Hans von Storch Geesthacht, Hamburg, and 青岛 Physical climate science – knowledge construction, limitations, and societal conditioning Hans von Storch Geesthacht, Hamburg, and 青岛 Joint workshop/seminar “How disciplines think and communicate“ for PhD students from social and natural sciences to explore the differences in scientific cultures USI@CLISAP, Hamburg, 22-23 June 2017

Physical Climate science Climate: Statistics of weather, the atmospheric effect on humans (Humboldt), and the physical etc. system which generates the weather. Main „tools“ of constructing knowlegde about dynamics of climate - observational evidence - models - statistical analysis A number of particularities, when compared to more traditional physical sciences - no real experiments possible - only one system - hardly any independent data, which has not yet be scrutinized by scientists and considered in the process of hypothesis formation - infinitely many degrees of freedom - societal relevance and competition with social constructions of climate as exploratory narratives.

Climate: statistics of weather Joint distributions of quantitative state variables associated with atmospheric , oceanic etc. weather (say, temperature, humidity, salinity, wind and currents, cloudiness, pressure , heat fluxes, wind stress, vertical stability, significant wave height …) Statistical parameters of such distributions such as means, variances, percentiles, extreme values, spatial and temporal co-variances, spectra, empirical orthogonal functions … Mean monthly patterns of sea level air pressure during 1979 to 2001 for January (top), July (bottom). (BACC, 2008)

Climate: atmospheric environment of humans Alexander von Humboldt, 1845: Cosmos, A Sketch of a Physical Description of the Universe “The term climate, taken in its most general sense, indicates all the changes in the atmosphere, which sensibly affect our organs, as temperature, humidity, variations in the barometrical pressure, the calm state of the air or the action of varying winds, the amount of electric tension, the purity of the atmosphere or its admixture with more or less noxious gaseous exhalations, and, finally, the degree of ordinary transparency and clearness of the sky, which is not only important with respect to the increased radiation from the earth, the organic development of plants, and the ripening of fruits, but also with reference to its influence on the feelings and mental conditions of men”.

Examples of scientific knowledge claims: Energy balance model Knowledge claim: This EBM mechanism (part of solar radiations reache surface and troposphere, which re-emit long-wave radiations to space. Some of re-emitted log-wave radiation is caught in the troposphere and partially “sent“ back, causing an increase in temperature, which causes more intense outward long wave radiation) describes to first order approximation the global energy budget and determines the temperature on Earth. Energy Balance Model (EBM) is an exploratory maximum simplicity model

E = b E + a A with b = albedo a = transmissivity E = short wave solar radiation A = long wave thermal radiation = sT4 without atmosphere a=1, b= 0 : Teq = - 4°C with present atmosphere a=0.64, b= 0.30 : Teq = +15°C

Examples of scientific knowledge claims: Inhomogeneity of data Annual mean wind speeds at some observation stations along the German North Sea coast. Intermittently abrupt significant jumps. Is this real change, or is it an artifact? J. Lindenberg, 2010

Examples of scientific knowledge claims: Inhomogeneity of data Causes of inhomogenities: Changes in Instruments Sampling frequencies Measuring units Environments (e.g. trees, buildings) Location Station relocations (Dotted lines) 1.25 m/s J. Lindenberg, 2010

Representativity of near surface wind speed measurements J. Lindenberg, 2010

Tools: observed evidence The issue of inhomogeneity The issue of independent obs Direct observations: in-situ and remote Indirect observations (proxies)

Tools: models Different types of models in different scientific disciplines Added value generation – Hesse‘s concept of neutral analogs Max complexity and min complexity models in climate sciences. - max complexity allow for experimentation, - in complexity constitute theory and understanding (e.g., EBM)

Hesse’s concept of models Reality and a model have attributes, some of which are consistent and others are contradicting. Other attributes are unknown whether reality and model share them. The consistent attributes are positive analogs. The contradicting attributes are negative analogs. Validating the model means to determine the positive and negative analogs. The “unknown” attributes are neutral analogs. Applying the model means to assume that specific neutral analogs are actually positive ones. The constructive part of a model is in its neutral analogs. Hesse, M.B., 1970: Models and analogies in science. University of Notre Dame Press, Notre Dame 184 pp.

Dynamical processes in a global atmospheric general circulation model

The issue of designing models is related to the expected added value. There is hardly a model „of something“ but mostly a model „for studying / simulating something“. Thus, models are conditioned upon the purpose of the model.

Models for reduction of complex systems identification of significant, small subsystems and key processes (cf. Hasselmann’s concepts of PIPs and POPs (1988)) often derived through scale analysis often derived semi–empirically constitutes “understanding”, i.e. theory construction of hypotheses characteristics: simplicity idealisation conceptualisation fundamental science approach

Models as surrogate reality dynamical, process-based models, experimentation tool (test of hypotheses) sensitivity analysis; including scenarios dynamically consistent interpretation and extrapolation of observations in space and time (“data assimilation”; “analysis”) forecast of detailed development (e.g. weather forecast) characteristics: complexity quasi-realistic mathematical/mechanistic engineering approach

Tools: statistical analysis Exploratory analysis Fitting reduced systems Data analysis Consistency analysis (detection and attribution)

Climate Sciences … … comprise much more issues than the geophysical issues of fluid dynamics and thermodynamics forcing. Impacts of climate variability and change are in the focus of academic interest, which is driven not only by scientific understanding but also by media constructions and value-based assumptions. “Climate” has very much to do with what is culturally believed and understood - both in the public and among scientific actors. “Climate” must therefore become a field of active social- and cultural research on the functioning of science-society interactions and scientific practice. Climate Science is much more than Physics.

Societal expectations When scientists speak to the public, then scientific statements are expected, which are associated with an authority based on “objectivity”. Society presumes that something like Merton‘s norms (CUDOS) are employed. This is so only to a limited extent (Bray-surveys) Climate Science is in a post-normal phase (following the concept of Funtovicz and Ravetz) Which role do climate scientists see themselves in?

Statements are scientific … when they have been derived by employing a scientific method - have „survived“ falsification, - have out-competed alternative explanations - can be reproduced by independent researchers when it is made clear that the statements do not represent “truth” but explanations, which for the time being are consistent with observations and theories considered valid, and better than other alternative explanations. At a later time, a re-consideration may be needed if new data and theories lead to contradictions or make better fitting explanations possible. But not when formulated by scientifically educated people, who do not employ the scientific method (for instance, do no consider alternative explanations, or opt for an explanation because of consistency with a specific school of research).

Robert K. Merton‘s CUDOS (1942) Communalism: the common ownership of scientific discoveries, according to which scientists give up intellectual property rights in exchange for recognition and esteem. Universalism: according to which claims to truth are evaluated in terms of universal or impersonal criteria, and not on the basis of race, class, gender, religion, or nationality. Disinterestedness: scientists, when presenting their work publicly, should do so without any prejudice or personal values and do so in an impersonal manner. Organized skepticism: all ideas must be tested and are subject to rigorous, structured community (peer review) scrutiny. Using the results of an the 2013 on-line survey of climate scientists concerning the norms of science, the climate scientists’ subscription to these norms are explored in this paper: Bray, D., and H. von Storch, 2015: The Normative Orientations of Climate Scientists. Science and Engineering Ethics, DOI 10.1007/s11948-014-9605-1

Communality Versus Solitariness Communality implies that research results should be the property of the entire scientific community. Scientific findings constitute a common heritage in which the equity of the individual producer is severely limited.’ Solitariness, the counter-norm of communality, implies that findings should be kept secret at least until publication.

Disinterestedness Versus Interestedness Disinterestedness implies that scientists should have no emotional or financial attachment to their work, be personally detached from truth claims, accept conclusions shaped only by evidence, and scientists should not campaign for a particular point of view or outcome. Disinterestedness also reflects the quality of perusing personal academic interests rather than the interests of funding agencies, policy priorities or institutional strategies. Interestedness means that the scientist has personal interests at stake in the reception of his or her results and work.

The data suggests that while Merton’s CUDOs remain the overall guiding moral principles, they are not fully endorsed or present in the conduct of climate scientists: there is a tendency to withhold results until publication, there is the intention of maintaining property rights, and the tendency to assign the significance of authored work according to the status of the author rather than content of the paper. Additionally, there is external influence defining research.

Postnormal science Jerry Ravetz, Silvio Funtovicz, 1986 and earlier facts uncertain: e.g. sensitivity of global mean temperature to doubling of CO2 concentration values in dispute, e.g., do we cement the world according to our present preferences or do we accept a generationally dynamical development? stakes high, e.g., costs for re-organizing global energy market and future damages decisions urgent, e.g., to be efficient, re-organization of e.g., traffic must be begun now. Jerry Ravetz, Silvio Funtovicz, 1986 and earlier State of science, when facts uncertain, values in dispute, stakes high and decisions urgent. In this state, science is not only done for reasons for curiosity but is asked for as support for preconceived value-based agendas. Climate Science is in a post-normal phase (Bray and von Storch, 1999)

Characteristic for postnormal conditions is Science is „de-scientized“, and „politicized“. Policy is „de-politicized“, and „scientized“. Policy decisions are framed as being “without alternative” – scientific knowledge leads to unique „solutions“ which need to be implemented without further democratic influence on the substance. Some scientists act as policy activists, while exploiting their public authority as scientists. Emergence of different knowledge claims, among them “alternative facts”. A post-normal situation is not “bad”, but needs recognition as such: - limitation of scientific expertise to the methodically sound core (re-scientizing), and - re-establishment of openly value-based democratic decision process (re-politicizing).

Two different construction of „climate change“ – scientific and cultural – which is more powerful? Cultural: „Klimakatastrophe“ Scientific: man-made change is real, can be mitigated to some extent but not completely avoided Lund and Stockholm Storms 31

Knowledge market The science-policy/public interaction is not an issue of „knowledge speaks to power“. The problem is not that the public is stupid or uneducated. The problem is that the scientific knowledge is confronted on the „explanation marked“ with other forms of knowledge (pre-scientific, outdated; traditional, morphed by different interests). Scientific knowledge does not necessarily “win” this competition. The social process „science“ is influenced by these other knowledge forms. Science can not be objective but should nevertheless strive to be so. 32

Climate scientists … transgress into policy-prescribing regularly so, uniformly (same direction) so. Trivialize social dynamics, and try to model the world, including the social sphere, as if its dynamics would be governed by a set of deterministic (or stochastic) equations. Typical pattern of a science in postnormal conditions (high inherent uncertainty; high stake, urgent decisions, values in dispute).

Physical scientists transgress …

Task of physical climate science is to offer explanation for a complex world, its dynamics, links and dependencies. not to derive what needs to be done, but what can be done. establish measures to establish quality of science by insisting on scientific method (cf. Merton‘s CUDOS). The capital of science is not the utility of the scientific findings but the methodology used to obtain such findings.

I wish you a good summer!