ALBERT

Description: This study examines the stable water isotope signal (δ18O) of three ice cores drilled on the Renland peninsula (East Greenland coast). While ice core δ18O measurements qualitatively are a measure of the local temperature history, the δ18O variability in precipitation actually reflects the integrated hydrological activity that the deposited ice experienced from the evaporation source to the condensation site. Thus, as Renland is located next to a fluctuating sea ice cover, the transfer function used to infer past temperatures from the δ18O variability is potentially influenced by variations in the local moisture conditions. The objective of this study is therefore to evaluate the δ18O variability of ice cores drilled on Renland and examine what amount of the signal that can be attributed to regional temperature variations. In the analysis, three ice cores are utilized to create stacked summer, winter and annually averaged δ18O signals (AD 1801-2014). The imprint of temperature on δ18O is first examined by correlating the δ18O stacks with instrumental temperature records from East Greenland (AD 1895-2014) and Iceland (AD 1830-2014) and with the regional climate model HIRHAM5 (AD 1980-2014). The results show that the δ18O variability correlates with regional temperatures on both a seasonal and an annual scale between 1910-2014 while δ18O is uncorrelated with Iceland temperatures between 1830-1909. Our analysis indicates that the unstable regional δ18O-temperature correlation does not result from changes in weather patterns through respectively strengthening and weakening of the North Atlantic Oscillation. Instead, the results imply that the varying δ18O-temperature relation is connected with the volume flux of sea ice exported through Fram Strait (and south along the coast of East Greenland). Notably, the δ18O variability only reflects the variations in regional temperature when the temperature anomaly is positive and the sea ice export anomaly is negative. It is hypothesized that this could be caused by a larger sea ice volume flux during cold years which suppresses the Iceland temperature signature in the Renland δ18O signal. However, more isotope-enabled modeling studies with emphasis on coastal ice caps are needed in order to quantify the mechanisms behind this observation. As the amount of Renland δ18O variability that reflects regional temperature varies with time, the results have implications for studies performing regression-based δ18O-temperature reconstructions based on ice cores drilled in the vicinity of a fluctuating sea ice cover.

Description: Recent observations have indicated rapidly increasing mass loss from the Greenland Ice Sheet. To explore the interactions and feedbacks of the ice sheets in the climate system, it is important to develop coupled climate-ice sheet models. The integration of an ice sheet model in a global model is challenging, and, currently, relatively few climate models include a two-way coupling to a dynamical ice sheet model. In this work package, we have continued developing the coupled ice sheet-climate model system comprising the global climate model EC-Earth and the Parallel Ice Sheet Model (PISM) for Greenland. The new model system, EC-Earth3-GrIS, is upgraded to include the recent model versions, EC-Earth3 and PISM version 1.2. In addition, a new module has been developed to handle the exchange of information between the ice sheet model and EC-Earth using the OASIS3- MCT software interface. The new module reads output from the ice sheet model and exchanges the fields with the relevant EC-Earth components. The ice sheet mask and topography are provided to the atmosphere and land surface components. The heat and freshwater fluxes from basal melt and ice discharge are provided to the ocean module via the runoff-mapper that routes surface runoff into the ocean. The new module also prepares the forcing fields for the ice sheet model, i.e., subsurface temperature and surface mass balance. These fields are calculated in EC- Earth3 using a land ice surface parameterization, developed explicitly for the Greenland ice sheet. The parameterization contains a responsive snow and ice albedo scheme and includes land ice characteristics in the calculation of heat and energy transfer at the surface. Experiments with and without the land ice surface parameterization have been carried out for preindustrial and present-day conditions to assess the influence of the surface parameterization on the calculated surface mass balance. The results show that the ice sheet responds stronger and more realistically to forcing changes when the new surface parameterization is used. Besides the model development, the results from experiments with the first model version, EC- Earth-PISM, have been analyzed. These results stress that a decent surface scheme with a responsive snow albedo scheme is necessary for investigating mass balance changes of the Greenland Ice Sheet. Overall, our results indicate that the feedbacks induced by the interactive ice sheet have a significant influence on Arctic climate change under warming conditions. In warm scenarios where the CO2 level is raised to four times the preindustrial level, the coupled model has a colder Arctic surface, a fresher ocean, and more sea-ice in winter.

Description: This study examines the stable water isotope signal (δ18O) of three ice cores drilled on the Renland peninsula (east Greenland coast). While ice core δ18O measurements qualitatively are a measure of the local temperature history, the δ18O variability in precipitation actually reflects the integrated hydrological activity that the deposited ice experienced from the evaporation source to the condensation site. Thus, as Renland is located next to fluctuating sea ice cover, the transfer function used to infer past temperatures from the δ18O variability is potentially influenced by variations in the local moisture conditions. The objective of this study is therefore to evaluate the δ18O variability of ice cores drilled on Renland and examine the amount of the signal that can be attributed to regional temperature variations. In the analysis, three ice cores are utilized to create stacked summer, winter and annually averaged δ18O signals (1801–2014 CE). The imprint of temperature on δ18O is first examined by correlating the δ18O stacks with instrumental temperature records from east Greenland (1895–2014 CE) and Iceland (1830–2014 CE) and with the regional climate model HIRHAM5 (1980–2014 CE). The results show that the δ18O variability correlates with regional temperatures on both a seasonal and an annual scale between 1910 and 2014, while δ18O is uncorrelated with Iceland temperatures between 1830 and 1909. Our analysis indicates that the unstable regional δ18O–temperature correlation does not result from changes in weather patterns through strengthening and weakening of the North Atlantic Oscillation. Instead, the results imply that the varying δ18O–temperature relation is connected with the volume flux of sea ice exported through Fram Strait (and south along the coast of east Greenland). Notably, the δ18O variability only reflects the variations in regional temperature when the temperature anomaly is positive and the sea ice export anomaly is negative. It is hypothesized that this could be caused by a larger sea ice volume flux during cold years which suppresses the Iceland temperature signature in the Renland δ18O signal. However, more isotope-enabled modeling studies with emphasis on coastal ice caps are needed in order to quantify the mechanisms behind this observation. As the amount of Renland δ18O variability that reflects regional temperature varies with time, the results have implications for studies performing regression-based δ18O–temperature reconstructions based on ice cores drilled in the vicinity of a fluctuating sea ice cover.

Description: This study examines the stable water isotope signal (δ18O) of three ice cores drilled on the Renland peninsula (East Greenland coast). While ice core δ18O measurements qualitatively are a measure of the local temperature history, the δ18O variability actually reflects the integrated hydrological activity that the deposited ice experienced from the evaporation source to the condensation site. Thus, as Renland is located next to a fluctuating sea ice cover, the transfer function used to infer past temperatures from the δ18O variability is potentially influenced by variations in the local moisture conditions. The objective of this study is therefore to evaluate the δ18O variability of ice cores drilled on Renland and examine what amount that can be attributed to regional temperature variations. In the analysis, three ice cores are utilized to create stacked summer, winter and annually averaged δ18O signals (AD 1801–2014). The imprint of temperature on δ18O is first examined by correlating the δ18O stacks with instrumental temperature records from East Greenland (AD 1895–2014) and Iceland (AD 1830–2014) and with the regional climate model HIRHAM5 (AD 1980–2014). The results show that the δ18O variability correlates with regional temperatures on both a seasonal and an annual scale between 1910–2014 while δ18O is uncorrelated with Iceland temperatures between 1830–1909. Our analysis indicates that the unstable regional δ18O-temperature correlation does not result from changes in weather patterns through respectively strengthening and weakening of the North Atlantic Oscillation. Instead, the results imply that the varying δ18O-temperature relation is connected with the volume flux of sea ice exported through Fram Strait (and south along the coast of East Greenland). Notably, the δ18O variability only reflects the variations in regional temperature when the temperature anomaly is positive and the sea ice export anomaly is negative. It is hypothesized that this could be caused by a larger sea ice volume flux during cold years which suppresses the Iceland temperature signature in the Renland δ18O signal. However, more isotope-enabled modeling studies with emphasis on coastal ice caps are needed in order to quantify the mechanisms behind this observation. As the amount of Renland δ18O variability that reflects regional temperature varies with time, the results have implications for studies performing regression-based δ18O-temperature reconstructions based on ice cores drilled in the vicinity of a fluctuating sea ice cover.

Description: Perennial snow, or firn, covers 80 % of the Greenland ice sheet and has the capacity to retain surface meltwater, influencing the ice sheet mass balance and contribution to sea-level rise. Multilayer firn models are traditionally used to simulate firn processes and estimate meltwater retention. We present, intercompare and evaluate outputs from nine firn models at four sites that represent the ice sheet's dry snow, percolation, ice slab and firn aquifer areas. The models are forced by mass and energy fluxes derived from automatic weather stations and compared to firn density, temperature and meltwater percolation depth observations. Models agree relatively well at the dry-snow site while elsewhere their meltwater infiltration schemes lead to marked differences in simulated firn characteristics. Models accounting for deep meltwater percolation overestimate percolation depth and firn temperature at the percolation and ice slab sites but accurately simulate recharge of the firn aquifer. Models using Darcy's law and bucket schemes compare favorably to observed firn temperature and meltwater percolation depth at the percolation site, but only the Darcy models accurately simulate firn temperature and percolation at the ice slab site. Despite good performance at certain locations, no single model currently simulates meltwater infiltration adequately at all sites. The model spread in estimated meltwater retention and runoff increases with increasing meltwater input. The highest runoff was calculated at the KAN_U site in 2012, when average total runoff across models (±2σ) was 353±610 mm w.e. (water equivalent), about 27±48 % of the surface meltwater input. We identify potential causes for the model spread and the mismatch with observations and provide recommendations for future model development and firn investigation.