We provide the experimental results of the MGMA method in SSPL framework for AVP. We implement two MGMA-Nets, including the MGMA-ResNet (RNB, built upon the classic ResNet architecture) and the MGMA-ShuffleNet (SFNB, built upon the lightweight ShuffleNet architecture), used for conducting experiments. We present the performance (RMSE, MAE) and efficiency (Params, FLOPs) metrics of our MGMA-SSPL models in predicting ERA5 variables (T2M, UV10, R and TCC). All the models are trained for 50 epochs, and they can be downloaded via the Google Drive or Baidu Netdisk links.
Method | Params | FLOPs | FPS |
---|---|---|---|
SFNB-Base | 0.37M | 2.98G | 993 |
RNB-Base | 0.48M | 3.66G | 931 |
SFNB-MGMA | 0.55M | 4.14G | 407 |
RNB-MGMA | 0.66M | 4.81G | 396 |
Method | Variable | RMSE | MAE | Config |
---|---|---|---|---|
SFNB-Base | t2m | 1.1154 | 0.7133 | configs/weather/t2m_5_625/MGMA_ShuffleV2_NONE.py |
RNB-Base | t2m | 1.1348 | 0.7339 | configs/weather/t2m_5_625/MGMA_Bottleneck_NONE.py |
SFNB-MGMA | t2m | 1.0831 | 0.6760 | configs/weather/t2m_5_625/MGMA_ShuffleV2.py |
RNB-MGMA | t2m | 1.0726 | 0.6689 | configs/weather/t2m_5_625/MGMA_Bottleneck.py |
Method | Variable | RMSE | MAE | Config |
---|---|---|---|---|
SFNB-Base | uv10 | 1.3692 | 0.9430 | configs/weather/uv10_5_625/MGMA_ShuffleV2_NONE.py |
RNB-Base | uv10 | 1.3606 | 0.9381 | configs/weather/uv10_5_625/MGMA_Bottleneck_NONE.py |
SFNB-MGMA | uv10 | 1.2938 | 0.8660 | configs/weather/uv10_5_625/MGMA_ShuffleV2.py |
RNB-MGMA | uv10 | 1.2855 | 0.8600 | configs/weather/uv10_5_625/MGMA_Bottleneck.py |
Method | Variable | RMSE | MAE | Config |
---|---|---|---|---|
SFNB-Base | r | 5.8830 | 4.1028 | configs/weather/r_5_625/MGMA_ShuffleV2_NONE.py |
RNB-Base | r | 5.8999 | 4.1061 | configs/weather/r_5_625/MGMA_Bottleneck_NONE.py |
SFNB-MGMA | r | 5.6384 | 3.8036 | configs/weather/r_5_625/MGMA_ShuffleV2.py |
RNB-MGMA | r | 5.6376 | 3.8242 | configs/weather/r_5_625/MGMA_Bottleneck.py |
Method | Variable | RMSE | MAE | Config |
---|---|---|---|---|
SFNB-Base | tcc | 0.2250 | 0.1588 | configs/weather/tcc_5_625/MGMA_ShuffleV2_NONE.py |
RNB-Base | tcc | 0.2253 | 0.1577 | configs/weather/tcc_5_625/MGMA_Bottleneck_NONE.py |
SFNB-MGMA | tcc | 0.2150 | 0.1461 | configs/weather/tcc_5_625/MGMA_ShuffleV2.py |
RNB-MGMA | tcc | 0.2150 | 0.1467 | configs/weather/tcc_5_625/MGMA_Bottleneck.py |