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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 forecasts initialized between Thursday 14th August 2025 and Thursday 4th 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
CMAandFDU1FengshunAdjust10.0720.1410.0280.001-0.013-0.0330.0230.0290.130.10.0640.114
CMAandFDU1FengshunHybrid30.0680.1220.036-0.0020.013-0.0130.0190.0410.0660.0960.0760.092
CMAandFDU1Fengshun100.0190.0490.001-0.0260.011-0.0460.01-0.0080.024-0.0020.0560.031
MicroEnsemble2MicroDuet20.0720.110.0460.0330.0280.0150.0490.0320.0570.0690.0780.117
MicroEnsemble2StillLearning40.0680.1030.0480.0270.0230.0070.0580.0260.0520.0950.0710.113
MicroEnsemble2Huracan90.0290.0310.0350.0130.0130.0030.0340.027-0.024-0.0320.0490.047
LP3LPM50.0530.0740.0480.0430.02-0.0150.0220.0420.040.0260.0710.068
AIFS4AIFSgaia60.0470.0730.043-0.0130.019-0.030.0530.0040.0410.0530.072-0.014
AIFS4AIFShera70.0450.0590.047-0.0140.021-0.0030.0260.0040.0560.0220.080.035
AIFS4AIFSthalassa80.0360.0570.03-0.0340.023-0.0220.013-0.0030.0190.0230.067-0.008
scienceAI5findforecast110.003-0.00.0060.0010.0010.012-0.010.01-0.002-0.0020.004-0.002
scienceAI5zephyr120.0-0.0-0.0-0.00.00.00.00.0-0.0-0.00.0-0.0
scienceAI5ngcm120.0-0.0-0.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu6KanguPlusPlus120.0-0.0-0.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu6KanguParametricPrediction120.0-0.0-0.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu6KanguS2SEasyUQ35-1.306-1.415-1.228-1.346-1.062-1.168-1.159-1.208-1.46-1.342-1.225-1.72
CliMA7CliMAWeather216-0.135-0.143-0.164-0.157-0.113-0.02-0.098-0.161-0.151-0.189-0.149-0.096
CliMA7CliMAWeather17-0.159-0.194-0.157-0.265-0.122-0.043-0.127-0.172-0.208-0.228-0.17-0.197
WindBorne8WeatherMesh18-0.196-0.161-0.206-0.295-0.192-0.36-0.2-0.223-0.185-0.189-0.202-0.205
FengWuW2S9FengWu219-0.223-0.176-0.367-0.084-0.262-0.087-0.326-0.119-0.088-0.3-0.443-0.214
FengWuW2S9FengWu21-0.264-0.34-0.247-0.156-0.128-0.172-0.19-0.187-0.367-0.444-0.334-0.25
NordicS2S10NordicS2S120-0.232-0.159-0.259-0.321-0.192-0.424-0.237-0.201-0.227-0.185-0.168-0.236
NordicS2S10NordicS2S323-0.362-0.383-0.344-0.389-0.266-0.495-0.298-0.297-0.469-0.444-0.29-0.455
NordicS2S10NordicS2S226-0.525-0.576-0.494-0.502-0.384-0.53-0.319-0.614-0.695-0.485-0.418-0.664
Team nameTeam rankModel nameModel rankGlobalTropicsNHem. ExTro.SHem. ExTro.NHem. PolarSHem. PolarEuropeN. Amer.S. Amer.AfricaAsiaOceania
CMAandFDU1FengshunAdjust10.0580.1090.0150.006-0.0070.017-0.0120.0490.0880.0880.0310.082
CMAandFDU1FengshunHybrid40.0430.0790.0140.01-0.0220.022-0.020.0390.0530.0530.0230.037
CMAandFDU1Fengshun70.0090.0230.0160.0070.002-0.034-0.0010.0150.003-0.0120.035-0.021
MicroEnsemble2MicroDuet20.0530.098-0.0010.047-0.0010.018-0.0220.0340.10.0640.0270.09
MicroEnsemble2StillLearning30.0490.096-0.0040.035-0.0050.008-0.0220.0180.0860.0860.0230.103
MicroEnsemble2Huracan80.0090.024-0.0210.037-0.015-0.013-0.0360.0220.047-0.027-0.0160.003
LP3LPM50.0270.052-0.0040.008-0.001-0.001-0.0430.0410.0440.0230.0210.003
AIFS4AIFSgaia60.0270.0480.02-0.016-0.008-0.001-0.0260.0390.0730.0120.026-0.035
AIFS4AIFShera90.0040.010.005-0.031-0.004-0.008-0.029-0.0020.056-0.0090.01-0.033
AIFS4AIFSthalassa15-0.006-0.0270.011-0.021-0.0020.022-0.0220.030.014-0.1070.011-0.065
scienceAI5findforecast100.0020.001-0.0010.013-0.0050.014-0.0150.0110.003-0.003-0.0020.008
scienceAI5zephyr110.0-0.0-0.0-0.00.00.00.00.0-0.0-0.00.0-0.0
scienceAI5ngcm110.0-0.0-0.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu6KanguPlusPlus110.0-0.0-0.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu6KanguParametricPrediction110.0-0.0-0.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu6KanguS2SEasyUQ35-1.351-1.471-1.254-1.257-1.008-1.337-1.196-1.421-1.412-1.552-1.146-1.458
CliMA7CliMAWeather216-0.214-0.242-0.288-0.188-0.113-0.047-0.166-0.178-0.225-0.35-0.274-0.226
CliMA7CliMAWeather18-0.238-0.286-0.225-0.234-0.238-0.137-0.217-0.14-0.252-0.387-0.297-0.26
FengWuW2S8FengWu217-0.236-0.257-0.3670.007-0.1490.047-0.128-0.211-0.128-0.332-0.45-0.26
FengWuW2S8FengWu20-0.287-0.393-0.273-0.081-0.11-0.133-0.108-0.228-0.392-0.517-0.343-0.299
NordicS2S9NordicS2S119-0.275-0.251-0.263-0.312-0.302-0.329-0.383-0.161-0.273-0.352-0.267-0.312
NordicS2S9NordicS2S325-0.498-0.643-0.302-0.31-0.395-0.526-0.463-0.306-0.605-0.699-0.384-0.683
NordicS2S9NordicS2S228-0.575-0.603-0.587-0.592-0.498-0.563-0.677-0.482-0.707-0.677-0.526-0.537
HAPPY10AZN21-0.34-0.419-0.278-0.878-0.31-0.023-0.25-0.292-0.598-0.3-0.31-0.798

Figures showing aggregated RPSSs for best-performing model from top 10 teams

Figures showing percentage of grid points with positive period-aggregated RPSSs

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