D03: Interactions between atmosphere and sea ice in the Arctic
PIs: Annette Rinke, Gunnar Spreen
The central aim of the project is (i) the improvement in understanding of feedback mechanisms between the atmosphere and sea ice–ocean in the Arctic and (ii) a quantification of the individual contributions of atmospheric circulation, Atmospheric Boundary Layer (ABL) and cloud processes, and sea ice changes to recently observed Arctic climate change. The differences between the observed sea ice retreat and simulation results from state–of–the–art regional coupled climate models will be assessed. Ensemble simulations with the coupled regional atmosphere–sea ice–ocean model of the Arctic climate system HIRHAM–NAOSIM are compared with new satellite–derived sea ice concentration, thickness and snow depth data. One of the main objectives is to realistically simulate the regional patterns of Arctic sea ice loss, changes in sea ice and snow thickness, and sea ice drift patterns. The aim is to identify and quantify the individual external and internal drivers and feedback mechanisms behind these changes. Combined with a comprehensive model evaluation, a series of model sensitivity studies with respect to key processes (sea ice/snow albedo, vertical mixing in the ABL, mixed–phase clouds) will help to quantify and improve the associated regional feedback processes in the model. Furthermore, we will attribute the Arctic Amplification to regional feedback processes arising from non–linear interactions between the atmosphere and sea ice–ocean and to the large–scale atmospheric circulation patterns and synoptic–scale processes including cyclones.
Hypothesis: Regional feedback processes arising from interactions between the atmosphereand sea ice-ocean and changes in the large-scale atmospheric circulation patterns are criticalmechanisms for the Arctic Amplification.
In order to test the hypothesis, we will address the following central questions:
- What are the mechanisms for the rapid Arctic sea ice loss?
- Which are the involved key regional atmosphere–sea ice feedback mechanisms?
- How can they appropriately be described in climate models?
Role within (AC)³
- D03 provides sea-ice data and regional feedback descriptions
- D03 relies on the data from (AC)³ for process- and climate-oriented evaluation
Prof. Dr. Klaus Dethloff
Alfred-Wegener-Institute Helmholtz Center for Polar and Marine Research (AWI)
Dr. Gunnar Spreen
University of Bremen
Institute of Environmental Physics (IUP)
Dr. Annette Rinke
Alfred-Wegener-Institute Helmholtz-Center for Polar and Marine Research (AWI)
Rostosky, R., G. Spreen, S.L. Farrell, T. Frost, G. Heygster, and C. Melsheimer, 2018: Snow Depth Retrieval on Arctic Sea Ice From Passive Microwave Radiometers—Improvements and Extensions to Multiyear Ice Using Lower Frequencies, Journal of Geophysical Research: Oceans, 123, doi:10.1029/2018JC014028
Rinke, A., D. Handorf, W. Dorn, K. Dethloff, J.C. Moore, X. Zhang, 2018: Atmospheric feedbacks on Arctic summer sea-ice anomalies in ensemble simulations of a coupled regional climate model, Advances in Polar Science, accepted
Sato, K., J. Inoue, A. Yamazaki, J.-H. Kim, A. Makshtas, V. Kustov, M. Maturilli, and K. Dethloff , 2018: Impact on predictability of tropical and mid-latitude cyclones by extra Arctic observations, Nature Scientific Reports, 8, 12104, doi:10.1038/s41598-018-30594-4
Dethloff, K., D. Handorf, R. Jaiser, A. Rinke, P. Klinghammer, 2018: Dynamical mechanisms of Arctic amplification, Annals of New York Academy of Sciences, doi:10.1111/nyas.13698
Lu, J., G. Heygster, and G. Spreen, 2018: Atmospheric Correction of Sea Ice Concentration Retrieval for 89 GHz AMR-E Observations, IEEE JSTARS, 11(5), 1442–1457, 10.1109/JSTARS.2018.2805193
M. Zahn, M. Akperov, A. Rinke, F. Feser, I.I. Mokhov, 2018: Trends of cyclone characteristics in the Arctic and their patterns from different re-analysis data, J. Geophys. Res., 123, 2737-2751, doi:10.1002/2017JD027439
Akperov, A. Rinke, and the Arctic Cordex Team, 2018: Cyclone activity in the Arctic from an ensemble of regional climate models (Arctic CORDEX), J. Geophys. Res., 123, 2537-2554, doi:10.1002/2017JD027703
Itkin, P., G. Spreen, S.M. Hvidegaard, H. Skourup, J. Wilkinson, S. Gerland, and M.A. Granskog, 2018: Contribution of deformation to sea-ice mass balance: a case study from an N-ICE2015 storm, Geophys. Res. Lett., 45, 789-796, doi:10.1002/2017GL076056
Pațilea, C., G. Heygster, M. Huntemann, and G. Spreen, 2017: Combined SMAP/SMOS Thin Sea Ice Thickness Retrieval. The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-168 (under review for The Cryosphere).
Rinke, A., M. Maturilli, R.M. Graham, H. Matthes, D. Handorf, L. Cohen, S.R. Hudson, and J.C. Moore, 2017: Extreme cyclone events in the Arctic: Wintertime variability and trends, Envir. Res. Lett., 12, 094006, doi:10.1088/1748-9326/aa7def
Graham, R. M., L. Cohen, A. A. Petty, L. N. Boisvert, A. Rinke, S. R. Hudson, M. Nicolaus, and M. A. Granskog, 2017: Increasing frequency and duration of Arctic winter warming events, Geophys. Res. Lett., 44, 6974–6983, doi:10.1002/2017GL073395
Graham, R.M., A. Rinke, L. Cohen, S.R. Hudson, V.P. Walden, M.A. Granskog, W. Dorn, M. Kayser, M. Maturilli, 2016: A comparison of the two Arctic atmospheric winter states observed during N‐ICE2015 and SHEBA, J. Geophys. Res. Atm., 122, 5716-5737, doi:10.1002/2016JD025475