Sam Sherriff-Tadano

The configuration of the Northern Hemisphere ice sheets during the Last and Penultimate Glacial Maxima (LGM; PGM) influenced millennial-scale climate changes, as well as solid Earth and sea level changes that occurred during the subsequent deglaciations, due to their effects on the atmosphere, ocean circulation, and the solid Earth. Thus, realistic simulations of these ice sheets are crucial for the initialisation of deglaciation experiments that can help improve our understanding of interactions between the climate, ice sheets and sea levels. Here, we produce the first large ensembles of complex coupled atmosphere–ice sheet model (FAMOUS-BISICLES) simulations of the PGM and LGM, varying 12 uncertain parameters that control the ice sheet albedo, ice dynamics and climate. We quantify the sensitivity to input parameters using Gaussian Process emulators to perform a Sobol sensitivity analysis. Albedo parameters have the largest influence on ice volumes for both ice sheets and time periods. Parameters controlling precipitation and sliding have a larger effect on Eurasian than North American ice sheet size due to the differences in geographical and climatic settings. Out of 120 parameter combinations, we find 4 that produce LGM and PGM ice volumes and extents compatible with palaeo-evidence. The resulting ice sheet configurations provide new and improved reconstructions of PGM Northern Hemisphere ice sheets for use as inputs in climate, ice sheet and sea level models.

The Arctic during the Last Interglacial period (LIG) was considered warmer than it is today. The previous study points to a large difference in the degree of simulated annual-mean Arctic warming among models. While recent reconstructions suggest the disappearance of summer sea ice in the Arctic at the LIG, many climate models fail to capture this feature. It is thus essential to investigate sources of uncertainty in climate models. The current study examines the impact of the temperature-cloud phase relationship. Sensitivity studies are conducted for the first time to explore the potential importance of this relationship in simulating the LIG climate. Two different cloud parameter sets are used for an atmosphere-ocean general circulation model with and without the dynamic vegetation feedback. The model with cloud parametrization that permits liquid water at lower temperatures and a larger fraction of supercooled liquid water at the same temperature simulates a warmer preindustrial (PI) climate, greater annual-mean Arctic warming at the LIG, and substantially reduced summer sea ice cover at the LIG. It is demonstrated that the low-level clouds play a crucial role in controlling the Arctic response via the greenhouse effect. The result indicates the importance of the temperature-cloud phase relationship in simulating the Arctic climate at the LIG. It also highlights the importance of accurately simulating modern sea ice thickness and representing the processes that affect the fraction of supercooled liquid water in clouds.

It has been hypothesized that the Earth may have experienced snowball events in the past, during which its surface became completely covered with ice. Previous studies used general circulation models to investigate the onset and climate of such snowball events. Using the MIROC4m coupled atmosphere–ocean climate model, this study examined the changes in the oceanic circulation during the onset of a modern snowball Earth and elucidated their evolution to steady states under the snowball climate. Abruptly changing the solar constant to 94 % of its present-day value caused the modern Earth climate to turn into a snowball state after ∼ 1300 years and initiated rapid increase in sea ice thickness. During onset of the snowball, extensive sea ice formation and melting of sea ice in the mid-latitudes caused substantial freshening of surface waters and salinity stratification. By contrast, such salinity stratification was absent if the duration between the change in the solar flux and the snowball onset was short. After snowball onset, the global sea ice cover and the buildup of salinity stratification caused drastic weakening in the deep ocean circulation. However, the meridional overturning circulation resumed within several hundred years after the snowball onset because the density flux by sea ice production weakens the salinity stratification. While the evolution of the oceanic circulation would depend on the continental distribution and the evolution of continental ice sheets, our results highlight the gradual growth of sea ice and associated brine rejection are essential factors for the transient evolution of the oceanic circulation in the snowball events.

The Arctic during the last interglacial period (LIG) was considered warmer than today. While a recent proxy-based study suggests the disappearance of summer sea ice in the Arctic at the LIG, many climate models fail to capture this feature. It is thus essential to investigate sources of uncertainty in numerical models. The current study examines the impact of the temperature-cloud phase relationship. Sensitivity studies are conducted for the first time to explore the potential importance of this relationship in simulating the LIG climate. Two different cloud parameter sets are used for an atmosphere-ocean general circulation model with and without the dynamic vegetation feedback. The model with cloud parametrization permitting liquid water at a lower temperature and a larger fraction of supercooled liquid water at the same temperature simulates a warmer preindustrial (PI) climate, larger annual mean Arctic warming at the LIG, and substantially reduced sea ice cover during summer at the LIG. It is demonstrated that the low-level clouds play a crucial role in controlling the Arctic response via the greenhouse effect. The result indicates the importance of the temperature-cloud phase relationship in simulating the Arctic climate at the LIG. It also highlights the importance of accurately simulating modern sea ice thickness and representing the processes that affect the fraction of supercooled liquid water in clouds.

The Arctic during the last interglacial period (LIG) was considered warmer than today. While a recent proxy-based study suggests the disappearance of summer sea ice in the Arctic at the LIG, many climate models fail to capture this feature. It is thus essential to investigate sources of uncertainty in numerical models. The current study examines the impact of the temperature-cloud phase relationship. Sensitivity studies are conducted for the first time to explore the potential importance of this relationship in simulating the LIG climate. Two different cloud parameter sets are used for an atmosphere-ocean general circulation model with and without the dynamic vegetation feedback. The model with cloud parametrization permitting liquid water at a lower temperature and a larger fraction of supercooled liquid water at the same temperature simulates a warmer preindustrial (PI) climate, larger annual mean Arctic warming at the LIG, and substantially reduced sea ice cover during summer at the LIG. It is demonstrated that the low-level clouds play a crucial role in controlling the Arctic response via the greenhouse effect. The result indicates the importance of the temperature-cloud phase relationship in simulating the Arctic climate at the LIG. It also highlights the importance of accurately simulating modern sea ice thickness and representing the processes that affect the fraction of supercooled liquid water in clouds.

The Arctic during the last interglacial period (LIG) was considered warmer than today. While a recent proxy-based study suggests the disappearance of summer sea ice in the Arctic at the LIG, many climate models fail to capture this feature. It is thus essential to investigate sources of uncertainty in numerical models. The current study examines the impact of the temperature-cloud phase relationship. Sensitivity studies are conducted for the first time to explore the potential importance of this relationship in simulating the LIG climate. Two different cloud parameter sets are used for an atmosphere-ocean general circulation model with and without the dynamic vegetation feedback. The model with cloud parametrization permitting liquid water at a lower temperature and a larger fraction of supercooled liquid water at the same temperature simulates a warmer preindustrial (PI) climate, larger annual mean Arctic warming at the LIG, and substantially reduced sea ice cover during summer at the LIG. It is demonstrated that the low-level clouds play a crucial role in controlling the Arctic response via the greenhouse effect. The result indicates the importance of the temperature-cloud phase relationship in simulating the Arctic climate at the LIG. It also highlights the importance of accurately simulating modern sea ice thickness and representing the processes that affect the fraction of supercooled liquid water in clouds.

The Arctic during the last interglacial period (LIG) was considered warmer than today. While a recent proxy-based study suggests the disappearance of summer sea ice in the Arctic at the LIG, many climate models fail to capture this feature. It is thus essential to investigate sources of uncertainty in numerical models. The current study examines the impact of the temperature-cloud phase relationship. Sensitivity studies are conducted for the first time to explore the potential importance of this relationship in simulating the LIG climate. Two different cloud parameter sets are used for an atmosphere-ocean general circulation model with and without the dynamic vegetation feedback. The model with cloud parametrization permitting liquid water at a lower temperature and a larger fraction of supercooled liquid water at the same temperature simulates a warmer preindustrial (PI) climate, larger annual mean Arctic warming at the LIG, and substantially reduced sea ice cover during summer at the LIG. It is demonstrated that the low-level clouds play a crucial role in controlling the Arctic response via the greenhouse effect. The result indicates the importance of the temperature-cloud phase relationship in simulating the Arctic climate at the LIG. It also highlights the importance of accurately simulating modern sea ice thickness and representing the processes that affect the fraction of supercooled liquid water in clouds.

The Arctic during the last interglacial period (LIG) was considered warmer than today. While a recent proxy-based study suggests the disappearance of summer sea ice in the Arctic at the LIG, many climate models fail to capture this feature. It is thus essential to investigate sources of uncertainty in numerical models. The current study examines the impact of the temperature-cloud phase relationship. Sensitivity studies are conducted for the first time to explore the potential importance of this relationship in simulating the LIG climate. Two different cloud parameter sets are used for an atmosphere-ocean general circulation model with and without the dynamic vegetation feedback. The model with cloud parametrization permitting liquid water at a lower temperature and a larger fraction of supercooled liquid water at the same temperature simulates a warmer preindustrial (PI) climate, larger annual mean Arctic warming at the LIG, and substantially reduced sea ice cover during summer at the LIG. It is demonstrated that the low-level clouds play a crucial role in controlling the Arctic response via the greenhouse effect. The result indicates the importance of the temperature-cloud phase relationship in simulating the Arctic climate at the LIG. It also highlights the importance of accurately simulating modern sea ice thickness and representing the processes that affect the fraction of supercooled liquid water in clouds.

The Arctic during the last interglacial period (LIG) was considered warmer than today. While a recent proxy-based study suggests the disappearance of summer sea ice in the Arctic at the LIG, many climate models fail to capture this feature. It is thus essential to investigate sources of uncertainty in numerical models. The current study examines the impact of the temperature-cloud phase relationship. Sensitivity studies are conducted for the first time to explore the potential importance of this relationship in simulating the LIG climate. Two different cloud parameter sets are used for an atmosphere-ocean general circulation model with and without the dynamic vegetation feedback. The model with cloud parametrization permitting liquid water at a lower temperature and a larger fraction of supercooled liquid water at the same temperature simulates a warmer preindustrial (PI) climate, larger annual mean Arctic warming at the LIG, and substantially reduced sea ice cover during summer at the LIG. It is demonstrated that the low-level clouds play a crucial role in controlling the Arctic response via the greenhouse effect. The result indicates the importance of the temperature-cloud phase relationship in simulating the Arctic climate at the LIG. It also highlights the importance of accurately simulating modern sea ice thickness and representing the processes that affect the fraction of supercooled liquid water in clouds.