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    Deep Learning for Postprocessing Global Probabilistic Forecasts on Subseasonal Time Scales 

    Source: Monthly Weather Review:;2024:;volume( 152 ):;issue: 003:;page 667
    Author(s): Horat, Nina; Lerch, Sebastian
    Publisher: American Meteorological Society
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    Machine Learning Methods for Postprocessing Ensemble Forecasts of Wind Gusts: A Systematic Comparison 

    Source: Monthly Weather Review:;2022:;volume( 150 ):;issue: 001:;page 235
    Author(s): Schulz, Benedikt;Lerch, Sebastian
    Publisher: American Meteorological Society
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    Corrigendum 

    Source: Monthly Weather Review:;2023:;volume( 151 ):;issue: 005
    Author(s): Schulz, Benedikt; Lerch, Sebastian
    Publisher: American Meteorological Society
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    Corrigendum 

    Source: Monthly Weather Review:;2023:;volume( 151 ):;issue: 005:;page 1321
    Author(s): Schulz, Benedikt; Lerch, Sebastian
    Publisher: American Meteorological Society
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    Postprocessing of Ensemble Weather Forecasts Using Permutation-Invariant Neural Networks 

    Source: Artificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 001
    Author(s): Höhlein, Kevin; Schulz, Benedikt; Westermann, Rüdiger; Lerch, Sebastian
    Publisher: American Meteorological Society
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    Can Machine Learning Models Be a Suitable Tool for Predicting Central European Cold Winter Weather on Subseasonal to Seasonal Time Scales? 

    Source: Artificial Intelligence for the Earth Systems:;2023:;volume( 002 ):;issue: 004
    Author(s): Kiefer, Selina M.; Lerch, Sebastian; Ludwig, Patrick; Pinto, Joaquim G.
    Publisher: American Meteorological Society
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    Precipitation Sensitivity to the Uncertainty of Terrestrial Water Flow in WRF-Hydro: An Ensemble Analysis for Central Europe 

    Source: Journal of Hydrometeorology:;2018:;volume 019:;issue 006:;page 1007
    Author(s): Arnault, Joël; Rummler, Thomas; Baur, Florian; Lerch, Sebastian; Wagner, Sven; Fersch, Benjamin; Zhang, Zhenyu; Kerandi, Noah; Keil, Christian; Kunstmann, Harald
    Publisher: American Meteorological Society
    Abstract: AbstractPrecipitation is affected by soil moisture spatial variability. However, this variability is not well represented in atmospheric models that do not consider soil moisture transport as a three-dimensional process. ...
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    Probabilistic Predictions from Deterministic Atmospheric River Forecasts with Deep Learning 

    Source: Monthly Weather Review:;2022:;volume( 150 ):;issue: 001:;page 215
    Author(s): Chapman, William E.;Delle Monache, Luca;Alessandrini, Stefano;Subramanian, Aneesh C.;Ralph, F. Martin;Xie, Shang-Ping;Lerch, Sebastian;Hayatbini, Negin
    Publisher: American Meteorological Society
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    Waves to Weather: Exploring the Limits of Predictability of Weather 

    Source: Bulletin of the American Meteorological Society:;2021:;volume( 102 ):;issue: 011
    Author(s): Craig, George C.;Fink, Andreas H.;Hoose, Corinna;Janjić, Tijana;Knippertz, Peter;Laurian, Audine;Lerch, Sebastian;Mayer, Bernhard;Miltenberger, Annette;Redl, Robert;Riemer, Michael;Tempest, Kirsten I.;Wirth, Volkmar
    Publisher: American Meteorological Society
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    Statistical Postprocessing for Weather Forecasts: Review, Challenges, and Avenues in a Big Data World 

    Source: Bulletin of the American Meteorological Society:;2021:;volume( 102 ):;issue: 003
    Author(s): Vannitsem, Stéphane;Bremnes, John Bjørnar;Demaeyer, Jonathan;Evans, Gavin R.;Flowerdew, Jonathan;Hemri, Stephan;Lerch, Sebastian;Roberts, Nigel;Theis, Susanne;Atencia, Aitor;Ben Bouallègue, Zied;Bhend, Jonas;Dabernig, Markus;De Cruz, Lesley;Hieta, Leila;M
    Publisher: American Meteorological Society
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