Rainfall data collected by various remote sensing instruments such as radars or satellites has different space-time resolutions. This study aims to improve the temporal resolution of radar rainfall products to help with more accurate climate change modeling and studies. In this direction, we introduce a solution based on EfficientNetV2, namely EfficientTempNet, to increase the temporal resolution of radar-based rainfall products from 10 minutes to 5 minutes. We tested EfficientRainNet over a dataset for the state of Iowa, US, and compared its performance to three different baselines to show that EfficientTempNet presents a viable option for better climate change monitoring.
@article{arxiv.2303.05552,
title = {EfficientTempNet: Temporal Super-Resolution of Radar Rainfall},
author = {Bekir Z Demiray and Muhammed Sit and Ibrahim Demir},
journal= {arXiv preprint arXiv:2303.05552},
year = {2023}
}
Comments
Published as a workshop paper at Tackling Climate Change with Machine Learning, ICLR 2023