Geographic Information Systems in Climatology

Definition

A geographical information system (GIS) is, fundamentally, a map that can be queried. It is what a map becomes when computer technology enables users to make individualized choices relating to its mode of representation and the data upon which it is based. In an electronic, digital world, it becomes possible to access, represent, and analyze information in multiple, integrated ways, and geographical information systems bring these options to bear on spatial and related data. Complex relationships and processes occurring in space are thereby subject to display and investigation. GIS makes it easier to discover facts about how large-scale processes, such as weather and climate change, work and to visualize the causal roles of location (both proximity and relative distance). GIS thus serves as an interface between the basic physical sciences, such as physics, chemistry, biology, and geology, and the sciences of human social development. As Lee Chapman and John E. Thornes remark, “the assessment and monitoring of the effects of climate change is truly a multidisciplinary exercise of which GIS provides a pivotal unifying role.”

GIS is usually regarded as having six principal components. First, people make and use the system and ask the questions. Second, data are identified as relevant for answering the questions. Third, computer software programs provide for display and analysis of the data. This includes not only GIS software but also databases and programs that permit imaging, drawing, statistical manipulation, and so on. Fourth, computer hardware runs the software. Hardware capabilities affect processing speed, ease of use, and the type of output available. Fifth, procedures define how the information is processed, interpreted, and used. Finally, a network links together all these elements and their real-world applications. The Internet permits GIS applications to draw upon data warehouses of all kinds, regardless of their physical location.

Because GIS involves the use of data drawn from many different sources, obtained and organized in many different ways, issues of quality control arise. For this reason, GIS must include information about its information—so-called metadata. Metadata provide answers to the traditional journalist’s questions—who, what, where, when, why, and how—and thereby enable users to assess the relevance, reliability, and comparability of different data sets. The manner in which concepts are defined, operationalized, and measured can affect how data are recorded and what the data mean.

Significance for Climate Change

Geographical information systems play an increasing role in all fields that employ spatial data, including agriculture, ecology, forestry, health and medicine, weather forecasting, hydrology, transportation, urban planning, energy generation and policy, and climatology. By utilizing concepts such as adjacency, area, direction, coincidence, connectivity, containment, direction, length, location, and shape, the properties of geographical entities and their relationships (indeed, any data that can be mapped) can be represented in simplified models by mathematical coordinates. Geographical information systems provide ways of discovering, organizing, and presenting data about past and current climate conditions relevant to such models. These data thus comprise the basis on which competing climate models project possible future climate-change scenarios; they also provide part of the basis for assessing the accuracy of the models.

The planet as a whole can be represented as an integrated series of boxes in a stack of checkerboards, or of layers in an onion, and the data relating to each component can serve as input into mathematical algorithms representing the constraints of physical laws and the operation of natural processes. The results can then be interpreted as showing something about how these data and processes interact to produce the phenomena represented. Representations of aspects of atmosphere, land, and ocean can be combined to model meterological processes in general circulation models. Running such models repeatedly, with different assumptions about inputs and processes, results in different outcomes, and these form the basis for projections about the climate’s future. Syukuro Manabe, of the National Oceanic and Atmospheric Administration (NOAA), was a pioneer of such modeling. The Goddard Institute for Space Studies (GISS) also has been a leader in the field, and its head, James E. Hansen, has played a leading role in the debate about global warming.

As geographical information systems and the remote-sensing data they so often rely on play an ever-larger role in understanding the planet’s dynamic processes, it is important to remember the many ways in which data can be misleading. Joseph Farman’s 1985 discovery of the Antarctic can serve as an object lesson in this regard: As related by science journalist Fred Pearce,

satellites had seen the ozone hole forming and growing over Antarctica all along, even before Farman had spotted it. But the computers on the ground that were analyzing the streams of data had been programmed to throw out any wildly abnormal readings.

Critics of GIS and other modeling technology emphasize the limitations of the climate-modeling process as a basis for reliable long-term climate forecasting. Models must include representations of natural processes that may be understood only approximately, and they must incorporate simplified parameters to stand for complex interactions in large areas of atmosphere, land, and ocean. When models that were originally developed to cover discrete phenomena are integrated, further uncertainties are introduced. Skeptics sometimes even suggest that models are designed in a way that insures desired outputs through the manipulation of parameters.

Proponents of computer modeling, in contrast, view limitations as temporary, representing natural steps in scientific progress, as models are revised in the light of researchers’ improved understanding of salient factors. Such proponents often urge, however, that policymakers cannot wait patiently for the modeling process to achieve perfection, since by the time scientists can provide unassailable data, it may be too late for action. Thus, decisions, like computer models themselves, must be based on the best data and procedures available at the time.

Throughout the 2020s, GIS systems were used to measure the continuing impact of global climate change. This included use in graphical models that measure how warming climates might impact the ecology in various regions, as well as visualizing the potential impacts of wildfires and other natural disasters.

Bibliography

Chapman, Lee, and John E. Thornes. “The Use of Geographical Information Systems in Climatology and Meteorology.” Progress in Physical Geography 27, no. 3 (2003): 313-330.

"GIS Applications in Climate Change: How GIS Transforms Our Climate Response." University of Southern California, 16 Sept. 2024, gis.usc.edu/blog/hot-or-cold-how-gis-changes-our-perceptions-of-climate-change/#:~:text=How%20GIS%20is%20Used%20in,remote%20sensors%20and%20satellite%20imagery. Accessed 13 Dec. 2024.

Green, David, and Terry Bossomaier. Online GIS and Spatial Metadata. New York: Taylor & Francis, 2002.

Kasianchuk, Peter, and Marnel Taggart, eds. GIS Education Solutions from ESRI: Introduction to ArcGIS I. Redlands, Calif.: ESRI Press, 2000-2004.

Kolbert, Elizabeth. Field Notes from a Catastrophe: Man, Nature, and Climate Change. New York: Bloomsbury, 2006.

Longley, Paul A., et al. Geographic Information Systems and Science. 2d ed. Hoboken, N.J.: John Wiley and Sons, 2005.

Maslin, Mark. Global Warming: A Very Short Introduction. New York: Oxford University Press, 2004.

Monmonier, Mark. How to Lie with Maps. 2d ed. Chicago: University of Chicago Press, 1996.

Ormsby, Tim, et al. Getting to Know ArcGIS Desktop. Redlands, Calif.: ESRI Press, 2001.

Pearce, Fred. With Speed and Violence: Why Scientists Fear Tipping Points in Climate Change. Boston: Beacon Press, 2007.