Public perceptions of global warming. The American public is dramatically divided over the question of global warming. Many accept the findings that have been developed by our scientists as being accurate, and being based on sound scientific principles. Others oppose the notion that global warming, due to human activity and originating primarily in the burning of fossil fuels, is “real”, i.e. that the planet is actually undergoing an abrupt change in its climate due to greenhouse gas accumulation.
A simplified classification of scientific investigations. Climate scientists, as members of the broad community of physical and biological scientists, undertake their studies according to well-established principles of scientific investigation. Some of these principles are described here. This characterization is necessarily simplified here for the benefit of the general public.
Science is undertaken as an objective, unbiased inquiry. First, all scientific investigation is undertaken as an open inquiry. What this means is that a scientist engages in an investigation with an unbiased mind, avoiding any prior expression of what the result of the investigation should reveal. Valid science is not conducted by adopting a conclusion at the outset and seeking out those particular findings or results that bear out the preordained conclusion stated at the outset, or by designing a study in such a way as to provide those results.
Hypothesis-driven experimentation. In the simplified view presented here, scientific investigations in general can be classified in one of two distinct ways. In the first, a scientist will initially formulate a hypothesis, and conduct experiments to confirm or deny the accuracy of predictions based on the hypothesis. Hypotheses usually build on experimental results already in hand, and are constructed around particular unproven statements or assumptions about the experimental system being studied, using experimental variables subject to the control of the experimentalist. Experiments are then devised that change one or another of the variables to characterize the effect of the variation on the outcome of the study.
Hypothesis-driven experimentation is readily devised to include a second, reference, condition of the system, which is intended to characterize the system in the absence of the variation imposed in the first experiment. This reference is usually called a “control” condition, or the experimental manipulation involving the reference is called the “control” experiment, or just simply the “control”. Then two parallel experiments are conducted in which the variable is changed in the first experiment but is held constant in the control system. The results obtained in the first, varied, system are compared with those of the control system, and an objectively valid conclusion is drawn based on the finding of a difference, and/or on the amount of the difference, between the experimental system and its control. At this point, the investigator will conclude that the hypothesis is correct if the results bear out the predictions made according to the hypothesis, or else will conclude that the hypothesis was incorrectly drawn if the results contradict the prediction of the hypothesis.
|Hypothesis-driven experiment, with a control for the variable C.|
|Descriptive experiment showing the time dependence of the value of a variable.|
The time dependence of properties measured by climate scientists. Since climate science is a descriptive process, and control systems are not available, climate scientists draw conclusions from the results of the data collected based on the time development of those data. Thus, if there be a control experiment in climate science, it is the state of the planetary variables, such as temperature, atmospheric concentrations of CO2, and so on, that existed at an earlier time, and the trends for those variables as time advances up to the present. Here again, it is important to emphasize that all such measurements are conducted in an unbiased way, i.e., that the data collection is a naïve process that is not influenced by preconceived ideas about what those data should be.
Data-driven models are used to predict future trends. The contentious aspect of global warming and climate science, to the extent that it may indeed be contentious, is developing predictions of the future behavior of the climate in response to the burning of fossil fuels, and the consequent accumulation of atmospheric greenhouse gases. The models used in these predictions are extremely complex. They are formulated in advanced mathematical terms that require massive computational power to implement them, and to arrive at predictive results. The models use existing experimental data as a basis, and embody various ways of characterizing future climate changes that assume that certain climate processes will prevail over the predicted time frame. Climate scientists recognize that the details of these predictions may differ based on the assumptions made, and that there may be a range of probable outcomes from one model or another. What is certain, however, is the overall conclusion that continued accumulation of greenhouse gases in the atmosphere will have detrimental effects on the global climate as the decades pass. Importantly, sound principles employing the scientific method have been used to characterize our planet’s climate to date, and the best scientific models are being implemented to try to understand the future trends of our climate.