This work introduces data-driven integration kernels, a framework that adds structure to nonlocal operator learning by explicitly separating nonlocal information aggregation from local nonlinear prediction, and demonstrates the framework for South Asian monsoon precipitation using a hierarchy of neural network models w...
S. L. Ferretti, Jerry Lin, S. Shamekh et al.· Environmental Data Science· 0 citations
A physics-inspired neural architecture that decomposes latent-state evolution into dedicated advection, diffusion, and reaction operators and achieves competitive deterministic forecast skill, with particularly strong performance at short to medium lead times, while preserving improved spectral fidelity and forecast ac...
Carlos A. Pereira, St'ephane Gaudreault, V. Dallerit et al.· arXiv.org· 5 citations
Despite their high accuracy on point-wise metrics, machine learning weather forecasting models can exhibit different failure modes such as blurring, periodic irregularities, and other unphysical spatial artifacts. This has motivated a variety of metrics to detect known failure cases. Existing metrics fix a representati...
Younes Elberkennou, Dmitri Demler, Thierry Meier et al.· 0 citations
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Rapid and spatially continuous precipitation monitoring is critical for flood, landslide, and other hydrometeorological hazard warnings, particularly in regions where rain-gauge and weather-radar networks are sparse. The coordinated use of heterogeneous satellite observations, including geostationary infrared, passive...
Yun-Fan Yang, Hao-Fei Sun, Xiu-Yu Sun et al.· 0 citations
Near-surface weather varies over tens to hundreds of meters, yet remains unresolved in analyses and forecasts. We test whether this variation can be inferred without resolving atmospheric dynamics. Combining sparse weather stations, high-resolution Earth observation, and coarse atmospheric dynamics, we infer temperatur...
Jonathan Giezendanner, Qidong Yang, Ruizhe Huang et al.· 0 citations
We present IRENE (Italian Radar Ensemble Nowcasting Experiment), a deep learning model for probabilistic short-range precipitation nowcasting over the Italian domain at \SI{1}{km} spatial and 5 min temporal resolution. IRENE adopts an encoder--forecaster architecture built on multi-scale Convolutional Gated Recurrent U...
Alessandro Camilletti, Gabriele Franch, Elena Tomasi et al.· 0 citations
Medium-range weather forecasting underpins operational and planning decisions across the energy industry. Developing competitive weather models was once the domain of national meteorological centers, but recent advances in machine-learned weather prediction (MLWP) have opened the field to industry. We present Aries, a...
Lukas Hedegaard Morsing, A. Bakhtiarnia, J. Olesen et al.· 0 citations
Subgrid parametrizations of vertical mixing in ocean models depend on free coefficients that cannot be measured directly and must be calibrated against high-fidelity references such as large-eddy simulations (LES). Existing approaches return point estimates and leave the associated uncertainty unquantified, a limitatio...
Luben M. C. Cabezas, Sacha Wendling, Aur\`ele Gallard et al.· 0 citations
This work uses unsupervised machine learning to identify eco-provinces with corresponding uncertainty measures based on output of a global simulation of phytoplankton functional types and develops a hierarchy of explainable dense ensemble networks to infer how well the eco-provinces can be detected from modeled ocean c...
Makayla McDevitt, Maike Sonnewald, S. Dutkiewicz· 0 citations
Robert Smithson's 1970 land artwork Spiral Jetty, located in the north arm of Utah's Great Salt Lake, has alternated between submergence and exposure during severe lake decline. We analyze 1,744 co-registered Landsat 4-9 and Sentinel-2 image chips spanning every year and calendar month from 1984 to 2025. A 14-feature c...
Imbalanced labels can cause frequent samples to dominate AI-based quantitative remote sensing, degrading rare-event retrieval. In rain-rate retrieval based on satellite infrared brightness temperatures, this imbalance leads to systematic underestimation of rare high-intensity rainfall. In this study, Hurdle-Retrieval M...
Fangjian Zhang, Xiaoyong Zhuge, Wenlan Wang et al.· 0 citations
