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Palaeo-Constraints on Future Climate Change Mat Collins, School of Engineering, Mathematics and Physical Sciences, University of Exeter Tamsin Edwards.

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Presentation on theme: "Palaeo-Constraints on Future Climate Change Mat Collins, School of Engineering, Mathematics and Physical Sciences, University of Exeter Tamsin Edwards."— Presentation transcript:

1 Palaeo-Constraints on Future Climate Change Mat Collins, School of Engineering, Mathematics and Physical Sciences, University of Exeter Tamsin Edwards (Bristol), Tom Russon (Edinburgh), James Pope (Leeds) + many others #RMetSMeet

2 Current Status of Global Projections Reto Knutti and Jan Sedláček Nature Climate Change, 2012

3 Climate Models and Modellers A significant fraction of climate science is in modelling, understanding, prediction and projection of future climate change “What can studying palaoclimates do for us?” Palaeoclimate reconstructions have been influential in showing that the climate could have been much different And have motivated modellers to reconfigure their models and run simulations of palaeoclimate But can they help improve models and reduce uncertainties in projections in a quantitative way?

4 Example: Last Glacial Maximum QUMP/PalaeoQUMP Simulations

5 Example: Last Glacial Maximum QUMP/PalaeoQUMP Simulations

6 Example: Last Glacial Maximum QUMP/PalaeoQUMP Simulations

7 Example: Last Glacial Maximum QUMP/PalaeoQUMP Simulations CS=3.7K

8 Example: Last Glacial Maximum QUMP/PalaeoQUMP Simulations

9 Example: Last Glacial Maximum QUMP/PalaeoQUMP Simulations

10 Example: Last Glacial Maximum 5-95%: 2.3K-5.0K QUMP/PalaeoQUMP Simulations 5-95% range K Sexton et al constrained by present-day means and trends

11 Example: Last Glacial Maximum 5-95%: 1.5K-5.8K QUMP/PalaeoQUMP Simulations

12 Example: Last Glacial Maximum 5-95%: - 0.4K-7.7K QUMP/PalaeoQUMP Simulations See also Schmidt et al Clim. Past Discuss.

13 Quantitative use of Palaeoclimate Data in Constraining Projections Potentially large ‘signal’, perhaps correlated with things we might want to project Also potentially large ‘noise’ arising from uncertainties in palaeo-reconstructions and uncertainties in forcings/boundary conditions Three examples Natural variations in the El Niño Southern Oscillation Pliocene Joint constraints from Mid-Holocene and Last Glacial Maximum

14 © Crown copyright Met Office El Niño Conditions (SST Anomalies) thermocline upwelling

15 El Niño Southern Oscillation (ENSO) Variability during the Last Millennium Russon et al. submitted Palmyra Atoll Western Cold Tongue NINO3

16 El Niño Southern Oscillation (ENSO) Variability during the Last Millennium Russon et al. submitted

17 Mid Pliocene Warm Period ( million years BP) Characterised by high (natural) concentrations of CO 2 (405 ppmv) Continental configuration similar to present day Palaeo reconstructions available from ocean sediments and plant fossils Simulations with perturbed parameter versions of HadCM3 using PRISM2 boundary conditions (reduced Rockies, Greenland and Antarctica, vegetation changes) James Pope

18 Temperature difference from STD B H K N D I L F J M PQ James Pope

19 Data-Model Comparison: Temperature Ensemble Member BStandardEnsemble Member P James Pope

20 Data-Model Comparison: Biomes B J P James Pope

21 CONSTRAINTS FROM MID-HOLOCENE AND LGM

22 STATISTICAL MODEL We want to make as few assumptions and judgements as possible We don’t feel confident weighting simulators by their relative success so we use the ensemble mean don’t include multiple versions of same simulator and check for outliers We work with the large-scale patterns of change Rougier, Goldstein and House (in review.): Second-order exchangeability analysis for multi-model ensembles. Journal of the American Statistical Association.

23 UPDATE CLIMATE SENSITIVITY still watching this space Edwards et al. in prep

24 Summary and Conclusions Palaeo-data can be used in a quantitative way in climate science The main issues are those of signal-to-noise and having the right simulations, observations and techniques Three examples Reconstructions of ENSO show that the period of modern-day observations is quite anomalous in comparison with the previous 1000 years Higher-sensitivity Pliocene simulations are more consistent with observations than lower sensitivity models Statistical frameworks are required to synthesise models and data (just like they are for modern-day observations and simulations) #RMetSMeet


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