Scientist
Research, Earth System Modelling, Ocean Modelling
Summary:
Lorenzo Zampieri is a scientist working on implementing machine-learning sea ice and ocean wave models within the AIFS framework.
During his career, his research focused on problems related to sea ice prediction and predictability, thermodynamic parameterization development, reanalyses evaluation and correction, geoengineering strategies for sea ice, and more. After completing his PhD at the Alfred Wegener Institute for Polar and Marine Research (AWI) in Bremerhaven, Germany, under the supervision of Prof. Thomas Jung and Dr. Helge Goessling, he did a postdoc at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, collaborating with Dr. Marika Holland.
Professional interests:
- Sea ice modelling
- Machine learning for Earth system modelling
- Sea ice predictions
- Polar climate system
Career background:
- B.Sc. in Physics from the University of Padova (Italy) [2011 – 2015]
- M.Sc. in Environmental Physics from the University of Bremen (Germany) [2015 – 2017]
- Ph.D. in Physics from the University of Bremen and the Alfred Wegener Institute for Polar and Marine Research (AWI; Germany) [2017 – 2021]
- Postdoctoral Researcher at the National Center for Atmospheric Research (NCAR; Colorado) [2021 – 2023]
- Junior Scientist at the Euro-Mediterranean Center on Climate Change (CMCC; Italy) [2023 – 2024]
- Scientist at the European Centre for Medium-Range Weather Forecasts (ECMWF; Germany) [2024 – present]
- 2025
- Francesco Cocetta, Lorenzo Zampieri, Doroteaciro Iovino (January 2025) The sea ice component of MUSE, the unstructured-mesh global ocean model of CMCC. DOI: 10.5194/egusphere-egu24-9802
- Lorenzo Zampieri, Nils Hutter, Francesco Cocetta (January 2025) Colocated airborne observations from MOSAiC enable sea ice process understanding and new model parameterization development. DOI: 10.5194/egusphere-egu24-9945
- Clare Eayrs, Lorenzo Zampieri (March 2025) Observational Requirements in the Context of AI prediction Systems - a PCAPS ORCAS Task Team. DOI: 10.5194/egusphere-egu25-14272
- Lorenzo Zampieri, Harrison Cook, Rachel Furner, Sara Hahner, Florian Pinault, Baudouin Raoult, Nina Raoult, Mario Santa Cruz, Matthew Chantry (March 2025) Coupling approaches for data-driven Earth system models. DOI: 10.5194/egusphere-egu25-4499
- Francesco Cocetta, Doroteaciro Iovino, Lorenzo Zampieri (March 2025) Evolution of Arctic sea ice in CMS reanalyses. DOI: 10.5194/egusphere-egu25-17548
- Rachel Furner, Rilwan Adewoyin, Mario Santa Cruz, Sara Hahner, Sarah Keeley, Kristian Mogensen, Lorenzo Zampieri (March 2025) Developing a data-driven global ocean model at ECMWF . DOI: 10.5194/egusphere-egu25-11883
- Sara Hahner, Jean Bidlot, Josh Kousal, Lorenzo Zampieri, Matthew Chantry (March 2025) Representing waves in ECMWF’s data-based forecasting system AIFS. DOI: 10.5194/egusphere-egu25-11946
- 2024
- Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, Lorenzo Zampieri (September 2024) Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids, Geoscientific Model Development. DOI: 10.5194/gmd-17-7067-2024
- Clare Eayrs, Won Sang Lee, Emilia Jin, Jean-François Lemieux, François Massonnet, Martin Vancoppenolle, Lorenzo Zampieri, Luke G. Bennetts, Ed Blockley, Eui-Seok Chung, Alexander D. Fraser, Yoo-geun Ham, Jungho Im, Baek-min Kim, Beong-Hoon Kim, Jinsuk Kim, Joo-Hong Kim, Seong-Joong Kim, Seung Hee Kim, Anton Korosov, Choon-Ki Lee, Donghyuck Lee, Hyun-Ju Lee, Jeong-Gil Lee, Jiyeon Lee, Jisung Na, In-woo Park, Jikang Park, Xianwei Wang, Shiming Xu, Sukyoung Yun (March 2024) Advances in Machine Learning Techniques Can Assist Across a Variety of Stages in Sea Ice Applications, Bulletin of the American Meteorological Society. DOI: 10.1175/bams-d-23-0332.1
- Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Sarah Keeley, Lukas Kluft, Nikolay V. Koldunov, Aleksei Koldunov, Tobias Kölling, Joshua Kousal, Kristian S. Mogensen, Tiago Quintino, Inna Polichtchouk, Domokos Sármány, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, Florian Andreas Ziemen (April 2024) Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5/NEMOv3.4. DOI: 10.5194/egusphere-2024-913
- Qian Wang, Fei Chai, Yang Zhang, Yinglong Joseph Zhang, Lorenzo Zampieri (January 2024) Development of a total variation diminishing (TVD) Sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids. DOI: 10.5194/gmd-2023-236
- Francesco Cocetta, Lorenzo Zampieri, Julia Selivanova, Doroteaciro Iovino (February 2024) GREP reanalysis captures the evolution of the Arctic Marginal Ice Zone across timescales. DOI: 10.5194/egusphere-2024-413
- Lorenzo Zampieri, David Clemens, Anne Sledd, Nils Hutter, Marika Holland (April 2024) Modeling the Winter Heat Conduction Through the Sea Ice System During MOSAiC, Geophysical Research Letters. DOI: 10.1029/2023gl106760
- Xiaoran Dong, Qinghua Yang, Yafei Nie, Lorenzo Zampieri, Jiuke Wang, Jiping Liu, Dake Chen (August 2024) Antarctic sea ice prediction with A convolutional long short-term memory network, Ocean Modelling. DOI: 10.1016/j.ocemod.2024.102386
- Francesco Cocetta, Lorenzo Zampieri, Julia Selivanova, Doroteaciro Iovino (October 2024) Assessing the representation of Arctic sea ice and the marginal ice zone in ocean–sea ice reanalyses, The Cryosphere. DOI: 10.5194/tc-18-4687-2024
- Yuchun Gao, Yongwu Xiu, Yafei Nie, Hao Luo, Qinghua Yang, Lorenzo Zampieri, Xianqing Lv, Petteri Uotila (November 2024) An Assessment of Subseasonal Prediction Skill of the Antarctic Sea Ice Edge, Journal of Geophysical Research: Oceans. DOI: 10.1029/2024JC021499
- 2023
- Lorenzo Zampieri, Gabriele Arduini, Marika Holland, Sarah Keeley, Kristian Mogensen, Matthew D. Shupe, Steffen Tietsche (March 2023) A machine learning correction model of the winter clear-sky temperature bias over the Arctic sea ice in atmospheric reanalyses, Monthly Weather Review. DOI: 10.1175/mwr-d-22-0130.1
- 2022
- Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay V. Koldunov, Thomas Rackow, Joakim Kjellsson, Helge F. Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, Thomas Jung (August 2022) AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model, Geoscientific Model Development. DOI: 10.5194/gmd-15-6399-2022
- Longjiang Mu, Lars Nerger, Jan Streffing, Qi Tang, Bimochan Niraula, Lorenzo Zampieri, Svetlana N. Loza, Helge F. Goessling (December 2022) Sea‐Ice Forecasts With an Upgraded AWI Coupled Prediction System, Journal of Advances in Modeling Earth Systems. DOI: 10.1029/2022ms003176
- Gabriele Arduini, Sarah Keeley, Jonathan Day, irina sandu, Lorenzo Zampieri, Gianpaolo Balsamo (July 2022) On the Importance of Representing Snow Over Sea‐Ice for Simulating the Arctic Boundary Layer, Journal of Advances in Modeling Earth Systems. DOI: 10.1029/2021ms002777
- 2021
- Lorenzo Zampieri, Frank Kauker, Jörg Fröhle, Hiroshi Sumata, Elizabeth C. Hunke, Helge F. Goessling (May 2021) Impact of Sea‐Ice Model Complexity on the Performance of an Unstructured‐Mesh Sea‐Ice/Ocean Model under Different Atmospheric Forcings, Journal of Advances in Modeling Earth Systems. DOI: 10.1029/2020MS002438
- Lorenzo Zampieri (January 2021) Sea-ice prediction across timescales and the role of model complexity. DOI: 10.26092/ELIB/446
- Jan Streffing, Tido Semmler, Lorenzo Zampieri, Thomas Jung (September 2021) Response of Northern Hemisphere weather and climate to Arctic sea ice decline: Resolution independence in Polar Amplification Model Intercomparison Project (PAMIP) simulations, Journal of Climate. DOI: 10.1175/jcli-d-19-1005.1
- 2020
- Mu L., Nerger L., Tang Q., Loza S.N., Sidorenko D., Wang Q., Semmler T., Zampieri L., Losch M., Goessling H.F. (April 2020) Toward a Data Assimilation System for Seamless Sea Ice Prediction Based on the AWI Climate Model, Journal of Advances in Modeling Earth Systems. DOI: 10.1029/2019MS001937
- 2019
- Zampieri L., Goessling H.F., Jung T. (April 2019) Predictability of Antarctic Sea Ice Edge on Subseasonal Time Scales, Geophysical Research Letters. DOI: 10.1029/2019GL084096
- Hutter N., Zampieri L., Losch M. (April 2019) Leads and ridges in Arctic sea ice from RGPS data and a new tracking algorithm, Cryosphere. DOI: 10.5194/tc-13-627-2019
- Lorenzo Zampieri, Helge F. Goessling (December 2019) Sea Ice Targeted Geoengineering Can Delay Arctic Sea Ice Decline but not Global Warming, Earth's Future. DOI: 10.1029/2019ef001230
- 2018
- Lorenzo Zampieri, Helge F. Goessling, Thomas Jung (September 2018) Bright Prospects for Arctic Sea Ice Prediction on Subseasonal Time Scales, Geophysical Research Letters. DOI: 10.1029/2018gl079394
- Nils Hutter, Lorenzo Zampieri, Martin Losch (October 2018) Leads and ridges in Arctic sea ice from RGPS data and a new tracking algorithm. DOI: 10.5194/tc-2018-207
- 2016
- Peruzzo S, Cervaro V, Dalla Palma M, Delogu R, De Muri M, Fasolo D, Franchin L, Pasqualotto R, Pimazzoni A, Rizzolo A, Tollin M, Zampieri L, Serianni G (February 2016) Castellated tiles as the beam-facing components for the diagnostic calorimeter of the negative ion source SPIDER.. DOI: 10.1063/1.4934848