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 7 forecasts initialized between Thursday 14th August 2025 and Thursday 25th September 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:

SON 2025 Regional RPSSs (Excel format)

Regional scores for the top 10 teams of global, period-aggregated, variable-averaged RPSSs

Team nameTeam rankModel nameModel rankGlobalTropicsNHem. ExTro.SHem. ExTro.NHem. PolarSHem. PolarEuropeN. Amer.S. Amer.AfricaAsiaOceania
MicroEnsemble1MicroDuet10.0710.1080.0380.0610.0350.0180.010.0520.0750.0680.0740.128
MicroEnsemble1StillLearning20.0650.0980.0380.0530.0320.0230.0130.0480.0640.090.0670.121
MicroEnsemble1Huracan90.030.0290.0260.0430.030.0170.0020.05-0.0-0.0440.0460.069
CMAandFDU2FengshunHybrid30.0580.1030.0230.0240.017-0.003-0.00.0580.0910.1020.0460.052
CMAandFDU2FengshunAdjust40.0580.1160.0150.017-0.009-0.0080.0090.0360.1220.1040.0380.072
CMAandFDU2Fengshun110.0010.022-0.007-0.0160.001-0.0690.0120.0220.016-0.0060.015-0.036
LP3LPM50.0450.0620.0340.0380.033-0.002-0.0060.0470.0490.0290.0620.065
AIFS4AIFShera60.040.0480.0350.0230.0390.0020.0190.0420.0680.0260.0510.042
AIFS4AIFSgaia70.0380.0630.0210.010.022-0.0140.0130.0370.0490.0450.0390.026
AIFS4AIFSthalassa80.030.0470.0190.0180.027-0.0060.0050.0260.0420.0220.0390.033
scienceAI5findforecast100.0010.001-0.0080.025-0.0010.01-0.0160.032-0.006-0.013-0.0180.039
scienceAI5zephyr12-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0
scienceAI5ngcm12-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0
KITKangu6KanguPlusPlus12-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0
KITKangu6KanguParametricPrediction12-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0
KITKangu6KanguS2SEasyUQ34-1.074-1.185-0.987-1.039-0.866-0.931-1.017-0.992-1.242-1.2-0.992-1.242
CliMA7CliMAWeather216-0.12-0.14-0.153-0.117-0.067-0.015-0.104-0.108-0.148-0.192-0.135-0.098
CliMA7CliMAWeather21-0.31-0.359-0.323-0.387-0.262-0.145-0.286-0.149-0.338-0.396-0.411-0.449
FengWuW2S8FengWu217-0.177-0.197-0.257-0.019-0.134-0.015-0.201-0.126-0.097-0.312-0.315-0.131
FengWuW2S8FengWu19-0.227-0.326-0.18-0.096-0.061-0.167-0.146-0.137-0.337-0.432-0.242-0.223
WindBorne9WeatherMesh18-0.182-0.16-0.139-0.311-0.129-0.482-0.2-0.202-0.202-0.164-0.105-0.24
HAPPY10AZN20-0.233-0.251-0.245-0.491-0.2950.084-0.098-0.324-0.257-0.191-0.281-0.515
Team nameTeam rankModel nameModel rankGlobalTropicsNHem. ExTro.SHem. ExTro.NHem. PolarSHem. PolarEuropeN. Amer.S. Amer.AfricaAsiaOceania
MicroEnsemble1MicroDuet10.0540.0880.0130.0610.0220.033-0.0150.0580.0610.0650.0380.101
MicroEnsemble1StillLearning20.050.0820.0150.0470.0220.037-0.0170.0510.0510.080.0390.093
MicroEnsemble1Huracan70.0170.023-0.0040.050.0170.021-0.0310.0550.006-0.0340.0060.055
CMAandFDU2FengshunAdjust30.0430.0860.0090.0080.0020.008-0.00.0410.0650.1020.0240.047
CMAandFDU2FengshunHybrid40.0380.0710.0090.0220.00.019-0.0050.0510.0390.0650.0180.042
CMAandFDU2Fengshun90.0040.0190.005-0.010.005-0.0540.0130.040.011-0.0020.006-0.04
LP3LPM50.0280.0460.0040.0180.0220.025-0.0330.0540.0240.0180.0270.04
AIFS4AIFSgaia60.0220.0430.0-0.0040.0090.016-0.0160.0510.0540.0150.00.015
AIFS4AIFShera80.0150.0240.001-0.0050.0140.017-0.0060.0240.0520.013-0.0030.027
AIFS4AIFSthalassa15-0.004-0.017-0.003-0.0040.0140.025-0.0140.0340.008-0.084-0.0070.014
KITKangu5KanguPlusPlus10-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0
KITKangu5KanguParametricPrediction10-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0
scienceAI5zephyr10-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0
scienceAI5ngcm10-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0-0.0
scienceAI5findforecast14-0.004-0.009-0.0060.0250.0120.004-0.0010.032-0.022-0.003-0.0210.026
KITKangu5KanguS2SEasyUQ32-1.124-1.244-1.05-1.073-0.91-0.99-0.999-1.143-1.171-1.411-1.032-1.132
CliMA7CliMAWeather216-0.156-0.189-0.212-0.12-0.065-0.022-0.17-0.128-0.18-0.256-0.193-0.163
CliMA7CliMAWeather20-0.35-0.403-0.371-0.397-0.287-0.225-0.258-0.154-0.35-0.478-0.483-0.47
FengWuW2S8FengWu217-0.186-0.251-0.2430.029-0.090.08-0.128-0.2-0.125-0.32-0.297-0.122
FengWuW2S8FengWu18-0.243-0.371-0.19-0.066-0.051-0.123-0.117-0.185-0.374-0.478-0.228-0.238
HAPPY9AZN19-0.261-0.318-0.232-0.604-0.250.007-0.182-0.322-0.429-0.239-0.205-0.544
WindBorne10WeatherMesh21-0.352-0.364-0.193-0.64-0.271-0.732-0.243-0.359-0.369-0.239-0.222-0.628

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