Precipitation Refinement on CONUS
2.818RMSErNSP
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| NSP2026.04 | 2.818 | 1.444 | 0.393 | 0.076 | 0.478 | 0.527 | |
| GSMaP GC2026.04 | 2.942 | 1.473 | 0.737 | 0.147 | 0.375 | 0.49 | |
| Linear regression2026.04 | 2.967 | 1.457 | 0.709 | 0.17 | 0.299 | 0.189 | |
| IDW2026.04 | 2.987 | 1.474 | 0.645 | 0.145 | 0.352 | 0.157 | |
| ViT2026.04 | 3.059 | 1.53 | 0.687 | 0.116 | 0.411 | 0.118 | |
| CNP2026.04 | 3.115 | 1.575 | 0.699 | 0.116 | 0.34 | 0.014 | |
| U-Net2026.04 | 3.123 | 1.563 | 0.666 | 0.1 | 0.461 | 0.064 | |
| ConvCNP2026.04 | 3.135 | 1.596 | 0.684 | 0.1 | 0.475 | 0.053 | |
| Kriging2026.04 | 3.204 | 1.645 | 0.774 | 0.177 | 0.006 | 0.007 | |
| GSMaP2026.04 | 3.638 | 1.826 | 1.017 | 0.179 | 0.288 | 0.483 | |
| Cokriging2026.04 | 3.706 | 1.789 | 1.065 | 0.22 | 0.279 | 0.461 | |
| GWR2026.04 | 3.739 | 1.627 | 0.662 | 0.155 | 0.376 | 0.229 | |
| XGBoost2026.04 | 3.741 | 1.827 | 1.062 | 0.179 | 0.284 | 0.487 | |
| EMOS2026.04 | 3.885 | 1.844 | 1.115 | 0.179 | 0.305 | 0.478 | |
| Quantile mapping2026.04 | 4.073 | 2.012 | 0.885 | 0.173 | 0.288 | 0.479 |