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 4 5 forecasts initialized between Thursday 14th August 2025 and Thursday 4th 11th September 2025 (inclusive). For a detailed description of the outputs, please refer to the section's overview.
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| title | Forecast window 1 (days 19 to 25) |
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| 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 |
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| CMAandFDU | 1 | FengshunAdjust | 1 | 0.072 | 0.141142 | 0.028021 | 0.001005 | -0.013016 | -0.033026 | 0.023008 | 0.029034 | 0.13146 | 0.1107 | 0.064057 | 0.114088 | | CMAandFDU | 1 | FengshunHybrid | 3 | 0.06807 | 0.122126 | 0.036026 | -0.00201 | 0.013009 | -0.013005 | -0.019005 | 0.04105 | 0.066097 | 0.096106 | 0.076066 | 0.092061 | | CMAandFDU | 1 | Fengshun | 10 | 0.019017 | 0.049041 | 0.001006 | -0.026023 | 0.011003 | -0.046049 | 0.01 | -0.008013 | 0.024016 | -0.002006 | 0.056048 | -0.031016 | | MicroEnsemble | 2 | MicroDuet | 2 | 0.072 | 0.11116 | 0.046033 | 0.033047 | 0.028019 | 0.015012 | 0.049022 | 0.032 | 0.057087 | 0.069075 | 0.07807 | 0.117113 | | MicroEnsemble | 2 | StillLearning | 4 | 0.068067 | 0.103109 | 0.048029 | 0.027043 | 0.023012 | 0.007006 | 0.058025 | 0.026024 | 0.052078 | 0.095101 | 0.071059 | 0.113116 | | MicroEnsemble | 2 | Huracan | 9 | 0.029027 | 0.031032 | 0.035021 | 0.013028 | 0.013004 | -0.003001 | 0.034015 | 0.027024- | 0.024012 | -0.032025 | 0.049038 | 0.04703 | | LPAIFS | 3 | LPMAIFSgaia | 5 | 0.053051 | 0.074084 | 0.048031 | 0.043001 | 0.02015 | -0.01502 | 0.022013 | 0.04201 | 0.04071 | 0.026063 | 0.071067 | -0.068012 | | AIFS | 43 | AIFSgaiaAIFShera | 6 | 0.04705 | 0.073068 | 0.04304 | -0.013012 | 0.019021 | -0.03007 | 0.053014 | 0.004013 | 0.041089 | 0.053039 | 0.072075 | -0.014021 | | AIFS | 43 | AIFSheraAIFSthalassa | 78 | 0.04504 | 0.059061 | 0.047026 | -0.01401 | 0.021 | -0.003006 | 0.026005 | 0.004006 | 0.056051 | 0.022037 | 0.08062 | -0.035013 | | AIFSLP | 4 | AIFSthalassaLPM | 87 | 0.03605 | 0.057073 | 0.03031 | -0.034046 | 0.023014 | -0.022009 | -0.013004- | 0.003038 | 0.019062 | 0.023035 | 0.067057 | -0.008051 | | scienceAI | 5 | findforecast | 11 | 0.003 | -0.0002 | 0.006003 | 0.001014 | -0.001012 | 0.012014 | -0.0102 | 0.01018 | -0.002006 | -0.002003 | -0.004005- | 0.002012 | | scienceAI | 5 | zephyr | 12 | -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 | ngcm | 12 | -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 | 6 | KanguPlusPlus | 12 | -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 | 6 | KanguParametricPrediction | 12 | -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 | 6 | KanguS2SEasyUQ | 35 | -1.306041 | -1.41512 | -10.228975 | -1.346076 | -10.062862 | -10.168956 | -10.159919 | -10.208976 | -1.46141 | -1.342066 | -10.22597 | -1.72369 | | CliMA | 7 | CliMAWeather2 | 16 | -0.13515 | -0.143156 | -0.164212 | -0.15715 | -0.113112 | -0.02007 | -0.098123 | -0.161182 | -0.151149 | -0.189214 | -0.149181 | -0.096136 | | CliMA | 7 | CliMAWeather | 1719 | -0.159215 | -0.194258 | -0.157205 | -0.265324 | -0.122201 | -0.043082 | -0.127192 | -0.172188 | -0.208243 | -0.228287 | -0.17246 | -0.197324 | | WindBorne | 8 | WeatherMesh | 1817 | -0.196174 | -0.161129 | -0.206187 | -0.295315 | -0.192174 | -0.36396 | -0.2192 | -0.223208 | -0.185124 | -0.189169 | -0.202166 | -0.205229 | | FengWuW2S | 9 | FengWu2 | 1918 | -0.22321 | -0.176189 | -0.367337 | -0.084076 | -0.262208 | -0.087053 | -0.326252 | -0.119108 | -0.088083 | -0.3305 | -0.443426 | -0.214245 | | FengWuW2S | 9 | FengWu | 21 | -0.264246 | -0.34328 | -0.247228 | -0.156134 | -0.128107 | -0.172163 | -0.19165 | -0.187161 | -0.367324 | -0.444424 | -0.33432 | -0.25274 | | NordicS2S | 10 | NordicS2S1 | 20 | -0.232237 | -0.159155 | -0.259255 | -0.321314 | -0.192274 | -0.424449 | -0.237279 | -0.201173 | -0.227214 | -0.18521 | -0.168183 | -0.236249 | | NordicS2S | 10 | NordicS2S3 | 23 | -0.362364 | -0.383376 | -0.344359 | -0.389335 | -0.266329 | -0.495519 | -0.298292 | -0.297316 | -0.469433 | -0.444454 | -0.29291 | -0.455414 | | NordicS2S | 10 | NordicS2S2 | 26 | -0.525517 | -0.576547 | -0.494 | -0.502448 | -0.38446 | -0.53555 | -0.319411 | -0.614535 | -0.695645 | -0.485491 | -0.418436 | -0.664618 |
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| title | Forecast window 2 (days 26 to 32) |
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| 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 |
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| CMAandFDU | 1 | FengshunAdjust | 1 | 0.058054 | 0.109102 | 0.015 | 0.00602 | -0.007012 | 0.017015 | -0.012002 | 0.049054 | 0.088085 | 0.088087 | 0.031018 | 0.08206 | | CMAandFDU | 1 | FengshunHybrid | 4 | 0.043037 | 0.079069 | 0.014011 | 0.01027 | -0.022 | 0.022028 | -0.02004 | 0.039052 | 0.053 | 0.053055 | 0.023004 | 0.037001 | | CMAandFDU | 1 | Fengshun | 79 | 0.009001 | 0.023007 | 0.016013 | 0.007019 | -0.002004 | -0.034032- | 0.001013 | 0.015024 | 0.003012 | -0.012026 | 0.035007 | -0.02106 | | MicroEnsemble | 2 | MicroDuet | 2 | 0.053052 | 0.098091 | -0.001002 | 0.047054 | -0.001008 | 0.018032 | -0.022016 | 0.034045 | 0.1084 | 0.064062 | 0.027 | 0.09076 | | MicroEnsemble | 2 | StillLearning | 3 | 0.049 | 0.096089 | -0.004001 | 0.035043 | -0.005003 | 0.008024 | -0.022019 | 0.018035 | 0.08607 | 0.086082 | 0.023 | 0.103097 | | MicroEnsemble | 2 | Huracan | 87 | 0.00901 | 0.024019 | -0.021016 | 0.037048 | -0.0150- | 0.013004 | -0.036022 | 0.022039 | 0.047028 | -0.027031 | -0.016011 | 0.003002 | | LP | 3 | LPM | 5 | 0.027025 | 0.052043 | -0.004 | 0.00802 | -0.001011- | 0.001017 | -0.04304 | 0.041052 | 0.044038 | 0.023024 | 0.021012 | -0.003014 | | AIFS | 4 | AIFSgaia | 6 | 0.027017 | 0.048031 | 0.02014 | -0.016008 | -0.008- | 0.001005 | -0.026008 | 0.039056 | 0.073057 | -0.012002 | -0.026006 | -0.035048 | | AIFS | 4 | AIFShera | 98 | 0.004003 | 0.01006 | -0.005001 | -0.031007 | -0.004014- | 0.008007 | -0.029017- | 0.002021 | 0.056055 | -0.009017 | -0.01017 | -0.033018 | | AIFS | 4 | AIFSthalassa | 15 | -0.006011 | -0.027037 | 0.011003 | -0.021014 | -0.002 | 0.022036 | -0.02201 | 0.03038 | 0.014011 | -0.107123 | -0.011017 | -0.065046 | | scienceAI | 5 | findforecast | 10 | 0.002001 | -0.0010 | -0.001003 | 0.013022 | -0.005007 | 0.014012 | -0.015004 | 0.011024 | -0.003005 | -0.003008 | -0.002013 | 0.008028 | | scienceAI | 5 | zephyr | 11 | -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 | ngcm | 11 | -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 | 6 | KanguPlusPlus | 11 | -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 | 6 | KanguParametricPrediction | 11 | -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 | 6 | KanguS2SEasyUQ | 3534 | -1.351076 | -1.471179 | -10.254995 | -10.257993 | -10.008792 | -1.337065 | -10.196952 | -1.421141 | -1.412144 | -1.552266 | -10.1469 | -1.458119 | | CliMA | 7 | CliMAWeather2 | 16 | -0.214213 | -0.242245 | -0.288296 | -0.188159 | -0.113114 | -0.047016 | -0.166228 | -0.178197 | -0.225235 | -0.35334 | -0.274267 | -0.22622 | | CliMA | 7 | CliMAWeather | 18 | -0.238277 | -0.286324 | -0.225271 | -0.234267 | -0.238281 | -0.137164 | -0.217232 | -0.14117 | -0.2523 | -0.387431 | -0.297371 | -0.26326 | | FengWuW2S | 8 | FengWu2 | 17 | -0.23623 | -0.257288 | -0.367306 | 0.007012 | -0.149111 | 0.047055 | -0.128111 | -0.211223 | -0.128127 | -0.332334 | -0.45389 | -0.26302 | | FengWuW2S | 8 | FengWu | 2019 | -0.287281 | -0.39341 | -0.273227 | -0.08107 | -0.11076 | -0.133155 | -0.1081 | -0.228211 | -0.392395 | -0.517503 | -0.3433 | -0.299346 | | NordicS2S | 9 | NordicS2S1 | 1920 | -0.275288 | -0.251248 | -0.263288 | -0.312304 | -0.302387 | -0.329326 | -0.383392 | -0.161193 | -0.27325 | -0.352319 | -0.267326 | -0.312322 | | NordicS2S | 9 | NordicS2S3 | 25 | -0.498525 | -0.643659 | -0.302347 | -0.31276 | -0.395464 | -0.526554 | -0.463475 | -0.306293 | -0.605575 | -0.699715 | -0.384471 | -0.683679 | | NordicS2S | 9 | NordicS2S2 | 2827 | -0.575589 | -0.603608 | -0.587615 | -0.59263 | -0.498553 | -0.563575 | -0.677702 | -0.482501 | -0.707732 | -0.67766 | -0.526568 | -0.537534 | | HAPPY | 10 | AZN | 21 | -0.34299 | -0.419353 | -0.278252 | -0.878678 | -0.31335 | -0.0230 | -0.2521 | -0.292311 | -0.598489 | -0.3256 | -0.3128 | -0.798609 |
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Figures showing aggregated RPSSs for best-performing model from top 10 teams
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| title | Near-surface air temperature (tas), forecast window 1 (days 19 to 25) |
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| title | Near-surface air temperature (tas), forecast window 2 (days 26 to 32) |
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| title | Mean sea level pressure (mslp), forecast window 1 (days 19 to 25) |
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| title | Mean sea level pressure (mslp), forecast window 2 (days 26 to 32) |
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| title | Accumulated precipitation (pr), forecast window 1 (days 19 to 25) |
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| title | Accumulated precipitation (pr), forecast window 2 (days 26 to 32) |
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Figures showing percentage of grid points with positive period-aggregated RPSSs
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| title | Near-surface air temperature (tas), forecast window 1 (days 19 to 25) |
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| title | Near-surface air temperature (tas), forecast window 2 (days 26 to 32) |
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| title | Mean sea level pressure (mslp), forecast window 1 (days 19 to 25) |
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| title | Mean sea level pressure (mslp), forecast window 2 (days 26 to 32) |
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| title | Accumulated precipitation (pr), forecast window 1 (days 19 to 25) |
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| title | Accumulated precipitation (pr), forecast window 2 (days 26 to 32) |
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Figures showing observed conditions with respect to defined ERA5 climatology
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| title | Near-surface air temperature (tas), forecast window 1 (days 19 to 25) |
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| title | Near-surface air temperature (tas), forecast window 2 (days 26 to 32) |
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| title | Mean sea level pressure (mslp), forecast window 1 (days 19 to 25) |
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| title | Mean sea level pressure (mslp), forecast window 2 (days 26 to 32) |
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| title | Accumulated precipitation (pr), forecast window 1 (days 19 to 25) |
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| title | Accumulated precipitation (pr), forecast window 2 (days 26 to 32) |
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