Using the climate of the past to predict the climate of the future. Danny McCarroll Swansea

Transcription

1 Using the climate of the past to predict the climate of the future Danny McCarroll Swansea

2 Millennium European climate of the last millennium EU 6 th Framework Integrated Project 41 partners January 2006 Dec 2010

3 Why were we funded? Reconstruct past climate Improve predictions of future climate change

4 Climate SensiIvity change in global mean equilibrium temperature aner a doubling of atmospheric carbon dioxide 1970s: 1.5 to 4.5 C IPCC 2007: 2.0 to 4.5 C values substanially higher than 4.5 C sill cannot be excluded

5 Likely range of mean global temperature increase by the end of the 21 st Century A1B: 1.7 C to 4.4 C A2: 2.0 C to 5.4 C Temperature increases over land are likely to be roughly twice the global average and even larger in the north.

6 Ensembles of model runs predict many possible futures: which are most likely? Note the uncertainty Is not symmetrical Change in temperature aner CO 2 doubling. Black lines: 2579 climatepredic'on.net runs. Red lines: year Hadley Centre simulaions Climateprediction.net

7 Simple one- box energy balance model to demonstrate the methodology Without palaeoclimate constraint 3 x CO2 stabilizaion scenario (similar to A1B unil 2100) With palaeoclimate constraint The overall likelihood of each model run is muliplicaion of: model- data mismatch in temp. likelihood of the choice of calibraion scaling coefficient model- data mismatch for the effecive heat capacity of ocean in the instrumental period. Millennium will use a GCM, incorporaing the geography of climate changes, and befer uncertainty esimates for the palaeoclimate reconstrucions (Distributed via climatepredic7on.net) Hiro Yamazaki, Chris HunIngford, Myles Allen, Dave Frame

8 Millennium test set We do not need to fill every grid square Different squares can contain different climate data One square can contain several different climate variables No need to average over Ime or space

9 Winter temperature based on documentary evidence for dates of first and last ship to use Stockholm harbour Calibration: R 2 =0.67 SE=1.16 DW=2.06 LinR=0.16(ns) Verification: R 2 =0.60 RE=0.56 CE=0.56 RMSE= temperatureanomalies (w.r.t ) JFMAStockholmtemperatures Reconstruction R=0.6 Verification: Lofa Leijonhufvud, Rob Wilson, Anders Moberg R=0.62 A The Holocene 2008, 18,

10 Extended back to AD 1500 Millennium special issue of Clima'c Change

11 Documentary evidence (DE) DE sources interpreted to ordinal scale indices Indices express the temperature extremity of a given month (from -3 extremely cold to +3 extremely warm) National T index series: Germany ( ) Switzerland ( ) Czech Republic ( ) Poland ( ) Hungary ( ) Low Countries ( ) CEU T index series used for crosschecking

12 Method of reconstruction Calibration Linear regression model Verification II Calibration Verification I

13 EU temperature reconstructions

14 Central Europe monthly, seasonal and annual temperatures Dobrovolný P, Moberg A, Brázdil R, Pfister C, Glaser R, Wilson R, van Engelen A, Limanówka D, Kiss A, Halíčková M, Macková J, Riemann D, Luterbacher J, Böhm R (2009) Monthly and seasonal temperature reconstrucions for Central Europe derived from documentary evidence and instrumental records since AD 1500

15 Northern tree line summer temperatures from tree rings: dominated by Volcanic forcing jja Temperature C Oort Wolf Spörer Maunder Dalton jja Temperature C Millennium northern timberline Year AD Year AD Sulphate loadings NH after Gao, and solar minima in green

16 Perturbed physics spin-up experiment. >25,000 variants of FAMOUS

17 Five solar forcing scenarios

18 Four volcanic forcing scenarios

19 The Millennium experiment 148 model variants (perturbed physics) 18 forcing combinations (Same aerosol and greenhouse gas forcing) 2664 Simulations AD800 to AD 2200 Distributed in 200-year long work units SRES A1B scenario until 2100 AD and held constant thereafter. (They are not all ready yet, and lots of gaps!)

20 20,000 to 30,000 FAMOUS model simulations have been running simultaneously on volunteer s computers

21 Web-interface of the ClimatePrediction.net system

22 Selected reconstructions 1 North Atlantic, May-Oct, AD , marine proxies 2 Northern Fennoscandia, Jun-Aug, AD , tree-ring proxies 3 Alpine region, Jun-Aug, AD , tree-ring and lake proxies 4 Pyrenees, May-Sep, AD , tree-ring proxies 5 Northern Fennoscandia, Apr-May, AD , river ice break records 6 Southeastern Sweden, Jan-Apr, AD , harbour freezing records 7 Central Europe, Dec-Feb, AD , documentary and early instrumental 8 Western Europe, Dec-Feb, AD , instrumental observations 9 Northern Italy, Dec-Feb, AD , instrumental observations We have a lot more!

23 Selected reconstructions

24 Model ranking procedure D 2 = quadratic distance value D 2 value is computed for each of the nine proxy sites D 2 value computed using unforced simulations T-value tests null hypothesis forced = unforced Local T-values summed and normalized Used 30-year non-overlapping averages (33 points) Ranks plotted using colours, red (best 10) to blue. This is a first attempt using incomplete datasuggestions welcome! Hiro Yamazaki, Anders Moberg, Alistair Hind, Rolf Sundberg

25 Preliminary results

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32 Concerns Model data still very incomplete 200-yr work units limit scope for internal variability 30-yr average may be too large for volcanic forcing Should ranking exclude the Greenhouse period? Uncertainty in proxy reconstructions not yet included Europe may be too small (internal > forced?) All suggestions warmly welcomed

33 Conclusions Method looks promising (but needs to be refined) Likely range of future temperatures is constrained Very high sensitivity models score poorly (good news) Bad news: All reasonable models under A1B predict >2 degrees C rise by 2100 for mean annual T of Europe