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Using the past to constrain the future: how the palaeorecord can improve estimates of global warming 大氣所碩一 闕珮羽 Tamsin L. Edwards.

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Presentation on theme: "Using the past to constrain the future: how the palaeorecord can improve estimates of global warming 大氣所碩一 闕珮羽 Tamsin L. Edwards."— Presentation transcript:

1 Using the past to constrain the future: how the palaeorecord can improve estimates of global warming 大氣所碩一 闕珮羽 Tamsin L. Edwards

2 Climate sensitivity Climate sensitivity is defined as the change in global mean equilibrium temperature after a doubling of atmospheric CO 2 concentration and provides a simple measure of global warming.

3 Estimate climate sensitivity ΔT : global mean temperature change (K) Q : forcing(Wm -2 ) λ: feedback parameter (Wm –2 K –1 ) Calculate λ using Q known, ΔT known Then use λ with the forcing of doubled CO 2 (Q 2×CO2 = 3.7Wm –2 ) to estimate the temperature change ΔT 2×CO2. feedback parameter is the same This makes the assumption that the feedback parameter is the same in both the known and doubled CO 2 climates.

4 Instrumental data Forcing changes between 1850 and the present day. Measurement of several forcings only began recently. The global temperature change from 1850 to the present is small (around 0.7°C) and the trend is complicated by natural variability. cause large uncertainties → cause large uncertainties

5 ‘ Probability Distribution Function ’ (pdf) ─ to obtain climate sensitivity Ensembles provide a powerful tool to explore climate sensitivity. ‘Prior’ shows only the predictions of each model and thus reflects the choice of model versions in creating the ensemble. weighted ‘Posterior’: Each ensemble member is then weighted by its success at simulating the modern climate. Weightings usually narrow the width of climate sensitivity pdf. (really?)

6 Climate sensitivity estimates ‘Climate sensitivity’ ensembles explicitly vary the climate sensitivity of the model, which is usually only possible in simpler models. ‘Perturbed physics’ ensembles vary the parameters that affect the physics in the model, within ranges that are thought to be reasonable. Many estimates have a width of about 3°C, some much larger, and many estimates with the same confidence limits are quite different. → Not resulted in narrower ranges.

7 Palaeoclimate data Different temperature change and the proportion of the change to CO 2 forcing. Including albedo forcing (Hoffert and Covey,1992) Only CO 2 forcing (Barron,1993) This is extremely high: global sensitivity is expected to be larger than tropical sensitivity, due to the large positive feedback of the polar ice sheets.

8 Constraining model estimates of climate sensitivity with palaeodata low resolution and a simplified ocean, and it has a broader, more scattered relationship strong linear correlation between ΔT LGM regional and ΔT 2×CO2 λ LGM and λ 2×CO2 are probably not constant.

9 Combining instrumental and palaeorecord constraints Palaeoclimate estimates of climate sensitivity are useful because they examine large climate changes but suffer from increased uncertainties in the climate and forcing estimates, while modern climate estimates have the reverse characteristics.

10 Discussion Coupled ocean atmosphere models may simulate very different spatial patterns of climatic variables such as SST. It is highly plausible that estimates of climate sensitivity will be improved by taking the patterns of climate change into account.

11 Summary 1. Comparing model simulations to spatially located data rather than regional averages. 2. Comparing model simulations of climate sensors directly with palaeodata, rather than climate reconstructions. 3. Extending the current range of palaeoclimate model ensembles.


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