1. CO 2 Lead/Lag Marcy Laub, Emily Malkin

2. “The Great Global Warming Swindle” CO 2 lag seen as dismantling it as a cause of global warming - deniers say climate change not anthropogenic https://www.youtube.com/watch?v=bi2QKY3z W8Q&t=0m26s

3. Initial Perturbation Milankovich Cycles: changes in Earth’s tilt and orbit around the sun cause changes in radiative forcing Their Effect: ➔ Warmer oceans release CO 2 ➔ CO 2 amplifies ★ Lag vs. warming duration Eccentricity Tilt/Obliquity Precession CO 2 Solubility vs. Temp.

4. Ice Structure Influence on Pressure and Transport Convective Zone Air mixed by surface wind that flows freely through very porous snow Diffusive Column Stagnant air mixed by movement of atoms and molecules Close-Off/LID, Gas trapped

5. Gas-Ice Age Difference Top of snowpack porous to bottom of firn, air diffuses throughout Air at bottom of firn trapped as pressure closes pores → younger air enclosed in older ice ★ Not the same as time lag

6. Measures of Synchronizing Ice and Gas Δage the difference in age between the ice and gas phases at any given depth Δdepth the depth difference between gas and ice of the same age

7. TI vs. TIII TI - Termination 1, last deglaciation, 21,000 ybp o Dust and isotope change in phase TIII - 240,000 ybp, deglaciation o Changes in dust before changes in isotope Different lead/lag conclusion for each Age (1000 ybp) δ 18 O (‰) TI TIII Deglaciation new old

8. Paper Summaries Caillon, et al. (2003): CO 2 has significant lag in TIII deglaciation, on a timescale consistent with Southern Ocean temperature-CO 2 feedbacks Parrenin, et al. (2013): CO 2 and temperature are synchronous from TI to present

9. Vostok Ice Drilling Station

10. Location of Vostok Allows for Age Model Uncertainties Due to Ice Flow Complications in measuring accumulation rates: ●Wind ●Upstream flow from west Acknowledged by Caillon but unaccounted for

11. Slower Densification at Low Accumulation Rates Antarctic ~5,000 year ice-gas age difference Greenland ~500-600 years Why? Antarctic accumulation rates are much lower at 166 mm/year vs. 2,500 mm/year Sahara: 25 mm/year, Boston: 1050 mm/year

12. Caillon uses D, deuterium o “Heavy hydrogen” isotope: 2 neutrons Fractionation of isotopes depends on temperature Well-Established Temperature Proxies Exist warm cold Isotopes in ice reflect temperature at time of deposition

13. Caillon Strives to Prove Ar as a Temp. Proxy Heavy element subject to gravitational fractionation Measurements from gas δ 40 Ar fractionation extent varies with DCH o Will show DCH-temp relationship Gas bubble trapped in ice containing Ar T proxy in gas eliminates need to determine Δage

14. D, Ar Exhibit Similar Patterns at Different Depths ●δD record from ice, well-established ●δ 40 Ar record from gas ●Same features ○2-step increase oldnew ★ δ 40 Ar hypothesized temperature proxy δDδD δ 40 Ar

15. D, Ar Relationship Offers Data Validation D measured in ice Ar measured in gas Use phasing to find Δdepth Convert Δdepth to Δage, using time resolution

16. Calculated Δage Allows Continuous Record Comparison ●FDM: Deeper firn depth for higher accumulation rates and colder temperatures ●Their results: high correlation between all 3 TIII Temp Accumulation δ 40 Ar Firn depth Primary driver of firn depth unclear newold thin thick

17. δ 40 Ar Record Creates More Accurate Firn Model ●Conclude no convective zone at TIII  Direct relationship at max DCH – DCH varies only with temp Error in total firn depth estimate DCH influenced more by temp. than accumulation From data

18. Axis Shift to Produce Best Temp-CO 2 Fit Shows Time Lag ●Shift CO 2 record back 800 yrs → R 2 = 0.88 for CO 2 and δ 40 Ar ●Plausible lag for S. Ocean feedback CO 2 lags temperature by 800 years, lag significant δ 40 A r CO 2 Note time axis difference

19. δ 40 Ar in the Context of Well-Documented Records Provides Sequence of TIII Deglaciation Events CO 2 CO 2 from 2nd source δ 40 Ar δ 18 O CH 4 ●CH 4, δ 18 O global signals ●δ 40 Ar increases before δ 18 O ○Antarctic warms ~6000 yr before N. hemisphere ●Note shallower CO 2 peak old new Northern warming lags, CO 2 leads global warming

20. Caillon Conclusions  Temperature leads CO 2 by 800±200 years CO 2 is an amplifier, and is exacerbated further by anthropogenic forcing

21. Controversial Bipolar Seesaw Hypothesis Links Greenland and Antarctic Ice Records T increase, Greenland T max, Antarctica Unconfirmed T changes in N & S hemisphere out of phase Rapid T increase in Greenland = T maximum in Antarctica Comparing T records synchronizes cores old new time

22. Estimating Timing of Antarctic Temp. Variations from Global CH 4 Signal Tie points: “signature” rapid CH 4 change Determine Δdepth between temp. proxy extrema and tie points → Only 3 Δdepth estimates, consistent with bipolar seesaw years before present δD (‰) CH4 (ppbv) EDC ice depth (m) Detectable CH 4 shift old new

23. Ice records synced by volcanic ash layers Synchronized EDC CH 4 record with EDML/TALDICE → Only 3 approximations of Δdepth for EDC Known from firn densification model At time=t Determining EDC Δdepth in Spite of Uncertainties Due to Slow Accumulation Rate

24. δ 15 N Confirmed as Reliable Δdepth Metric δ 15 N agrees with other metrics → conv. zone assumption upheld → δ 15 N varies directly with DCH δ 15 N data more continuous Firn densification model δ 15 N data, N best fit EDML, TALDICE, Seesaw Δdepth Core depth (m) Δdepth can be estimated for entire core Most N data within dashed line, 1σ

25. Assumptions Allow for Computation of a Continuous Δdepth from δ 15 N δ 15 N Record Lock-In Depth, continuous record Δdepth, continuous record no convective zone firn models CO 2 and T records on same time axis convert to time

26. Noise Reduced by Stacking Core Data Antarctic Temperature Stack (ATS) comprised of EDC, Vostok, Dome Fuji, TALDICE and EDML cores ➔ Synchronize core records ➔ Convert δD and corrected δ 18 O record to T record ➔ Average the five cores for each point in time (resampled every 20 years) Standard deviation for 220-year moving average: SD, EDC =.52°C SD, ATS =.20°C >

27. Core Records as a Six-Point Linear Function 10,000 Monte Carlo simulations give 4 tie points → probability distribution fits data around points Linear be start, tie and end points Forces linear fit and phasing within a given window

28. Temp. and CO 2 Phasing Without Ice-Gas Age Difference Pearson corr, aCO2/ATS =.993 4 points where linear slopes shift o CO 2 break leads ATS twice, o CO 2 break lags ATS twice, Lead/lag magnitudes insignificant age  Temp change,°C  Atmospheric CO2, ppm Rad. forcing of aCO2, W/m 2 CH4, ppb TI Bolling Osc. Holocene Younger Dryas old new

29. Chosen Linear Fit Influences Phasing Original breakpoint New linear fit New breakpoint ~800 years Synchronicity potentially an artifact of the data fitting Magnified temperature change data at TI

30. Underestimation of CO 2 During Abrupt Spikes and Using Linear aCO 2 Measure TI: 10 ± 160 years, CO2 leads Bolling Oscillation: -260 ± 130 years, CO2 lags o Corrected for “fast increases,” -10 ± 130 yrs Younger Dryas: 60 ± 120 years, CO2 leads Holocene: -500 ± 90 years, CO2 lags o Corrected, -130 ± 90 years ★ Corrections maintain insignificance of lead/lag

31. Parrenin Conclusions ★ Temperature and CO2 are synchronous CO2 acts as an amplifier for weak ~0.6°C global warming by rCO2 Effective δ 15 N method - adopted by outside studies

32. Independent Data Find T and CO 2 Coupled Presented by Brook (2013) Pedro uses coastal cores, existing CO2, temp proxies Same conclusions of synchronicity despite different methodology Pedro, et al. Parrenin, et al. CO2 (ppm) Age T Anomaly T Index

33. Ice Impurities Thought to Influence Fractionation TI: Same trend btw dust and N Conclusions not necessarily conflicting Vostok depth, m EDC depth, m TIII: Dust peaks before Ar