This page provides an overview of regional forecast skill for the SON 2025 period. Forecast scores are updated automatically every week throughout the competitive period. The current data includes 3 4 forecasts initialized between Thursday 14th August 2025 and Thursday 28th August 4th September 2025 (inclusive). For a detailed description of the outputs, please refer to the section's overview.
...
| Expand |
|---|
| title | Forecast window 1 (days 19 to 25) |
|---|
|
| Team name | Team rank | Model name | Model rank | Global | Tropics | NHem. ExTro. | SHem. ExTro. | NHem. Polar | SHem. Polar | Europe | N. Amer. | S. Amer. | Africa | Asia | Oceania |
|---|
| MicroEnsembleCMAandFDU | 1 | MicroDuetFengshunAdjust | 1 | 0.071072 | 0.106141 | 0.05028 | 0.039001 | -0.029013 | -0.02033 | 0.072023 | 0.019029 | 0.05713 | 0.0651 | 0.094064 | 0.105114 | | MicroEnsembleCMAandFDU | 1 | StillLearningFengshunHybrid | 23 | 0.069068 | 0.103122 | 0.054036 | -0.034002 | 0.03013 | -0.01013 | 0.078019 | 0.012041 | 0.055066 | 0.087096 | 0.092076 | 0.102092 | | MicroEnsembleCMAandFDU | 1 | HuracanFengshun | 910 | 0.032019 | 0.031049 | 0.041001 | -0.029026 | 0.015011 | -0.014046 | 0.06501 | -0.015008- | 0.018024 | -0.039002 | 0.063056 | 0.057031 | | CMAandFDUMicroEnsemble | 2 | FengshunAdjustMicroDuet | 32 | 0.066072 | 0.12911 | 0.033046 | 0.012033 | 0.001028 | -0.049015 | 0.046049 | 0.022032 | 0.118057 | 0.075069 | 0.082078 | 0.117 | | CMAandFDUMicroEnsemble | 2 | FengshunHybridStillLearning | 4 | 0.065068 | 0.117103 | 0.037048 | 0.007027 | 0.016023 | -0.021007 | 0.052058 | 0.031026 | 0.044052 | 0.095 | 0.091071 | 0.092113 | | CMAandFDUMicroEnsemble | 2 | FengshunHuracan | 109 | 0.015029 | 0.049031 | -0.001035- | 0.043013 | 0.008013 | -0.048003 | 0.032034 | -0.035027 | -0.009024 | -0.01032 | 0.065049 | 0.067047 | | LP | 3 | LPM | 5 | 0.053 | 0.076074 | 0.049048 | 0.051043 | 0.01802 | -0.027015 | 0.048022 | 0.021042 | 0.03504 | 0.036026 | 0.087071 | 0.062068 | | AIFS | 4 | AIFSgaia | 6 | 0.047 | 0.073 | 0.04043 | -0.004013 | 0.021019 | -0.02303 | 0.078053 | -0.032004 | 0.032041 | 0.065053 | 0.082072 | -0.008014 | | AIFS | 4 | AIFShera | 7 | 0.044045 | 0.059 | 0.038047 | -0.002014 | 0.02021 | -0.005003 | 0.049026 | -0.034004 | 0.058056 | 0.031022 | 0.08208 | 0.061035 | | AIFS | 4 | AIFSthalassa | 8 | 0.035036 | 0.064057 | 0.01503 | -0.013034 | 0.018023 | -0.04022 | 0.019013 | -0.038003 | 0.012019 | 0.038023 | 0.068067 | -0.02008 | | KITKanguscienceAI | 5 | KanguPlusPlusfindforecast | 11 | -0.0003 | -0.0- | 0.0006- | 0.0001- | 0.0001- | 0.0012 | -0.001- | 0.001 | -0.0002 | -0.0002- | 0.0004 | -0.0002 | | KITKanguscienceAI | 5 | KanguParametricPredictionzephyr | 1112 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | scienceAI | 5 | findforecastngcm | 1112 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | scienceAIKITKangu | 56 | zephyrKanguPlusPlus | 1112 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | scienceAIKITKangu | 56 | ngcmKanguParametricPrediction | 1112 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | KITKangu | 56 | KanguS2SEasyUQ | 3835 | -1.324306 | -1.43415 | -1.221228 | -1.327346 | -1.157062 | -1.195168 | -1.167159 | -1.133208 | -1.42346 | -1.436342 | -1.263225 | -1.81472 | | CliMA | 7 | CliMAWeatherCliMAWeather2 | 16 | -0.094135 | -0.118143 | -0.107164 | -0.146157 | -0.077113 | -0.03102 | -0.039098 | -0.114161 | -0.123151 | -0.153189 | -0.121149 | -0.088096 | | CliMA | 7 | CliMAWeather2CliMAWeather | 17 | -0.095159 | -0.109194 | -0.109157 | -0.118265 | -0.095122 | -0.028043 | -0.07127 | -0.136172 | -0.102208 | -0.161228 | -0.09517 | -0.039197 | | WindBorne | 8 | WeatherMesh | 18 | -0.203196 | -0.181161 | -0.21206 | -0.26295 | -0.21192 | -0.30136 | -0.2132 | -0.229223 | -0.204185 | -0.24189 | -0.197202 | -0.228205 | | FengWuW2S | 9 | FengWu2 | 19 | -0.247223 | -0.163176 | -0.434367 | -0.085084 | -0.346262 | -0.123087 | -0.435326 | -0.145119 | -0.073088 | -0.2943 | -0.506443 | -0.175214 | | FengWuW2S | 9 | FengWu | 21 | -0.287264 | -0.3634 | -0.289247 | -0.149156 | -0.154128 | -0.176172 | -0.24519 | -0.195187 | -0.381367 | -0.463444 | -0.378334 | -0.27325 | | NordicS2S | 10 | NordicS2S1 | 20 | -0.249232 | -0.173159 | -0.285259 | -0.324321 | -0.164192 | -0.409424 | -0.193237 | -0.227201 | -0.197227 | -0.228185 | -0.153168 | -0.279236 | | NordicS2S | 10 | NordicS2S3 | 23 | -0.39362 | -0.402383 | -0.376344 | -0.402389 | -0.313266 | -0.495 | -0.29298 | -0.359297 | -0.5469 | -0.456444 | -0.29629 | -0.461455 | | NordicS2S | 10 | NordicS2S2 | 2826 | -0.556525 | -0.625576 | -0.547494 | -0.441502 | -0.393384 | -0.45753 | -0.269319 | -0.678614 | -0.725695 | -0.601485 | -0.451418 | -0.636664 |
|
| Expand |
|---|
| title | Forecast window 2 (days 26 to 32) |
|---|
|
| Team name | Team rank | Model name | Model rank | Global | Tropics | NHem. ExTro. | SHem. ExTro. | NHem. Polar | SHem. Polar | Europe | N. Amer. | S. Amer. | Africa | Asia | Oceania |
|---|
| CMAandFDU | 1 | FengshunAdjust | 1 | 0.057058 | 0.107109 | 0.025015 | 0.008006 | -0.002007 | 0.016017 | -0.008012 | 0.048049 | 0.083088 | 0.083088 | 0.049031 | 0.104082 | | CMAandFDU | 1 | FengshunHybrid | 4 | 0.046043 | 0.077079 | 0.034014 | 0.01301 | -0.015022 | 0.028022 | -0.01802 | 0.037039 | 0.046053 | 0.045053 | 0.046023 | 0.061037 | | CMAandFDU | 1 | Fengshun | 97 | 0.003009 | 0.01023 | 0.017016 | 0.015007 | 0.005002 | -0.029034 | -0.001 | 0.007015 | -0.012003 | -0.025012 | 0.034035 | -0.003021 | | MicroEnsemble | 2 | MicroDuet | 2 | 0.054053 | 0.092098 | -0.018001 | 0.035047 | -0.015001 | 0.016018 | -0.029022 | 0.029034 | 0.0931 | 0.054064 | 0.039027 | 0.10109 | | MicroEnsemble | 2 | StillLearning | 3 | 0.053049 | 0.094096 | -0.022004 | 0.02035 | -0.013005 | 0.002008 | -0.038022 | 0.013018 | 0.084086 | 0.079086 | 0.041023 | 0.112103 | | MicroEnsemble | 2 | Huracan | 78 | 0.011009 | 0.021024 | -0.001021 | 0.026037 | -0.005015 | -0.019013 | -0.012036 | 0.02022 | 0.031047 | -0.037027 | -0.001016 | 0.026003 | | LP | 3 | LPM | 5 | 0.033027 | 0.054052 | -0.02004 | 0.003008 | -0.015001 | -0.008001 | -0.013043 | 0.046041 | 0.053044 | 0.014023 | 0.039021 | 0.017003 | | AIFS | 4 | AIFSgaia | 6 | 0.024027 | 0.04048 | 0.02502 | -0.013016 | -0.003008 | -0.004001 | -0.004026 | 0.033039 | 0.078073 | -0.007012 | 0.023026 | -0.02035 | | AIFS | 4 | AIFShera | 89 | 0.009004 | 0.01401 | 0.005 | -0.008031 | -0.002004 | -0.013008 | -0.007029 | -0.006002 | 0.072056 | -0.023009 | 0.00501 | -0.001033 | | AIFS | 4 | AIFSthalassa | 15 | -0.007006 | -0.028027 | 0.013011 | -0.034021 | -0.002 | 0.024022 | -0.008022 | 0.01803 | 0.017014 | -0.126107 | 0.011 | -0.048065 | | KITKanguscienceAI | 5 | KanguPlusPlusfindforecast | 10 | -0.0002- | 0.0001 | -0.0001- | 0.0013 | -0.0005- | 0.0014 | -0.0015- | 0.0011- | 0.0003 | -0.0003 | -0.0002- | 0.0008 | | KITKanguscienceAI | 5 | KanguParametricPredictionzephyr | 1011 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | scienceAI | 5 | findforecastngcm | 1011 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | scienceAIKITKangu | 56 | zephyrKanguPlusPlus | 1011 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | scienceAIKITKangu | 56 | ngcmKanguParametricPrediction | 1011 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | KITKangu | 56 | KanguS2SEasyUQ | 3835 | -1.38351 | -1.494471 | -1.32254 | -1.22257 | -1.016008 | -1.336337 | -1.229196 | -1.431421 | -1.496412 | -1.559552 | -1.197146 | -1.388458 | | CliMA | 7 | CliMAWeatherCliMAWeather2 | 16 | -0.179214 | -0.226242 | -0.173288 | -0.232188 | -0.132113 | -0.072047 | -0.144166 | -0.11178 | -0.237225 | -0.35235 | -0.228274 | -0.111226 | | CliMA | 7 | CliMAWeather2CliMAWeather | 1718 | -0.201238 | -0.23286 | -0.255225 | -0.232234 | -0.114238 | -0.064137 | -0.131217 | -0.15314 | -0.224252 | -0.352387 | -0.267297 | -0.19526 | | NordicS2SFengWuW2S | 8 | NordicS2S1FengWu2 | 1817 | -0.26236 | -0.27257 | -0.225367- | 0.31007 | -0.172149- | 0.285047 | -0.312128 | -0.158211 | -0.325128 | -0.406332 | -0.20445 | -0.27226 | | NordicS2SFengWuW2S | 8 | NordicS2S3FengWu | 2520 | -0.507287 | -0.69393 | -0.283273 | -0.378081 | -0.25611 | -0.524133 | -0.329108 | -0.348228 | -0.696392 | -0.8517 | -0.346343 | -0.718299 | | NordicS2S | 89 | NordicS2S2NordicS2S1 | 2819 | -0.574275 | -0.648251 | -0.56263 | -0.643312 | -0.339302 | -0.498329 | -0.521383 | -0.531161 | -0.738273 | -0.69352 | -0.499267 | -0.597312 | | FengWuW2SNordicS2S | 9 | FengWu2NordicS2S3 | 1925 | -0.266498 | -0.266643 | -0.425302 | -0.00331 | -0.225395 | -0.042526 | -0.212463 | -0.257306 | -0.127605 | -0.33699 | -0.493384 | -0.304683 | | FengWuW2SNordicS2S | 9 | FengWuNordicS2S2 | 2028 | -0.312575 | -0.419603 | -0.313587 | -0.08592 | -0.138498 | -0.123563 | -0.127677 | -0.271482 | -0.429707 | -0.558677 | -0.374526 | -0.294537 | | HAPPY | 10 | AZN | 21 | -0.3934 | -0.46419 | -0.384278 | -0.854878 | -0.31331 | -0.028023 | -0.40925 | -0.354292 | -0.653598 | -0.3583 | -0.35231 | -0.728798 |
|
Figures showing aggregated RPSSs for best-performing model from top 10 teams
| Expand |
|---|
| title | Near-surface air temperature (tas), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Near-surface air temperature (tas), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Mean sea level pressure (mslp), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Mean sea level pressure (mslp), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Accumulated precipitation (pr), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Accumulated precipitation (pr), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |
Figures showing percentage of grid points with positive period-aggregated RPSSs
| Expand |
|---|
| title | Near-surface air temperature (tas), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Near-surface air temperature (tas), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Mean sea level pressure (mslp), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Mean sea level pressure (mslp), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Accumulated precipitation (pr), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Accumulated precipitation (pr), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |
Figures showing observed conditions with respect to defined ERA5 climatology
| Expand |
|---|
| title | Near-surface air temperature (tas), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Near-surface air temperature (tas), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Mean sea level pressure (mslp), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Mean sea level pressure (mslp), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Accumulated precipitation (pr), forecast window 1 (days 19 to 25) |
|---|
|
 Image Removed  Image Added |
| Expand |
|---|
| title | Accumulated precipitation (pr), forecast window 2 (days 26 to 32) |
|---|
|
 Image Removed  Image Added |