E04: precipitation & snowfall: Processes, extremes and impacts
Precipitation, and in particular, snowfall are critical components in the Arctic climate system influencing atmospheric thermodynamics and surface characteristics, e.g., snow depth and albedo, which can affect sea-ice growth and melt processes, and thus, surface temperature. The first phase demonstrated the difficulties to assess Arctic precipitation by either observations, reanalysis or modelling advocating a multi-parameter, multi-data set approach. Cyclones and anomalous moisture transport (AMT) from subpolar regions (sometimes termed atmospheric rivers) play a major role for the Arctic hydrometeorological climate in general, and for water vapour and precipitation particularly. However, their role for Arctic precipitation and snowfall intensity and patterns are hardly studied. Thus, a focus of this project will be the systematic assessment of AMT by exploiting precipitation and snowfall information from in–situ measurements, various satellite data, high-resolution reanalyses and simulations. By integrating data from various (AC)³ projects and upcoming Arctic campaigns (MOSAiC, HALO-(AC)³) we will study the complex relationships among water vapour, relative humidity, precipitation efficiency, and air temperature anomalies. We will identify the impact of cyclones and AMT on regional precipitation amount and phase, as well as on the surface energy budget. This will cover different scales, from individual events to long-term characteristics of different seasons and regions. At the same time,
the precipitation/snowfall intensity will be related to representative weather patterns and associated moisture advection and temperature conditions to understand the response of snowfall on the largescale atmospheric circulation and the influence of key meteorological factors that modulate snowfall variability between the different weather patterns. We will explore if this link is different during extreme events than during average conditions. The skill of Arctic-focussed ICON simulations of water vapour (AMT), clouds, and precipitation/snowfall will be quantified in a two-way approach. The classical observation-to-model method will be complemented by the model-to-observation approach using radar relectivity and brightness temperature as has been established in the first phase of this project. Dedicated model sensitivity studies will help clarifying the factors important for the formation and persistence of AMT, and related snowfall. We will investigate both, extreme snowfall and cyclone/AMT cases of different location, strength, and pathway, with the aim to identify the relative importance of atmospheric and sea-ice conditions for the moisture, precipitation eiciency, and snowfall. The contribution of AMT to surface warming (by increased water vapour and thermal-infrared downward radiation, and cloud radiative effect) and tropospheric warming (by cloud production and latent heat release) will be quantified. E04 coordinates the (AC)³ crosscutting activity (CCA4)
Changes in atmospheric conditions and sea-ice decline lead to significant modifications in regional moisture transport and snowfall patterns in the Arctic, which significantly affects the surface energy budget.
Specifically we want to answer the following questions:
- What is the specific role of anomalous moisture transport for precipitation and snowfall, and what is the related impact on surface and tropospheric warming?
- What are the relationships between changes in temperature, water vapour and precipitation, and snowfall amount and efficiency?
Achievemnets phase I
E04 investigated Arctic snowfall from measurements, reanalysis and modelling. For this purpose a consistent data set of CloudSat radar reflectivity and microwave brightness temperature, and synthetic satellite data from Regional Climate Model (RCM) simulations was built. We have developed and tested algorithms to describe the spatio-temporal features of snowfall using CloudSat data, including first regime identification. Furthermore, an improved knowledge about the differences in precipitation magnitude and phase, and their variability and trends among the commonly used global reanalyses and most recent high resolution Arctic System Reanalysis (ASRv2) has been achieved. The derivation of trend patterns of cyclone characteristics derived from an ensemble of reanalyses and an ensemble of RCMs has been done, allowing a quantification of uncertainty of recent changes and their representation in models (Akperov et al., 2018; Zahn et al., 2018).
Role within (AC)³
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)
Prof. Dr. Susanne Crewell
University of Cologne
Institute for Geophysics and Meteorology (IGM)
Viceto, C., Gorodetskaya, I. V., Rinke, A., Maturilli, M., Rocha, A., and Crewell, S., 2022: Atmospheric rivers and associated precipitation patterns during the ACLOUD and PASCAL campaigns near Svalbard (May–June 2017): case studies using observations, reanalyses, and a regional climate model, Atmos. Chem. Phys., 22, 441–463, https://doi.org/10.5194/acp-22-441-2022.
Bresson, H., Rinke, A., Mech, M., Reinert, D., Schemann, V., Ebell, K., Maturilli, M., Viceto, C., Gorodetskaya, I., and Crewell, S., 2022: Case study of a moisture intrusion over the Arctic with the ICOsahedral Non-hydrostatic (ICON) model: resolution dependence of its representation, Atmos. Chem. Phys., 22, 173–196, https://doi.org/10.5194/acp-22-173-2022.
Wang, D.; Guo, J.; Xu, H.; Li, J.; Lv, Y.; Solanki, R.; Guo, X.; Han, Y.; Chen, T.; Ding, M.; Chen, A.; Bian, L. and Rinke, A., 2021. Vertical structures of temperature inversions and clouds derived from high-resolution radiosonde measurements at Ny-Alesund, Svalbard. Atm. Res., 254, 105530, 10.1016/j.atmosres.2021.105530
Inoue, J., Sato, K., Rinke, A., Cassano, J. J., Fettweis, X., Heinemann, G., et al., 2021. Clouds and radiation processes in regional climate models evaluated using observations over the ice-free Arctic Ocean. J. Geophys. Res.: Atmos., 126, e2020JD033904. https://doi.org/10.1029/2020JD033904
M. Akperov, W. Zhang, P. A. Miller, I. I. Mokhov, V. A. Semenov, H. Matthes, B. Smith and A. Rinke, 2021. Responses of Arctic cyclones to biogeophysical feedbacks under future warming scenarios in a regional Earth system model, Env. Res. Lett., 16, 064076, https://doi.org/10.1088/1748-9326/ac0566
Zhang, X., Fu, Y., Han, Z., J.E. Overland, A. Rinke, H. Tang, T. Vihma, and M.Y. Wang, 2021. Extreme Cold Events from East Asia to North America in Winter 2020/21: Comparisons, Causes, and Future Implications. Adv. Atmos. Sci. . https://doi.org/10.1007/s00376-021-1229-1
A. Rinke, J. J. Cassano, E. N. Cassano, R. Jaiser, D. Handorf, 2021; Meteorological conditions during the MOSAiC expedition: Normal or anomalous?. Elementa-Sci. Anthrop. 9 (1): 00023. doi: https://doi.org/10.1525/elementa.2021.00023
Crewell, S., Ebell, K., Konjari, P., Mech, M., Nomokonova, T., Radovan, A., Strack, D., Triana-Gómez, A. M., Noël, S., Scarlat, R., Spreen, G., Maturilli, M., Rinke, A., Gorodetskaya, I., Viceto, C., August, T., and Schröder, M., 2021: A systematic assessment of water vapor products in the Arctic: from instantaneous measurements to monthly means, Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021.
Sedlar, J., Tjernström, M., Rinke, A., Orr, A., Cassano, J., Fettweis, X., et al., 2020. Confronting Arctic troposphere, clouds, and surface energy budget representations in regional climate models with observations. J. Geophys. Res. Atmos., 125. https://doi.org/10.1029/2019JD031783
Rinke, A., B. Segger, S. Crewell, M. Maturilli, T. Naakka, T. Nygaard, T. Vihma, F. Alshawaf, G. Dick, and J. Wickert, and J. Keller, 2019: Trends of vertically integrated water vapor over the Arctic during 1979-2016: Consistent moistening all over? J. Clim., 32, 6096-6116, doi:10.1175/JCLI-D-19-0092.1
Akperov, M., A. Rinke, and 21 coauthors, 2019: Future projections of cyclone activity in the Arctic for the 21st century from regional climate models (Arctic-CORDEX), Glob. Planet. Change, 182, 103005, doi:10.1016/j.gloplacha.2019.103005
Graham, R., L. Cohen, N. Ritzhaupt, B. Segger, R. Graversen, A. Rinke, V.P. Walden, M.A. Granskog, S.R. Hudson, 2019: Evaluation of six atmospheric reanalyses over Arctic sea ice from winter to early spring, accepted for publication in J. Clim., 32 (14), 4121-4143, doi:10.1175/JCLI-D-18-0643.1
Radovan A., S. Crewell, E.M. Knudsen, and A. Rinke, 2019: Environmental conditions for polar low formation and development over the Nordic Seas: study of January cases based on the Arctic System Reanalysis, Tellus A, 71 (1), 1-16, doi:10.1080/16000870.2019.1618131
Wendisch, M., A. Macke, A. Ehrlich, C. Lüpkes, M. Mech, D. Chechin, K. Dethloff, C. Barrientos, H. Bozem, M. Brückner, H.-C. Clemen, S. Crewell, T. Donth, R. Dupuy, C. Dusny, K. Ebell, U. Egerer, R. Engelmann, C. Engler, O. Eppers, M. Gehrmann, X. Gong, M. Gottschalk, C. Gourbeyre, H. Griesche, J. Hartmann, M. Hartmann, B. Heinold, A. Herber, H. Herrmann, G. Heygster, P. Hoor, S. Jafariserajehlou, E. Jäkel, E. Järvinen, O. Jourdan, U. Kästner, S. Kecorius, E.M. Knudsen, F. Köllner, J. Kretzschmar, L. Lelli, D. Leroy, M. Maturilli, L. Mei, S. Mertes, G. Mioche, R. Neuber, M. Nicolaus, T. Nomokonova, J. Notholt, M. Palm, M. van Pinxteren, J. Quaas, P. Richter, E. Ruiz-Donoso, M. Schäfer, K. Schmieder, M. Schnaiter, J. Schneider, A. Schwarzenböck, P. Seifert, M.D. Shupe, H. Siebert, G. Spreen, J. Stapf, F. Stratmann, T. Vogl, A. Welti, H. Wex, A. Wiedensohler, M. Zanatta, S. Zeppenfeld, 2019: The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multi-Platform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification, Bull. Amer. Meteor. Soc., 100 (5), 841–871, doi:10.1175/BAMS-D-18-0072.1
Knudsen, E.M., and O.J. de Bolsée, 2019: The role of climate scientists in the post-factual society, Geoscience Communication, 2, 83–93, doi:10.5194/gc-2-83-2019
Knudsen, E.M., B. Heinold, S. Dahlke, H. Bozem, S. Crewell, I. V. Gorodetskaya, G. Heygster, D. Kunkel, M. Maturilli, M. Mech, C. Viceto, A. Rinke, H. Schmithüsen, A. Ehrlich, A. Macke, C. Lüpkes, M. Wendisch, 2018: Meteorological conditions during the ACLOUD/PASCAL field campaign near Svalbard in early summer 2017, Atmos. Chem. Phys., 18, 17995-18022, doi:10.5194/acp-18-17995-2018
He, S., Knudsen, E.M., Thompson, D.W.J., and Furevik, T., 2018: Evidence for predictive skill due to Arctic summertime sea-ice extent anomalies, Geophys. Res. Lett., 45, 9114-9122, doi:10.1029/2018GL078281
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
Kayser, M., Maturilli, M., Graham, R.M., Hudson, S.R., Rinke, A., Cohen, L., Kim, J.-H., Park, S.j., Moon, W., and Granskog, M.A., 2017: Vertical thermodynamic structure of the troposphere during the Norwegian young sea ICE expedition (N-ICE2015), J. Geophys. Res. Atmos., 122, 10855-10872, doi:10.1002/2016JD02089
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
Wendisch, M., M. Brückner, J. P. Burrows, S. Crewell, K. Dethloff, K. Ebell, Ch. Lüpkes, A. Macke, J. Notholt, J. Quaas, A. Rinke, and I. Tegen, 2017: Understanding causes and effects of rapid warming in the Arctic. Eos, 98, doi:10.1029/2017EO064803