CVLGMar 9, 2023

EfficientTempNet: Temporal Super-Resolution of Radar Rainfall

arXiv:2303.05552v17 citationsh-index: 46
Originality Synthesis-oriented
AI Analysis

This work addresses the need for higher temporal resolution in radar rainfall products to enhance climate change modeling, but it appears incremental as it adapts an existing method to a specific domain.

The study tackled the problem of low temporal resolution in radar rainfall data by introducing EfficientTempNet, which increased the resolution from 10 to 5 minutes, showing it as a viable option for improved climate change monitoring.

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.

Foundations

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