7 citations as recorded by crossref.

1. Temporal downscaling meteorological variables to unseen moments: Continuous temporal downscaling via Multi-source Spatial–temporal-wavelet feature Fusion and Time-Continuous Manifold S. Gao et al. https://doi.org/10.1016/j.isprsjprs.2025.09.001
2. Machine Learning in Climate Downscaling: A Critical Review of Methodologies, Physical Consistency, and Operational Applications H. Najafi et al. https://doi.org/10.3390/w18020271
3. Neural network based on high freedom dynamic collaboration of flows for meteorological data temporal downscaling J. Wang et al. https://doi.org/10.1016/j.isprsjprs.2026.02.017
4. A novel framework for stepless wind speed prediction via latent linear continuum flow and spatiotemporal information fusion S. Gao et al. https://doi.org/10.1016/j.neucom.2026.132776
5. Estimate energy and flow via inter-boundary attention-based algorithm for meteorological variables evolution estimation S. Gao et al. https://doi.org/10.1016/j.engappai.2026.116043
6. Machine learning for reconstructing meteorological data using ERA5 A. Rad et al. https://doi.org/10.1016/j.rineng.2026.111512
7. Hourly temporal downscaling of CMIP6 data for photovoltaic energy modelling under climate change: A case study for Portugal P. Montesino Fernández et al. https://doi.org/10.1016/j.ecmx.2026.101944