the Coupled Model Intercomparison Project (CMIP6) provides the framework for all of the models’ results to be connected and compared. The Project endorses or “oversees” 23 sub-set Model Intercomparison Projects (MIPs), which each project focuses more specifically on certain topics found within AR6 such as land use, paleoclimate, and decadal climate prediction [Section 1.5.4.3]. Models are then evaluated by their respective MIP, looking for current or future improvements to models, emergent findings that should be further scrutinized, whether figures can be published with these findings, and if the results are reproducible. This evaluation not only provides increased internal communication within those findings but also adds a layer of quality control to the final report [Section 1.5.4.5].

So how does the information in these climate models actually show up in AR6 or get communicated? Figure 1.26 is a great example that displays, over a timescale from 0 CE to 2300 CE, four parcels of information: respective concentrations of carbon dioxide, methane, and nitrous oxide in the atmosphere as well as the global mean temperature. As you move toward the right of the graph, around the year 2015, you see where the modeling of different scenarios takes over from the historical data. All the different colored lines for all four parcels of information represent specific SSP scenarios used throughout AR6 for granular future projections going to 2100 and more coarse projections going beyond into 2300 [Section 1.6.1]. As you can see, the human influence (also known as anthropogenetic) of burning fossil fuels, thus releasing more greenhouse gases into the atmosphere, is leading to a rapid warming of the planet. You can also see that for the past 2000 years, the earth’s temperature and atmospheric composition have been remarkably stable up until about 180 years ago with the onset of the Industrial Revolution and ubiquitous fossil fuel use.

FIGURE 1.26 (will be inserted following the final edit of IPCC AR6)

More granularity can be achieved not only for the global but for regional climates and modeled not only in a graph but in a more visually apparent rendering. Figure 1.14 shows just that with observed temperature change in 2020 relative to 1850-1900 [Section 1.4.2.2]. The top left panel shows global temperature change, and to what degree where we can see a significant proportion of the planet has warmed, both over land and sea. That panel is then broken down further into regional graphs that show the historic temperature change with year-to-year variability for North America, Northern Europe, East Asia, Northern South America, Tropical Africa, and Australasia.

FIGURE 1.14 (will be inserted following the final edit of IPCC AR6)

It is crucial in these models that we can visualize the temperature changes across the globe but also see how they fit into a historical and regional context. Then we can approach these graphs and models with a better appreciation of the magnitude of climate change as it affects large and small areas of the world. For example, in Figure 1.14, we can see warming in the Arctic of 2.0^oC – 2.5^oC. That causes many downstream effects, like the thawing of Arctic permafrost and melting of the Greenland Continental Ice Sheet. Those effects may be taking place on the other side of the globe from a coastal city, like Honolulu, Rio de Janeiro, or Sydney, but the warming causes that ice melt which raises global sea levels, which affects these cities directly.

Models do have their limitations in the form of uncertainties. When it comes to predicting future climates, uncertainty is the nature of the beast, so to speak. However, modeling tries to manage this issue by identifying the sources of uncertainty and conducting real-world experiments to help better inform the modeling [Section 1.4.3]. Sources of uncertainty include radiative forcing, climate response, natural and internal climate variations, and the interactions between variability and radiative forcings [Section 1.4.3.1]. Considerations for describing these have been made for, and the IPCC calls out these areas of uncertainty, which are considered possible but “very unlikely,” “highly uncertain,” or “potentially surprising” [Section 1.4.4].

Figure 1.15 illustrates this managing of uncertainty well, not only with elements of climate projections but also showing how there is a cascade effect as the modeling moves deeper into the future. For each of the six plots, you see three defined “layers.” Starting from the bottom layer, we see a wide range of possibilities modeled in the individual ensemble members, which then feed up into the average of the particular model ensembles. That middle layer then is refined once again into the top layer of the modeled scenario. Each set of colored lines in the plot shows the “distilling” process from many individual models that are varied in their predictions to getting a final scenario that can be better understood and which has captured but also mitigated the uncertainties in the model. As time moves forward, we see in the 2081-2100 plots a much more varied range of predictions as the uncertainty in those ensemble members compounds as they compute further and further into the future, with layer upon layer of uncertain interaction, causing this visual and computational cascade effect.

FIGURE 1.15 (will be inserted following the final edit of IPCC AR6)

Let’s end the second half of Chapter 1’s summary report with a comparison between the IPCC’s first assessment report done in 1990 and 2021’s assessment report. The improvements between then and now are many and varied that stem from technological advances, such as a supercomputer’s modeling power, which spur new developments in model resolution, climate modeling schemes and parameters, and the overall amount of modeling scenarios that can be generated. Not only have advancements in technology improved the content of the ARs between 1990 and 2021, but most importantly, new data from research, observations, and geological records have informed key aspects of scientific climate knowledge and to what degree, human influence has had on the climate.

Some of the notable highlights [Section FAQ 1:1] that have been achieved since 1990’s FAR are:

• Recorded global ocean heat content went from being assessed in a 26 year period in only two regions to now being assessed globally spanning 147 years.
• In geological records of temperature, sea level, and CO2, we see an average increase of 94,417% over the time spans captured compared to 1990! The most significant increase with CO2 records from 160,000 years being assessed in 1990 to 450 million years being assessed in 2021 – a 281,150% increase!
• Adding four new climate modeling elements of aerosol and cloud interactions, land use/cover, land and ocean biogeochemistry, and atmospheric chemistry – up to 8 elements from 4 in 1990.
• And not least of all, human influence on the climate is an established fact, where it was just suspected in 1990.

FIGURE FAQ 1.1 (will be inserted following the final edit of IPCC AR6)

As figure 1 in FAQ 1.1 asks, “Do we understand climate change better than when the IPCC started?” The answer is a resounding YES! The hope is that this impactful and indispensable work continues so that, when AR7 is released in another handful of years, we can still respond confidently with “yes” to, “Do we understand climate change better than FAR, or even AR6?” Despite all of these improvements and newly informed findings to the IPCC’s AR6, the fact still remains that human influences are without a doubt causing climate change. The primary anthropogenetic cause driving climate change is greenhouse gas emissions from burning fossil fuels, namely coal, oil, and fossil gas (aka natural gas). The very real and urgent hope is that by the time of the IPCC’s next assessment report, we can answer “yes” to a different and more critical question, “Did we do enough to prevent the worst effect of climate change from being realized?”