This page provides an overview of regional forecast skill for the MAM 2026 period. Forecast scores are updated automatically every week throughout the competitive period. The current data includes 3 forecasts initialized between Thursday 12th February 2026 and Thursday 26th February 2026 (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:
MAM 2026 Regional RPSSs (Excel format)
Regional scores for the top 10 teams of global, period-aggregated, variable-averaged RPSSs
| 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 | FengshunHybrid | 1 | 0.087 | 0.117 | 0.078 | 0.006 | 0.052 | 0.077 | 0.044 | 0.125 | 0.036 | 0.067 | 0.083 | 0.144 | | CMAandFDU | 1 | FengshunAdjust | 5 | 0.077 | 0.105 | 0.08 | 0.001 | -0.016 | 0.089 | 0.059 | 0.088 | 0.028 | 0.097 | 0.078 | 0.098 | | CMAandFDU | 1 | Fengshun | 15 | 0.037 | 0.036 | 0.024 | 0.011 | 0.076 | 0.032 | 0.003 | 0.085 | -0.019 | 0.022 | 0.043 | 0.088 | | AIFS | 2 | AIFSgaia | 2 | 0.083 | 0.104 | 0.081 | -0.015 | 0.06 | 0.078 | 0.009 | 0.153 | 0.01 | 0.061 | 0.091 | 0.143 | | AIFS | 2 | AIFSthalassa | 8 | 0.066 | 0.079 | 0.064 | 0.015 | 0.054 | 0.05 | -0.034 | 0.179 | -0.024 | 0.065 | 0.078 | 0.081 | | AIFS | 2 | AIFShera | 11 | 0.052 | 0.059 | 0.054 | -0.02 | 0.057 | 0.047 | -0.078 | 0.128 | -0.063 | 0.0 | 0.098 | 0.097 | | MicroEnsemble | 3 | Huracan | 3 | 0.08 | 0.114 | 0.057 | -0.006 | 0.051 | 0.072 | 0.045 | 0.101 | 0.07 | 0.054 | 0.061 | 0.173 | | MicroEnsemble | 3 | MicroDuet | 6 | 0.075 | 0.105 | 0.065 | 0.015 | 0.024 | 0.071 | 0.054 | 0.085 | 0.06 | 0.061 | 0.055 | 0.16 | | MicroEnsemble | 3 | StillLearning | 10 | 0.057 | 0.071 | 0.068 | 0.019 | 0.021 | 0.066 | 0.06 | 0.065 | 0.023 | 0.036 | 0.053 | 0.156 | | LP | 4 | LPM | 4 | 0.079 | 0.108 | 0.054 | 0.015 | 0.075 | 0.07 | -0.014 | 0.114 | 0.026 | 0.052 | 0.078 | 0.168 | | CLINT | 5 | CLINTDD | 7 | 0.066 | 0.091 | 0.041 | 0.017 | 0.066 | 0.065 | -0.019 | 0.128 | 0.066 | -0.015 | 0.045 | 0.181 | | CLINT | 5 | CLINTMF | 9 | 0.064 | 0.088 | 0.039 | 0.009 | 0.073 | 0.066 | -0.027 | 0.123 | 0.055 | -0.018 | 0.046 | 0.18 | | CLINT | 5 | CLINTSE | 12 | 0.05 | 0.072 | 0.033 | 0.004 | 0.06 | 0.023 | -0.034 | 0.133 | 0.049 | -0.043 | 0.023 | 0.173 | | scienceAI | 6 | zephyr | 13 | 0.043 | 0.039 | 0.056 | 0.003 | 0.031 | 0.041 | 0.077 | 0.086 | 0.048 | 0.013 | 0.05 | 0.035 | | scienceAI | 6 | ngcm | 14 | 0.039 | 0.033 | 0.065 | 0.014 | 0.061 | -0.015 | 0.079 | 0.063 | 0.045 | -0.018 | 0.077 | 0.061 | | scienceAI | 6 | findforecast | 23 | -0.026 | -0.063 | 0.008 | -0.033 | -0.025 | 0.028 | 0.027 | 0.006 | -0.033 | -0.097 | -0.03 | -0.066 | | JR | 7 | slowMamba | 16 | 0.034 | 0.049 | 0.033 | -0.004 | 0.065 | -0.052 | -0.014 | 0.129 | 0.044 | 0.033 | 0.035 | 0.067 | | IgnisNeuralis42 | 8 | GCast42 | 17 | 0.029 | 0.034 | 0.036 | -0.026 | 0.002 | 0.062 | 0.093 | 0.021 | 0.038 | 0.009 | 0.013 | 0.009 | | UWAtmosNVIDIA | 9 | DLESyMS2Sv1 | 18 | 0.028 | 0.031 | 0.017 | -0.061 | 0.023 | 0.074 | 0.032 | 0.022 | -0.043 | 0.04 | 0.027 | 0.059 | | SBUHybrid | 10 | HybridPPx | 19 | 0.02 | 0.002 | 0.035 | 0.01 | 0.089 | -0.007 | -0.026 | 0.088 | -0.054 | 0.024 | 0.019 | 0.022 | | SBUHybrid | 10 | HybridAC | 21 | 0.005 | -0.024 | 0.013 | 0.009 | 0.071 | 0.025 | -0.037 | 0.05 | -0.046 | -0.002 | -0.001 | -0.03 |
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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 |
|---|
| CMAandFDU | 1 | FengshunHybrid | 1 | 0.055 | 0.074 | 0.05 | -0.01 | 0.019 | 0.046 | 0.047 | 0.069 | -0.004 | 0.073 | 0.071 | 0.067 | | CMAandFDU | 1 | Fengshun | 5 | 0.038 | 0.056 | 0.022 | -0.01 | -0.0 | 0.028 | -0.048 | 0.106 | 0.001 | 0.063 | 0.012 | 0.075 | | CMAandFDU | 1 | FengshunAdjust | 7 | 0.036 | 0.068 | 0.029 | -0.018 | -0.065 | 0.047 | 0.039 | 0.041 | -0.012 | 0.097 | 0.028 | 0.036 | | MicroEnsemble | 2 | Huracan | 2 | 0.049 | 0.07 | 0.042 | -0.048 | 0.043 | 0.035 | 0.043 | 0.059 | 0.032 | 0.031 | 0.073 | 0.087 | | MicroEnsemble | 2 | MicroDuet | 4 | 0.041 | 0.053 | 0.042 | -0.017 | 0.017 | 0.042 | 0.053 | 0.033 | 0.033 | 0.023 | 0.055 | 0.063 | | MicroEnsemble | 2 | StillLearning | 11 | 0.03 | 0.034 | 0.039 | -0.013 | 0.008 | 0.032 | 0.048 | 0.023 | 0.02 | 0.005 | 0.051 | 0.059 | | LP | 3 | LPM | 3 | 0.043 | 0.064 | 0.02 | -0.007 | 0.041 | 0.039 | -0.027 | 0.064 | -0.013 | 0.045 | 0.06 | 0.065 | | CLINT | 4 | CLINTDD | 6 | 0.037 | 0.052 | 0.011 | -0.017 | 0.041 | 0.042 | -0.01 | 0.069 | -0.014 | 0.029 | 0.041 | 0.087 | | CLINT | 4 | CLINTMF | 9 | 0.035 | 0.046 | 0.013 | -0.022 | 0.045 | 0.046 | -0.013 | 0.072 | -0.025 | 0.022 | 0.044 | 0.083 | | CLINT | 4 | CLINTSE | 15 | 0.018 | 0.03 | -0.003 | -0.026 | 0.032 | 0.009 | -0.02 | 0.052 | -0.038 | 0.003 | 0.024 | 0.082 | | AIFS | 5 | AIFSgaia | 8 | 0.036 | 0.05 | 0.028 | -0.0 | 0.01 | 0.038 | -0.007 | 0.089 | -0.033 | 0.071 | 0.027 | 0.03 | | AIFS | 5 | AIFShera | 16 | 0.018 | 0.01 | 0.03 | -0.025 | 0.059 | 0.032 | -0.02 | 0.092 | -0.051 | -0.016 | 0.041 | -0.034 | | AIFS | 5 | AIFSthalassa | 21 | -0.018 | -0.066 | 0.035 | 0.012 | 0.001 | 0.022 | -0.022 | 0.08 | -0.143 | -0.053 | 0.019 | -0.057 | | IgnisNeuralis42 | 6 | GCast42 | 10 | 0.03 | 0.049 | 0.021 | -0.008 | -0.057 | 0.051 | 0.039 | -0.013 | 0.039 | 0.062 | 0.028 | -0.008 | | SBUHybrid | 7 | HybridPPx | 12 | 0.024 | 0.012 | 0.043 | -0.029 | 0.081 | -0.002 | -0.014 | 0.064 | -0.047 | 0.056 | 0.06 | -0.044 | | SBUHybrid | 7 | HybridAC | 19 | 0.004 | -0.013 | 0.029 | -0.024 | 0.025 | 0.006 | -0.002 | 0.022 | -0.027 | 0.031 | 0.022 | -0.063 | | JR | 8 | slowMamba | 13 | 0.022 | 0.038 | 0.021 | 0.001 | 0.012 | -0.054 | -0.014 | 0.072 | 0.007 | 0.016 | 0.046 | 0.037 | | UWAtmosNVIDIA | 9 | DLESyMS2Sv1 | 14 | 0.019 | 0.036 | -0.008 | -0.035 | 0.01 | 0.03 | -0.002 | 0.027 | 0.004 | 0.072 | 0.013 | -0.018 | | scienceAI | 10 | zephyr | 17 | 0.016 | 0.011 | 0.034 | -0.006 | -0.013 | 0.022 | 0.046 | 0.057 | 0.015 | -0.021 | 0.01 | -0.025 | | scienceAI | 10 | ngcm | 18 | 0.014 | 0.009 | 0.033 | 0.005 | 0.004 | -0.012 | 0.032 | 0.065 | 0.029 | -0.034 | 0.011 | -0.018 | | scienceAI | 10 | findforecast | 22 | -0.03 | -0.073 | 0.008 | -0.017 | -0.005 | 0.006 | 0.035 | -0.01 | -0.024 | -0.095 | -0.018 | -0.088 |
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Figures showing aggregated RPSSs for best-performing model from top 10 teams
Figures showing evolution of skill scores
Figures showing percentage of grid points with positive period-aggregated RPSSs
Figures showing observed conditions with respect to defined ERA5 climatology