Data Assimilation for the PETM 56 Million Years Ago

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Data Assimilation for the PETM 56 Million Years Ago Mingsong Li Penn State | Geosciences & ADAPT Fuqing Zhang, Lee Kump Andy Ridgwell, Brewster Malevich, Jess Tierney, Greg Hakim, Robert Tardif, Jiang Zhu, Chris Poulsen

ocean acidification, global warming, sea level rise, … ODP South Atlantic Ocean https://en.wikipedia.org/wiki/JOIDES_Resolution ocean acidification, global warming, sea level rise, … (almost) everything you ever wanted to know about the future Kennett & Stott, 1991 Nature Zachos et al., 2005 Science

Carbon release to atmosphere 10 times faster than in the past The Past is the Key to Forecasting the Future Paleocene–Eocene Thermal Maximum Kump, 2011 Carbon release to atmosphere 10 times faster than in the past (Cui et al., 2011 Nat. Geosci.)

Data – Model comparison What did we know? Data – Model comparison Dunkley Jones et al. (2013) Global mean surface temperature (SST) anomaly for the PETM is within the range of 4-5 °C

What we do The first DA study for the PETM will answer questions: How hot was it during the PETM? Where should we deploy observations for PETM studies?

Prior: cGENIE Earth system model atmosphere cGENIE model http://seao2.info Eocene 36 x 36 (10° lon. x ~5° lat.) configuration, ocean: 16 layers 75-member ensemble pCO2 ranges from 4-18 X present atmospheric level (1120 – 5040 ppm) Steady state after 10,000 years spin-up time

SST paleoclimate proxy TEX86 ☆ δ18O O Mg/Ca △ Size: proxy data numbers

PETM SST Posterior: ensemble mean and variance (only δ18O assimilated) Iteration #1 Iteration #2 Iteration #3 Iteration #24

PETM DA (δ18O only) 33.3°C very preliminary, maybe incorrect result

Challenge: Large misfit between proxy and prior(+Proxy System Map) Site IB10B Site 401 Prior+PSM Posterior Proxy (Mg/Ca) Posterior Prior+PSM Proxy (TEX86) TEX86 Mg/Ca

PETM DA Challenge: Additional large uncertainties? (Mg/Ca data only) Global mean SST (TEX86 data only) Global mean SST Diagenesis (destroying primary signal), vital effects (biological processes overriding environmental signals)

Where should we deploy observations for PETM studies?

Impact factor: Trace of Pb - Pa = pre-analysis post-analysis sum of covariance between the given site and all sites Trace of Pb - Pa = variance of state variable observation variance (Hamill and Snyder, 2002; Stuart et al., 2007; Bei et al., 2012; Xie et al., 2013)

Impact factor: Trace of Pb - Pa = Impact sum of covariance between the given site and all sites

Evaluating impact factor Hypothesis: A site with a higher impact factor has better performance to reduce the proxy-prior misfit, and vice versa Misfit between prior and proxy (before assimilation) Misfit between posterior and proxy (after assimilation) Evaluation Reduced misfit = -

Evaluating impact factor IB10b IB10a TEX86=0.928 TEX86=0.935 Fur, Denmark TEX86 data only R = 0.362 R = 0.843 Nice, but a couple of outliers?

Future work How to evaluate additional large uncertainties in proxy data? Will more δ18O and Mg/Ca data be helpful for evaluation of impact factor?