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21.9: Review

  • Page ID
    10978
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    Climate is defined as the weather averaged over long periods of time; e.g., 30 yr. Earth’s climate is controlled by both external and internal processes. External processes include the balance between incoming solar radiation and outgoing infrared (IR) radiation. Internal processes include changes to the composition or structure of the atmosphere that alter how energy is distributed within the Earth-ocean-atmosphere-cryosphere-biosphere system.

    Externally, changes in Earth’s orbit around the sun as predicted by Milankovitch can alter the amount of sunlight reaching Earth, and changes in the tilt of Earth’s axis can alter the severity of the seasons. Solar output can also vary. Changes in Earth’s average albedo (via snow cover, cloud cover, or coverage of vegetation) can modulate the amount of radiation lost from the Earth system, thereby changing the way that the Earth responds to such external forcings.

    Internally, chemicals that normally exist in the atmosphere (water vapor, carbon dioxide, etc.) absorb IR radiation, causing the air to become warmer and re-radiate a large amount of IR radiation back toward the Earth’s surface. This greenhouse effect does not have perfect efficiency, because some wavelength bands of IR radiation can escape directly to space through the so-called “atmospheric window.” Anthropogenic and natural changes to these greenhouse gases can alter the greenhouse efficiency and shift the climate equilibrium — an effect called “climate change.”

    Internally, chemicals that normally exist in the atmosphere (water vapor, carbon dioxide, etc.) absorb IR radiation, causing the air to become warmer and re-radiate a large amount of IR radiation back toward the Earth’s surface. This greenhouse effect does not have perfect efficiency, because some wavelength bands of IR radiation can escape directly to space through the so-called “atmospheric window.” Anthropogenic and natural changes to these greenhouse gases can alter the greenhouse efficiency and shift the climate equilibrium — an effect called “climate change.”

    Some processes in the atmosphere cause negative feedbacks that tend to stabilize the climate, while other positive-feedback processes tend to amplify climate variations. Many of these feedbacks apply to external, internal, natural, and anthropogenic forcings. Overall, our climate is remarkable steady.

    Short-term (few years to few decades) variations in Earth’s climate are also observed. El Niño is one example out of many such “oscillations” in the climate signal.

    Researchers have classified the current climate (Köppen). They also utilize tools including global climate models (GCMs), principal component analysis (PCA), Hovmöller diagrams, and conceptual models (e.g., daisyworld) to study climate variability.

    INFO • Hovmöller Diagram

    A Hovmöller diagram is a plot of a meteorological variable as a function of date and longitude. Usually date is along the ordinate — increasing downward. Longitude is along the abscissa. The meteorological variable is contoured with grey or color fill. The latitude or latitudinal band of these meteorological observations is fixed, and is specified in the figure legend or caption. These diagrams are useful for detecting the zonal movement of weather features over time.

    For example, suppose that on 1 January you flew an airplane around the world along the equator (0° latitude), and remotely measured the sea surface temperature (SST). After subtracting the average SST, you would be left with a temperature anomaly T’ at each point around the equator. Suppose the first graph below shows what you measured.

    Later, on 15 January, make the same flight, and plot your measurements (second graph below). Repeat the flights for many different dates.

    Instead of plotting each circumnavigation on a separate graph, we can write all the T’ numbers on the same diagram of time vs. longitude. Then analyze the result as you learned in the Map Analysis chapter, by drawing isotherms of T’. The result is a Hovmöller diagram (third diagram below). You can use any meteorological variable, not just T’.

    Fig. 21.i Red & blue show positive & negative T’ (°C) patterns at the equator that propagate eastward with time.

    Screen Shot 2020-04-14 at 4.48.23 PM.pngScreen Shot 2020-04-14 at 4.49.05 PM.png

    PERSPECTIVES • Scientific Ethics

    It is a worthy human trait to strive to be the best. But for scientists measuring their success by the papers they publish, the temptation to cheat can unfortunately drive people to be unethical.

    Such unethical issues have been discussed by C. J. Sindermann (1982: Winning the Games Scientists Play. Plenum. 290 pp) and by the Sigma Xi scientific research society (1984: Honor in Science. Sigma Xi Pubs., 41 pp):

    “• Massaging – performing extensive transformations... to make inconclusive data appear to be conclusive;

    Extrapolating – developing curves [or proposing theories] based on too few data points, or predicting future trends based on unsupported assumptions about the degree of variability measured;

    Smoothing [or trimming] – discarding data points too far removed from expected or mean values;

    Slanting [or cooking] – deliberately emphasizing and selecting certain trends in the data, ignoring or discarding others which do not fit the desired or preconceived pattern;

    Fudging [or forging] – creating data points to augment incomplete data sets or observations; and

    Manufacturing – creating entire data sets de novo, without benefit of experimentation or observation.”

    Recommendation: Don’t cheat. It can mislead colleagues and policy makers, and can ruin your career.


    This page titled 21.9: Review is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by Roland Stull via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.

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