Poster
in
Workshop: Tackling Climate Change with Machine Learning: Global Perspectives and Local Challenges

EfficientTempNet: Temporal Super-Resolution of Radar Rainfall

Bekir Demiray ⋅ Muhammed Sit ⋅ Ibrahim Demir

Keywords: Time-series analysis Climate science and climate modeling Earth science Extreme weather Computer vision and remote sensing Earth observations and monitoring

[ Poster]

Abstract

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.

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