Climate models come in various levels of simplicity—or complexity. Therefore, Isaac M. Held of the Geophysical Fluid Dynamics Laboratory in Princeton proposes to compare and rank models by placing them into a hierarchical system [1].Someday we may be able to say, “Climate modeling—there's an app for that.”Brian Hayes, 2014.
Brian Hayes illustrates that climate models not only differ in complexity by what geophysical details they capture via model design, but that—from a user point of view—they also differ in code availability & readability, interface design, interactivity options, patchwork structure and applied programming language [2]. Certain implementations are still based on FORTRAN, a computer language from the punched-card era. Although mathematically powerful, this is not the first language you are thinking of when building an app for smart devices.
Encouragingly and convincingly, Hayes argues for the importance of simple climate models as precursors or complements to those with higher complexity: “primitive” models are able to capture and highlight unique patterns and behavior, such as a self-reinforcing effect. For example, a model with latitudinally striped Earth zones, which can respond to adjustments in the solar constant, the albedo of land and ice, and a greenhouse-effect parameter, succeeds in capturing a feedback loop in which cooling promotes ice cover, followed by further cooling of Earth's average temperature [bit-player.org/extras/climate/ebm.html].
Certainly, climate models exhibit uncertainties with respect to prediction of future climates. Some models, however, successfully decode and reproduce aspects of the past climate evolution. If models of manageable complexity are able to show us what triggers sudden climate shifts, we may be interested to have them at our fingertips—as apps for educational or entertaining purpose. Virtually experimenting with Earth climate is okay. Any other climate experiments will have critical consequences.
Keywords: computational models, computer simulation, evolution of Earth's climate, climate change, understanding models, feedback mechanism.
References and more to explore
[1] Isaac M. Held: The Gap between Simulation and Understanding in Climate Modeling. American Meteorological Society November 2005, pp. 1609-1614. Online: www.gfdl.noaa.gov/bibliography/related_files/ih0501.pdf.
[2] Brian Hayes: Clarity in Climate Modeling. American Scientist November-December 2014, 102 (6), pp. 422-425.
Online: www.americanscientist.org/issues/pub/clarity-in-climate-modeling.
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