RainNet
Introduced by Chen et al. in RainNet: A Large-Scale Imagery Dataset and Benchmark for Spatial Precipitation Downscaling
RainNet is a real (non-simuated) large-scale spatial precipitation downscaling dataset that contains 62,424 pairs of low-resolution and high-resolution precipitation maps for 17 years. Contrary to simulated data, this real dataset covers various types of real meteorological phenomena (e.g., Hurricane, Squall, etc.), and shows the physical characters - Temporal Misalignment, Temporal Sparse and Fluid Properties - that challenge the downscaling algorithms.
Source: https://github.com/neuralchen/RainNetPapers
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