Transient (monsoonal) climate behavior in CLIMBER

1. Transient (monsoonal) climatebehavior in CLIMBER Erik Tuenter Faculty of Geosciences, Utrecht University, The Netherlands Royal Netherlands Meteorological Institute (KNMI) Contact: (tuenter@knmi.nl)

2. Dedicated to Prof. Dr. Nanne Weber (1959-2011) S.L. Weber and E. Tuenter: The impact ofvarying ice-sheets and greenhouse gases on the intensity and timing of boreal summer monsoons. Quaternary Science Reviews 30, 469-479, 2011.

3. Introduction Model/method Results: *Surface air temperature *Northern Hemisphere monsoons *Sea surface temperature and Antarctic temperature (comparison to proxies) Conclusions

4. The response of Earth’s climate to orbital forcing (i.e, precession, obliquity and eccentricity) often shows phase differences. In other words, on Milankovitch timescales climate can lead or lag the orbital forcing. This is found in proxies. Example: Cold season Atlantic SST (Sea Surface Temperature).

5. Example of leads and lags in proxy data: Cold season Atlantic Sea Surface Temperature (SST). Minimumice volume Minimumice volume Min. Prec Max. Obl. Specmap, Imbrie et al. 1989

6. The response of Earth’s climate to orbital forcing (i.e, precession, obliquity and eccentricity) often shows phase differences. In other words, on Milankovitch timescales climate can lead or lag the orbital forcing. This is found in proxies. Example: Cold season Atlantic SST (Sea Surface Temperature). Other examples: Sapropels in the Mediterranean Sea: Youngest sapropel (~8 kyr BP) lags precession by about 3 kyr (Lourens et al., 1996). Might be caused by a lag of the African monsoon at the precession band. In the Indian/Asian monsoon lags are found ranging from 3 to 8 kyr (Ziegler et al. (2010), Clemens et al. (2008, 2010), Wang et al. (2005, 2008)).

7. Most phase differences are found during the late Pleistocene (~last million yrs) that are dominated by large glacial variations in ice-sheet volumes and greenhouse gas concentrations. This complicates the interpretation of leads and lags between the orbital forcing and the climate response. Climate models can help to understand orbital induced phase differences by performing (very!) long simulations. Drawback: Computational costs are very high. Only possible with a low-resolution climate model. We performed four long (650 kyr BP until present-day) transient simulations using a climate model of intermediate complexity (CLIMBER-2.3). Goal: Unravel the separate and combined influences of orbital forcing, Northern Hemisphere ice-sheets and greenhouse gas concentrations on climate. Focus will be on the glacial-interglacial variations in temperature and monsoonal precipitation and their possible phase differences compared to obliquity and precession.

8. Introduction Model/method Results: *Surface air temperature *Northern Hemisphere monsoons *Sea surface temperature and Antarctic temperature (comparison to proxies) Conclusions

9. Model:CLIMBER-2.3 Atmosphere: Resolution 10o latitude, 51o longitude. It does not contain weather events but uses sophisticated parameterisation of transports on synoptic scales. Ocean/sea-ice: Three zonally averaged basins, 2.5o latitude, 20 unequal vertical levels. Thermodynamic sea-ice model. Vegetation: VECODE: Fractions of trees, grass and bare soil. No ice sheet model and no carbon cycle model

10. Simulations (650 kyr BP until present-day)

11. Orbital forcing Main periods: 400 and 100 kyr Main periods: 23 and 19 kyr Main period: 41 kyr

12. Orbital Parameters Maximum precession Minimum precession Maximum obliquity Minimum obliquity

13. Incoming monthly insolation (W/m2) Precession Obliquity -15 -15 -15 Pmin - Pmax Tmax - Tmin

14. Incoming annual insolation (W/m2) Precession Obliquity Pmin - Pmax Tmax - Tmin

15. GHG concentrations (ppmv) Total ice volume (106 km3) 650 600 500 400 300 200 100 0 Time (kyr BP) Prescribed GHG: Sum of CH4 (as equivalent CO2) and CO2 from Antarctic ice core Epica Dome C (Lüthi et al. (2008), Loulergue et al. (2008)). Prescribed ice-sheets: From inverse modeling with a 3D ice-sheet model (Bintanja et al. (2005)) based On Lisiecki and Raymo (2005) benthic d18O stack. Only Eurasian and Laurentide vary (Greenland and Antarctica are fixed)! No transport of fresh water between the ice-sheets and oceans!

16. Spectral analysis GHG and ice-sheets 100 kyr 100 kyr Power 41 kyr 41 kyr 23 kyr 23 kyr Frequency Frequency

17. Introduction Model/method Results: *Surface air temperature *Northern Hemisphere monsoons *Sea surface temperature and Antarctic temperature (comparison to proxies) Conclusions

19. Annual SAT 85N 55N 85S 15N

20. 100 kyr Annual SAT 85N 55N 41 kyr 23 kyr 15N 85S

21. Amplification/weakening precession (23kyr) signal in annual SAT compared to run O

22. Amplification/weakening obliquity (41kyr) signal in annual SAT compared to run O

23. Phase differences annual SAT Lags/leads annual SAT compared to precession and obliquity computed with cross-correlation between band-pass filtered annual SAT at the 23 kyr or 41 kyr band and filtered precession or obliquity. Lag ice-sheets with respect to precession: 4.3 kyr (corr. 0.84) Lag GHG with respect to precession: No significant correlation Lag ice-sheets with respect to obliquity: 7.1 kyr (corr. -0.94) Lag GHG with respect to obliquity: 6.2 kyr (corr. 0.93)

26. Introduction Model/method Results: *Surface air temperature *Northern Hemisphere monsoons *Sea surface temperature and Antarctic temperature (comparison to proxies) Conclusions

27. African, Indian, and East Asian monsoon (June-July-August)

28. African Indian JJA precipitation (mm/day) NH monsoons East Asian Green: O Blue: OI Red: OG Black: OIG

29. Indian African 23 kyr 19 kyr 100 kyr 41 kyr Spectra JJA precipitation NH monsoons East Asian Green: O Blue: OI Red: OG Black: OIG

30. Amplification/weakening orbital periods NH monsoons compared to run O

31. Monsoonal variance that is explained by each forcing factor and by the co-variances between forcing factors (in % of total variance)

32. Lead/lag (kyr) monsoons Lag GHG precession: undef; Lag ice-sheets precession: 4.3 kyr Lag GHG obliquity: 6.2 kyr; Lag ice-sheets obliquity: 7.1 kyr

33. Introduction Model/method Results: *Surface air temperature *Northern Hemisphere monsoons *Sea surface temperature and Antarctic temperature (comparison to proxies) Conclusions

34. 100 kyr Red: SST Proxy (UK37) 57N;17W (Lawrence et al., 2009) Green: Modeled SST for SON in run OIG Correlation: 0.60 41 kyr 23 kyr

35. 100 kyr Red: SST Proxy (UK37) 19N;116E (Herbert et al., 2010) Green: Modeled SST in DJF in run OIG Correlation: 0.61 41 kyr 23 kyr

36. 100 kyr Red: SST Proxy (UK37) 43S;9E (Martinez-Garcia et al., 2010) Green: Modeled Annual SST in run OIG Correlation: 0.65 41 kyr 23 kyr

37. 100 kyr Red: Temperature Proxy (Deuterium) 75S;123E (Jouzel et al., 2007) Green: Modeled SAT for DJF in run OIG Correlation: 0.55 41 kyr 23 kyr

38. Conclusions (1) Monsoons Direct precession forcing dominates NH-monsoons. Ice-sheets and GHG slightly weaken precession signal but do not influence the phase (lag is very close to zero). 2. GHG and ice-sheets strongly amplify the obliquity signal and increase the lag (from 0 to 2-3 kyr) in the African and Indian monsoon. Compared to proxies (3-8 kyr) this lag is still small. Caveats in model? Resolution problem? Or do proxies reflect a lag caused within the ocean instead of a direct monsoonal lag? 3. Influence of ice-sheets and GHG on the East Asian monsoon is very small. This is in contrast with other model simulations (Yin et al. 2009). Could be explained by lack of mid-latitudinal weather dynamics in CLIMBER.

39. Conclusions (2) Temperature 1. Ice-sheets and GHG introduce a 100 kyr signal, strongly increase the obliquity signal and (to a lesser degree) the precession signal in the annual SAT. 2.Ice-sheets and GHG increase the lag of the annual SAT to 3-4 kyr (precession) and 6-7 kyr (obliquity). 3. Compared to proxies, away from the NH ice-sheets CLIMBER strongly underestimates the 100 kyr and (to a lesser degree) the obliquity signal in both SAT and SST. It seems CLIMBER lacks a ‘climatic bridge (in the atmosphere and/or ocean) from high NH latitudes to low NH latitudes and to the Southern Hemisphere. This could improve if fresh water transport from and to the ice-sheets is included that can strongly affect the thermohaline circulation. Ongoing research. Contact: (tuenter@knmi.nl)