Skip to content
DraconiticResearch
Search Sources API
190,839 studies31 sourcesUpdated 49 min ago
PreprintCC BY 4.0EGUsphere

Explaining patterns learned by neural networks for detection of atmospheric surface fronts in gridded atmospheric data

Related

  1. Every Fixed Metric Has a Blind Spot: A Learned Atmospheric Critic for Scoring Forecast Realism
    Younes Elberkennou, Dmitri Demler, Thierry Meier +3
    arXivPreprintCC BY 4.0Full textAtmospheric science & meteorologyarXiv
  2. The ARTMIP Tier 2 Polar Synthesis: A comparative analysis of polar atmospheric river detection tools in historical and future climate states
    Kyle S. Mattingly, Michelle Maclennan, Joseph Schnaubelt +31
    EGUspherePreprintCC BY 4.0General earth scienceEGUsphere
  3. 4D Parallelism Unlocks Exascale Bayesian Neural Networks for High-Fidelity Atmospheric Modeling
    Deifilia Kieckhefen, Juan Pedro Gutiérrez Hermosillo Muriedas, Lars Helge Heyen +12
    arXivPreprintCC BY 4.0Full textAtmospheric science & meteorologyarXiv
  4. Non-dendritic hydrologic networks: foundational patterns, algorithms, and a global empirical demonstration
    David Blodgett, Taher Chegini, Ryan Gillespie +1
    EGUspherePreprintCC BY 4.0General earth scienceEGUsphere
  5. Non-linear failure patterns in urban road networks exposed to flooding
    Konstantinos Karagiorgos, Nikos I. Kavallaris, Ole Sönnerborn +2
    PLOS OnePeer-reviewedCC BY 4.0Full textHydrology & soilsPLOS
BibTeX
@misc{radke2026explaining,
  title = {{Explaining patterns learned by neural networks for detection of atmospheric surface fronts in gridded atmospheric data}},
  author = {Tim Radke and Johanna Baehr and Marc Rautenhaus},
  howpublished = {EGUsphere},
  year = {2026},
  month = oct,
  doi = {10.5194/egusphere-2026-3877},
  url = {https://doi.org/10.5194/egusphere-2026-3877},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Explaining patterns learned by neural networks for detection of atmospheric surface fronts in gridded atmospheric data
AU  - Tim Radke
AU  - Johanna Baehr
AU  - Marc Rautenhaus
PY  - 2026
DA  - 2026/10/30
PB  - EGUsphere
DO  - 10.5194/egusphere-2026-3877
UR  - https://doi.org/10.5194/egusphere-2026-3877
ER  -