stat.AP · 2026-08-04 · No. 74

Applications, 2026-08-04.

1 new papers in stat.AP. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    Probabilistic Deep Learning for Drought Forecasting: Role of Internal Climate Variability

    Henri Funk, Cornelia Gruber, Göran Kauermann, Helmut Küchenhoff, Magdalena Mittermeier

    stat.AP · cs.LG · physics.ao-ph

    Predicting drought risk is essential for anticipating impacts on water resources, agriculture, ecosystems, and climate adaptation planning. Yet drought forecasts remain uncertain because variability can substantially alter regional precipitation and evaporative demand. Treating this variability as unstructured noise ignores the fact that internal variability has spatial, seasonal, and temporal structure and thus contains information that can...

    arxiv.org/abs/2608.01864 · PDF

This edition is part of The Daily Abstract — stat.AP archive. Subscribe to receive these in your inbox each morning, automatically translated to Spanish, with reply-to-PDF: arxivdaily.ignorelist.com.

Colophon Set in Georgia, with system sans for interface chrome and a monospaced stack for code and paper identifiers. Sole accent: amber #D99C5E. Built and served on an always-free VM. The masthead is set 14% letterspaced because newspapers do that and it works.