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 2 3 forecasts initialized between Thursday 14th August 2025 and Thursday 21st 28th August 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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| CMAandFDUMicroEnsemble | 1 | FengshunAdjustMicroDuet | 1 | 0.086071 | 0.169106 | 0.02305 | 0.006039 | 0.002029 | -0.05902 | 0.036072 | 0.006019 | 0.15057 | 0.119065 | 0.105094 | 0.13105 | | CMAandFDUMicroEnsemble | 1 | FengshunHybridStillLearning | 2 | 0.072069 | 0.132103 | 0.026054 | -0.0034 | 0.02803 | -0.03301 | 0.038078 | 0.008012 | 0.035055 | 0.123087 | 0.116092 | 0.057102 | | CMAandFDUMicroEnsemble | 1 | FengshunHuracan | 109 | 0.016032 | 0.055031 | -0.006041- | 0.075029 | 0.032015 | -0.067014 | 0.021065 | -0.029015 | -0.02018 | -0.037039 | 0.083063 | 0.06057 | | MicroEnsembleCMAandFDU | 2 | StillLearningFengshunAdjust | 3 | 0.072066 | 0.104129 | 0.046033 | 0.027012 | 0.03001 | -0.024049 | 0.067046 | -0.01022 | 0.038118 | 0.096075 | 0.105082 | 0.071117 | | MicroEnsembleCMAandFDU | 2 | MicroDuetFengshunHybrid | 4 | 0.072065 | 0.105117 | 0.041037 | 0.026007 | 0.031016 | -0.03021 | 0.061052 | -0.0031 | 0.037044 | 0.063095 | 0.106091 | 0.077092 | | MicroEnsembleCMAandFDU | 2 | HuracanFengshun | 910 | 0.036015 | 0.034049 | -0.039001 | -0.006043 | 0.018008 | -0.022048 | 0.056032 | -0.009035- | 0.038009 | -0.03501 | 0.083065 | 0.033067 | | AIFSLP | 3 | AIFSgaiaLPM | 5 | 0.065053 | 0.097076 | 0.032049 | 0.011051 | 0.043018 | -0.009027 | 0.079048 | -0.069021 | 0.03035 | 0.094036 | 0.113087 | 0.037062 | | AIFS | 34 | AIFSheraAIFSgaia | 6 | 0.065047 | 0.082073 | 0.04404 | 0.001004 | 0.032021 | -0.01023 | 0.077078 | -0.053032 | 0.083032 | 0.045065 | 0.106082 | 0.078008 | | AIFS | 34 | AIFSthalassaAIFShera | 87 | 0.048044 | 0.082059 | 0.013038 | -0.038002 | 0.02802 | -0.055005 | 0.026049 | -0.064034 | 0.005058 | 0.067031 | 0.096082 | -0.024061 | | LPAIFS | 4 | LPMAIFSthalassa | 78 | 0.061035 | 0.08064 | 0.055015 | -0.038013 | 0.015018 | -0.00304 | 0.065019 | -0.002038 | 0.033012 | 0.041038 | 0.103068 | 0.03102 | | KITKangu | 5 | 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 | 5 | 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 | | scienceAI | 5 | findforecast | 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 | 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 | 5 | KanguS2SEasyUQ | 38 | -1.28324 | -1.37343 | -1.141221 | -1.284327 | -1.169157 | -1.235195 | -1.095167 | -1.036133 | -1.403423 | -1.37436 | -1.222263 | -1.826814 | | CliMA | 7 | CliMAWeather2CliMAWeather | 16 | -0.075094 | -0.092118 | -0.09107 | -0.192146 | -0.038077 | 0.046031 | -0.066039 | -0.109114 | -0.144123 | -0.159153 | -0.065121 | -0.012088 | | CliMA | 7 | CliMAWeatherCliMAWeather2 | 17 | -0.078095 | -0.095109 | -0.095109 | -0.197118 | -0.042095 | 0.045028 | -0.06907 | -0.113136 | -0.143102 | -0.163161 | -0.07095 | -0.019039 | | WindBorne | 8 | WeatherMesh | 18 | -0.179203 | -0.128181 | -0.23721 | -0.18926 | -0.20721 | -0.337301 | -0.244213 | -0.244229 | -0.139204 | -0.19624 | -0.176197 | -0.183228 | | FengWuW2S | 9 | FengWu2 | 19 | -0.275247 | -0.172163 | -0.467434 | -0.154085 | -0.396346 | -0.224123 | -0.509435 | -0.109145 | -0.056073 | -0.344294 | -0.564506 | -0.245175 | | FengWuW2S | 9 | FengWu | 2221 | -0.305287 | -0.38136 | -0.323289 | -0.236149 | -0.181154 | -0.103176 | -0.308245 | -0.199195 | -0.416381 | -0.512463 | -0.412378 | -0.3273 | | NordicS2S | 10 | NordicS2S1 | 20 | -0.285249 | -0.208173 | -0.372285 | -0.324 | -0.185164 | -0.39409 | -0.241193 | -0.326227 | -0.226197 | -0.257228 | -0.198153 | -0.399279 | | NordicS2S | 10 | NordicS2S3 | 23 | -0.42139 | -0.397402 | -0.506376 | -0.378402 | -0.379313 | -0.414495 | -0.40929 | -0.445359 | -0.5165 | -0.42456 | -0.387296 | -0.54461 | | NordicS2S | 10 | NordicS2S2 | 2928 | -0.573556 | -0.634625 | -0.611547 | -0.445441 | -0.418393 | -0.387457 | -0.308269 | -0.715678 | -0.82725 | -0.534601 | -0.535451 | -0.66636 |
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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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| MicroEnsembleCMAandFDU | 1 | StillLearningFengshunAdjust | 1 | 0.054057 | 0.094107 | 0.026025 | 0.033008 | -0.044002 | 0.001016 | 0.048008 | 0.026048 | 0.089083 | 0.068083 | 0.048049 | 0.123104 | | MicroEnsembleCMAandFDU | 1 | MicroDuetFengshunHybrid | 24 | 0.052046 | 0.087077 | 0.02034 | 0.053013 | -0.039015 | 0.019028 | 0.038018 | 0.047037 | 0.101046 | 0.034045 | 0.043046 | 0.107061 | | MicroEnsembleCMAandFDU | 1 | HuracanFengshun | 79 | 0.016003 | 0.02201 | 0.002017 | 0.057015 | 0.031005 | -0.005029 | 0.032001 | 0.04007 | -0.047012 | -0.052025 | 0.0034 | 0.065003 | | CMAandFDUMicroEnsemble | 2 | FengshunHybridMicroDuet | 32 | 0.048054 | 0.075092 | 0.036018 | 0.022035 | 0.009015 | 0.025016 | 0.045029 | 0.03029 | 0.045093 | 0.063054 | 0.056039 | 0.069101 | | CMAandFDUMicroEnsemble | 2 | FengshunAdjustStillLearning | 43 | 0.046053 | 0.08094 | 0.035022 | 0.01902 | 0.017013 | 0.014002 | 0.039038 | 0.048013 | 0.065084 | 0.051079 | 0.053041 | 0.131112 | | CMAandFDUMicroEnsemble | 2 | FengshunHuracan | 97 | 0.005011 | 0.018021 | -0.01001 | 0.016026 | 0.013005 | -0.031019 | 0.02012 | -0.01702- | 0.002031 | -0.014037 | 0.032001 | 0.069026 | | LP | 3 | LPM | 5 | 0.036033 | 0.065054 | 0.01802 | 0.018003 | 0.032015 | -0.026008 | 0.024013 | 0.047046 | 0.051053 | 0.031014 | 0.043039 | 0.058017 | | AIFS | 4 | AIFSgaia | 6 | 0.025024 | 0.04604 | 0.004025 | -0.024013 | -0.012003 | 0.009004 | 0.031004- | 0.004033 | 0.083078 | -0.016007 | 0.018023 | -0.03302 | | AIFS | 4 | AIFShera | 8 | 0.012009 | 0.023014 | -0.004005 | -0.023008 | -0.015002 | -0.013 | -0.036007 | -0.038006 | 0.075072 | -0.003023 | 0.007005 | 0.051001 | | AIFS | 4 | AIFSthalassa | 1015 | -0.002007 | -0.01028 | 0.007013 | -0.004034 | -0.012002 | 0.012024 | -0.02008 | 0.002018 | 0.011017 | -0.061126 | 0.009011 | -0.011048 | | KITKangu | 5 | KanguPlusPlus | 1110 | -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 | 5 | KanguParametricPrediction | 1110 | -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 | findforecast | 1110 | -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 | zephyr | 1110 | -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 | 1110 | -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 | 5 | KanguS2SEasyUQ | 38 | -1.41938 | -1.522494 | -1.37332 | -1.0922 | -1.149016 | -1.365336 | -1.237229 | -1.406431 | -1.511496 | -1.626559 | -1.306197 | -1.299388 | | CliMA | 7 | CliMAWeather | 16 | -0.173179 | -0.221226 | -0.203173 | -0.181232 | -0.094132 | -0.026072 | -0.101144 | -0.10311 | -0.155237 | -0.391352 | -0.247228 | -0.106111 | | CliMA | 7 | CliMAWeather2 | 17 | -0.181201 | -0.22723 | -0.214255 | -0.192232 | -0.1114 | -0.033064 | -0.113131 | -0.111153 | -0.171224 | -0.408352 | -0.251267 | -0.105195 | | NordicS2S | 8 | NordicS2S1 | 18 | -0.2526 | -0.27927 | -0.192225 | -0.231 | -0.153172 | -0.319285 | -0.176312 | -0.146158 | -0.284325 | -0.444406 | -0.195204 | -0.228272 | | NordicS2S | 8 | NordicS2S3 | 2425 | -0.473507 | -0.70169 | -0.245283 | -0.14378 | -0.275256 | -0.396524 | -0.214329 | -0.431348 | -0.649696 | -0.8218 | -0.338346 | -0.485718 | | NordicS2S | 8 | NordicS2S2 | 2928 | -0.581574 | -0.69648 | -0.60256 | -0.498643 | -0.299339 | -0.355498 | -0.416521 | -0.628531 | -0.671738 | -0.84969 | -0.465499 | -0.378597 | | FengWuW2S | 9 | FengWu2 | 19 | -0.255266 | -0.224266 | -0.437425 | 0.032003 | -0.256225 | 0.018042 | -0.264212 | -0.212257 | -0.066127 | -0.25733 | -0.529493 | -0.247304 | | FengWuW2S | 9 | FengWu | 20 | -0.305312 | -0.408419 | -0.315313 | -0.03508 | -0.138 | -0.107123 | -0.174127 | -0.214271 | -0.411429 | -0.517558 | -0.398374 | -0.3294 | | HAPPY | 10 | AZN | 21 | -0.41839 | -0.49346 | -0.407384 | -0.788854 | -0.226313 | -0.179028 | -0.326409 | -0.478354 | -0.761653 | -0.353358 | -0.311352 | -0.654728 |
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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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