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mlosch |
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climate-change detection tests on prior subjective |
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assessments of the probability of an externally |
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statistical detection and attribution tests by |
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combining a number of different climate-change |
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signal-to-noise analyses because of inadequate |
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taken from recent conventional analyses of |
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climate-change detection and attribution for three |
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cases of climate-change forcing by increasing |
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greenhouse-gas concentrations, increasing |
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greenhouse-gas and aerosol concentrations, and |
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variations in solar insolation. The enhancement of |
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Bayesian analysis of a number of different |
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climate-change indices is demonstrated in a further |
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example. However, this advantage of the Bayesian |
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approach can be achieved only within the framework |
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of a subjective rather than objective analysis. The |
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conventional and Bayesian approach both exhibit |
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specific advantages and shortcomings, so that a |
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parallel application of both methods is probably the |
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most promising detection and attribution strategy.} |
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abstract = {In the conventional approach to the detection of an |
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anthropogenic or other externally forced climate |
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change signal, optimal filters (fingerprints) are |
1342 |
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used to maximize the ratio of the observed climate |
1343 |
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change signal to the natural variability noise. If |
1344 |
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detection is successful, attribution of the observed |
1345 |
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climate change to the hypothesized forcing mechanism |
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is carried out in a second step by comparing the |
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observed and predicted climate change signals. In |
1348 |
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contrast, the Bayesian approach to detection and |
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attribution makes no distinction between detection |
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and attribution. The purpose of filtering in this |
1351 |
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case is to maximize the impact of the evidence, the |
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observed climate change, on the prior probability |
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that the hypothesis of an anthropogenic origin of |
1354 |
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the observed signal is true. Whereas in the |
1355 |
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conventional approach model uncertainties have no |
1356 |
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|
direct impact on the definition of the optimal |
1357 |
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detection fingerprint, in optimal Bayesian filtering |
1358 |
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they play a central role. The number of patterns |
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retained is governed by the magnitude of the |
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predicted signal relative to the model |
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uncertainties, defined in a pattern space normalized |
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by the natural climate variability. Although this |
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results in some reduction of the original phase |
1364 |
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space, this is not the primary objective of Bayesian |
1365 |
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filtering, in contrast to the conventional approach, |
1366 |
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in which dimensional reduction is a necessary |
1367 |
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|
prerequisite for enhancing the signal-to-noise |
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ratio. The Bayesian filtering method is illustrated |
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for two anthropogenic forcing hypotheses: greenhouse |
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gases alone, and a combination of greenhouse gases |
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plus sulfate aerosols. The hypotheses are tested |
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against 31-year trends for near-surface temperature, |
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summer and winter diurnal temperature range, and |
1374 |
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precipitation. Between six and thirteen response |
1375 |
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patterns can be retained, as compared with the one |
1376 |
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|
or two response patterns normally used in the |
1377 |
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|
conventional approach. Strong evidence is found for |
1378 |
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the detection of an anthropogenic climate change in |
1379 |
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|
temperature, with some preference given to the |
1380 |
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combined forcing hypothesis. Detection of recent |
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anthropogenic trends in diurnal temperature range |
1382 |
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and precipitation is not successful, but there |
1383 |
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remains strong net evidence for anthropogenic |
1384 |
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climate change if all data are considered jointly.} |
1385 |
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} |
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title = {On the Transport, Variability and Origin of Dense |
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Zantopp}, |
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title = {Variability of Structure and Transport of the |
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{F}lorida {C}urrent in the Period Range of Days to |
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title = {Tidally Driven Mixing in a Numerical Model of the |
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@misc{sloss88, |
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author = {P. W. Sloss}, |
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title = {Data Announcement 88-{MGG}-02, Digital Relief of the |
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title = {Baroclinic Transport Variability of the {A}ntarctic |
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@Article{sloyan00:_circul_renew_modif_antar_mode_inter_water, |
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author = {Bernadette M. Sloyan and Stephen R. Rintoul}, |
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title = {Circulation, Renewal and Modification of {A}ntarctic |
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Mode and Intermediate Water}, |
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author = {Bernadette M. Sloyan and Stephen R. Rintoul}, |
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title = {Estimates of Area--averaged Diapycnal Fluxes from |
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Basin--scale Budgets}, |
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@Article{sloyan00:_south_ocean_limb_global_deep_overt_circul, |
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author = {Bernadette M. Sloyan and Stephen R. Rintoul}, |
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title = {The {S}outhern {O}cean Limb of the Global Deep |
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Overturning Circulation}, |
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@Article{sloyan01:_cir_ren_mod_AAmwiw, |
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author = {Bernadette M. Sloyan and Stephen R. Rintoul}, |
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title = {Circulation, Renewal and Modification of {A}ntarctic |
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Mode and Intermediate Water}, |
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@Article{sloyan01:_south_ocean_limb_global_deep_overt_circul, |
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author = {Bernadette M. Sloyan and Stephen R. Rintoul}, |
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title = {The {S}outhern {O}cean Limb of the Global Deep |
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Overturning Circulation}, |
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year = 2001, |
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@article{speer00, |
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