scholarly journals A model-data comparison of the Last Glacial Maximum surface temperature changes

2018 ◽  
Author(s):  
Akil Hossain ◽  
Xu Zhang ◽  
Gerrit Lohmann
Keyword(s):  
Surface Temperature ◽  
Last Glacial Maximum ◽  
Planktonic Foraminifera ◽  
Ice Sheet ◽  
Glacial Maximum ◽  
Model Data ◽  
Last Glacial ◽  
Proxy Records ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Abstract. Over the Last Glacial Maximum (LGM, ~ 21 ka BP), the presence of vast Northern Hemisphere ice-sheets caused abrupt changes in surface topography and background climatic state. While the ice-sheet extent is well known, several conflicting ice-sheet topography reconstructions suggest that there is uncertainty in this boundary condition. The terrestrial and sea surface temperature (SST) of the LGM as simulated with six different Laurentide Ice Sheet (LIS) reconstructions in a fully coupled Earth System Model (COSMOS) have been compared with the subfossil pollen and plant macrofossil based and marine temperature proxies reconstruction. The terrestrial reconstruction shows a similar pattern and in good agreement with model data. The SST proxy dataset comprises a global compilation of planktonic foraminifera, diatoms, radiolarian, dinocyst, alkenones and planktonic foraminifera Mg / Ca-derived SST estimates. Significant mismatches between modeled and reconstructed SST have been observed. Among the six LIS reconstructions, Tarasov’s LIS reconstruction shows the highest correlation with reconstructed terrestrial and SST. In the case of radiolarian, Mg / Ca, diatoms and foraminifera show a positive correlation while dinocyst and alkenones show very low and negative correlation with the model. Dinocyst-based SST records are much warmer than reconstructed by other proxies as well as Pre-industrial (PI) temperature. However, there are large discrepancies between model temperatures and temperature recorded by different proxies. Eight different PMIP3 models also compared with temperature proxies reconstruction which show mismatches with the proxy records might be due to misinterpreted and/or biased proxy records. Therefore, it has been speculated that considering different habitat depths and growing seasons of the planktonic organisms used for SST reconstruction could provide a better agreement of proxy data with model results on a regional scale. Moreover, it can reduce model-data misfits. It is found that shifting in the habitat depth and living season can remove parts of the observed model-data mismatches in SST anomalies.

scholarly journals An ice sheet model of reduced complexity for paleoclimate studies

2015 ◽  
Vol 6 (2) ◽  
pp. 1395-1443
Author(s):  
B. Neff ◽  
A. Born ◽  
T. F. Stocker
Keyword(s):  
Surface Temperature ◽  
Last Glacial Maximum ◽  
Computational Efficiency ◽  
Ice Sheet ◽  
Glacial Maximum ◽  
Last Glacial ◽  
Ice Volume ◽  
Reduced Complexity ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Abstract. IceBern2D is a vertically integrated ice sheet model to investigate the ice distribution on long timescales under different climatic conditions. It is forced by simulated fields of surface temperature and precipitation of the last glacial maximum and present day climate from a comprehensive climate model. This constant forcing is adjusted to changes in ice elevation. Bedrock sinking and sea level are a function of ice volume. Due to its reduced complexity and computational efficiency, the model is well-suited for extensive sensitivity studies and ensemble simulations on extensive temporal and spatial scales. It shows good quantitative agreement with standardized benchmarks on an artificial domain (EISMINT). Present day and last glacial maximum ice distributions on the Northern Hemisphere are also simulated with good agreement. Glacial ice volume in Eurasia is underestimated due to the lack of ice shelves in our model. The efficiency of the model is utilized by running an ensemble of 400 simulations with perturbed model parameters and two different estimates of the climate at the last glacial maximum. The sensitivity to the imposed climate boundary conditions and the positive degree day factor β, i.e., the surface mass balance, outweighs the influence of parameters that disturb the flow of ice. This justifies the use of simplified dynamics as a means to achieve computational efficiency for simulations that cover several glacial cycles. The sensitivity of the model to changes in surface temperature is illustrated as a hysteresis based on 5 million year long simulations.

scholarly journals The Last Glacial Maximum and Heinrich Event 1 in terms of climate and vegetation around the Alboran Sea: a preliminary model-data comparison

2005 ◽  
Vol 337 (10-11) ◽  
pp. 983-992 ◽  
Author(s):  
Masa Kageyama ◽  
Nathalie Combourieu Nebout ◽  
Pierre Sepulchre ◽  
Odile Peyron ◽  
Gerhard Krinner ◽  
...  
Keyword(s):  
Last Glacial Maximum ◽  
Glacial Maximum ◽  
Model Data ◽  
Last Glacial ◽  
Data Comparison ◽  
Heinrich Event ◽  
Preliminary Model ◽  
The Last Glacial Maximum ◽  
Heinrich Event 1 ◽  
The Last Glacial

Extent and age of the Last Glacial Maximum in the southeastern sector of the Scandinavian Ice Sheet

2001 ◽  
Vol 31 (1-4) ◽  
pp. 407-425 ◽  
Author(s):  
Juha Pekka Lunkka ◽  
Matti Saarnisto ◽  
Valeri Gey ◽  
Igor Demidov ◽  
Vera Kiselova
Keyword(s):  
Last Glacial Maximum ◽  
Ice Sheet ◽  
Glacial Maximum ◽  
Last Glacial ◽  
Scandinavian Ice Sheet ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Exploring the complex uncertainties in coupled climate-ice simulations of the Last Glacial Maximum

2021 ◽  
Author(s):  
Lauren Gregoire ◽  
Niall Gandy ◽  
Lachlan Astfalck ◽  
Robin Smith ◽  
Ruza Ivanovic ◽  
...  
Keyword(s):  
Mass Balance ◽  
Last Glacial Maximum ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Glacial Maximum ◽  
Sea Surface ◽  
Surface Mass ◽  
Last Glacial ◽  
The Last Glacial Maximum ◽  
The Last Glacial

<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>

Antarctic Ice Sheet changes since the Last Glacial Maximum

2022 ◽  
pp. 623-687
Author(s):  
Martin Siegert ◽  
Andrew S. Hein ◽  
Duanne A. White ◽  
Damian B. Gore ◽  
Laura De Santis ◽  
...  
Keyword(s):  
Last Glacial Maximum ◽  
Ice Sheet ◽  
Glacial Maximum ◽  
Antarctic Ice Sheet ◽  
Last Glacial ◽  
The Last Glacial Maximum ◽  
The Last Glacial

scholarly journals How cold was Europe at the Last Glacial Maximum? A synthesis of the progress achieved since the first PMIP model-data comparison

2007 ◽  
Vol 3 (2) ◽  
pp. 331-339 ◽  
Author(s):  
G. Ramstein ◽  
M. Kageyama ◽  
J. Guiot ◽  
H. Wu ◽  
C. Hély ◽  
...  
Keyword(s):  
Last Glacial Maximum ◽  
General Circulation ◽  
General Circulation Models ◽  
Glacial Maximum ◽  
Model Data ◽  
Last Glacial ◽  
Data Comparison ◽  
The Last Glacial Maximum ◽  
Winter Cooling ◽  
The Last Glacial

Abstract. The Last Glacial Maximum has been one of the first foci of the Paleoclimate Modelling Intercomparison Project (PMIP). During its first phase, the results of 17 atmosphere general circulation models were compared to paleoclimate reconstructions. One of the largest discrepancies in the simulations was the systematic underestimation, by at least 10°C, of the winter cooling over Europe and the Mediterranean region observed in the pollen-based reconstructions. In this paper, we investigate the progress achieved to reduce this inconsistency through a large modelling effort and improved temperature reconstructions. We show that increased model spatial resolution does not significantly increase the simulated LGM winter cooling. Further, neither the inclusion of a vegetation cover compatible with the LGM climate, nor the interactions with the oceans simulated by the atmosphere-ocean general circulation models run in the second phase of PMIP result in a better agreement between models and data. Accounting for changes in interannual variability in the interpretation of the pollen data does not result in a reduction of the reconstructed cooling. The largest recent improvement in the model-data comparison has instead arisen from a new climate reconstruction based on inverse vegetation modelling, which explicitly accounts for the CO2 decrease at LGM and which substantially reduces the LGM winter cooling reconstructed from pollen assemblages. As a result, the simulated and observed LGM winter cooling over Western Europe and the Mediterranean area are now in much better agreement.

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