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  • AMER METEOROLOGICAL SOC  (2)
  • Copernicus Publications  (2)
  • 1
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    AMER METEOROLOGICAL SOC
    In:  EPIC3Journal of Physical Oceanography, AMER METEOROLOGICAL SOC, 49(5), pp. 1159-1181, ISSN: 0022-3670
    Publication Date: 2019-06-11
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 2
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    AMER METEOROLOGICAL SOC
    In:  EPIC3Journal of Hydrometeorology, AMER METEOROLOGICAL SOC, 16(2), pp. 598-614, ISSN: 1525-755X
    Publication Date: 2015-06-05
    Description: Over the past decades Europe has experienced heavy floods with major consequences for thousands of people and billions of Euros worth of damage. In particular, the summer 2013 flood in Central Europe showed how vulnerable modern society is to hydrological extremes and emphasizes once more the need for improved forecast methods of such extreme climatic events. Based on a multiple linear regression model, it is shown here that 55% of the June 2013 Elbe River extreme discharge could have been predicted using May precipitation, soil moisture and sea level pressure. Moreover, our model was able to predict more than 75% of the total Elbe River discharge for June 2013 (in terms of magnitude) by incorporating also the amount of precipitation recorded during the days prior the flood, but the predicted discharge for the June 2013 event was still underestimated by 25%. Given that all predictors used in the model are available at the end of each month, the forecast scheme can be used to predict extreme events and to provide early warnings for upcoming floods. The forecast methodology could be efficient for other rivers also, depending on their location and their climatic background.
    Repository Name: EPIC Alfred Wegener Institut
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  • 3
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    Copernicus Publications
    In:  EPIC3Earth System Dynamics, Copernicus Publications, 10(1), pp. 189-203, ISSN: 2190-4979
    Publication Date: 2021-02-16
    Description: Sea ice in both polar regions is an important indicator of the expression of global climate change and its polar amplification. Consequently, broad interest exists on sea ice coverage, variability and long-term change. However, its predictability is complex and it depends strongly on different atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we applied a robust statistical model based on different oceanic and atmospheric parameters to calculate an estimate of the September sea ice extent (SSIE) on a monthly timescale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months’ oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive/critical regions in global coupled climate models with a focus on sea ice formation.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 4
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    Copernicus Publications
    In:  EPIC3Geoscientific Model Development, Copernicus Publications, 12(9), pp. 3991-4012, ISSN: 1991-959X
    Publication Date: 2019-09-16
    Description: A study of the scalability of the Finite-volumE Sea ice–Ocean circulation Model, Version 2.0 (FESOM2), the first mature global model of its kind formulated on unstructured meshes, is presented. This study includes an analysis of the main computational kernels with a special focus on bottlenecks in parallel scalability. Several model enhancements improving this scalability for large numbers of processes are described and tested. Model grids at different resolutions are used on four high-performance computing (HPC) systems with differing computational and communication hardware to demonstrate the model's scalability and throughput. Furthermore, strategies for improvements in parallel performance are presented and assessed. We show that, in terms of throughput, FESOM2 is on a par with state-of-the-art structured ocean models and, in a realistic eddy-resolving configuration (1/10∘ resolution), can achieve about 16 years per day on 14 000 cores. This suggests that unstructured-mesh models are becoming very competitive tools in high-resolution climate modeling. We show that the main bottlenecks of FESOM2 parallel scalability are the two-dimensional components of the model, namely the computations of the external (barotropic) mode and the sea-ice model. It is argued that these bottlenecks are shared with other general ocean circulation models.
    Repository Name: EPIC Alfred Wegener Institut
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