The climate change dilemma: big science, the globalizing of climate and the loss of the human scale

Abstract

This paper explores a crucial dilemma behind the failure of climate politics: the “dehumanization” of the concept of climate, i.e., the emergence of a predominance of global perspectives, conceptions, and knowledge of climate, which do not translate into local knowledge, experience, and political action. On the one hand, twentieth-century climate science improved understanding of global climate change tremendously. On the other hand, it focused on reductionist quantification and modeling and emphasis on large spatial and temporal scales. This research direction produced large- and global-scale knowledge and can aptly be described as knowledge from above. Climatology in its original Humboldtian conception, in contrast, focused on detailed local information. The human dimension—the support of human affairs—was at the core of it. This understanding of climatology involved priority of local-scale knowledge and can be regarded a version of knowledge from below, which still predominated in the first half of the twentieth century. In my paper, I will explore the question how the understanding of climate was “dehumanized” by globalizing research approaches and scientific conceptions through the twentieth century. Scientific and political interests pushed a globalizing agenda and produced a conceptual and discursive detachment of climate knowledge from human scales. The paper argues that it is important to understand the historical and ideological foundation of knowledge from above and its epistemic and social authority, if we aim at re-establishing recognition of knowledge from below and the lost links between both types of knowledge.

Activist Naomi Klein’s film on climate change This Changes Everything paradigmatically shows a dilemma of climate change politics. “I’ve always kind of hated films about climate change,” she confessed in the opening of her film. Guardian reviewer Henry Barnes paraphrased her explanation: “they’re boring, they’re presumptive, they always, always include shots of polar bears.” He agrees: “Klein’s absolutely right. Climate change documentaries struggle to make the story personal. The breadth of the problem is too large to filter through relatable characters easily. Unfortunately,” the review continued, this film “fails in exactly the same ways,” except that it went easy on the polar bears (Barnes 2015). Klein’s and the reviewer’s frustration about the documentaries points to a crucial dilemma of the climate change problem: it is abstract, largely invisible, and hardly touches people emotionally. Obviously, it is difficult to mobilize people and politics, if the issue at stake does not capture the imagination and stir emotions.

Swiss climatologist Martine Rebetez provided three major reasons why it is difficult to relate to the problem of climate change: First, “the direct perception of climate change by humans is practically impossible because of the temporal scales associated with this change; second, the vast spatial scales characteristic of global change are difficult to relate to everyday life (compared for instance to direct effects of air or water pollution); third, global change issues are often too abstract and cannot be related to personal experience” (Rebetez 1996, p. 495). Rebetez emphasized the inappropriateness of long-term average values, to which climate scientists refer: they do not fit with personal scales and experience. We cannot sense and see climate change. It is an abstract problem, not a perceivable issue of local and personal experience and life worlds.

Many authors have criticized that climate research provided global- and large-scale information on climate change and its drivers but was significantly less able to provide locally relevant information, which is accessible to the experience of people and political institutions and better links to regional and local policy demands (e.g., Turner et al. 1990; Jasanoff and Martello 2004; Hulme 2010). Earth system science and global models offer a “panoptic gaze” (Barnett et al. 2009). “Climates plural became global climate singular, regional climate variations became global climate change” (Hulme 2010, p. 560), and climate knowledge became detached from humans (Sörlin 2012; Carey 2010). The homogenized understanding of climate change produced de-contextualized, top-down views of planetary knowledge. It separated knowledge making from meaning-making and global fact from local value (Jasanoff 2010). Even more, the scaling-up to the global allowed “the new global environmental change agenda [to] ‘trump’ local processes and agendas” (Radcliffe et al. 2010, p. 103). Earth science literature of the past 25 years “is immense,” historian James R. Fleming writes, “but it sorely lacks its human dimensions” (Fleming 2014, p. 580)—an observation which has been repeated for at least the same number of years (e.g., Turner et al. 1990; Jacobson and Price 1990; Stern et al. 1992).

The techno-scientific modeling industry (as it can arguably been called) is run by thousands of scientists in many scientific and business institutions, which usually operate physically and ideologically detached from local settings, contexts and stakeholders and construct environmental knowledge with birds-eye views from far above. Implicit to the environmental modeling business is a “monolithic framing” of environmental issues (Bryan Wynne 2016) and a politics of knowledge that establishes, reinforces and perpetuates privileged epistemic authority of models and model-based knowledge compared with alternative perspectives and forms of knowledge from below. Modeling and model-based knowledge from above have gained a hegemonic status and contributed significantly to marginalize alternative knowledge practices, which have a clearly lower status in the main theatres of environmental science, discourse and decision making.

While modeling based knowledge carries privileged status and epistemic authority, the types and scales of knowledge it offers often conflict with local knowledge needs. Climate and climate impact models suffer from predictive limitations in at least three ways. First, they fail to provide sufficiently reliable predictive knowledge on the local scale, because modeling uncertainty increases significantly with smaller scales and downscaling efforts with regional climate models lack credibility. Second, they fail to predict severe climatic events such as floodings or droughts, which have particularly severe consequences for local farmers, transport and industry. Third, they ignore or simplify socio-economic complexities such as demand and price cycles for agricultural products, which interact with environmental factors.

As a result, “epistemic disjunctures” (Mehta et al. 2018), inconsistent knowledge practices from above and below, have emerged. These disjunctures raise the question whether and how lost links can be re-established either by changed or new knowledge practices or by mediators such as knowledge brokers and interlocutors, which can connect, negotiate, and accommodate the diverse, maybe conflicting resources of knowledge from above and below. This article argues that re-establishing the lost link between knowledge from above and knowledge from below requires an understanding of the historical and ideological foundations of globalized, model-based knowledge and its rise to epistemic hegemony. Where from comes the knowledge from above? Which interests and forces shaped, justified and promoted it? How and why did it gain the epistemic status it presently enjoys?

History does not run short of ironies. The environmental knowledge needed by agriculture, fishery, transport, and industry once was the very scope of climatology. Climatology fashioned a strong bottom-up philosophy. It focused on comprehensive collection of local data and knowledge for an understanding of local environments and the support of human affairs. This disciplinary identity, which prevailed from the nineteenth to the mid-twentieth centuries and seemed to resonate with knowledge demands from below, was marginalized in competition with techno-scientific modeling endeavors in the Cold War era. Ironically, we owe an extraordinary expansion of the atmospheric sciences and of atmospheric and climate knowledge precisely to the fact that local diversity and detail was neglected in favor of globalized top-down perspectives. The look from above helped to reduce the chaotic diversity and complexity of weather and climate and make it amenable to physical theory, which eventually delivered numerical weather prediction and, in addition, widely held promises of human control of weather and climate.

This article provides a historical account of the coming of age of today’s globalized climate science, the focus on large spatial and temporal scales, and the loss of the human dimension in climate research and understanding. Climate science adopted a path of globalizing reductionism that boasted epistemic superiority and effectively marginalized the human oriented bottom-up “classical” climatology. This globalized science with its predilections, framings and ideologies did not simply emerge as a result of scientific progress or an inherent logic of science or nature. The roots of globalized climate science reach at least back to the nineteenth century. The globalizing of climate science was dependent on political and cultural contexts and changing politics of knowledge. Ideologies of science, such as the priority of quantification and mathematical theory, and promises of control, such as of colonial environments in the age of imperialism, natural resources during fascist and National Socialist rule in the early twentieth century and geopolitical interests during the Cold War, all played their part.

“Classical climatology” and its globalizing tendencies

Alexander von Humboldt in many ways led the way to the emerging scientific discipline of climatology, which later some climatologists referred to as “classical climatology” (e.g., Flohn 1954, pp. 11–13; Khrgian 1970, p. 312). According to Humboldt, climate meant “in the most general sense all changes in the atmosphere which noticeably affect the human organs”, such as temperature, precipitation, humidity, barometric pressure or wind (von Humboldt 1845, p. 340). This concept of climate was linked to a specific location, to the surface of the earth and directly related to human experience. It represented a holistic concept, as it involved all atmospheric phenomena affecting the human senses and, in addition, included the investigation both of the impact of humans on climate and of climate on humans. Subdisciplines of climatology such as urban climatology addressed the impact of humans on climate, whereas medical climatology and bioclimatology focused on the impact of climate on humans.

Climatology pursued a bottom-up research strategy based on local observation. It conceived climate as an aggregate, made up of and caused by local conditions. In addition, climatological research had a strong function and identity of serving society and national interests. It provided weather data and climatological information for human activities such as agriculture, fishery, transport and industry as well as characterizations of climates on the globe. It supported and profited from the colonial ventures in the age of imperialism, such as the investigation of unfamiliar climates and the agricultural and medical challenges it posed (Livingstone 2002; Coen 2011), and it supported (and prospered from) National Socialist efforts in expanding and optimizing agricultural production in Nazi Germany (Flohn 1936; Heymann 2009). Hermann Flohn, one of the leading German climatologists in the twentieth century, called classical climatology a “clearly on humans oriented climatology” (Flohn 1954, p. 11). The director of the German Reichswetterdienst Ludwig Weickmann even praised Humboldt’s observation-based, anti-reductionist, holistic research program in a public lecture as a “a fight against the tyranny of the number, against formula and law, against the whole dehumanization of nature through science” (Weickmann 1944, p. 9).

While its bottom-up research program and a strong appreciation of local diversity and detail characterized classical climatology, it included seeds of globalizing perspectives. First, Humboldt already pursued the construction of perspectives of climate on large spatial scales. Second, the colonial ventures of imperial powers, especially Britain and France, established and reinforced a global scope of climatology. Third, classical climatology focused on the surface of the earth, but meteorologists and climatologists recognized the need to expand meteorological observation into higher layers of the atmosphere and investigate the global atmospheric circulation.

Humboldt’s scientific conception of climatological investigation was strongly influenced by his expeditions and the experiences, observations, and measurements he made in other parts of the world. His investigations of climates revealed a global grasp. Based on series of temperature measurements, he diligently applied the method of mean values and invented the concept of isotherms. From 730 observations of daily minimum and maximum temperatures all over the northern hemisphere, he calculated annual temperature averages and constructed his famous map of isotherms of the northern hemisphere, which showed that lines of equal average temperatures were not parallel to the equator (Knobloch 2007, p. 12, see Fig. 1). With the averaging of series of data, he established an ingenious and objective measure for climatic features.

Fig. 1
figure1

Humboldt’s map of isotherms published in 1817 (based on Hellmann 1897, chart 2)

Climatologists such as the Austrian Julius Hann, head of the Central Office for Meteorology and Geomagnetism in Vienna, and the Russian-German Wladimir Köppen, head of the German Marine Observatory in Hamburg, adopted Humboldt’s conception of climate and made it the basis of a rigorous empirical science. Climatology in their vein was an effort of systematic collection and evaluation of series of meteorological data and of analyzing statistically their broader relationships in order to identify the specificities of local and regional climates. Hann’s Handbook of Climatology, first published in 1883, “laid the cornerstone of modern climatology” (Coen 2010, p. 844). It defined the major features of classical climatology and its research program, became internationally a standard work of reference for what came to be called the “averaging climatology” and was expanded in later editions reflecting the progress of the field (Coen 2010, pp. 843–846).

Hann was very clear about the difference between meteorology and climatology. He considered it the task of meteorology to trace back atmospheric phenomena to physical laws and discover the causal relations in the sequence of atmospheric phenomena. “Meteorology essentially is theorizing; she decomposes the complex of atmospheric processes to link partial phenomena to physical laws.” Climatology, in contrast, was according to Hann descriptive and holistic with the task “to provide a preferably lively image of the interaction of atmospheric phenomena at one location.” Furthermore, in climatology, “those meteorological phenomena have priority, which cause the greatest influence on organic life on earth” (von Hann 1908, pp. 3–4).Footnote 1 Köppen conceded that in climatology, in contrast to other disciplines, “theories … step back, the ordered collection of facts is the prevailing goal” (Köppen 1895, p. 614).

The scope of Hann’s climatology was global in the sense that it collected and analyzed climatological information about all regions on earth. Comprehensive collections of meteorological data series served further statistical analysis with the goal to discern characteristics and patterns of local and regional climate. The diversity of climatological information and detail aroused interest in creating classifications and taxonomic order. One paradigmatic achievement of classical climatology was Köppen’s influential classification of climates and the construction of global maps of climatic zones, which were widely distributed and still are in use today (see Fig. 2; Köppen 1884, 1936; Wilcock 1968).

Fig. 2
figure2

Climates of the earth according to Köppen-Geiger (reproduced from https://www.geographie.uni-bonn.de/dias-klimazonen-koeppen)

The rise of imperial science in the colonies was a second globalizing force and strongly reinforced global perspectives in climatology. Challenging climates in tropical regions and fears of drought, desiccation, agrarian failure, and famine pushed the development of medical, field, and meteorological sciences. Increasingly, complex infrastructures of colonial rule under the British and French after the mid-eighteenth century provided the basis for information networks needed to collate systematically environmental information on a global basis (Grove 1995, 1997). The opportunity to compare data and experiences from distant lands with the homeland directly stimulated thinking about global patterns and connections of climate and its relation to the the variability of vegetation. Letters exchanged between East India Company naturalists in different regions facilitated the discovery of climatic links and justifiably the first description of what we would now call teleconnections (climate anomalies being related to each other at large distances) associated with a very strong El Niño that occurred in 1791 (Grove and Adamson 2018). In the nineteenth century, meteorological departments and observatories in India, Australia, and Africa provided a more sophisticated understanding of large-scale pressure systems and fluctuations and of relations of global-scale tropical circulation and the strength of the Asian monsoon. Until the mid-twentieth century, colonial observation networks remained an important source of climatological data and helped to expand climatological knowledge about distant world regions (Mahony 2016; Lehmann 2017).

A third globalizing force related to the so-called discovery of the third dimension, the meteorology, and the climatology of the higher atmosphere. Physical theories of large-scale atmospheric circulation had been discussed since the eighteenth century, but observational evidence was very sparse in comparison. Mountain stations and, since the late nineteenth century, observations with the help of balloons and kites gave rise to a new climatological subdiscipline after the turn of the century, which was named “aerology” by Köppen (Nebeker 1995, p. 48). Köppen revealed in an overview of climatology from 1895 that the expansion to the vertical dimension was foreign to the established understanding of “climatology as a surface-oriented discipline.” Climatologists “will maybe … not anymore want it to be counted to climatology” (Köppen 1895, p. 619).

In the early twentieth century, the rising demand of weather information for air traffic during and after World War I pushed the expansion of aerological observation. Since the 1930s, the introduction of radiosondes (which could send measurement results back to earth by radiowaves) caused a quick increase of data and knowledge about the higher atmosphere (Flohn 1950). Based on such data, German meteorologist Richard Scherhag constructed high-altitude weather maps since 1935. From pressure differences at high altitudes of about 5 km, he derived the existence of strong wind velocities. German meteorologists and climatologists investigated these winds, called “jet streams” (“Strahlstrom”) by meteorologist Heinrich Seilkopf, which for language and political reasons reached the USA only much later (Flohn 1992). After World War II, German meteorologist and climatologist Hermann Flohn and Swedish meteorologist Sverre Pettersen developed a consistent theory of the planetary circulation. The “conquest of the third dimension,” as Flohn called the inclusion of higher layers of the atmosphere in climatological investigation, helped to explain climatic phenomena on the surface of the earth such as the monsoon (Flohn 1950; Petterssen 1950).

Humboldt’s isotherms, climatological investigation in the colonies, Köppen’s climate classes and global maps of climate zones, as well as the investigation of the higher atmosphere represented forces and forms of a globalization of weather and climate knowledge. In Köppen’s system, the climate of individual locations dissolved in averaged temperatures and climatic features of large climatic zones, necessarily divested of local detail and specificity, and in tropical teleconnections and three-dimensional climatology of the atmospheric circulation, local details disappeared in larger-scale weather and climate systems. This strategy of disregarding local detail facilitated a gain of knowledge by establishing and discerning larger geographical patterns and systemic relations of weather and climate. However, it did not replace but supplemented descriptive climatology and the appreciation of local detail. Prewar climatology accommodated an integration of local detail and global pattern, geographical and physical understanding and the relation of climate and human activity. The most important epistemic gain of globalization was an interest in and promises of an improved understanding of the larger-scale causal relations of the dynamics of the atmosphere. The concept of climate shifted from being a solely geographical concept linked to specific locations to becoming, in addition, a physical concept linked to the global dynamics of the atmosphere. Emulating the term “dynamic meteorology,” Swedish meteorologist Tor Bergeron called the new physical approach consequently “dynamic climatology” (Bergeron 1930).

Measurements above the clouds and weather maps on the 500 millibar pressure level (approximately 5500 m above the surface of the earth) contributed to detaching climatological investigation from human experience and perceptibility. Climatology, however, continued to attach high priority to the human dimension of climatological research. First, climatologists kept a strong dedication to empirical data collection and local detail on which larger-scale knowledge was to be built. Second, larger-scale knowledge served to inform and provide a better understanding of local weather and climate conditions in order to support political goals such as improving agricultural output (bioclimatology) and human health and well-being (medical climatology). Third, meteorologists and climatologists continued to share a personal and emotional relation to weather and climate. Fourth, the major task of climatology remained the support of agriculture, industry and human health, as demonstrated by the rise of subdisciplines such as agrometeorology and bioclimatology in the early twentieth century.

Testimony to climatological thinking in the first half of the twentieth century was the reluctance with which climatologists received the theory of global climate change by British engineer Guy Callendar in the 1930s. The investigation of long-term or secular changes in climate had a long history, but an understanding of these changes had remained futile (e.g., Fleming 1998; Lehmann 2015). Discussions on changing climates resurfaced when investigations of glacier volumes by Swedish glaciologist Hans Ahlmann and observations at meteorological stations showed a significant warming trend in northern Europe since about 1920. Building on work about the greenhouse effect by Joseph Fourier, John Tyndall, and Svante Arrhenius in the nineteenth century, Callendar suspected that rising levels of carbon dioxide were the cause of the warming. He completely reworked the theory of infrared radiative transfer, estimated the rise of carbon dioxide levels, calculated warming due to the enhanced greenhouse effect and put his calculations in relationship to collected observational data on surface temperature trends (Callendar 1938; Fleming 2007, pp. 65–77). The majority of climatologists, however, questioned the explanatory power of his conclusions or remained explicitly reluctant about such far-reaching claims. Callender faced many objections: for example, the neglect of atmospheric processes such as heat transfer, temperature inversions and modifications of the general circulation. George Simpson, director of the Meteorological Office in London, concluded that the increase of carbon dioxide and temperature “must be taken as rather a coincidence.” The observed rise in temperature “was probably only … one of the peculiar variations which all meteorological elements experienced” (Callendar 1938, p. 237).

The physical understanding of climate and the loss of the human scale

Classical climatology was, in essence, a geographical science. Even though it was part of its ethos to put priority on empirical data and put high value on local detail in the observational record, many of its advocates, such as Hann and Köppen, envisaged the application of physical laws and quantitative physical understanding to climatic and weather processes (Lehmann 2015; Coen 2010). This pertained in particular to the investigation of processes in the higher atmosphere, an area of research with which climatologists according to Köppen reached a “boundary, at which the geographical element retreats to the physical and climatology passes over to meteorology in a narrower sense” (Köppen 1895, p. 627). The climatological data-based, detail-oriented and holistic paradigm created significant barriers to quantitative physical approaches, because the enormous variety of weather phenomena escaped simple mathematical relations. Theoreticians, in contrast, attempted to attack the objective of a quantitative physical understanding from the opposite end, from pure physical theory—most influentially so Norwegian physicist Vilhelm Bjerknes. Bjerknes developed around the turn of the twentieth century a foundational theoretical framework consisting of seven non-linear partial differential equations for the quantitative description of atmospheric processes. These equations described in principle the dynamic development of seven meteorological parameters at any point in time and space and offered promise to solve the problem of weather prediction based on the application of physical laws and the solution of the differential equations representing these laws (Bjerknes 1904; Gramelsberger 2009).

This work was a decisive step in the history of meteorology and climatology, even though its revolutionary power became fully effective only half a century later. The description of atmospheric parameters and processes in purely mathematical language was stripped of any human elements or relations to human affairs. It replaced the human-oriented holism in climatology with physical reductionism and a degree of abstraction that was beyond human perceptibility. Bjerknes’ so-called primitive equations, however, proved impractical initially, because they could not be solved analytically. During World War I, British scientist Lewis Fry Richardson attempted an approximate so-called numerical solution of the differential equations for a weather prediction. This approximation involved a transformation into finite difference equations for the calculation of averaged values of meteorological parameters on a spatial grid (Fig. 3). The weather elements (temperature, pressure, wind, etc.) could not be calculated exactly point by point, but only approximated as average values representing a grid element of several hundred kilometers side length. This approach of numerical weather prediction required very lengthy and tedious computations. An attempt to calculate a weather prediction for one past day in 1910 for two grid elements took Richardson six weeks (Richardson 2007; Lynch 2006). Richardson estimated in 1922 that the computation of a weather forecast for the next day would require a workforce of 64.000 human computers (Richardson 2007, p. 219).

Fig. 3
figure3

A representation of the grid on which Lewis Fry Richardson performed his numerical approximation of a weather prediction for 20 May 1910 (Richardson 2007, p. iii)

Though he could not solve the primitive equations, Bjerknes perfectly appropriated the science of weather to serve fishery interests. This strategy brought him sufficient resources from the Norwegian state to build the influential Bergen School of meteorology (Friedman 1989). The Bergen School became famous for its polar front theory, which described large-scale weather systems and cyclone generation. This approach excited meteorologists and atmospheric scientists interested in the physics of the atmosphere and of weather prediction. It was not before the Cold War, however, until the vision of weather prediction came to fruition. Military interests and ample military funding pushed the development of computers during World War II and helped to realize numerical weather prediction after the war. In 1950, a team around mathematician John von Neumann and meteorologist Jule Gregory Charney simulated for the first time “weather by the numbers” (Harper 2008; Nebeker 1995) by solving numerically drastically simplified versions of the primitive equations on one of the first digital computers. The rise of numerical weather prediction also set the course for the simulation of climate, which began with a bold experiment by Norman Phillips in 1955. Phillips, a member of von Neumann and Charney’s team, simulated with a further simplified version of the weather model a period of 30 days. While this was no simulation of a realistic situation, it turned out to be surprisingly successful. Phillips’ model experiment reproduced patterns of the atmospheric circulation. He concluded: “the verisimilitude of the forecast flow patterns suggests quite strongly that it [the model] contains a fair element of truth” (Phillips 1956, p. 154). The experiment was path-breaking in two ways: First, it showed that computer-based simulation could serve to simulate atmospheric and climatic phenomena. Second, it proved that “[n]umerical integration of this kind … give[s] us [the] unique opportunity to study largescale meteorology as an experimental science,” as the British meteorologist Eric Eady pointed out in 1956 (quoted in Lewis 1998, p. 52).

Climate models, so-called General Circulation Models (GCM), served as a virtual laboratory to investigate the dynamics of atmospheric processes and improve its understanding. Whereas initially this research field remained small and only few groups built and experimented with climate models, it experienced a quick expansion after about 1970. Technological factors such as the quick rise of computer power and political contexts such as the disastrous Sahel drought with hundred thousands of deaths and the emerging environmental movement increased the interest in climate modeling significantly. Measurements by Charles D. Keeling had established rising carbon dioxide levels in the atmosphere by the early 1960s (Weart 2008; Edwards 2010). In the early 1970s, in the context of thriving environmental concerns, leading scientists re-interpreted the CO2 question as a potentially huge future threat to humankind and helped to put global warming on the international scientific and political agenda (Heymann and Hundebøl 2017). In 1979, the WMO World Climate Conference held in Geneva concluded in its “Final Declaration”: “It is possible that some effects on a regional and global scale may be detectable before the end of this century and become significant before the middle of the next century” (WMO 1979, p. 714). The global observation of temperature trends did not show warming, but rather stagnation or even cooling between the late 1940s and the late 1970s, but climate models suggested warming, and climate prediction was to become their main political objective.

Climate scientist James E. Hansen set the course for model development and use with a dedicated effort aimed at “taking the model and using it for climate applications,” as he expressed it (quoted in Weart 2000). In 1981 he published the first long-term model projections of global climate change in the journal Science (Hansen et al. 1981). While many climate scientists received this article with strong criticism, because Hansen based his claims on a knowingly simple model with tremendous uncertainties involved, it nevertheless pointed the future direction: the focus on long-term climate prediction and the use of climate models as political instruments (Heymann and Hundebøl 2017). At the same time, climate modelers had adopted Cold War system thinking and appreciated the systemic character of the atmosphere and climate and its interactions with the other earth systems such as the hydrosphere, cryosphere, biosphere and pedosphere. Since the 1980s, quickly expanding knowledge and computer power facilitated giant leaps forward in transforming the system idea into computer code. Reflecting the Gaia vision of an earth as a complex system of interacting entities, Francis P. Bretherton coined the term Earth System Science (Bretherton, 1985). Earth system modeling, the coupling of physical models of atmospheric processes on different scales with ocean models, generalizations of ice and soil models and, later, with chemical and biological models became the predominant paradigm over the next decades, earth system models the standard for the simulation of IPCC climate projections.

The increasing interest in a physical understanding of climate opened perspectives to the larger scales in the horizontal geographical and the vertical dimensions. First, many climatic processes, in fact, proved systemic on a global scale from the global distribution of solar irradiation to the air movements and temperature distributions caused by it. Second, the operationalization of the primitive equations even facilitated predictive power based on the laws of physics. This operationalization, however, was only feasible with the computational power of modern computers. It was based on numerical approximation, which replaced the exactitude of local data with averaged information in a large grid element. In global climate modeling, grid points were initially spaced about 500 km apart (representing an area of the size of Britain). With rising computer power, the spatial resolution could be increased to about 110 km between grid points in the last IPCC report (representing an area about eight times as large as London). Likewise, the temporal scale to be covered by numerical prediction was limited either to few days ahead in weather prediction (due to the chaotic behavior of the atmosphere) or to a long-term perspective decades and even centuries ahead.

German climatologist Hermann Flohn, aware of the increasing epistemic disjunction between geography-oriented classical climatology and physics-oriented dynamic climatology, sought to create a broader, unified discipline, which he suggested to call “modern climatology” (Heymann 2009). He attempted to realize the reconciliation of both subdisciplines in his own professional career. His vision, however, proved futile. First, the actors and their epistemic repertoires and standards, their interests, approaches, practices and paradigms proved so disjunct that mutual recognition and dialogue was increasingly untenable. Second, new generations of scientists were drawn to the power of quantitative numerical models, which offered the understanding, simulation and prediction of increasingly complex systems (Heymann 2010b). To many, modeling approaches represented an exciting front of research, whereas traditional climatology appeared a dull and reactionary backwater. Third, the politics of knowledge during the early Cold War privileged techno-scientific endeavors such as the numerical modeling of complex environmental systems, which promised scientific, environmental and geopolitical control (Hamblin 2013). The empirical bottom-up tradition of classical climatology with its respect of local diversity and detail lost out to theoretical top-down approaches and their sweeping, global ambitions.

Globalizing reductionism in climate science

The globalizing tendency in climate investigation in conjunction with physical reductionism constituted a development path of globalizing reductionism. It owed to scientific, political, cultural, and technological conditions. Climate proved an immensely complex phenomenon based on globally linked interactions. How else than with a globalizing perspective could it be properly understood? Paul Edwards, hence, described the emergence of planetary observation systems as “quasi-obligatory globalism” (Edwards 2006).

At the same time, climate is a political and cultural phenomenon (Hulme 2016). The relations to scale in classical climatology clearly had their own political motivations ranging from colonial interests in the imperial era to nationalsocialism and its obsession with autarchy in Nazi Germany. The age of imperialism with its colonial phantasies called for attention for the exploration of geographies and climates on earth and pushed a global purview of climatology (Grove 1997; Livingstone 1993, pp. 216–293). Martin Mahony argued that the “Empire was thus a convenient shortcut to a truly ‘global' science” creating “a new interest in worldwide ‘centres of action’, wherein large pressure or temperature gradients might hold the key (…) to understanding weather patterns across large expanses of the globe” (Mahony 2016, pp. 29–30). Global and local scales in climatology, however, were not necessarily in tension which each other, but interacting and in productive connection. Meteorological and climatological exploration, as Mahony puts it, was “shuttling between the local and the global, the national and the international” to expand knowledge and understanding (Mahony 2016, p. 30).

The nineteenth century was also a time, in which a rampant ideology of science spread and called for the physicalization of the atmosphere. Meteorology and climatology had a low status due to its descriptive tradition and lack of causal and quantitative understanding. In the twentieth century, Vilhelm Bjerknes’ equations and simulation experiments by John von Neumann’s team bore the promise to raise meteorology and climatology to full-grown scientific disciplines (Harper 2008; Nebeker 1995). Bjerknes and von Neumann both exemplified the close alignment of the politics and science of the atmosphere, which was characteristic for the twentieth century: The atmospheric sciences promised to serve matters of national interest such as weather information, weather and climate prediction and weather and climate control, which were deemed essential for agriculture, fisheries, air traffic, military operations, and environmental control (Friedman 1989; Aspray 1990). At the same time, they profited from ample resources and funding by state and military authorities, particularly during World War II, the Cold War and—in times of climate change and IPCC—towards the end of the century.

While the conceptual basis of physical climate science was seeded and developed since the nineteenth century, only computers after World War II facilitated and completed this shift. The phase shift did not emerge within the traditional climatological research community. It represented the emergence of a new research community dominated by theoretical meteorologists and physicists. The use of large computers, the development of increasingly complex models and the simulation and management of terabytes of data made it a big techno-science in the postwar era with significant consequences. First, the physics-based modeling approach gained predominance and effectively marginalized the empirical research tradition in climatology (Heymann 2009, 2010a). The ambitions and promises of weather and climate modeling matched well with both Cold War ideologies of big science and, after 1970, techno-scientific attempts to describe and gain control over human-caused environmental problems. Second, the meaning of the term climate changed from a geographical to a physical concept. It lost its immediate conjunction to a certain location and became a concept related to large and even global scales. Third, human affairs fell out of the equations and only mattered, if at all, as boundary condition (e.g., in form of human emissions of atmospheric pollutants). Climate models operating on grid elements of several hundred kilometers grid size proved excellent tools to investigate the dynamic behavior of the atmosphere, such as climatic changes over large spatial and temporal scales, but they set strict limitations to the investigation of processes on smaller or very small scales. The rising importance of climate change since the 1970s made global mean temperature—an artificial parameter divested of all spatial information and inaccessible to the senses—a lead parameter of climate science.

A crucial element in the culture of modern climate science was technology. Computers and computer models both helped to push and shape the globalizing agendas, as did other technologies such as satellites and satellite observation constructing a “global gaze” (Edwards 2006) and ice core drilling techniques allowing access to 800,000 years history of climatic change back into the past (Jouzel et al. 2007). Technologies fostered globalizing reductionism. It helped with constructing and proliferating large-scale knowledge about weather and climate and with creating and shaping institutions, socio-technical systems and infrastructures of big science. Furthermore, technology dressed climate science with momentum, power, epistemic authority and control. It became accessory of scientific elitism and of epistemic distinction and a doorkeeper of access to authoritative climate research (Heymann 2012; Heymann et al. 2017).

Globalizing reductionism, on the other hand, charged a high price: it brought a neglect of the small-scale and of local perspectives, largely cancelled humans out of the picture and depreciated alternative, local, and indigenous forms of climate knowledge. Since about the 1980s, attempts proliferated to factor in again the smaller scales and human dimensions—although mostly within the established modeling paradigm. These attempts comprised efforts of downscaling climate models, increasing temporal and spatial resolution and in launching regional modeling attempts to bring regional information back into the picture. The mathematics of numerical approximation under conditions of limited computer power, however, set smaller-scale approaches with climate models strict limitations. It seemed “ironic that we cannot represent the effects of the small-scale processes by making direct use of the well-known equations that govern them,” climate modeler David Randall and his co-authors remarked with some frustration (Randall et al. 2003, p. 1548). They considered the loss of the small scale as a “deadlock” and perceived the restrictions imposed on their physics as “something scandalous” and “almost shocking”, as climate modeling historian Hélène Guillemot puts it (Guillemot 2017, p. 130).

The important role of different scales, the challenge of integrating them and the rise of globalizing reductionism was by no means a feature of climatology and climate science alone but a more general phenomon in the geophysical and ecological sciences. Representations and modeling strategies focusing on large-scale patterns and abstracting from local detail emerged for example in disciplines as diverse as ecology and epidemiology (Worster 1994; Rusnock 2002). Deborah R. Coen described the tensions caused by interests in different scales for the case of seismology, which experienced “incongruities between the global visions of scientific modernizers and the local realities of communities at risk” (Coen 2013, p. 163). Attempts to make seismology a uniform, truly global science and seismological observation and description internationally comparable pushed the development of a macroseismology, which abstracted information from local context and language. It involved “the construction of incommensurability between scientific expertise and common experience,” it devalued local detail and human experience (Coen 2013, p. 267). While nineteenth-century seismology went about bridging global and local scales of inquiry, Coen traces the loss of the human scale in seismology in the twentieth century—much as in climate science. Coen, however, rejects the conclusion that the human and planetary perspectives are “incommensurable” and calls for historical research to show how local and global scales of investigation have been bridged (Coen 2016).

Many attempts to broaden the purview of climate science to the social mostly remained within the quantitative modeling paradigm. An example is the attempt to estimate the impacts and costs of climate change (e.g., Stern 2006). Adding quantitative impact and economic models to the models of the natural world exemplifies the authority and momentum of the modeling approach, which expanded globalizing reductionism to the realm of the social. Humans were brought in as abstract entities without attention or respect for the local, personal, and emotional. More recently, scholars in the humanities, particularly historians and anthropologists, demanded to pay attention to humanities perspectives in global change research in order to broaden scholarly and public discourse, consider knowledge of past culture-environment relations and produce more comprehensive and more robust knowledge about climate, environmental, and cultural change (Holm et al. 2012; Palsson et al. 2012).

The history of globalized climate research and the authority and ideologies it carries teach us the difficulties of this ambition. First, it is not only a task of bringing disjunct epistemic cultures in contact and fashioning a “middle” between knowledge from above and knowledge from below by knowledge brokers and interlocutors. Globalized climate science comes with powerful historical and ideological baggage that needs to be analyzed, deconstructed and put in broader perspective. Second, globalized climate science still claims and retains not only epistemic superiority but holds the techno-scientific and political power to maintain it. Thousands of scientists in the numerical modeling business, large-scale technological infrastructures and powerful institutions maintain momentum and protect their privileged status. Significant progress is hard to imagine unless social forces have become strong enough to enforce significant transformations of this techno-scientific culture and its epistemic status in comparison with alternative types of climate knowledge. Third, attempts to strengthen and refashion the “human dimension” are welcome and urgently needed, but well advised to avoid the trap of globalizing reductionism. The concept of the Anthropocene, which researchers in the humanities and social sciences adopted enthusiastically, operates at a very large scale and runs the risk to become another vehicle of globalizing reductionism. It remains to be seen whether, how and in what ways it can help to put the human and the local back into the picture of climate and environmental change.

Conclusion

Climate investigation during the twentieth century took a path of globalizing reductionism. At the core of it was a shift in the investigation of climate from climatology as a geographical discipline to quantitative physical climate science with climate modelling and simulation emerging as a leading practice in atmospheric knowledge production. The original holistic and descriptive research tradition in climatology with its focus on empirical data and attention to local detail was replaced by reductionist quantitative science with primary concern for dynamic processes on larger spatial scales. At the close of the twentieth century, the physical approach to climate and the development and use of climate models and simulations had come to play a hegemonic role in the construction of climate knowledge (e.g., Shackley et al. 1998; Hulme 2008). Climate science operated on large spatial and temporal scales, put priority on global knowledge and marginalized the small scales. The overarching question of global climate change demanded globally averaged and long-term temporal information about climate, in which spatial and temporal detail—that in real life mattered most to humans—played a subordinate role.

Notes

  1. 1.

    All translations by the author.

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Heymann, M. The climate change dilemma: big science, the globalizing of climate and the loss of the human scale. Reg Environ Change 19, 1549–1560 (2019). https://doi.org/10.1007/s10113-018-1373-z

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Keywords

  • Climate change
  • Climate modeling
  • Scale of knowledge
  • Human scale
  • Globalization
  • Uncertainty
  • Environmental humanities