Malte Müller

• Palerme, Cyril; Lavergne, Thomas; Rusin, Jozef; Melsom, Arne; Brajard, Julien & Kvanum, Are Frode Helvig [Show all 9 contributors for this article] (2024). Improving short-term sea ice concentration forecasts using deep learning. The Cryosphere. ISSN 1994-0416. 18(4), p. 2161–2176. doi: 10.5194/tc-18-2161-2024. Show summary

  Reliable short-term sea ice forecasts are needed to support maritime operations in polar regions. While sea ice forecasts produced by physically based models still have limited accuracy, statistical post-processing techniques can be applied to reduce forecast errors. In this study, post-processing methods based on supervised machine learning have been developed for improving the skill of sea ice concentration forecasts from the TOPAZ4 prediction system for lead times from 1 to 10 d. The deep learning models use predictors from TOPAZ4 sea ice forecasts, weather forecasts, and sea ice concentration observations. Predicting the sea ice concentration for the next 10 d takes about 4 min (including data preparation), which is reasonable in an operational context. On average, the forecasts from the deep learning models have a root mean square error 41 % lower than TOPAZ4 forecasts and 29 % lower than forecasts based on persistence of sea ice concentration observations. They also significantly improve the forecasts for the location of the ice edges, with similar improvements as for the root mean square error. Furthermore, the impact of different types of predictors (observations, sea ice, and weather forecasts) on the predictions has been evaluated. Sea ice observations are the most important type of predictors, and the weather forecasts have a much stronger impact on the predictions than sea ice forecasts.

• Jeuring, Jelmer; Samuelsen, Eirik Mikal; Lamers, Machiel; Müller, Malte; Hjøllo, Bjørn Åge & Bertino, Laurent [Show all 7 contributors for this article] (2024). Map-Based Ensemble Forecasts for Maritime Operations: An Interactive Usability Assessment with Decision Scenarios. Weather, Climate, and Society. ISSN 1948-8327. 16(1), p. 235–256. doi: 10.1175/WCAS-D-23-0076.1.
• Gerland, Sebastian; Ingvaldsen, Randi Brunvær; Reigstad, Marit; Sundfjord, Arild; Bogstad, Bjarte & Chierici, Melissa [Show all 41 contributors for this article] (2023). Still Arctic? — The changing Barents Sea. Elementa: Science of the Anthropocene. ISSN 2325-1026. 11(1), p. 1–62. doi: 10.1525/elementa.2022.00088. Full text in Research Archive Show summary

  The Barents Sea is one of the Polar regions where current climate and ecosystem change is most pronounced. Here we review the current state of knowledge of the physical, chemical and biological systems in the Barents Sea. Physical conditions in this area are characterized by large seasonal contrasts between partial sea-ice cover in winter and spring versus predominantly open water in summer and autumn. Observations over recent decades show that surface air and ocean temperatures have increased, sea-ice extent has decreased, ocean stratification has weakened, and water chemistry and ecosystem components have changed, the latter in a direction often described as “Atlantification” or “borealisation,” with a less “Arctic” appearance. Temporal and spatial changes in the Barents Sea have a wider relevance, both in the context of large-scale climatic (air, water mass and sea-ice) transport processes and in comparison to other Arctic regions. These observed changes also have socioeconomic consequences, including for fisheries and other human activities. While several of the ongoing changes are monitored and quantified, observation and knowledge gaps remain, especially for winter months when field observations and sample collections are still sparse. Knowledge of the interplay of physical and biogeochemical drivers and ecosystem responses, including complex feedback processes, needs further development.

• Müller, Malte; Knol-Kauffman, Maaike; Jeuring, Jelmer & Palerme, Cyril (2023). Arctic shipping trends during hazardous weather and sea-ice conditions and the Polar Code’s effectiveness. npj Ocean Sustainability. ISSN 2731-426X. 2. doi: 10.1038/s44183-023-00021-x. Full text in Research Archive
• Bakketun, Åsmund; Blyverket, Jostein & Müller, Malte (2023). Using a reanalysis driven land surface model for initialization of a numerical weather prediction system. Weather and forecasting. ISSN 0882-8156. 38(11), p. 2155–2168. doi: 10.1175/WAF-D-22-0184.1. Full text in Research Archive
• Müller, Malte; Batrak, Yurii; Dinessen, Frode; Grote, Johannes Rafael & Wang, Keguang (2023). Challenges in the Description of Sea Ice for a Kilometer-Scale Weather Forecasting System. Weather and forecasting. ISSN 0882-8156. 38(7), p. 1157–1171. doi: 10.1175/WAF-D-22-0134.1.
• Rabault, Jean; Müller, Malte; Voermans, Joey; Brazhnikov, Dmitry; Turnbull, Ian & Marchenko, Aleksey [Show all 28 contributors for this article] (2023). A dataset of direct observations of sea ice drift and waves in ice. Scientific Data. ISSN 2052-4463. 10. doi: 10.1038/s41597-023-02160-9. Full text in Research Archive Show summary

  Variability in sea ice conditions, combined with strong couplings to the atmosphere and the ocean, lead to a broad range of complex sea ice dynamics. More in-situ measurements are needed to better identify the phenomena and mechanisms that govern sea ice growth, drift, and breakup. To this end, we have gathered a dataset of in-situ observations of sea ice drift and waves in ice. A total of 15 deployments were performed over a period of 5 years in both the Arctic and Antarctic, involving 72 instruments. These provide both GPS drift tracks, and measurements of waves in ice. The data can, in turn, be used for tuning sea ice drift models, investigating waves damping by sea ice, and helping calibrate other sea ice measurement techniques, such as satellite based observations.

• Herrmannsdörfer, Lia F; Müller, Malte; Shupe, Matthew D. & Rostosky, Philip (2023). Surface temperature comparison of the Arctic winter MOSAiC observations, ERA5 reanalysis, and MODIS satellite retrieval. Elementa: Science of the Anthropocene. ISSN 2325-1026. 11(1). doi: 10.1525/elementa.2022.00085.
• Ødemark, Karianne; Müller, Malte; Palerme, Cyril & Tveito, Ole Einar Ellingbø (2023). Recent changes in circulation patterns and their opposing impact on extreme precipitation at the west coast of Norway. Weather and Climate Extremes. ISSN 2212-0947. 39. doi: 10.1016/j.wace.2022.100530. Full text in Research Archive
• Thomas, Erin E. & Müller, Malte (2022). Characterizing vertical upper ocean temperature structures in the European Arctic through unsupervised machine learning. Ocean Modelling. ISSN 1463-5003. 177. doi: 10.1016/j.ocemod.2022.102092. Full text in Research Archive Show summary

  In-situ observations of subsurface ocean temperatures are, in many regions, inconsistently distributed in time and space. These spatio-temporal inconsistencies in the observational network lead to difficulties in utilizing those observations effectively for ocean model evaluation or understanding larger-scale ocean characteristics. Model accuracy of subsurface ocean characteristics is especially important within regions that contain complex ocean structures. One such region is the European Arctic which not only contains several types of water masses with unique characteristics, but also wintertime sea ice coverage and complex bathymetry. This study presents an unsupervised neural networking technique that can be used in combination with traditional ocean model evaluation techniques to provide additional information on the accuracy of modeled vertical ocean temperature profiles. Self-organizing maps is an unsupervised machine learning technique that we apply to approximately twenty thousand Argo and CTD temperature profiles from 2012 to 2020 in the European Arctic to categorize the observed vertical ocean temperature structures in the top 150 m. The observed ocean profile categories, or neurons, defined by the self-organizing map show strong spatial and temporal dependencies. We then use the neuron weights, or the learned temperature profile structure of each neuron, to validate the spatial and temporal variability of modeled vertical temperature structures. This analysis gives us new insights about the model’s capabilities to reproduce specific vertical structures of the top-most ocean layer within different regions and seasons. Mapping modeled ocean temperature profiles onto the neuron-space of the observationally-defined self organized map highlights the potential of this method to advance our understanding of model deficiencies in that region.

• Müller, Malte; Kelder, Timo & Palerme, Cyril (2022). Decline of sea-ice in the Greenland Sea intensifies extreme precipitation over Svalbard. Weather and Climate Extremes. ISSN 2212-0947. 36. doi: 10.1016/j.wace.2022.100437. Full text in Research Archive
• Blair, Berill; Müller, Malte; Palerme, Cyril; Blair, Rayne; Crookall, David & Knol-Kauffman, Maaike [Show all 7 contributors for this article] (2022). Coproducing Sea Ice Predictions with Stakeholders Using Simulation. Weather, Climate, and Society. ISSN 1948-8327. 14(2), p. 399–413. doi: 10.1175/WCAS-D-21-0048.1. Full text in Research Archive
• Rabault, Jean; Nose, Takehiko; Hope, Gaute; Müller, Malte; Breivik, Øyvind & Voermans, Joey [Show all 20 contributors for this article] (2022). OpenMetBuoy-v2021: An Easy-to-Build, Affordable, Customizable, Open-Source Instrument for Oceanographic Measurements of Drift and Waves in Sea Ice and the Open Ocean. Geosciences. ISSN 2076-3263. 12(3). doi: 10.3390/geosciences12030110. Full text in Research Archive
• Daher, Houraa; Arbic, Brian K.; Williams, James G.; Ansong, Joseph K.; Boggs, Dale H. & Müller, Malte [Show all 18 contributors for this article] (2021). Long-Term Earth-Moon Evolution With High-Level Orbit and Ocean Tide Models. Journal of Geophysical Research (JGR): Planets. ISSN 2169-9097. 126(12), p. 1–39. doi: 10.1029/2021JE006875.
• Thomas, Erin E.; Müller, Malte; Bohlinger, Patrik; Batrak, Yurii & Szapiro, Nicholas (2021). A Kilometer-Scale Coupled Atmosphere-Wave Forecasting System for the European Arctic. Weather and forecasting. ISSN 0882-8156. 36(6), p. 2087–2099. doi: 10.1175/WAF-D-21-0065.1. Full text in Research Archive
• von Schuckmann , Karina; Traon, Pierre-Yves; Smith, Neville; Pascual, Ananda; Djavidnia, Samuel & Gattuso, Jean-Pierre [Show all 22 contributors for this article] (2021). Copernicus Marine Service Ocean State Report, Issue 5. Journal of operational oceanography. Publisher: The Institute of Marine Engineering, Science & Technology. ISSN 1755-876X. 14(S1). doi: 10.1080/1755876X.2021.1946240. Full text in Research Archive
• Palerme, Cyril & Müller, Malte (2021). Calibration of sea ice drift forecasts using random forest algorithms. The Cryosphere. ISSN 1994-0416. 15(8), p. 3989–4004. doi: 10.5194/tc-15-3989-2021.
• von Schuckmann, K.; Le Traon, Pierre-Yves; Smith, Neville; Pascual, Ananda; Djavidnia, Samuel & Gattuso, Jean-Pierre [Show all 13 contributors for this article] (2020). Copernicus Marine Service Ocean State Report, issue 4. Journal of operational oceanography. Publisher: The Institute of Marine Engineering, Science & Technology. ISSN 1755-876X. 13(1), p. 1–172. doi: 10.1080/1755876X.2020.1785097.
• Ødemark, Karianne; Müller, Malte & Tveito, Ole Einar Ellingbø (2020). Changing lateral boundary conditions for probable maximum precipitation studies: A physically consistent approach. Journal of Hydrometeorology. ISSN 1525-755X. 22(1), p. 113–123. doi: 10.1175/JHM-D-20-0070.1. Full text in Research Archive
• Kelder, Timo; Müller, Malte; Slater, L.J.; Marjoribanks, T.I.; Wilby, R.L. & Prudhomme, Christel [Show all 9 contributors for this article] (2020). Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes. npj Climate and Atmospheric Science. ISSN 2397-3722. 3. doi: 10.1038/s41612-020-00149-4. Full text in Research Archive
• Løken, Trygve Kvåle; Rabault, Jean; Thomas, Erin E.; Müller, Malte; Christensen, Kai Håkon & Sutherland, Graig [Show all 7 contributors for this article] (2020). A comparison of wave observations in the Arctic marginal ice zone with spectral models. Proceedings of the IAHR International Symposium on ice. ISSN 2414-6331. p. 499–508.
• Løken, Trygve Kvåle; Rabault, Jean; Jensen, Atle; Sutherland, Graig; Christensen, Kai Håkon & Müller, Malte (2020). Wave measurements from ship mounted sensors in the Arctic marginal ice zone. Cold Regions Science and Technology. ISSN 0165-232X. 182. doi: 10.1016/j.coldregions.2020.103207. Full text in Research Archive
• Hegdahl, Trine J.; Engeland, Kolbjørn; Müller, Malte & Sillmann, Jana (2020). An event-based approach to explore selected present and future atmospheric river–induced floods in Western Norway. Journal of Hydrometeorology. ISSN 1525-755X. 21(9), p. 2003–2021. doi: 10.1175/JHM-D-19-0071.1. Full text in Research Archive Show summary

  The aim of this study is to investigate extreme precipitation events caused by atmospheric rivers and compare their flood impact in a warmer climate to current climate using an event-based storyline approach. The study was set up by selecting four high precipitation events from 30 years of present and future climate simulations of the high-resolution global climate model EC-Earth. The two most extreme precipitation events within the selection area for the present and future climate were identified, and EC-Earth was rerun creating 10 perturbed realizations for each event. All realizations were further downscaled with the regional weather prediction model, AROME-MetCoOp. The events were thereafter used as input to the operational Norwegian flood-forecasting model for 37 selected catchments in western Norway, and the magnitude and the spatial pattern of floods were analyzed. The role of the hydrological initial conditions, which are important for the total flooding, were analyzed with a special emphasis on snow and soil moisture excess. The results show that the selected future extreme precipitation events affected more catchments with larger floods, compared to the events from present climate. In addition, multiple realizations of the meteorological forcing and four different hydrological initial conditions, e.g. soil saturation and snow storage, were important for the estimation of the maximum flood level. The meteorological forcing (e.g. the internal variability/perturbed output) accounts for the highest contribution to the spread in flood magnitude; however, for some events and catchments the hydrological initial conditions affected the magnitudes of floods more than the meteorological forcing.

• Schaller, Nathalie; Sillmann, Jana; Müller, Malte; Haarsma, Reindert; Hazeleger, Wilco & Hegdahl, Trine Jahr [Show all 10 contributors for this article] (2020). The role of spatial and temporal model resolution in a flood event storyline approach in western Norway. Weather and Climate Extremes. ISSN 2212-0947. 29. doi: 10.1016/j.wace.2020.100259. Full text in Research Archive Show summary

  We apply a physical climate storyline approach to an autumn flood event in the West Coast of Norway caused by an atmospheric river to demonstrate the value and challenges of higher spatial and temporal resolution in simulating flood impacts. We use a modelling chain whose outputs are familiar and used operationally, for example to issue flood warnings. With two different versions of a hydrological model, we show that (1) the higher spatial resolution between the global and regional climate model is necessary to realistically simulate the high spatial variability of precipitation in this mountainous region and (2) only with hourly data are we able to capture the fast flood-generating processes leading to the peak streamflow. The higher resolution regional atmospheric model captures the fact that with the passage of an atmospheric river, some valleys receive high amounts of precipitation and others not, while the coarser resolution global model shows uniform precipitation in the whole region. Translating the event into the future leads to similar results: while in some catchments, a future flood might be much larger than a present one, in others no event occurs as the atmospheric river simply does not hit that catchment. The use of an operational flood warning system for future events is expected to facilitate stakeholder engagement.

• Haigh, Ivan D.; Pickering, Mark D.; Green, J.A. Mattias; Arbic, Brian K.; Arns, Arne & Dangendorf, Sönke [Show all 18 contributors for this article] (2020). The tides they are a-changin': A comprehensive review of past and future nonastronomical changes in tides, their driving mechanisms, and future implications. Reviews of Geophysics. ISSN 8755-1209. 58:e2018RG000636(1), p. 1–39. doi: 10.1029/2018RG000636.
• Aaboe, Signe; Aguiar, Eva; Álvarez Fanjul, Enrique; Alvera-Azcárate, Aida; Aouf, Lotfi & Barciela, Rosa [Show all 113 contributors for this article] (2019). Copernicus Marine Service Ocean State Report, Issue 3. Journal of operational oceanography. Publisher: The Institute of Marine Engineering, Science & Technology. ISSN 1755-876X. 12, p. 1–123. doi: 10.1080/1755876X.2019.1633075.
• Batrak, Yurii & Müller, Malte (2019). On the warm bias in atmospheric reanalyses induced by the missing snow over Arctic sea-ice. Nature Communications. ISSN 2041-1723. 10(1). doi: 10.1038/s41467-019-11975-3.
• Howe, Bruce M.; Arbic, Brian K.; Aucan, Jérome; Barnes, Chris; Bayliff, Nigel & Becker, Nathan [Show all 25 contributors for this article] (2019). Smart cables for observing the global ocean: Science and implementation. Frontiers in Marine Science. ISSN 2296-7745. 6. doi: 10.3389/fmars.2019.00424.
• Bohlinger, Patrik; Breivik, Øyvind; Economou, Theodoros & Müller, Malte (2019). A novel approach to computing super observations for probabilistic wave model validation. Ocean Modelling. ISSN 1463-5003. 139:101404, p. 1–10. doi: 10.1016/j.ocemod.2019.101404. Full text in Research Archive
• Palerme, Cyril; Müller, Malte & Melsom, Arne (2019). An intercomparison of verification scores for evaluating the sea ice edge position in seasonal forecasts. Geophysical Research Letters. ISSN 0094-8276. 46(9), p. 4757–4763. doi: 10.1029/2019GL082482.
• Melsom, Arne; Palerme, Cyril & Müller, Malte (2019). Validation metrics for ice edge position forecasts. Ocean Science. ISSN 1812-0784. 15(3), p. 615–630. doi: 10.5194/os-15-615-2019. Show summary

  Retreating sea ice in the Arctic Ocean gives rise to increased naval traffic with shorter navigation distances. Hence, information about the position of the sea ice edge is crucial for safe navigation. In the present study we explore methods for examining the quality of sea ice edge forecasts. We conclude that the forecast quality can be monitored with results from a set of four quantities. We also recommend the use of maps which display discrepancies in the positions of the sea ice edge.

• Sérazin, Guillaume; Penduff, Thierry; Barnier, Bernard; Molines, Jean-Marc; Arbic, Brian K. & Müller, Malte [Show all 7 contributors for this article] (2018). Inverse cascades of kinetic energy as a source of intrinsic variability: A global OGCM study. Journal of Physical Oceanography. ISSN 0022-3670. 48(6), p. 1385–1408. doi: 10.1175/JPO-D-17-0136.1.
• Batrak, Yurii & Müller, Malte (2018). Atmospheric response to kilometer‐scale changes in sea‐ice concentration within the Marginal Ice Zone. Geophysical Research Letters. ISSN 0094-8276. 45(13), p. 6702–6709. doi: 10.1029/2018GL078295.
• Li, Zhuhua; von Storch, Jin-Song & Müller, Malte (2017). The K1 internal tide simulated by a 1/10° OGCM. Ocean Modelling. ISSN 1463-5003. 113, p. 145–156. doi: 10.1016/j.ocemod.2017.04.002.
• Müller, Malte; Batrak, Yurii; Kristiansen, Jørn; Køltzow, Morten Andreas Ødegaard; Noer, Gunnar & Korosov, Anton (2017). Characteristics of a convective-scale weather forecasting system for the European Arctic. Monthly Weather Review. ISSN 0027-0644. 145(12), p. 4771–4787. doi: 10.1175/MWR-D-17-0194.1.
• Müller, Malte; Homleid, Mariken; Ivarsson, Karl-Ivar; Køltzow, Morten Andreas Ødegaard; Lindskog, Magnus & Midtbø, Knut Helge [Show all 15 contributors for this article] (2017). AROME-MetCoOp: A Nordic Convective-Scale Operational Weather Prediction Model. Weather and forecasting. ISSN 0882-8156. 32(2), p. 609–627. doi: 10.1175/WAF-D-16-0099.1.
• Li, Zhuhua; von Storch, Jin-Song & Müller, Malte (2015). The M2 Internal Tide Simulated by a 1/10° OGCM. Journal of Physical Oceanography. ISSN 0022-3670. 45(12), p. 3119–3135. doi: 10.1175/JPO-D-14-0228.1.
• Müller, Malte; Arbic, Brian K.; Richman, James G.; Shriver, Jay F.; Kunze, Eric & Scott, Robert [Show all 8 contributors for this article] (2015). Toward an internal gravity wave spectrum in global ocean models. Geophysical Research Letters. ISSN 0094-8276. 42(9), p. 3474–3481. doi: 10.1002/2015GL063365.
• Fer, Ilker; Müller, Malte & Peterson, Algot Kristoffer (2015). Tidal forcing, energetics, and mixing near the Yermak Plateau. Ocean Science. ISSN 1812-0784. 11(2), p. 287–304. doi: 10.5194/os-11-287-2015. Full text in Research Archive
• Müller, Malte; Cherniawsky, Josef Y.; Foreman, Michael G.G. & von Storch, Jin-Song (2014). Seasonal variation of the M 2 tide. Ocean Dynamics. ISSN 1616-7341. 64(2), p. 159–177. doi: 10.1007/s10236-013-0679-0.
• Gräwe, Ulf; Burchard, Hans; Müller, Malte & Schuttelaars, Henk M. (2014). Seasonal variability in M<sub>2</sub> and M<sub>4</sub> tidal constituents and its implications for the coastal residual sediment transport. Geophysical Research Letters. ISSN 0094-8276. 41(15), p. 5563–5570. doi: 10.1002/2014GL060517.
• Arbic, Brian K.; Müller, Malte; Richman, James G.; Shriver, Jay F.; Morten, Andrew J. & Scott, Robert B. [Show all 8 contributors for this article] (2014). Geostrophic turbulence in the frequency-wavenumber domain: Eddy-driven low-frequency variability. Journal of Physical Oceanography. ISSN 0022-3670. 44(8), p. 2050–2069. doi: 10.1175/JPO-D-13-054.1.
• Stammer, Detlef; Ray, Richard D.; Andersen, Ole Baltazar; Arbic, Brian K.; Bösch, Wolfgang & Carrère, Loren [Show all 27 contributors for this article] (2014). Accuracy assessment of global barotropic ocean tide models. Reviews of Geophysics. ISSN 8755-1209. 52(3), p. 243–282. doi: 10.1002/2014RG000450.
• Müller, Malte (2013). On the space- and time-dependence of barotropic-to-baroclinic tidal energy conversion. Ocean Modelling. ISSN 1463-5003. 72, p. 242–252. doi: 10.1016/j.ocemod.2013.09.007.
• Skiba, Aaron W.; Zeng, Libo; Arbic, Brian K.; Müller, Malte & Godwin, William J. (2013). On the Resonance and Shelf/Open-Ocean Coupling of the Global Diurnal Tides. Journal of Physical Oceanography. ISSN 0022-3670. 43(7), p. 1301–1324. doi: 10.1175/JPO-D-12-054.1.

View all works in Cristin

• Müller, Malte & Knol-Kauffman, Maaike (2024). Forbedret bruk av prognoser kan øke sikkerheten for arktisk shipping. Skipsrevyen. ISSN 0800-2282.
• Trubbach, Saskia; Sander, Gunnar; Knol-Kauffman, Maaike; Jeuring, Jelmer & Müller, Malte (2024). Navigating the waves of maritime safety regulations in the Norwegian Arctic. Fram Forum. ISSN 1893-5532. p. 1–10.
• Müller, Malte & Knol-Kauffman, Maaike (2023). Improved use of forecasts can increase the safety of Arctic shipping. The Circle. ISSN 2074-076X. p. 20–21.
• Müller, Malte; Batrak, Yurii; Dinessen, Frode; Grote, Johannes Rafael & Wang, Keguang (2023). Challenges in the description of sea-ice for a kilometer-scale weather forecasting system.
• Müller, Malte; Kelder, Timo & Palerme, Cyril (2023). Extreme precipitation over Svalbard and its relation to the recent decline of sea-ice in the Greenland Sea.
• Müller, Malte; Batrak, Yurii; Hermannsdörfer, Lia Francisca; Shupe, Matthew D. & Rostosky, Philip (2023). Analysis of the representation of sea ice surface temperature and radiative states in atmospheric reanalyses .
• Müller, Malte (2023). Importance of Sea - Ice - Atmosphere Interactions for Kilometer-Scale Weather Prediction .
• Müller, Malte; Batrak, Yurii; Thomas, Erin E.; Dinessen, Frode; Wang, Keguang & Williams, Timothy (2023). Towards an Arctic coupled kilometer-scale atmosphere, snow/sea-ice, ocean, and wave forecasting system.
• Knol-Kauffman, Maaike; Arbo, Peter; Jeuring, Jelmer; Müller, Malte; Palerme, Cyril & Sydnes, Maria [Show all 8 contributors for this article] (2023). Arctic risk paradoxes: Understanding activity trends and safety in Svalbard waters.
• Rabault, Jean; Müller, Malte; Hope, Gaute; Breivik, Øyvind; Nose, Takehiko & Voermans, Joey [Show all 16 contributors for this article] (2023). Collecting Marginal Ice Zone ground truth observations: recent deployments, data use, and outstanding questions.
• Müller, Malte (2022). Atmosphere, sea-ice, ocean, and wave interactions in a coupled kilometer-scale Arctic forecasting system .
• Thomas, Erin E. & Müller, Malte (2022). Characterizing Upper Ocean Temperature Structures in the European Arctic: Self-organizing Mapping for Model Validation.
• Seuthe, Lena; Bluhm, Bodil Annikki Ulla Barbro; Reigstad, Marit; Steer, Adam; Lundesgaard, Øyvind & Gerland, Sebastian [Show all 8 contributors for this article] (2022). Beyond satellite observations of sea ice. Fram Forum. ISSN 1893-5532.
• Thomas, Erin E.; Müller, Malte; Szapiro, Nicholas; Bohlinger, Patrik; Batrak, Yurii & Palerme, Cyril (2021). An Arctic coupled kilometer-scale atmosphere, sea-ice, and wave forecasting system.
• Müller, Malte; Kelder, Timo & Palerme, Cyril (2021). Extreme precipitation over Svalbard and its relation to the recent decline of sea-ice.
• Müller, Malte; Jeuring, Jelmer; Thomas, Erin E.; Palerme, Cyril; Hjøllo, Bjørn Åge & Høylandskjær, Ståle [Show all 8 contributors for this article] (2021). Tailored probabilistic weather and sea ice forecasting services for Arctic marine operators.
• Müller, Malte; Sundfjord, Arild & Årthun, Marius (2021). Rekordlite is og økt skipstrafikk i Arktis: Hvordan forbereder vi oss på framtiden? . High North News.
• Müller, Malte; Stige, Leif Christian; Gabrielsen, Geir W.; Rinaldo, Øyvind; Knudsen, Stig Morten & Rødven, Rolf [Show all 8 contributors for this article] (2020). Arctic Frontiers side event FROM NANSEN LEGACY SCIENCE TO USEFUL KNOWLEDGE FOR SOCIETY.
• Løken, Trygve Kvåle; Rabault, Jean; Thomas, Erin E.; Müller, Malte; Christensen, Kai Håkon & Sutherland, Graig [Show all 7 contributors for this article] (2020). A comparison of wave observations in the Arctic marginal ice zone with spectral models.
• Løken, Trygve Kvåle; Rabault, Jean; Jensen, Atle; Sutherland, Graig; Christensen, Kai Håkon & Müller, Malte (2019). Wave measurements from ship mounted sensors in the Arctic marginal ice zone.
• Evans, Anna Kathinka Dalland; Batrak, Yurii & Müller, Malte (2019). Ny metode for varsling av vær i arktisk. Forskning.no. ISSN 1891-635X.
• Evans, Anna Kathinka Dalland; Batrak, Yurii & Müller, Malte (2019). New method for weather forecasting in the arctic. sciencenorway.no.
• Thomas, Erin E.; Batrak, Yurii; Müller, Malte; Carrasco, Ana & Sætra, Øyvind (2019). Atmosphere-Wave Coupling in an Arctic NWP System.
• Thomas, Erin E.; Batrak, Yurii; Müller, Malte; Carrasco, Ana & Sætra, Øyvind (2019). Atmosphere-Wave Coupling in a NWP System.
• Müller, Malte (2019). On the warm bias of atmospheric reanalysis over sea-ice in Arctic winter. .
• Løken, Trygve Kvåle; Rabault, Jean; Jensen, Atle; Christensen, Kai Håkon & Müller, Malte (2019). Wave statistics from ship mounted sensors in the marginal ice zone.
• Breivik, Øyvind; Rabault, Jean; Hole, Lars R; Christensen, Kai Håkon; Müller, Malte & Jensen, Atle [Show all 7 contributors for this article] (2019). Bølger i isen påvirker Arktis. Å forstå isdønningene kan forbedre værvarsler og klimamodeller. Forskning.no. ISSN 1891-635X.
• Arbic, Brian K.; Alford, Matthew H.; Ansong, Joseph K.; Buijsman, Maarten C.; Ciotti, Robert B. & Farrar, J. Thomas [Show all 27 contributors for this article] (2018). A Primer on Global Internal Tide and Internal Gravity Wave Continuum Modeling n HYCOM and MITgcm . In Chassignet, Eric P. (Eds.), New Frontiers in Operational Oceanography. GODAE OceanView. ISSN 1720549974. p. 307–392.
• Müller, Malte & Batrak, Yurii (2018). On the warm bias of atmospheric reanalysis over sea-ice in Arctic winter.
• Müller, Malte & Batrak, Yurii (2018). Convective-scale atmospheric modelling in the Arctic: Model characteristics and sensitivity to the sea-ice representation.
• Müller, Malte & Sivle, Anders Doksæter (2018). Maritimt forskning - SALIENSEAS. Skipsrevyen. ISSN 0800-2282. 5.
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