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- Author or Editor: A. H. Gordon x
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Abstract
Global and hemispheric series of surface temperature anomalies are examined in an attempt to isolate any specific features of the structure of the series that might contribute to the global warming of about 0.5°C which has been observed over the past 100 years. It is found that there are no significant differences between the means of the positive and negative values of the changes in temperature from one year to the next; neither do the relative frequencies of the positive and negative values differ from the frequencies that would be expected by chance with a probability near 0.5. If the interannual changes are regarded as changes of unit magnitude and plotted in a Cartesian frame of reference with time measured along the x axis and yearly temperature differences along the y axis, the resulting path closely resembles the kind of random walk that occurs during a coin-tossing game.
We hypothesize that the global and hemispheric temperature series are the result of a Markov process. The climate system is subjected to various forms of random impulses. It is argued that the system fails to return to its former state after reacting to an impulse but tends to adjust to a new state of equilibrium as prescribed by the shock. This happens because a net positive feedback accompanies each shock and slightly alters the environmental state.
Abstract
Global and hemispheric series of surface temperature anomalies are examined in an attempt to isolate any specific features of the structure of the series that might contribute to the global warming of about 0.5°C which has been observed over the past 100 years. It is found that there are no significant differences between the means of the positive and negative values of the changes in temperature from one year to the next; neither do the relative frequencies of the positive and negative values differ from the frequencies that would be expected by chance with a probability near 0.5. If the interannual changes are regarded as changes of unit magnitude and plotted in a Cartesian frame of reference with time measured along the x axis and yearly temperature differences along the y axis, the resulting path closely resembles the kind of random walk that occurs during a coin-tossing game.
We hypothesize that the global and hemispheric temperature series are the result of a Markov process. The climate system is subjected to various forms of random impulses. It is argued that the system fails to return to its former state after reacting to an impulse but tends to adjust to a new state of equilibrium as prescribed by the shock. This happens because a net positive feedback accompanies each shock and slightly alters the environmental state.
Abstract
The authors present an analytical climate model, which has the features that (i) the atmosphere is a simple oscillator for all periods ≤1 year, (ii) the ocean stores heat, (iii) the ocean exchanges momentum with the atmosphere, and (iv) random forcing exists due to atmospheric thermodynamics and oceanic dynamics. The piecewise analytical integration of coupled linear equations for sea temperature, air-sea temperature difference, and air-sea velocity difference generates experimental climates. The exchange parameters of the algorithm, except for the exchange coefficient for heat with the deep ocean, am calibrated to the observed climate using the annual cycle, and random forcing is applied over intervals of one year. The atmospheric random forcing leads to bounded random walks, the extent of which increases as the exchange coefficient with the deep ocean decreases, and the oceanic random forcing generates a stationary response. It is found that the observed statistics of the global temperature series can be reproduced by either a relatively large heat exchange coefficient with the deep ocean and little oceanic variability or a smaller exchange coefficient with a larger oceanic variability. Plausible exchange coefficient values imply random walk lengths of at least a century-long timescale.
Abstract
The authors present an analytical climate model, which has the features that (i) the atmosphere is a simple oscillator for all periods ≤1 year, (ii) the ocean stores heat, (iii) the ocean exchanges momentum with the atmosphere, and (iv) random forcing exists due to atmospheric thermodynamics and oceanic dynamics. The piecewise analytical integration of coupled linear equations for sea temperature, air-sea temperature difference, and air-sea velocity difference generates experimental climates. The exchange parameters of the algorithm, except for the exchange coefficient for heat with the deep ocean, am calibrated to the observed climate using the annual cycle, and random forcing is applied over intervals of one year. The atmospheric random forcing leads to bounded random walks, the extent of which increases as the exchange coefficient with the deep ocean decreases, and the oceanic random forcing generates a stationary response. It is found that the observed statistics of the global temperature series can be reproduced by either a relatively large heat exchange coefficient with the deep ocean and little oceanic variability or a smaller exchange coefficient with a larger oceanic variability. Plausible exchange coefficient values imply random walk lengths of at least a century-long timescale.
