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 1 forecasts initialized between Thursday 14th August 2025 and Thursday 18th September 14th 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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| MicroEnsembleAIFS | 1 | MicroDuetAIFShera | 1 | 0.073087 | 0.116108 | 0.032083 | -0.053059 | 0.024044 | 0.021024 | 0.018092 | -0.044028 | 0.082055 | 0.072057 | 0.069147 | 0.117061 | | MicroEnsembleAIFS | 1 | StillLearningAIFSgaia | 3 | 0.067081 | 0.108133 | 0.02905 | -0.04808 | 0.018034 | -0.017024 | 0.019091 | -0.039074 | -0.07103 | 0.097139 | 0.059156 | 0.125035 | | MicroEnsembleAIFS | 1 | HuracanAIFSthalassa | 96 | 0.027075 | 0.032129 | 0.019037 | -0.035127 | 0.014029 | -0.00805 | 0.014039 | -0.038046 | -0.006113- | 0.036128 | 0.039129 | 0.043061 | | CMAandFDU | 2 | FengshunAdjust | 2 | 0.07085 | 0.14171 | 0.017015 | -0.016073- | 0.016005 | -0.02022 | 0.013063 | -0.038024 | 0.138095 | 0.105054 | 0.046113 | 0.087053 | | CMAandFDU | 2 | FengshunHybrid | 47 | 0.065064 | 0.119125 | 0.019002 | -0.02047 | 0.008046 | -0.002021- | 0.002037 | -0.06026 | -0.096064 | 0.101107 | 0.045122 | -0.044023 | | CMAandFDU | 2 | Fengshun | 10 | 0.012035 | 0.031086 | -0.006 | -0.008082 | 0.006048 | -0.053041 | 0.023066 | -0.023041 | -0.024008- | 0.0103 | 0.031083 | -0.05104 | | LPMicroEnsemble | 3 | LPMMicroDuet | 54 | 0.049077 | 0.074108 | 0.026049 | -0.042022 | 0.019032 | -0.0065- | 0.012105 | -0.045002 | -0.058019 | 0.035063 | 0.054109 | 0.052092 | | AIFSMicroEnsemble | 43 | AIFSheraStillLearning | 65 | 0.04077 | 0.05102 | 0.031058 | -0.018009 | 0.02404 | 0.013064 | 0.019119 | -0.029004 | -0.071002 | 0.027056 | 0.048113 | 0.019082 | | AIFSMicroEnsemble | 43 | AIFSgaiaHuracan | 79 | 0.037047 | 0.065044 | 0.01706 | -0.008045 | 0.00602 | -0.014069 | 0.007104 | -0.025005 | -0.05209 | -0.041015 | 0.036099 | -0.01204 | | AIFSLP | 4 | AIFSthalassaLPM | 8 | 0.036062 | 0.058083 | 0.018061 | -0.004014 | 0.022024 | 0.002017 | -0.0087 | 0.022019 | 0.049032 | 0.02021 | 0.04092 | -0.012021 | | scienceAIKITKangu | 5 | findforecastKanguPlusPlus | 11 | -0.0010 | -0.0010 | -0.0030 | -0.0190 | -0.0090 | -0.0070 | -0.0150.028 | -0.0060 | -0.0140 | -0.0140 | -0.0 | -0.0310 | | scienceAIKITKangu | 5 | zephyrKanguParametricPrediction | 1211 | -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 | ngcmfindforecast | 1211 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | KITKanguscienceAI | 65 | KanguPlusPluszephyr | 1211 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | -0.0 | | KITKanguscienceAI | 65 | KanguParametricPredictionngcm | 1211 | -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 | 65 | KanguS2SEasyUQ | 3539 | -1.063235 | -1.15434 | -01.984045 | -1.074357 | -01.847094 | -1.001265 | -01.952194 | -10.0876 | -1.177493 | -1.145446 | -01.957178 | -1.321673 | | CliMA | 7 | CliMAWeather2CliMAWeather | 16 | -0.1304 | -0.143039 | -0.178052 | -0.11424 | -0.084037- | 0.003063 | -0.112011 | -0.133087 | -0.147151 | -0.203024 | -0.156019 | -0.104137 | | CliMA | 7 | CliMAWeatherCliMAWeather2 | 2217 | -0.25904 | -0.303041 | -0.256049 | -0.327238 | -0.232039- | 0.119068 | -0.224008 | -0.166086 | -0.287159 | -0.34025 | -0.332017 | -0.37129 | | WindBorne | 8 | WeatherMesh | 1718 | -0.166125 | -0.125082 | -0.163206 | -0.296259 | -0.14153 | -0.424132 | -0.2202 | -0.208187 | -0.15114 | -0.163184 | -0.123141 | -0.226358 | | FengWuW2S | 9 | FengWu2 | 1819 | -0.19126 | -0.198135 | -0.289434 | -0.043255 | -0.158471 | -0.02625 | -0.219732 | -0.117042 | -0.083124 | -0.315452 | -0.358491 | -0.224126 | | FengWuW2S | 9 | FengWu | 1922 | -0.23633 | -0.332385 | -0.194331 | -0.111388 | -0.07427 | -0.172177 | -0.146462 | -0.139162 | -0.339524 | -0.427629 | -0.276393 | -0.278269 | | HAPPYSibyl | 10 | AZNClimSDE | 20 | -0.244298 | -0.259344 | -0.255306 | -0.538515 | -0.29919 | -0.069364 | -0.072277 | -0.299186 | -0.30328 | -0.219519 | -0.316315 | -0.443572 |
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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 | MicroDuetFengshunAdjust | 1 | 0.046061 | 0.081117 | -0.001029 | 0.063002 | 0.009033 | -0.034014- | 0.031003 | 0.052058 | 0.077133 | 0.0611 | 0.022072 | 0.086129 | | MicroEnsembleCMAandFDU | 1 | StillLearningFengshunHybrid | 2 | 0.043053 | 0.07808 | -0.002032 | 0.052028 | 0.005025 | 0.03302 | -0.03101 | 0.044027 | 0.06606 | 0.075065 | 0.019077 | 0.089047 | | MicroEnsembleCMAandFDU | 1 | HuracanFengshun | 714 | -0.009002 | 0.016001 | -0.019006 | 0.054029 | 0.003053 | 0.018 | -0.04308 | 0.051006 | -0.024- | 0.034007 | -0.016077 | 0.042 | 0.031078 | | CMAandFDUMicroEnsemble | 2 | FengshunAdjustStillLearning | 3 | 0.033051 | 0.071099 | 0.004006 | 0.01039 | -0.009045 | -0.004022 | -0.003019 | 0.036019 | 0.06095 | 0.084083 | 0.011055 | 0.038094 | | CMAandFDUMicroEnsemble | 2 | FengshunHybridMicroDuet | 4 | 0.029045 | 0.059087 | 0.0020 | 0.024047 | -0.016042 | -0.018013 | -0.01026 | 0.048046 | 0.045114 | 0.058017 | -0.001044 | 0.023103 | | CMAandFDUMicroEnsemble | 2 | FengshunHuracan | 138 | -0.006009 | 0.002021 | -0.003017 | 0.053 | 0.032 | -0.005044 | -0.047 | 0.009032 | 0.0240.001048 | -0.01506- | 0.002001 | -0.046059 | | LP | 3 | LPM | 5 | 0.022036 | 0.037-0.004056 | 0.026 | 0.012044 | 0.023022 | -0.059 | -0.00204 | 0.056036 | 0.039077 | 0.021024 | 0.008066 | 0.013006 | | AIFS | 4 | AIFSgaia | 6 | 0.013024 | 0.03204 | -0.003013- | 0.012032 | -0.005029 | 0.008029 | -0.018017 | -0.051 | 0.054118 | 0.001009 | -0.015033- | 0.008009 | | AIFS | 4 | AIFShera | 87 | 0.004009 | 0.013014 | -0.00902- | 0.015005 | -0.006045 | -0.01015- | 0.016009 | -0.024083 | 0.054078 | -0.011007- | 0.023019 | 0.007061 | | AIFS | 4 | AIFSthalassa | 15 | -0.016005 | -0.035028- | 0.0080 | -0.01007 | 0.002021 | 0.023026 | -0.021013 | -0.037046 | 0.00604 | -0.11308- | 0.02303 | -0.013117 | | KITKangu | 5 | KanguPlusPlus | 9 | -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 | 9 | -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 | zephyrfindforecast | 9 | -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 | ngcmzephyr | 9 | -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 | 149 | -0.010 | -0.0180 | -0.0090 | -0.0280 | -0.0040 | -0.0 | -0.010 | -0.0270 | -0.0240 | -0.0150 | -0.0250 | -0.0190 | | KITKangu | 5 | KanguS2SEasyUQ | 3439 | -1.08639 | -1.202441 | -1.004309 | -10.025861 | -01.84343 | -1.003442 | -1.014219 | -1.106261 | -1.168532 | -1.326509 | -01.955364 | -1.132174 | | CliMA | 7 | CliMAWeather2CliMAWeather | 16 | -0.1861 | -0.227138 | -0.245114 | -0.145127 | -0.086031- | 0.013024 | -0.206122 | -0.15212 | -0.22117 | -0.304269 | -0.226103- | 0.187089 | | CliMA | 7 | CliMAWeatherCliMAWeather2 | 2117 | -0.33106 | -0.389142 | -0.333123 | -0.368138 | -0.286037- | 0.202 | -0.318134 | -0.109133 | -0.35513 | -0.49278 | -0.435102- | 0.41609 | | FengWuW2S | 8 | FengWu2 | 1718 | -0.199264 | -0.261203 | -0.265457 | 0.029008 | -0.105308 | -0.09054 | -0.108301 | -0.226058 | -0.117098 | -0.33276 | -0.331616 | -0.178282 | | FengWuW2S | 8 | FengWu | 1820 | -0.25535 | -0.38476 | -0.205363 | -0.065106 | -0.064205- | 0.136007 | -0.109271 | -0.203139 | -0.37587 | -0.491678 | -0.252472 | -0.269333 | | HAPPYNordicS2S | 9 | AZNNordicS2S1 | 19 | -0.291315 | -0.328342 | -0.26824 | -0.68825 | -0.338161 | -0.021439 | -0.214153 | -0.396165 | -0.468283 | -0.227584 | -0.254259 | -0.569272 | | NordicS2S | 109 | NordicS2S1NordicS2S3 | 2027 | -0.305527 | -0.248778 | -0.33428 | -0.343111 | -0.387328 | -0.335427 | -0.48321 | -0.24477 | -0.289704 | -0.28923 | -0.333413 | -0.306589 | | NordicS2S | 109 | NordicS2S3NordicS2S2 | 2529 | -0.492606 | -0.577731 | -0.385654 | -0.298764 | -0.451222 | -0.59092 | -0.53437 | -0.267669 | -0.52278 | -0.694854 | -0.483503 | -0.559553 | | NordicS2SSibyl | 10 | NordicS2S2ClimSDE | 2721 | -0.591386 | -0.615392 | -0.609319 | -0.591779 | -0.513261 | -0.603506 | -0.727276 | -0.465345 | -0.717634 | -0.631409 | -0.57322 | -0.545 |
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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 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
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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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