paper
2025
Observations & remote sensing
Evaluation or intercomparison of existing models
CNN / U-NetRNN / LSTM / ConvLSTMClassical ML (trees, GP, linear, kernels)0–6 hColorado State University (incl. CIRA) Journal
2025-01-01
022
Jan 2025
Tiantian Yu, V. Chandrasekar, Hao Wang et al.
IEEE Transactions on Geoscience and Remote Sensing
Colorado State University (incl. CIRA)
Dual-polarization radar with CNN, LSTM and other ML models improves snowfall estimates; CNN reaches R2 of 0.98 for accumulation at one site.
The Accuracy of Different Methods in Improving Quantitative Snowfall Estimation Based on Dual-Frequency Dual-Polarization Doppler Radar
In one sentence. Dual-polarization radar with CNN, LSTM and other ML models improves snowfall estimates; CNN reaches R2 of 0.98 for accumulation at one site.
Labels
- Topic
- Observations & remote sensing
- Type
- Evaluation or intercomparison of existing models
- Method
- CNN / U-Net, RNN / LSTM / ConvLSTM, Classical ML (trees, GP, linear, kernels)
- Time scale
- 0–6 h
- Domain
- Local / station
- Data
- Radar, Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.1109/tgrs.2025.3629129 OpenAlex:W7103996297
- Added
- 2026-10-22
Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.