scholarly journals A large increase in the carbon inventory of the land biosphere since the Last Glacial Maximum: constraints from multi-proxy data

2018 ◽  
Author(s):  
Aurich Jeltsch-Thömmes ◽  
Gianna Battaglia ◽  
Olivier Cartapanis ◽  
Samuel L. Jaccard ◽  
Fortunat Joos

Abstract. Atmospheric CO2 increased by about 90 ppm across the transition from the Last Glacial Maximum (LGM) to the end of the preindustrial (PI) period. The contribution of changes in land carbon stocks to this increase remains uncertain. Estimates of the PI-LGM difference in land biosphere carbon inventory (∆land) range from −400 to +1,500 GtC, based on upscaling of scarce paleo soil carbon or pollen data. A perhaps more reliable approach infers ∆land from reconstructions of the stable carbon isotope ratio in the ocean and atmosphere assuming isotopic mass balance with recent studies yielding ∆land values of about 300–400 GtC. Surprisingly, however, earlier studies considered a mass balance for the ocean–atmosphere–land biosphere system only. Thereby, these studies neglect carbon exchange with sediments, weathering-burial flux imbalances, and the influence of the deglacial reorganization on the isotopic budgets. We show this neglect to significantly bias low deglacial ∆land in simulations using the Bern3D Earth System Model of Intermediate Complexity v.2.0s. We constrain ∆land to ∼ 850 GtC (median estimate; 450 to 1250 GtC 1σ range) by using reconstructed changes in atmospheric δ13C, marine δ13C, deep Pacific carbonate ion concentration, and atmospheric CO2 as observational targets in a Monte Carlo ensemble with half a million members. Sensitivities of the target variables to changes in individual deglacial carbon cycle processes are established from factorial simulations over the past 21,000 years with the Bern3D model. These are used in the Monte Carlo ensemble and provide forcing–response relationships for future model–model and model–data comparisons. Uncertainties in the estimate of ∆land remain considerable due to model and proxy data uncertainties. Yet, it is likely that ∆land is larger than 450 GtC and highly unlikely that the carbon inventory in the land biosphere was larger for the LGM than during the recent preindustrial period.

2019 ◽  
Vol 15 (2) ◽  
pp. 849-879 ◽  
Author(s):  
Aurich Jeltsch-Thömmes ◽  
Gianna Battaglia ◽  
Olivier Cartapanis ◽  
Samuel L. Jaccard ◽  
Fortunat Joos

Abstract. Past changes in the inventory of carbon stored in vegetation and soils remain uncertain. Earlier studies inferred the increase in the land carbon inventory (Δland) between the Last Glacial Maximum (LGM) and the preindustrial period (PI) based on marine and atmospheric stable carbon isotope reconstructions, with recent estimates yielding 300–400 GtC. Surprisingly, however, earlier studies considered a mass balance for the ocean–atmosphere–land biosphere system only. Notably, these studies neglect carbon exchange with marine sediments, weathering–burial flux imbalances, and the influence of the transient deglacial reorganization on the isotopic budgets. We show this simplification to significantly reduce Δland in simulations using the Bern3D Earth System Model of Intermediate Complexity v.2.0s. We constrain Δland to ∼850 GtC (median estimate; 450 to 1250 GtC ±1SD) by using reconstructed changes in atmospheric δ13C, marine δ13C, deep Pacific carbonate ion concentration, and atmospheric CO2 as observational targets in a Monte Carlo ensemble with half a million members. It is highly unlikely that the land carbon inventory was larger at LGM than PI. Sensitivities of the target variables to changes in individual deglacial carbon cycle processes are established from transient factorial simulations with the Bern3D model. These are used in the Monte Carlo ensemble and provide forcing–response relationships for future model–model and model–data comparisons. Our study demonstrates the importance of ocean–sediment interactions and burial as well as weathering fluxes involving marine organic matter to explain deglacial change and suggests a major upward revision of earlier isotope-based estimates of Δland.


2021 ◽  
Vol 17 (1) ◽  
pp. 171-201
Author(s):  
Cameron M. O'Neill ◽  
Andrew McC. Hogg ◽  
Michael J. Ellwood ◽  
Bradley N. Opdyke ◽  
Stephen M. Eggins

Abstract. We conduct a model–data analysis of the marine carbon cycle to understand and quantify the drivers of atmospheric CO2 concentration during the last glacial–interglacial cycle. We use a carbon cycle box model, “SCP-M”, combined with multiple proxy data for the atmosphere and ocean, to test for variations in ocean circulation and Southern Ocean biological export productivity across marine isotope stages spanning 130 000 years ago to the present. The model is constrained by proxy data associated with a range of environmental conditions including sea surface temperature, salinity, ocean volume, sea-ice cover and shallow-water carbonate production. Model parameters for global ocean circulation, Atlantic meridional overturning circulation and Southern Ocean biological export productivity are optimized in each marine isotope stage against proxy data for atmospheric CO2, δ13C and Δ14C and deep-ocean δ13C, Δ14C and CO32-. Our model–data results suggest that global overturning circulation weakened during Marine Isotope Stage 5d, coincident with a ∼ 25 ppm fall in atmospheric CO2 from the last interglacial period. There was a transient slowdown in Atlantic meridional overturning circulation during Marine Isotope Stage 5b, followed by a more pronounced slowdown and enhanced Southern Ocean biological export productivity during Marine Isotope Stage 4 (∼ −30 ppm). In this model, the Last Glacial Maximum was characterized by relatively weak global ocean and Atlantic meridional overturning circulation and increased Southern Ocean biological export productivity (∼ −20 ppm during MIS 3 and MIS 2). Ocean circulation and Southern Ocean biological export productivity returned to modern values by the Holocene period. The terrestrial biosphere decreased by 385 Pg C in the lead-up to the Last Glacial Maximum, followed by a period of intense regrowth during the last glacial termination and the Holocene (∼ 600 Pg C). Slowing ocean circulation, a colder ocean and to a lesser extent shallow carbonate dissolution contributed ∼ −70 ppm to atmospheric CO2 in the ∼ 100 000-year lead-up to the Last Glacial Maximum, with a further ∼ −15 ppm contributed during the glacial maximum. Our model results also suggest that an increase in Southern Ocean biological export productivity was one of the ingredients required to achieve the Last Glacial Maximum atmospheric CO2 level. We find that the incorporation of glacial–interglacial proxy data into a simple quantitative ocean transport model provides useful insights into the timing of past changes in ocean processes, enhancing our understanding of the carbon cycle during the last glacial–interglacial period.


2006 ◽  
Vol 2 (6) ◽  
pp. 1105-1153 ◽  
Author(s):  
D. M. Roche ◽  
T. M. Dokken ◽  
H. Goosse ◽  
H. Renssen ◽  
S. L. Weber

Abstract. The Last Glacial Maximum climate is one of the classic benchmarks used both to test the ability of coupled models to simulate climates different from that ot the present-day and to better understand the possible range of mechanisms that could be involved in future climate change. It also bears the advantage of being one of the most well documented periods with respect to palaeoclimatic records, allowing a thorough data-model comparison. We present here an ensemble of Last Glacial Maximum climate simulations obtained with the Earth System model LOVECLIM, including coupled dynamic atmosphere, ocean and vegetation components. The climate obtained using standard parameter values is then compared to available proxy data for the surface ocean, vegetation, oceanic circulation and atmospheric conditions. Interestingly, the oceanic circulation obtained resembles that of the present-day, but with increased overturning rates. As this result is in contradiction with the "classic" palaeoceanographic view, we ran a range of sensitivity experiments to explore the response of the model and the possibilities for other oceanic circulation states. After a critical review of our LGM state with respect to available proxy data, we conclude that the balance between water masses obtained is consistent with the available data although the specific characteristics (temperature, salinity) are not in full agreement. The consistency of the simulated state is further reinforced by the fact that the mean surface climate obtained is shown to be generally in agreement with the most recent reconstructions of vegetation and sea surface temperatures, even at regional scales.


2021 ◽  
Author(s):  
Lauren Gregoire ◽  
Niall Gandy ◽  
Lachlan Astfalck ◽  
Robin Smith ◽  
Ruza Ivanovic ◽  
...  

<p>Simulating the co-evolution of climate and ice-sheets during the Quaternary is key to understanding some of the major abrupt changes in climate, ice and sea level. Indeed, events such as the Meltwater pulse 1a rapid sea level rise and Heinrich, Dansgaard–Oeschger and the 8.2 kyr climatic events all involve the interplay between ice sheets, the atmosphere and the ocean. Unfortunately, it is challenging to simulate the coupled Climate-Ice sheet system because small biases, errors or uncertainties in parts of the models are strongly amplified by the powerful interactions between the atmosphere and ice (e.g. ice-albedo and height-mass balance feedbacks). This leads to inaccurate or even unrealistic simulations of ice sheet extent and surface climate. To overcome this issue we need some methods to effectively explore the uncertainty in the complex Climate-Ice sheet system and reduce model biases. Here we present our approach to produce ensemble of coupled Climate-Ice sheet simulations of the Last Glacial maximum that explore the uncertainties in climate and ice sheet processes.</p><p>We use the FAMOUS-ICE earth system model, which comprises a coarse-resolution and fast general circulation model coupled to the Glimmer-CISM ice sheet model. We prescribe sea surface temperature and sea ice concentrations in order to control and reduce biases in polar climate, which strongly affect the surface mass balance and simulated extent of the northern hemisphere ice sheets. We develop and apply a method to reconstruct and sample a range of realistic sea surface temperature and sea-ice concentration spatio-temporal field. These are created by merging information from PMIP3/4 climate simulations and proxy-data for sea surface temperatures at the Last Glacial Maximum with Bayes linear analysis. We then use these to generate ensembles of FAMOUS-ice simulations of the Last Glacial maximum following the PMIP4 protocol, with the Greenland and North American ice sheets interactively simulated. In addition to exploring a range of sea surface conditions, we also vary key parameters that control the surface mass balance and flow of ice sheets. We thus produce ensembles of simulations that will later be used to emulate ice sheet surface mass balance.  </p>


2013 ◽  
Vol 9 (4) ◽  
pp. 1571-1587 ◽  
Author(s):  
R. O'ishi ◽  
A. Abe-Ouchi

Abstract. When the climate is reconstructed from paleoevidence, it shows that the Last Glacial Maximum (LGM, ca. 21 000 yr ago) is cold and dry compared to the present-day. Reconstruction also shows that compared to today, the vegetation of the LGM is less active and the distribution of vegetation was drastically different, due to cold temperature, dryness, and a lower level of atmospheric CO2 concentration (185 ppm compared to a preindustrial level of 285 ppm). In the present paper, we investigate the influence of vegetation change on the climate of the LGM by using a coupled atmosphere-ocean-vegetation general circulation model (AOVGCM, the MIROC-LPJ). The MIROC-LPJ is different from earlier studies in the introduction of a bias correction method in individual running GCM experiments. We examined four GCM experiments (LGM and preindustrial, with and without vegetation feedback) and quantified the strength of the vegetation feedback during the LGM. The result shows that global-averaged cooling during the LGM is amplified by +13.5 % due to the introduction of vegetation feedback. This is mainly caused by the increase of land surface albedo due to the expansion of tundra in northern high latitudes and the desertification in northern middle latitudes around 30° N to 60° N. We also investigated how this change in climate affected the total terrestrial carbon storage by using offline Lund-Potsdam-Jena dynamic global vegetation model (LPJ-DGVM). Our result shows that the total terrestrial carbon storage was reduced by 597 PgC during the LGM, which corresponds to the emission of 282 ppm atmospheric CO2. In the LGM experiments, the global carbon distribution is generally the same whether the vegetation feedback to the atmosphere is included or not. However, the inclusion of vegetation feedback causes substantial terrestrial carbon storage change, especially in explaining the lowering of atmospheric CO2 during the LGM.


2013 ◽  
Vol 79 (1) ◽  
pp. 49-54 ◽  
Author(s):  
Barbara M. Heyman ◽  
Jakob Heyman ◽  
Thomas Fickert ◽  
Jonathan M. Harbor

AbstractDuring the last glacial maximum (LGM), glaciers existed in scattered mountainous locations in central Europe between the major ice masses of Fennoscandia and the Alps. A positive degree-day glacier mass-balance model is used to constrain paleo-climate conditions associated with reconstructed LGM glacier extents of four central European upland regions: the Vosges Mountains, the Black Forest, the Bavarian Forest, and the Giant Mountains. With reduced precipitation (25–75%), reflecting a drier LGM climate, the modeling yields temperature depressions of 8–15°C. To reproduce past glaciers more severe cooling is required in the west than in the east, indicating a strong west–east temperature anomaly gradient.


1998 ◽  
Vol 25 (4) ◽  
pp. 531-534 ◽  
Author(s):  
Adeline Fabre ◽  
Gilles Ramstein ◽  
Catherine Ritz ◽  
Sophie Pinot ◽  
Nicolas Fournier

2013 ◽  
Vol 9 (1) ◽  
pp. 367-376 ◽  
Author(s):  
J. D. Annan ◽  
J. C. Hargreaves

Abstract. Some recent compilations of proxy data both on land and ocean (MARGO Project Members, 2009; Bartlein et al., 2011; Shakun et al., 2012), have provided a new opportunity for an improved assessment of the overall climatic state of the Last Glacial Maximum. In this paper, we combine these proxy data with the ensemble of structurally diverse state of the art climate models which participated in the PMIP2 project (Braconnot et al., 2007) to generate a spatially complete reconstruction of surface air (and sea surface) temperatures. We test a variety of approaches, and show that multiple linear regression performs well for this application. Our reconstruction is significantly different to and more accurate than previous approaches and we obtain an estimated global mean cooling of 4.0 ± 0.8 °C (95% CI).


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