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  • 1
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    A Mach-Zender digital holographic microscope with sub-micrometer resolution for imaging and tracking of marine micro-organisms (2014)
    American Institute of Physics
    Details
    Publication Date: 2014-12-01
    Print ISSN: 0034-6748
    Electronic ISSN: 1089-7623
    Topics: Electrical Engineering, Measurement and Control Technology , Physics
    Published by American Institute of Physics
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    PAPER CURRENT
  • 2
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    Sea‐Ice Forecasts With an Upgraded AWI Coupled Prediction System (2022)
    Mu, Longjiang ; Nerger, Lars ; Streffing, Jan ; [et al.]
    Details
    Publication Date: 2024-02-05
    Description: A new version of the AWI Coupled Prediction System is developed based on the Alfred Wegener Institute Climate Model v3.0. Both the ocean and the atmosphere models are upgraded or replaced, reducing the computation time by a factor of 5 at a given resolution. This allowed us to increase the ensemble size from 12 to 30, maintaining a similar resolution in both model components. The online coupled data assimilation scheme now additionally utilizes sea‐surface salinity and sea‐level anomaly as well as temperature and salinity profile observations. Results from the data assimilation demonstrate that the sea‐ice and ocean states are reasonably constrained. In particular, the temperature and salinity profile assimilation has mitigated systematic errors in the deeper ocean, although issues remain over polar regions where strong atmosphere‐ocean‐ice interaction occurs. One‐year‐long sea‐ice forecasts initialized on 1 January, 1 April, 1 July and 1 October from 2003 to 2019 are described. To correct systematic forecast errors, sea‐ice concentration from 2011 to 2019 is calibrated by trend‐adjusted quantile mapping using the preceding forecasts from 2003 to 2010. The sea‐ice edge raw forecast skill is within the range of operational global subseasonal‐to‐seasonal forecast systems, outperforming a climatological benchmark for about 2 weeks in the Arctic and about 3 weeks in the Antarctic. The calibration is much more effective in the Arctic: Calibrated sea‐ice edge forecasts outperform climatology for about 45 days in the Arctic but only 27 days in the Antarctic. Both the raw and the calibrated forecast skill exhibit strong seasonal variations.
    Description: Plain Language Summary: Ocean data sparseness and systematic model errors pose problems for the initialization of coupled seasonal forecasts, especially in polar regions. Our global forecast system follows a seamless approach with refined ocean resolution in the Arctic. The new version presented here features higher computational efficiency and utilizes more ocean and sea‐ice observations. Ice‐edge forecasts outperform a climatological benchmark for about 1 month, comparable to established systems.
    Description: Key Points: We describe an upgrade of the AWI Coupled Prediction System with new ocean and atmosphere models and more observations assimilated. Independent evaluations show advances in the new version on the analysis of the sea‐ice and ocean states against the old one. Calibrated sea‐ice edge forecasts outperform a climatological benchmark for around 1 month in both hemispheres.
    Description: National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: Deutsche Forschungsgemeinschaft
    Description: https://doi.org/10.5281/zenodo.6335383
    Description: https://github.com/FESOM/fesom2/releases/tag/AWI-CM3_v3.0
    Description: https://doi.org/10.5281/zenodo.6335498
    Description: https://oasis.cerfacs.fr/en/
    Description: https://doi.org/10.5281/zenodo.4905653
    Description: http://forge.ipsl.jussieu.fr/ioserver
    Description: https://doi.org/10.5281/zenodo.6335474
    Description: http://pdaf.awi.de/
    Description: https://doi.org/10.5281/zenodo.6481116
    Keywords: ddc:551.6 ; seamless sea ice forecast ; multivariate data assimilation ; forecast calibration ; spatial probability score
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
  • 3
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    The Arctic Ocean and the Marginal Ice Zone (MIZ) (2017)
    Norwegian Academy for Polar Research
    In:  EPIC3The Arctic Ocean and the marginal ice zone (MIZ). Interdisciplinary research, management practices and policy developments., Norwegian Academy for Polar Research, 53 p.
    Details
    Publication Date: 2018-02-18
    Description: We focus on an interdisciplinary approach to under- stand the MIZ, to highlight that the occurring Arctic change has potentially profound implications for both the natural environment and human activities. The report discusses the MIZ from natural sciences’ perspective and focuses on its properties. Additionally, the relations of the MIZ with human activities and governance is also addressed. We draw on our own (participants) conclusions about how the gained knowledge sheds the new light on our perceptions about future tourism development within the MIZ, as a case study, which was not studied in detail so far. Tourism is a fast-growing industry in the Arctic that requires an adequate un- derstanding of the fast changing and unpredictable MIZ, in order to ensure sustainable development of the region. The relations between the MIZ and tourism are studied in the contexts of natural and built environment, infrastructure development, oil and gas exploration, shipping activities, manage- ment and law regulations. It is concluded that tourism in the MIZ should be studied as a complex discipline, which takes into account natural and anthropogenic values and vulnerabilities of the MIZ, as well as challenges and opportunities caused by climate change and technology development.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Miscellaneous , notRev
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  • 4
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    Spatial Damped Anomaly Persistence of the sea ice edge as a benchmark for dynamical forecast systems (2021)
    In:  EPIC3Journal of Geophysical Research: Oceans, 126(12), ISSN: 2169-9275
    Details
    Publication Date: 2022-11-07
    Description: Accelerated loss of the sea-ice cover and increased human activities in the Arctic emphasize the need for skillful prediction of sea-ice conditions at subseasonal to seasonal (S2S) timescales. To assess the quality of predictions, dynamical forecast systems can be benchmarked against reference forecasts based on present and past observations of the ice edge. However, the simplest types of reference forecasts—persistence of the present state and climatology—do not exploit the observations optimally and thus lead to an overestimation of forecast skill. For spatial objects such as the ice-edge location, the development of damped-persistence forecasts that combine persistence and climatology in a meaningful way poses a challenge. We have developed a probabilistic reference forecast method that combines the climatologically derived probability of ice presence with initial anomalies of the ice-edge location, both derived from satellite sea-ice concentration data. No other observations, such as sea-surface temperature or sea-ice thickness, are used. We have tested and optimized the method based on minimization of the Spatial Probability Score. The resulting Spatial Damped Anomaly Persistence forecasts clearly outperform both simple persistence and climatology at subseasonal timescales. The benchmark is about as skillful as the best-performing dynamical forecast system in the S2S database. Despite using only sea-ice concentration observations, the method provides a challenging benchmark to assess the added value of dynamical forecast systems.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
    Format: application/pdf
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  • 5
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    Sea‐Ice Forecasts With an Upgraded AWI Coupled Prediction System (2022)
    American Geophysical Union (AGU)
    In:  EPIC3Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), 14(12), ISSN: 1942-2466
    Details
    Publication Date: 2023-06-23
    Description: A new version of the AWI Coupled Prediction System is developed based on the Alfred Wegener Institute Climate Model v3.0. Both the ocean and the atmosphere models are upgraded or replaced, reducing the computation time by a factor of 5 at a given resolution. This allowed us to increase the ensemble size from 12 to 30, maintaining a similar resolution in both model components. The online coupled data assimilation scheme now additionally utilizes sea-surface salinity and sea-level anomaly as well as temperature and salinity profile observations. Results from the data assimilation demonstrate that the sea-ice and ocean states are reasonably constrained. In particular, the temperature and salinity profile assimilation has mitigated systematic errors in the deeper ocean, although issues remain over polar regions where strong atmosphere-ocean-ice interaction occurs. One-year-long sea-ice forecasts initialized on 1 January, 1 April, 1 July and 1 October from 2003 to 2019 are described. To correct systematic forecast errors, sea-ice concentration from 2011 to 2019 is calibrated by trend-adjusted quantile mapping using the preceding forecasts from 2003 to 2010. The sea-ice edge raw forecast skill is within the range of operational global subseasonal-to-seasonal forecast systems, outperforming a climatological benchmark for about 2 weeks in the Arctic and about 3 weeks in the Antarctic. The calibration is much more effective in the Arctic: Calibrated sea-ice edge forecasts outperform climatology for about 45 days in the Arctic but only 27 days in the Antarctic. Both the raw and the calibrated forecast skill exhibit strong seasonal variations.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 6
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    SIPN South: six years of coordinated seasonal Antarctic sea ice predictions (2023)
    Frontiers Media SA
    In:  EPIC3Frontiers in Marine Science, Frontiers Media SA, 10, pp. 1148899-1148899, ISSN: 2296-7745
    Details
    Publication Date: 2023-06-23
    Description: Antarctic sea ice prediction has garnered increasing attention in recent years, particularly in the context of the recent record lows of February 2022 and 2023. As Antarctica becomes a climate change hotspot, as polar tourism booms, and as scientific expeditions continue to explore this remote continent, the capacity to anticipate sea ice conditions weeks to months in advance is in increasing demand. Spurred by recent studies that uncovered physical mechanisms of Antarctic sea ice predictability and by the intriguing large variations of the observed sea ice extent in recent years, the Sea Ice Prediction Network South (SIPN South) project was initiated in 2017, building upon the Arctic Sea Ice Prediction Network. The SIPN South project annually coordinates spring-to-summer predictions of Antarctic sea ice conditions, to allow robust evaluation and intercomparison, and to guide future development in polar prediction systems. In this paper, we present and discuss the initial SIPN South results collected over six summer seasons (December-February 2017-2018 to 2022-2023). We use data from 22 unique contributors spanning five continents that have together delivered more than 3000 individual forecasts of sea ice area and concentration. The SIPN South median forecast of the circumpolar sea ice area captures the sign of the recent negative anomalies, and the verifying observations are systematically included in the 10-90% range of the forecast distribution. These statements also hold at the regional level except in the Ross Sea where the systematic biases and the ensemble spread are the largest. A notable finding is that the group forecast, constructed by aggregating the data provided by each contributor, outperforms most of the individual forecasts, both at the circumpolar and regional levels. This indicates the value of combining predictions to average out model-specific errors. Finally, we find that dynamical model predictions (i.e., based on process-based general circulation models) generally perform worse than statistical model predictions (i.e., data-driven empirical models including machine learning) in representing the regional variability of sea ice concentration in summer. SIPN South is a collaborative community project that is hosted on a shared public repository. The forecast and verification data used in SIPN South are publicly available in near-real time for further use by the polar research community, and eventually, policymakers.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 7
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    Inter-comparison of Ice Presence between Different Satellite-based Observational Datasets and Initial Model Forecasts (2022)
    In:  EPIC3
    Details
    Publication Date: 2024-02-20
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 8
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    Ice Edge Verification -- Measuring the skill in our forecasts and disagreement in our observations
    In:  EPIC3
    Details
    Publication Date: 2024-02-20
    Repository Name: EPIC Alfred Wegener Institut
    Type: Thesis , notRev
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