Multi-fingerprint detection and attribution analysis of greenhouse gas, greenhouse gas-plus-aerosol and solar forced climate change |
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Authors: | G C Hegerl K Hasselmann U Cubasch J F B Mitchell E Roeckner R Voss J Waszkewitz |
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Institution: | (1) Max-Planck-Institut für Meteorologie, Hamburg, Germany, DE;(2) Deutsches Klimarechenzentrum, Hamburg, Germany, DE;(3) Hadley Centre for Climate Prediction and Research, Bracknell, UK., GB |
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Abstract: | A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single
fingerprint is optimal for the detection of climate change, further tests of the statistical consistency of the detected climate
change signal with model predictions for different candidate forcing mechanisms require the simultaneous application of several
fingerprints. Model-predicted climate change signals are derived from three anthropogenic global warming simulations for the
period 1880 to 2049 and two simulations forced by estimated changes in solar radiation from 1700 to 1992. In the first global
warming simulation, the forcing is by greenhouse gas only, while in the remaining two simulations the direct influence of
sulfate aerosols is also included. From the climate change signals of the greenhouse gas only and the average of the two greenhouse
gas-plus-aerosol simulations, two optimized fingerprint patterns are derived by weighting the model-predicted climate change
patterns towards low-noise directions. The optimized fingerprint patterns are then applied as a filter to the observed near-surface
temperature trend patterns, yielding several detection variables. The space-time structure of natural climate variability
needed to determine the optimal fingerprint pattern and the resultant signal-to-noise ratio of the detection variable is estimated
from several multi-century control simulations with different CGCMs and from instrumental data over the last 136 y. Applying
the combined greenhouse gas-plus-aerosol fingerprint in the same way as the greenhouse gas only fingerprint in a previous
work, the recent 30-y trends (1966–1995) of annual mean near surface temperature are again found to represent a significant
climate change at the 97.5% confidence level. However, using both the greenhouse gas and the combined forcing fingerprints
in a two-pattern analysis, a substantially better agreement between observations and the climate model prediction is found
for the combined forcing simulation. Anticipating that the influence of the aerosol forcing is strongest for longer term temperature
trends in summer, application of the detection and attribution test to the latest observed 50-y trend pattern of summer temperature
yielded statistical consistency with the greenhouse gas-plus-aerosol simulation with respect to both the pattern and amplitude
of the signal. In contrast, the observations are inconsistent with the greenhouse-gas only climate change signal at a 95%
confidence level for all estimates of climate variability. The observed trend 1943–1992 is furthermore inconsistent with a
hypothesized solar radiation change alone at an estimated 90% confidence level. Thus, in contrast to the single pattern analysis,
the two pattern analysis is able to discriminate between different forcing hypotheses in the observed climate change signal.
The results are subject to uncertainties associated with the forcing history, which is poorly known for the solar and aerosol
forcing, the possible omission of other important forcings, and inevitable model errors in the computation of the response
to the forcing. Further uncertainties in the estimated significance levels arise from the use of model internal variability
simulations and relatively short instrumental observations (after subtraction of an estimated greenhouse gas signal) to estimate
the natural climate variability. The resulting confidence limits accordingly vary for different estimates using different
variability data. Despite these uncertainties, however, we consider our results sufficiently robust to have some confidence
in our finding that the observed climate change is consistent with a combined greenhouse gas and aerosol forcing, but inconsistent
with greenhouse gas or solar forcing alone.
Received: 28 April 1996 / Accepted: 27 January 1997 |
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