Simulating Heinrich Events in a Complex Climate ModelFlorian Ziemen1,2, Christian Rodehacke2, Andreas Chlond2, Uwe Mikolajewicz2

1 International Max Planck Research School on Earth System Modelling, florian.ziemen@zmaw.de; 2 Max Planck Institute for Meteorology

International Max Planck Research School on Earth System Modelling

Max-Planck-Institut für Meteorologie

Heinrich events and Dansgaard-Oeschger events were the dominant features of the Last Glacial (LG) climate variability. The main actors dur-ing a Heinrich event are the Laurentide Ice Sheet (LIS) and the Atlantic Ocean. One assumes that a Heinrich event is caused by internal oscillations of the LIS that release large amounts of ice (up to 10 m of global sea level equivalent) into the north-

ern Atlantic. The sea level rises and the meridi-onal overturning circulation decreases strongly. The breakdown phase of a Heinrich event lasts for about 1 kyr and Heinrich events recurred with intervals on the order of 7 kyrs during the LG. We investigate Heinrich events in coupled ice sheet - climate model simulations under Last Glacial Maximum (LGM) conditions.

Introduction

Model setupWe couple the climate model ECHAM5/MPIOM with the modified Parallel Ice Sheet Model (mPISM).We run ECHAM5 in T31 resolution. MPIOM works on a bipolar grid with poles over Green-land and Antarctica. The grid resolution in MPI-OM varies between 30 km around Greenland and 380 km at the equator. In mPISM, we extended the sliding parameter-ization described in Calov et al, 2002 by model-ing basal water and its advection with the basal ice velocity. In contrast to the model SICOPO-LIS used by Calov, PISM uses the Shallow Shelf Approximation for MacAyeal-Style ice streams. Our grid covers most of the northern hemisphere at a fixed resolution of 20 km.

We interpolate monthly mean temperature and temperature standard deviation maps from the climate model to the finer ice sheet grid and ap-ply a temperature height correction of -6.5 K / km.For the precipitation, we use a linear transition between -17 and +7 °C to partition it into its solid and liquid fractions. To represent the height des-ert effect, at altitudes above 2 km, we apply an exponential correction with a factor of 0.5 / km as described in Budd and Smith, 1979.We determine the surface mass balance of the ice sheet from the interpolated values with the posi-tive degree day (PDD) method. We feed the glacier mask, the surface elevations, and the hydrological fluxes from mPISM back into the climate model.

The LGM temperature anomalies show that dedi-cated model simulations are necessary to obtain a realistic glacial climate (cf. Background Climate). Standard PDD methods use a fixed surface tem-perature standard deviation. This is unrealistic when modeling the LGM ice sheets because the standard deviation is much higher in Siberia than in Greenland or Scandinavia. We compute the standard deviation from the output of our climate model. This proved very beneficial for the repre-sentation of the ice sheets (cf. Coupling and Ice Sheets).

mPISM is able to simulate repeated collapse event cycles (not shown here). When we feed the ice sheet geometry and mass balance of a collapse event into ECHAM5/MPIOM, we see large scale cooling in the northern Hemisphere and a local warming above the Hudson bay area. Part of the temperature changes can be explained by the changes in topography, but there is a clear shift in the patterns in the Hudson Bay area and there are strong effects from changes in the ocean circulation and sea ice cover in the Atlantic (cf. Collapse Events).

Results

We perform coupled ice sheet - climate mod-el simulations without flux correction. In these simulations we are able to maintain a reasonable LGM climate including the ice sheet distribution.We are now starting to investigate Heinrich events in our coupled model system. Our first re-

sults show the importance of the non-linearities in the climate response to a collapsing ice sheet and demonstrate the necessity of fully coupled simulations for a better understanding of glacial climate dynamics.

Conclusion

Difference between simulated LGM and present day sur-face temperatures.

LGM annual mean surface temperatures obtained in our coupled ice sheet - climate model.

Surface temperature standard deviationsin June/July/August. The standard deviationswere calculated for each month individually andthen averaged over the three months of the sum-mer season and 100 years of model output.

Surface elevations after a multi-millenialcoupled run. The ice sheets are outlined in red.

Background Climate Collapse Events

Coupling and Ice Sheets

Surface temperature difference between climate runs forced with a collapsing LIS and its regrown state. The colors match those of the topography plot at a lapse rate of about -6.5 K / km.

Change in Topography between the collapsed Lauren-tide Ice Sheet and its regrown state as seen by ECHAM5.

Budd and Smith, 1979, The growth and retreat of ice sheets in response to orbital radiation changes Bueler and Brown, 2009, The shallow shelf approximation as a “sliding law” in a thermomechanically coupled ice sheet modelCalov et al, 2002, Large-scale instabilities of the Lauren-tide Ice Sheet simulated in a fully coupled climate-system modelKageyama et al, 2010, Modelling glacial climatic millenial-scale variability related to changes in the Atlandic meridi-onal overturning circulation: a review

MacAyeal, 1989, Large-Scale Ice Flow Over a Viscous Basal Sediment: Theory and Application to Ice Stream B, Ant-arcticaMacAyeal, 1993, Binge/Purge oscillations of the Lauren-tide Ice Sheet as a cause of the North Atlantic’s Heinrich eventsMikolajewicz et al, 2007, Effect of ice sheet interactions in anthropogenic climate change simulationsOtto-Bliesner and Brady, 2010, The sensitivity of the cli-mate response to the magnitude and location of freshwa-ter forcing: last glacial maximum experiments

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