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| Titel |
Scaling in global climate records: is the nonlinear paradigm the emperor's new clothes? |
| VerfasserIn |
Kristoffer Rypdal, Martin Rypdal, Hege-Beate Fredriksen |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250125135
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| Publikation (Nr.) |
 EGU/EGU2016-4672.pdf |
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| Zusammenfassung |
| The reigning paradigm is that scaling in climate time series is a result of internal
nonlinearities in the dynamical equations and analogous to the scale-invariant cascades in
turbulence. This picture is quite reasonable for the high-dimensional spatiotemporal
variability of the atmosphere interacting with the mixed ocean layer up to decadal time scales.
However, GCMs with, and without, full ocean circulation indicate that scaling on
longer time scales in global mean temperature data depends on the heat transport
into the deep ocean mediated by this circulation. The global surface temperature
response involves several time constants, one involving the heat capacity of the
mixed layer, and the others the heat capacities of different water masses of the
ocean. A linear “N-box model" describing the heat exchange between N such
masses, is capable of producing the observed scaling characteristics. In fact even
a two-box model with two exponential relaxation times produces results almost
indistinguishable from a power-law response model, and both provide accurate descriptions
of the response of AOGCMs in the CMIP5 ensemble. The response of the global
atmospheric CO2 concentration to past and future anthropogenic emissions can also be
modeled rather accurately by a power-law linear response function on time scales up to
centuries. As an illustration a simple conceptual model for the global mean surface
temperature response to CO2 emissions is presented and analysed. It consists of linear
long-memory models for the temperature anomaly response ΔT to radiative forcing and
atmospheric CO2-concentration response ΔC to emission rate. The responses are
connected by the standard logarithmic relation between CO2 concentration and
its radiative forcing. The model depends on two sensitivity parameters, αT and
αC, and two “inertia parameters,” the memory exponents βT and βC. Based on
observation data, and constrained by results from CMIP5 models, the likely values and
range of these parameters are estimated, and projections of future warming for the
parameters in this range are computed for various idealised, but instructive, emission
scenarios. |
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