Figure - available from: Geophysical Research Letters
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As in Figure 3 but for areas between 30° and 70°N only. The peak temperature anomaly in the posterior mean is 1.9 K.
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Understanding past climate is invaluable for evaluating the natural context of man‐made warming. Long term surface‐air temperature records only exist at a few locations. To reconstruct global trends further back in time proxies must then be used. Measurements from such systems are then calibrated against observed climate vari...
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... rj-McMC algorithms find their primary application in seismological studies [Bodin et al., 2012;Poggiali et al., 2019;Zhao et al., 2022], but our results demonstrate that this technique can be successfully used to invert paleoclimate time series. Previous studies used rj-McMC algorithms for paleoclimatic reconstructions (e.g., Hopcroft et al., 2009, andGallagher, 2023), but their analysis encompasses the last millennium, and their forward model does not include a T-CO 2 dependence. Cox and Brenhin Keller (2023) prove an interesting application of Bayesian inversion of a CO 2 time series at Cretaceous-Paleogene Boundary (K-Pg). ...
Future goals and strategies for mitigating ongoing climate changes rely on the understanding of the global carbon cycle and its connections to climate. Evidence from ice cores regarding past atmospheric CO2 and temperature changes through glacial-interglacial oscillations provide crucial insight into the natural variability of carbon cycling. However, poor constraints on atmospheric CO2 input and output fluxes limit our quantitative under-standing of late Pleistocene carbon cycling and climate changes. In this study, we describe an inversion method based on a reversible-jump Markov chain Monte Carlo (rj-McMC) algorithm and a general formulation of the geological carbon cycle to estimate paleo-fluxes of CO2. We present results from two synthetic tests and a real case study based on data from the ice core of Dome Fuji. Results from synthetic tests demonstrate the capability of the algorithm to retrieve reliable estimates of atmospheric CO2 input and output fluxes inverting the time derivative of the atmospheric CO2 record and using its temperature time series as a further constraint. Results from the Dome Fuji case study underscore systematic pulses of input CO2 fluxes into the atmosphere during deglaciations predating peaks of T and output CO2 fluxes by ~2.5 kyrs. The retrieved surface source and sink CO2 fluxes as well as future applications of the algorithm presented here will provide new insights to assess past climate driving mechanisms and inform projections of future climatic trajectories
... Bayesian approaches to GST reconstruction have the advantage of allowing for the direct incorporation of such information through prior distributions while also fully accounting for uncertainty in the inferred GST histories (Wang, 1992;Woodbury & Ferguson, 2006). Hopcroft and Gallagher (2023) recently applied one such method (Hopcroft et al., 2007) to the International Heat Flow Commission database of 1,012 temperature profiles, reaffirming that 20th century warming is anomalous in comparison to the 500-year period prior to industrialization. This database, however, features relatively few profiles in Arctic and subarctic regions which are known to be warming 2-3 times faster than the global average (Isaksen et al., 2022). ...
Reconstructing historical climate change from deep ground temperature measurements in cold regions is often complicated by the presence of permafrost. Existing methods are typically unable to account for latent heat effects due to the freezing and thawing of the active layer. In this work, we propose a novel method for reconstructing historical ground surface temperature (GST) from borehole temperature measurements that accounts for seasonal thawing and refreezing of the active layer. Our method couples a recently developed fast numerical modeling scheme for two‐phase heat transport in permafrost soils with an ensemble‐based method for approximate Bayesian inference. We evaluate our method on two synthetic test cases covering both cold and warm permafrost conditions as well as using real data from a 100 m deep borehole on Sardakh Island in northeastern Siberia. Our analysis of the Sardakh Island borehole data confirms previous findings that GST in the region have likely risen by 5–9°C between the pre‐industrial period of 1750–1855 and 2012. We also show that latent heat effects due to seasonal freeze‐thaw have a substantial impact on the resulting reconstructed surface temperatures. We find that neglecting the thermal dynamics of the active layer can result in biases of roughly −1°C in cold conditions (i.e., mean annual ground temperature below −5°C) and as much as −2.6°C in warmer conditions where substantial active layer thickening (>200 cm) has occurred. Our results highlight the importance of considering seasonal freeze‐thaw in GST reconstructions from permafrost boreholes.
Climate warming has caused increased air temperature as well as increased subsurface temperature. Many previous studies on subsurface warming simplified heat advection by neglecting the horizontal component of regional groundwater flow or even neglected heat advection accompanying groundwater flow. In this study, the simultaneous control of heat advection and conduction on subsurface warming is numerically investigated in a 2D hypothetical basin cross section. By calculating the increment of subsurface temperature, we find that heat advection could accelerate subsurface warming. In a given basin, subsurface warming in the recharge area with downward groundwater flow is more significant than that in the discharge area with upward groundwater flow. By using a 1D model with vertical groundwater flow only for comparison, we find that in any part of a basin, even if the horizontal flux is very small compared with the vertical flux, neglecting the horizontal flux would underestimate the propagation depth of climate warming. This implies that when the propagation depth of climate warming is a priori known variable, existing 1D models would overestimate downward groundwater flux or underestimate upward groundwater flux. Moreover, we find pumping would cause deeper propagation depths of climate warming by accelerating groundwater circulation, whereas basin-scale heterogeneity and anisotropy of hydraulic conductivity would cause shallower propagation depths of climate warming because of the relative dominance of horizontal flow. By demonstrating the importance of 2D groundwater flow on subsurface warming, the results provide new insight into understanding the regulation of temperature among the atmosphere, the hydrosphere and the lithosphere.
