Climate model results from the VR-LANDCLIM project

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Carl Krog
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1 Climate model results from the VR-LANDCLIM project Presentation given at the NordForsk LANDCLIM workshop at SMHI, Norrköping, 24 February 2011 Erik Kjellström, Gustav Strandberg and Ulla Kokfelt

2 Outline Climate modelling in the Swedish LANDCLIM project Climate models and data sets Forcing conditions Results 6 ky BP versus LIA Proxy-data comparison Some limitations/problems Summary

3 Climate modelling in the Swedish LANDCLIM project To simulate climate and analyse feedback effects of vegetation change and human-induced land cover change at 6000 and 200 BP using RCA3

4 Climate models and data sets RCA3 simulations forced by 1) ERA40 (reanalysis data) ) ECHO-G (AOGCM) time slices representative of 6 kbp from an 8000-year integration. These corresponds to and BP) and the last Millenium ( ) Proxy data 1) Grudd tree-ring data representative of AMJJA T2m in northern Sweden (Torne Träsk) 2) Meier et alproxy data for wine growth season representative of AMJJA T2m in the Swiss Plateau

5 Forcing conditions in ECHO-G Astronomical parameters e.g. Berger et al Solar constant Solanki et al Crowley, 2000 GHGs Etheridge et al Flückiger et al. 2002

Forcing condition in RCA3 Orbital parameters are set to present-day values GHGs are changing as in ECHO-G No volcanoes Present-day vegetation Test: decreasing insolation by 6% (corresponds to c 30

6 Forcing condition in RCA3 Orbital parameters are set to present-day values GHGs are changing as in ECHO-G No volcanoes Present-day vegetation Test: decreasing insolation by 6% (corresponds to c 30 W/m2 in summer) Kjellström, E., Brandefelt, J., Näslund, J.O., Smith, B., Strandberg, G. and Wohlfarth, B, 2009: Climate conditions in Sweden in a 100,000 year time perspective. Svensk Kärnbränslehantering AB, report TR-09-04, Swedish Nuclear Fuel and Waste Management, SE Stockholm, Sweden, 139 pp.

7 Horizontal resolution in the two models ECHO-G (T30 200km longitude by 400 km in latitude) RCA3 (50 x 50 km)

8 Simulating the Holocene: the ECHO-G Oetzi simulation Downscaling 100-year periods Baltic area

9 Mid-Holocence vs LIA in Sweden 2m-temperature LIA 6 ky BP Large variability, esp. in DJF

10 Mid-Holocence vs LIA in Sweden 2m-temperature LIA 6 ky BP Mid-Holocene warmer on average, esp. in DJF

11 Mid-Holocence vs LIA 2m-temperature 6 ky BP LIA 6 ky BP - LIA JJA DJF ANN

12 What is proxy-data telling us about 6 ka? Warmer in summer NW NE NW CW SW NE CE SE CW CE SW SE Davis et al. QSR, 2003

13 Mid-Holocence vs LIA in Sweden Precipitation LIA 6 ky BP Mid-Holocene wetter in winter and drier in summer

14 Mid-Holocence vs LIA Precipitation 6 ky BP LIA 6 ky BP - LIA JJA ANN Wetter DJF Drier

15 Simulated temperature in Sweden during the last millenium

16 Long-term variability as inferred from proxies and from RCA3 Larger interannual variability in RCA3 than in the proxies for Torne Träsk. Similar in both data sets for the Swiss Plateau Differences in 20C trends at the two sites

Variability during the Little Ice Age as inferred from

at decadal time-scales between the two sites in the

47 for 30-year filtered data) No such anticorrelation

17 Variability during the Little Ice Age as inferred from proxies and from RCA3 Some degree of anti-correlation at decadal time-scales between the two sites in the proxy-based data (r=-0.47 for 30-year filtered data) No such anticorrelation in the model The degree of correlation for individual years is very small between the two sites

18 Are the proxies reliable in the recent past climate? Interannual variabiliy in proxy-based data and reanalysisdriven data are highly correlated (r=0.74) and the varaibility is of similar size. ECHO-Gdriven simulation is not well correlated to proxy-data.

19 Are the proxies reliable in the recent past climate? Interannual variabiliy in proxy-based data and reanalysisdriven data are highly correlated (r=0.62) and the varaibility is of similar size. ECHO-Gdriven simulation is not well correlated to proxy-data.

20 Summary RCA3 simulations with present-day land-cover for 6 ky BP and LIA (or rather the last Millenium) have been performed The simulated 6k yr BP climate was warmer than the LIA climate in Sweden (particularly in winter) The simulated 6k yr BP climate was drier than the LIA climate in Sweden in summer Preliminary comparisons to proxy-data shows that the interannual variability in AMJJA-temperature proxies is highly correlated to RCA3-ERA40 indicating that the proxies are reliable Long-term variability in the LIA show some degree of anticorrelation between AMJJA temperatures in N. Sweden and the Swiss Plateau. This is not seen in the model simulation

21 Outlook What should we do next? Extend the analysis of the data for other parts of Europe Identify and use more different proxy data sets Use observational data for the last centuries, in particular CRU for the recent past decades (as this is the reference data set used with LPJ-GUESS) Perform new simulations with other land-cover data From LPJ-GUESS From Reconstructions

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