This page provides an overview of regional forecast skill for the DJF 2025 period. Forecast scores are updated automatically every week throughout the competitive period. The current data includes 1 forecasts initialized between Thursday 13th November 2025 and Thursday 13th November 2025 (inclusive). For a detailed description of the outputs, please refer to the section's overview.
Regional skill score files
All regional RPSSs are available to download via the following link:
DJF 2025 Regional RPSSs (Excel format)
Regional scores for the top 10 teams of global, period-aggregated, variable-averaged RPSSs
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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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| AIFS | 1 | AIFShera | 1 | 0.16 | 0.183 | 0.081 | 0.268 | 0.091 | 0.16 | 0.019 | 0.1 | 0.132 | 0.216 | 0.095 | 0.194 | | AIFS | 1 | AIFSthalassa | 2 | 0.148 | 0.154 | 0.095 | 0.308 | 0.086 | 0.136 | 0.032 | 0.096 | 0.108 | 0.124 | 0.122 | 0.196 | | AIFS | 1 | AIFSgaia | 3 | 0.146 | 0.17 | 0.07 | 0.278 | 0.06 | 0.147 | 0.021 | 0.118 | 0.179 | 0.191 | 0.036 | 0.194 | | LP | 2 | LPM | 4 | 0.14 | 0.164 | 0.053 | 0.236 | 0.062 | 0.223 | 0.021 | 0.065 | 0.083 | 0.22 | 0.071 | 0.169 | | MicroEnsemble | 3 | StillLearning | 5 | 0.134 | 0.154 | 0.068 | 0.231 | 0.039 | 0.219 | 0.05 | 0.059 | 0.104 | 0.177 | 0.093 | 0.137 | | MicroEnsemble | 3 | MicroDuet | 6 | 0.128 | 0.158 | 0.052 | 0.225 | 0.026 | 0.192 | 0.041 | 0.045 | 0.095 | 0.198 | 0.085 | 0.118 | | MicroEnsemble | 3 | Huracan | 8 | 0.104 | 0.126 | 0.002 | 0.235 | -0.01 | 0.238 | -0.024 | 0.045 | 0.04 | 0.218 | -0.001 | 0.111 | | CMAandFDU | 4 | FengshunHybrid | 7 | 0.114 | 0.168 | 0.005 | 0.198 | 0.031 | 0.172 | -0.015 | -0.036 | 0.107 | 0.197 | 0.095 | 0.161 | | CMAandFDU | 4 | FengshunAdjust | 10 | 0.09 | 0.157 | -0.004 | 0.135 | 0.024 | 0.029 | -0.022 | -0.047 | 0.103 | 0.211 | 0.053 | 0.121 | | CMAandFDU | 4 | Fengshun | 14 | 0.007 | 0.008 | 0.048 | -0.007 | 0.01 | -0.105 | 0.053 | -0.037 | 0.043 | 0.238 | -0.025 | -0.249 | | UWAtmosNVIDIA | 5 | DLESyMS2Sv1 | 9 | 0.092 | 0.141 | 0.013 | 0.188 | 0.016 | 0.065 | 0.015 | -0.016 | 0.094 | 0.181 | 0.057 | 0.176 | | JR | 6 | slowMamba | 11 | 0.064 | 0.118 | -0.006 | 0.095 | -0.024 | 0.038 | -0.073 | -0.002 | 0.14 | 0.039 | 0.06 | 0.073 | | scienceAI | 7 | zephyr | 12 | 0.057 | 0.054 | 0.007 | 0.142 | 0.018 | 0.11 | 0.009 | -0.012 | -0.03 | 0.026 | 0.049 | 0.089 | | scienceAI | 7 | ngcm | 13 | 0.025 | 0.05 | 0.01 | 0.11 | -0.013 | -0.134 | -0.019 | -0.016 | 0.003 | -0.021 | 0.053 | 0.095 | | scienceAI | 7 | findforecast | 20 | -0.001 | -0.005 | -0.009 | 0.06 | -0.025 | 0.01 | 0.071 | -0.049 | -0.053 | 0.003 | 0.026 | -0.035 | | IgnisNeuralis42 | 8 | GCast42 | 15 | 0.002 | 0.027 | -0.006 | -0.041 | -0.004 | 0.004 | 0.084 | -0.074 | 0.015 | 0.038 | 0.054 | -0.103 | | CelestScience | 9 | Tellus | 16 | 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 | 9 | KanguS2SEasyUQ | 16 | 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 | 9 | KanguPlusPlus | 16 | 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 | 9 | KanguParametricPrediction | 16 | 0.0 | -0.0 | 0.0 | -0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 | -0.0 | 0.0 | -0.0 |
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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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| MicroEnsemble | 1 | Huracan | 1 | 0.064 | 0.052 | 0.103 | 0.06 | 0.017 | 0.067 | 0.074 | 0.126 | -0.035 | 0.008 | 0.128 | 0.049 | | MicroEnsemble | 1 | MicroDuet | 2 | 0.063 | 0.061 | 0.093 | 0.091 | 0.007 | 0.052 | 0.08 | 0.085 | -0.015 | 0.102 | 0.122 | 0.005 | | MicroEnsemble | 1 | StillLearning | 3 | 0.058 | 0.05 | 0.103 | 0.092 | 0.009 | 0.055 | 0.078 | 0.092 | -0.022 | 0.092 | 0.104 | -0.015 | | LP | 2 | LPM | 4 | 0.054 | 0.046 | 0.089 | 0.054 | 0.01 | 0.028 | 0.022 | 0.092 | 0.003 | 0.045 | 0.121 | -0.02 | | IgnisNeuralis42 | 3 | GCast42 | 5 | 0.048 | 0.089 | 0.035 | 0.07 | -0.042 | -0.043 | 0.074 | -0.003 | 0.023 | 0.057 | 0.083 | 0.074 | | AIFS | 4 | AIFShera | 6 | 0.022 | -0.055 | 0.133 | 0.005 | 0.061 | 0.069 | 0.09 | 0.12 | -0.168 | 0.085 | 0.127 | -0.122 | | AIFS | 4 | AIFSgaia | 8 | 0.017 | -0.059 | 0.129 | 0.033 | 0.062 | -0.003 | 0.093 | 0.148 | -0.114 | 0.021 | 0.095 | -0.058 | | AIFS | 4 | AIFSthalassa | 15 | -0.002 | -0.085 | 0.106 | 0.012 | 0.042 | 0.022 | 0.07 | 0.141 | -0.132 | -0.059 | 0.079 | -0.034 | | UWAtmosNVIDIA | 5 | DLESyMS2Sv1 | 7 | 0.018 | -0.013 | 0.096 | 0.037 | -0.046 | 0.036 | 0.079 | 0.052 | -0.047 | 0.059 | 0.085 | -0.013 | | scienceAI | 6 | zephyr | 9 | 0.0 | -0.042 | 0.045 | 0.003 | -0.008 | 0.067 | 0.111 | 0.002 | -0.025 | -0.042 | 0.026 | -0.035 | | scienceAI | 6 | findforecast | 16 | -0.005 | -0.008 | 0.023 | 0.03 | -0.038 | -0.055 | 0.059 | -0.018 | 0.015 | -0.001 | 0.011 | -0.032 | | scienceAI | 6 | ngcm | 21 | -0.049 | -0.087 | 0.007 | -0.015 | 0.002 | -0.099 | 0.057 | -0.026 | -0.069 | -0.038 | -0.011 | -0.073 | | CelestScience | 7 | Tellus | 10 | 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 | 7 | KanguS2SEasyUQ | 10 | 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 | 7 | KanguPlusPlus | 10 | 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 | 7 | KanguParametricPrediction | 10 | 0.0 | -0.0 | 0.0 | -0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -0.0 | -0.0 | 0.0 | -0.0 | | CliMA | 9 | CliMAWeather2 | 14 | -0.001 | -0.004 | 0.022 | 0.031 | -0.024 | -0.017 | 0.061 | -0.053 | -0.037 | 0.015 | 0.069 | 0.011 | | CliMA | 9 | CliMAWeather | 20 | -0.037 | -0.077 | 0.008 | -0.018 | -0.097 | 0.126 | 0.055 | -0.074 | -0.16 | 0.004 | 0.014 | -0.097 | | JR | 10 | slowMamba | 17 | -0.008 | -0.078 | 0.069 | 0.053 | 0.012 | 0.108 | 0.091 | -0.045 | -0.137 | -0.006 | 0.065 | 0.022 |
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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 evolution of skill scores
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| title | Weekly RPSSs for near-surface air temperature (tas), forecast window 1 (days 19 to 25) |
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| title | Weekly RPSSs for near-surface air temperature (tas), forecast window 2 (days 26 to 32) |
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| title | Weekly RPSSs for mean sea level pressure (mslp), forecast window 1 (days 19 to 25) |
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| title | Weekly RPSSs for mean sea level pressure (mslp), forecast window 2 (days 26 to 32) |
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| title | Weekly RPSSs for accumulated precipitation (pr), forecast window 1 (days 19 to 25) |
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| title | Weekly RPSSs for accumulated precipitation (pr), forecast window 2 (days 26 to 32) |
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| title | Weekly RPSSs for variable-averaged (average), forecast window 1 (days 19 to 25) |
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| title | Weekly RPSSs for variable-averaged (average), forecast window 2 (days 26 to 32) |
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| title | Aggregated RPSSs for near-surface air temperature (tas), forecast window 1 (days 19 to 25) |
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| title | Aggregated RPSSs for near-surface air temperature (tas), forecast window 2 (days 26 to 32) |
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| title | Aggregated RPSSs for mean sea level pressure (mslp), forecast window 1 (days 19 to 25) |
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| title | Aggregated RPSSs for mean sea level pressure (mslp), forecast window 2 (days 26 to 32) |
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| title | Aggregated RPSSs for accumulated precipitation (pr), forecast window 1 (days 19 to 25) |
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| title | Aggregated RPSSs for accumulated precipitation (pr), forecast window 2 (days 26 to 32) |
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| title | Aggregated RPSSs for variable-averaged (average), forecast window 1 (days 19 to 25) |
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| title | Aggregated RPSSs for variable-averaged (average), 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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