A data–model approach to interpreting speleothem oxygen isotope records from monsoon regions

Abstract

Abstract. Reconstruction of past changes in monsoon climate from speleothem oxygen isotope (δ18O) records is complex because δ18O signals can be influenced by multiple factors including changes in precipitation, precipitation recycling over land, temperature at the moisture source, and changes in the moisture source region and transport pathway. Here, we analyse >150 speleothem records of the Speleothem Isotopes Synthesis and AnaLysis (SISAL) database to produce composite regional trends in δ18O in monsoon regions; compositing minimises the influence of site-specific karst and cave processes that can influence individual site records. We compare speleothem δ18O observations with isotope-enabled climate model simulations to investigate the specific climatic factors causing these regional trends. We focus on differences in δ18O signals between the mid-Holocene, the peak of the Last Interglacial (Marine Isotope Stage 5e) and the Last Glacial Maximum as well as on δ18O evolution through the Holocene. Differences in speleothem δ18O between the mid-Holocene and the Last Interglacial in the East Asian and Indian monsoons are small, despite the larger summer insolation values during the Last Interglacial. Last Glacial Maximum δ18O values are significantly less negative than interglacial values. Comparison with simulated glacial–interglacial δ18O shows that changes are principally driven by global shifts in temperature and regional precipitation. Holocene speleothem δ18O records show distinct and coherent regional trends. Trends are similar to summer insolation in India, China and southwestern South America, but they are different in the Indonesian–Australian region. Redundancy analysis shows that 37 % of Holocene variability can be accounted for by latitude and longitude, supporting the differentiation of records into individual monsoon regions. Regression analysis of simulated precipitation δ18O and climate variables show significant relationships between global Holocene monsoon δ18O trends and changes in precipitation, atmospheric circulation and (to a lesser extent) source area temperature, whereas precipitation recycling is non-significant. However, there are differences in regional-scale mechanisms: there are clear relationships between changes in precipitation and δ18O for India, southwestern South America and the Indonesian–Australian regions but not for the East Asian monsoon. Changes in atmospheric circulation contribute to δ18O trends in the East Asian, Indian and Indonesian–Australian monsoons, and a weak source area temperature effect is observed over southern and central America and Asia. Precipitation recycling is influential in southwestern South America and southern Africa. Overall, our analyses show that it is possible to differentiate the impacts of specific climatic mechanisms influencing precipitation δ18O and use this analysis to interpret changes in speleothem δ18O.

Precipitation Oxygen Isotope Changes Over East Asia Driven by Sea Surface Conditions During the Last Glacial Maximum

“…Our study shows more depleted δ 18 O p in both annual and summer over East Asia during the LGM relative to the PI, well consistent with previous paleoclimate reconstruction and modeling (Eagle et al, 2013). However, these results contrast with recent geological evidence that indicated more enriched δ 18 O p over East Asia during the LGM (Parker et al, 2021), which appears to be supported by previous modeling studies that suggested an enrichment of δ 18 O p in response to precipitation deficit over East Asia due to a weakened EASM during the LGM (Hoffmann & Heimann, 1997;Jasechko et al, 2015). Nevertheless, this "amount effect" is challenged by increasing evidence verifying that changes in δ 18 O p over East Asia largely reflect changes in water vapor source and pathway instead of local precipitation amount (Huang et al, 2018;Pausata et al, 2011).…”

“…Particularly in the Indian Peninsula and Indochina Peninsula, both regions showed dramatic depletion of δ 18 O p during the LGM (gray bars in Figure 3a) in response to heavy rainfall (gray bars in Figure 3b). The δ 18 O p changes spatially lagged behind the precipitation changes, suggesting that strong rainout due to heavy rainfall has a significant effect on δ 18 O p drop (Maher & Thompson, 2012; Parker et al., 2021).…”

Quaternary rainfall variability is governed by insolation in northern China and ice-sheet forcing in the South

“…Critical understanding of hydroclimate indication in rainfall isotopes of Southeast Asia remains lacking. Paleoclimate studies have mainly associated changes of rainfall isotopes in this region with rainfall amount 60 , moisture transport 61,62 , moisture convergence 16 and global ocean δ 18 O variance with glaciation 43 . In our iTraCE results, annual and JJA simulation between 20 ka and 10 ka suggest positive δ 18 O loading corresponding to decreased rainfall in Sumatra and southern Borneo; however, most regions of Sumatra and Borneo suggest decreased spring and autumn rainfall corresponding to negative δ 18 O (Supplementary Fig.…”

Investigating oxygen and carbon isotopic relationships in speleothem records over the last millennium using multiple isotope-enabled climate models

“…ECHAM5-wiso has been used extensively within the paleoclimate field, as well as for present time (for example, Werner et al, 2016;Langebroek et al, 2011;Goursaud et al, 2018). The fully coupled version of the model ECHAM5/MPI-OM ESM has very good agreement with both present-day isotope observations from the GNIP database, as well as with ice core 5 and speleothem proxies during mid-Holocene (MH, Comas-Bru et al, 2019), last glacial maximum (LGM Werner et al, 2016;Comas-Bru et al, 2019), and for last interglacial (Parker et al, 2021). Both in the ESM and with the atmospheric component (ECHAM5-wiso), a warm bias in the model is found over high-latitudinal regions, especially over Greenland and Antarctica (Werner et al, 2011(Werner et al, , 2016 and has been attributed to the coarse spatial resolution in the atmospheric component of the model (Werner et al, 2016) resulting in an underestimation of isotope depletion in these regions.…”