Peer Review10.5194/cp-2023-65-ac1
Reply on RC1
Francesco Muschitiello
- 07 Nov 2023
TL;DR: The new transfer function quantifies the age difference between GICC05 and U-Th timescale during the last glacial period and significantly reduces dating uncertainty.
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Abstract: <strong class="journal-contentHeaderColor">Abstract.</strong> This study presents the first continuously measured transfer function that quantifies the age difference between the Greenland Ice-Core Chronology 2005 (GICC05) and the U-Th timescale during the last glacial period. The transfer function was estimated using an automated algorithm for Bayesian inversion that allows inferring a continuous and objective synchronization between Greenland ice-core and East Asia Summer Monsoon speleothem data. The algorithm is based on an alignment model that considers prior knowledge on the GICC05 counting error, but also samples synchronization scenarios that exceed the differential dating uncertainty of the annual-layer count in ice cores, which are currently not detectable using conventional alignments techniques. The transfer function is on average 52 % more precise than previous estimates and significantly reduces the absolute dating uncertainty of the GICC05 back to 48 kyr ago. The results reveal that GICCC05 is, on average, systematically younger than the U-Th timescale by 0.97 %. However, they also highlight that the annual-layer counting error is not strictly correlated over extended periods of time, and that within the coldest Greenland Stadials the differential dating uncertainty is likely underestimated by ~10–15 %. Importantly, the analysis implies for the first time that during the Last Glacial Maximum GICC05 overcounts ice layers by ~15 % –a bias attributable to a higher frequency of sub-annual layers due to changes in the seasonal cycle of precipitation and mode of dust deposition to the Greenland Ice Sheet. The new timescale transfer function provides important constraints on the uncertainty surrounding the stratigraphic dating of the Greenland age-scale and enables an improved chronological integration of ice cores, U-Th-dated and radiocarbon-dated paleoclimate records on a common timeline. The transfer function is available as supplements to this study.
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Figures
Figure 1. a. Instantaneous (lag 0) spatial correlation between mean decadal surface air temperature at the NGRIP site and mean decadal land surface temperatures during the last glacial period (11-60 kyr b2k) as simulated with the HadCM3B-M2.1 coupled general circulation model 720 (Armstrong et al., 2019). The simulation incorporates Dansgaard-Oeschger cycles, Heinrich Events, and shorter-term variability, with a spatial climate fingerprint derived from a Last Glacial Maximum (LGM) freshwater hosing experiment applied over the North Atlantic Ocean. The location of NGRIP, the East Asian summer monsoon (EASM) region and Hulu Cave are also shown. b. EASM domain showing the location of speleothem records compiled by Corrick et al. (2020) and used in this study. Numbering: 1. Dashibao; 2. Dongge; 3. Furong; 4. Maboroshi; 5. Sanbao; 6. Shizi; 7. Songjia1; 8. Songjia3; 9. Wulu3; 10. Wulu32; 11.Xiaobailong; 12. Yamen; 13. Yangkou. Reference to 725 the cave site is provided in Corrick et al. (2020). c. Cross-correlation between simulated NGRIP air temperature and EASM precipitation between 11 and 60 kyr ago. The EASM region is defined here as the average of 10-40˚N and 95-125˚E. The timeseries were bandpass filtered to quantify leads and lags at millennial and shorter timescales, respectively. d. Same as (c) but for the LGM using transient climate model simulations (Armstrong et al., 2019; Liu et al., 2009) and equilibrium experiments from CMIP6 (Kageyama et al., 2021). Results from HadCM3B and CCSM3 span the interval ~17.5-21kyr b2k, whereas for CMIP6 only simulations longer than 200 years were considered for 730 the cross-correlation analysis. Dashed lines reflect the 95% significance level against first order autoregressive (AR1) noise. 
Figure 4. MCMC synchronization of GICC05 to the U-Th timescale during the last glacial period and resulting timescale transfer function. a. Synchronized Greenland Ca2+ data on the U-Th timescale using the posterior median estimate of the MCMC synchronization. The synchronization was derived from stratigraphic alignment of the Greenland Ca2+ data to the East Asian summer monsoon (EASM) PC1 (see Section 2.1 for details). Shadings reflect the empirical 68 and 95% confidence intervals from the 10,000 member ensemble. Greenland 755 Stadials (GS) and timing of Heinrich Events (H) are indicated at the top. b. Comparison between the synchronized ice-core data and the Hulu Cave 18O record with its associated age uncertainty (grey shading: dark, 68%; dark 95%). All proxy records are shown in normalized 
Figure 3. Stack of NGRIP Ca2+ and Hulu Cave 18O records using a technique in which 13 individual events are centered at the midpoint of their abrupt transition, i.e. either DO warming (onset of GIs) or DO cooling (onset of GSs) (note the reverse scale). The events were 745 normalized and averaged to highlight the shared climatic signal at multidecadal and centennial timescales (>50 year low-pass filtered) and compare the duration of the abrupt DO transitions between Greenland ice cores and Hulu Cave speleothems. Shading reflects the variability across the events used for stacking. The midpoints of the abrupt transitions were identified using a Bayesian change-point analysis method (Erdman and Emerson, 2007). 
Figure 6. Inferred estimates of the relative annual-layer counting error for the GICC05 chronology based on MCMC synchronization to the U-Th timescale. a. GISP2 temperature reconstruction NGRIP annual layer thickness (Martin et al., 2023) presented with partitioning of Greenland Stadials (GS) and timing of Heinrich Events (H; grey vertical bars). Underlying dashed levels show the ±2 temperature range of stadials GS-1 to GS-13. Interstadial-stadial transitions were identified using a Bayesian change point procedure (Erdman and Emerson, 775 2007). The blue vertical bar denotes GS-4, i.e. the coldest stadial (3.3˚C colder than the average). b. NGRIP insoluble dust concentration record (Ruth et al., 2003) (note the reverse scale). c. Comparison between the maximum relative counting error of the GICC05 (grey shading) and the differential dating uncertainties inferred from the CLIM synchronization, respectively, presented with their posterior median (thick lines) and pointwise 68% credible intervals (shading). Positive (negative) values indicate an undercount (overcount) of ice layers in Greenland ice cores. d. U-Th dated climate records of the Last Glacial Maximum (LGM) in the European Alps after synchronization to the 780 GICC05 timescale by applying the transfer function presented in this study. U-Th ages of cryogenic cave carbonates (Spötl et al., 2021) with their ±2 uncertainty (white squares) indicating the timing of the maximum mountain glacier extent over the European Alps, and 18O values of precipitation from the Sieben Hengste stalagmite record (Luetscher et al., 2015) (orange). The Sieben Hengste record reveals a maximum strengthening and southerly displacement of the westerly winds during GS-3. All records are presented on the GICC05 timescale. 
Figure 2. Proxy-climate data used for the climate synchronization (CLIM) presented in this study and shown on their original timescale. a. Mineral-dust derived Ca2+ ion concentration record from NGRIP (Erhardt et al., 2019) on the GICC05 timescale (Rasmussen et al., 2006; Svensson et al., 2008). Partitioning of Greenland Interstadials (GI) and Greenland Stadial (GS) 2 are indicated. b. High-resolution Hulu Cave 735 18O record (Cheng et al., 2016; H. Cheng et al., 2021) on the revised U-Th timescale (Cheng et al., 2018; H. Cheng et al., 2021) and individual U-Th measurements with their ±2 uncertainty (grey squares). c. Stack of speleothem 18O records from the East Asian Summer Monsoon (EASM) region presented in Corrick et al. (2020) and used in this study. 18O values are expressed as anomalies from the record mean. Individual U-Th measurements associated with each record are also presented. Numbering refers to location of cave sites shown in Fig. 1b. d. First principal component (PC1) of the 14 EASM speleothem records presented in (c) from the MCPCA procedure used in this 740 study (see Section 2.1 for details). The solid line indicates the median from the 10,000 member ensemble, while shadings reflect the empirical 68 and 95% confidence intervals from the ensemble. 
Figure 5. Posterior timescale transfer function based on the MCMC synchronization of the GICC05 to the U-Th timescale. Positive values indicate that the U-Th timescale is older than GICC05. The transfer function is presented with its median (thick lines) and pointwise 95% 765 credible intervals (shading). The results are compared to the transfer function presented in Adolphi et al. (2018), which is based on a compilation of U-Th-dated 14C records, including the low-resolution and less precisely dated Hulu Cave data (Southon et al., 2012). The markers with error bars (±2) show discrete match points inferred from comparison of ice-core 10Be records and absolutely dated 14C data, 14C-dated volcanic eruptions identified in Greenland ice cores (Muscheler et al., 2020; Svensson et al., 2020), and methane match points between WAIS Divide and GISP2 ice cores (Martin et al., 2023). The dashed lines highlight the maximum counting uncertainty of GICC05. 770
References
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