Abstract:
We propose that the approx. 100-k.y. cycle seen in terrestrial glaciation is due to changes in meteor flux that come from changes in the Earth's orbit. This model can explain a 70-k.y. 'anomalous' period in climate data and the apparent discrepancy between present extraterrestrial fluxes and those in oceanic sediments. It can be tested by measuring Ir densities in sediments and ice during glacials and interglacials.Keywords:
Extraterrestrial Life
Climate state
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A two‐dimensional climate model which links the northern hemisphere atmosphere, ocean mixed layer, sea ice, and continents has been asynchronously coupled to a model of the three main northern ice sheets and their underlying bedrock. The coupled model has been used to test the influence of several factors, including snow surface albedo over the ice sheets, in producing plausible ice age simulations using astronomically derived insolation and CO 2 data from the Vostok ice core. The impact of potentially important processes, such as the water vapor transport, clouds, and deep sea circulation, was not investigated in this study. After several sensitivity experiments designed to identify the main mechanisms governing surface temperature and ice accumulation, the model is first run with ice sheet feedback by forcing it only with the astronomical insolation over the past 122 kyr. Large variations of ice volume are simulated between 122 and 55 kyr B.P., with a rapid latitudinal extension of the North American and Eurasian ice sheets starting at 120 kyr B.P. The simulated last glacial maximum is at 19 kyr B.P. The model is able to simulate deglaciation as well. The simulated evolution of the three northern ice sheets is generally in phase with geological reconstructions. The major discrepancy between the simulation and paleoclimate reconstructions lies in the underestimation of temperature variations (linked with an underestimation of the ice sheet extent and an excess in the prescribed CO 2 concentration). Sensitivity experiments show that ablation is more important to the ice sheet response than snow precipitation variations. In the model a key mechanism in the deglaciation after the last glacial maximum appears to be the “aging” of snow, which decreases its albedo. The other factors which play an important role are, in decreasing level of importance, the ice sheet altitude, insolation, taiga cover, and ice sheet extent. A final set of experiments addresses the effects of CO 2 on the simulated climate of the last glacial maximum and on a new long term experiment covering the last 122 kyr. This last experiment is made by forcing the model with both insolation and CO 2 variations. This additional forcing improves the temperature and ice volume results. Despite the limitations inherent to the present modeling approach, the sensitivity experiments performed can provide insight into the relative importance of possible mechanisms responsible for the building and melting of huge ice sheets during the last glacial‐interglacial cycle.
Ice-sheet model
Paleoclimatology
Deglaciation
Greenland ice sheet
Ice core
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Citations (170)
Abstract. A frequently cited atmospheric CO2 threshold for the onset of Antarctic glaciation of ~780 ppmv is based on the study of DeConto and Pollard (2003) using an ice sheet model and the GENESIS climate model. Proxy records suggest that atmospheric CO2 concentrations passed through this threshold across the Eocene–Oligocene transition ~34 Ma. However, atmospheric CO2 concentrations may have been close to this threshold earlier than this transition, which is used by some to suggest the possibility of Antarctic ice sheets during the Eocene. Here we investigate the climate model dependency of the threshold for Antarctic glaciation by performing offline ice sheet model simulations using the climate from 7 different climate models with Eocene boundary conditions (HadCM3L, CCSM3, CESM1.0, GENESIS, FAMOUS, ECHAM5 and GISS_ER). These climate simulations are sourced from a number of independent studies, and as such the boundary conditions, which are poorly constrained during the Eocene, are not identical between simulations. The results of this study suggest that the atmospheric CO2 threshold for Antarctic glaciation is highly dependent on the climate model used and the climate model configuration. A large discrepancy between the climate model and ice sheet model grids for some simulations leads to a strong sensitivity to the lapse rate parameter.
Antarctic ice sheet
Ice-sheet model
Proxy (statistics)
Climate state
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Citations (76)
Landform
Glacial landform
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Citations (1)
Abstract Examining the nature of ice sheet and sea level response to past episodes of enhanced greenhouse gas forcing may help constrain future sea level change. Here, for the first time, we present the transient nature of ice sheets and sea level during the late Pliocene. The transient ice sheet predictions are forced by multiple climate snapshots derived from a climate model set up with late Pliocene boundary conditions, forced with different orbital forcing scenarios appropriate to two Marine Isotope Stages (MISs), MIS KM5c, and K1. Our results indicate that during MIS KM5c both the Antarctic and Greenland ice sheets contributed to sea level rise relative to present and were relatively stable. Insolation forcing between the hemispheres was out of phase during MIS K1 and led to an asynchronous response of ice volume globally. Therefore, when variations of precession were high, inferring the behavior of ice sheets from benthic isotope or sea level records is complex.
Orbital forcing
Forcing (mathematics)
Ice-sheet model
Antarctic ice sheet
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Citations (26)
HadCM3
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The importance of Arctic Ocean sea ice coverage for global climate (change) is widely acknowledged. Due to its high albedo and its capacity to insulate the sea surface from the atmosphere the ice directly impacts on the oceanic and atmospheric heat and moisture balance and thus affects large-scale circulation patterns. At the same time, sea ice displays a sensitive responder to changes in 1) orbital forcing (i.e. insolation), 2) large-scale wind patterns (governing ice drift) and 3) ocean temperature (e.g. due to fluctuations in the Atlantic water advection). Among climate proxies preserved within marine sediments the IP25 sea ice biomarker and the novel PIP25 index derived therefrom seem to be most promising means for sea ice reconstructions in the Arctic (Belt et al., 2007; Muller et al., 2011). The identification of this molecule in marine sediment cores thus enables the assessment of spatial and temporal variations in sea ice coverage through time. Among numerical climate models the high-resolution regional ocean-sea ice model NAOSIM repeatedly has been applied for palaeo sea ice modelling studies (e.g. Starz et al., 2012). Here we present and discuss biomarker-based sea ice reconstructions with an unusual high temporal resolution covering the past glacial, deglacial and the Holocene climate history of eastern Fram Strait. These proxy results are complemented by model data obtained from NAOSIM. The documentation of changing sea ice conditions that accompanied the transition from the last glacial to interglacial climate mode contributes to the understanding of oceanic and atmospheric driving and feedback mechanisms associated with this large-scale climate shift. Furthermore, the continuous biomarker records from Fram Strait enable the assessment of how fast sea surface conditions (i.e. sea ice cover) responded to climate perturbations. Events of abruptly retreating or advancing sea ice cover as well as long-term trends are observable. Comparison of these proxy reconstructions with numerical modelling data (i.e. time-slice experiments) also allows for a cross-evaluation of both approaches and provides information about potential weak points and the benefit of coupling biomarker and NAOSIM sea ice studies.
References
Belt et al., 2007. Organic Geochemistry 38 (1): 16-27.
Muller et al., 2011. Earth and Planetary Science Letters 306 (3–4): 137-148.
Starz et al., 2012. Earth and Planetary Science Letters 357–358: 257-267.
Sea ice concentration
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Citations (0)
Snowmelt
Ice-albedo feedback
Albedo (alchemy)
Snow field
Meltwater
Climate state
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Citations (13)
Ice-sheet model
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Citations (0)
A box model of the coupled ocean, atmosphere, sea ice, and land ice climate system is used to study glacial‐interglacial oscillations under seasonally and orbitally varying solar forcing. The dominant 100 kyr oscillation in land ice volume has the familiar sawtooth shape of climate proxy records, and to zeroth order, it does not depend on the seasonal and Milankovitch forcing. The sea ice controls, via its albedo and insulating effects, the atmospheric moisture fluxes and precipitation that enable the land ice sheet growth. This control and the rapid growth and melting of the sea ice allow the sea ice to rapidly switch the climate system from a growing ice sheet phase to a retreating ice sheet phase and to shape the oscillation's sawtooth structure. A specific physical mechanism is proposed by which the insolation changes act as a pacemaker, setting the phase of the oscillation by directly controlling summer melting of ice sheets. This mechanism is shown to induce deglaciations during periods of lower summer insolation. Superimposed on the 100 kyr are the linear Milankovitch‐forced frequencies of 19, 23, and 41 kyr. The transition from 41 kyr glacial cycles to 100 kyr cycles one million years ago may be explained as being due to the activation of the sea ice switch at that time. This would be the case if sea ice extent was more limited during the warmer climate of the early Pleistocene.
Ice-albedo feedback
Milankovitch cycles
Orbital forcing
Climate oscillation
Climate state
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Citations (205)
Abstract. In contrast to the Arctic, where total sea ice extent (SIE) has been decreasing for the last three decades, Antarctic SIE has shown a small, but significant increase during the same time period. However, in 2016, an unusually early onset of the melt season was observed; the maximum Antarctic SIE was already reached as early as August rather than end of September, and was followed by a rapid decrease. The decline of the sea ice area (SIA) started even earlier, namely in July. The decay was particularly strong in November where Antarctic SIE exhibited a negative anomaly (compared to the 1979–2015 average) of approximately 2 Mio. km2, which, combined with reduced Arctic SIE, led to a distinct minimum in global SIE. ECMWF- Interim reanalysis data were used to investigate possible atmospheric influences on the observed phenomena. The early onset of the melt and the rapid decrease in SIA and SIE were associated with atmospheric flow patterns related to a positive ZW3 index, i.e. synoptic situations leading to strong meridional flow. Particularly, in the first third of November northerly flow conditions in the Weddell Sea and the Western Pacific triggered accelerated sea ice decay, which was continued in the following weeks due to positive feed-back effects, leading to the extraordinary low November SIE. In 2016, the monthly mean SAM index reached its second lowest November value since the beginning of the satellite observations. SIE decrease was preconditioned by SIA decrease. A better spatial and temporal coverage of reliable ice thickness data is needed to assess the change in ice mass rather than ice area.
Anomaly (physics)
Atmospheric Circulation
Siberian High
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Citations (12)