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 13 forecasts initialized between Thursday 13th November 2025 and Thursday 5th 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:

DJF 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
MicroEnsemble1MicroDuet10.0830.1070.0870.0330.0650.030.0610.1140.0250.1180.0830.064
MicroEnsemble1StillLearning20.0710.0880.0870.030.0680.0130.060.110.0120.1170.0710.052
MicroEnsemble1Huracan60.0580.0540.0860.0110.0810.020.070.124-0.0250.0290.0580.058
LP2LPM30.0670.0840.0840.0010.0760.0050.0650.121-0.0030.0850.0590.055
AIFS3AIFShera40.0630.0580.096-0.0040.0890.0180.1210.096-0.0290.0440.0820.054
AIFS3AIFSgaia70.0430.0420.077-0.0020.0430.0010.0460.11-0.0450.0210.0450.058
AIFS3AIFSthalassa90.0410.0220.0790.0120.0830.010.0650.103-0.068-0.0090.0590.064
CMAandFDU4FengshunHybrid50.060.0760.0760.0040.07-0.0020.0660.0880.0070.0760.0690.042
CMAandFDU4FengshunAdjust80.0420.0560.0450.0060.0410.0020.0510.0240.0070.0710.0540.031
CMAandFDU4Fengshun120.0090.0110.018-0.0010.013-0.0020.005-0.019-0.0450.0150.047-0.021
UWAtmosNVIDIA5DLESyMS2Sv1100.0260.0340.0250.0090.0260.0110.0430.028-0.0080.0130.0120.047
CliMA6CliMAWeather2110.0130.0230.011-0.0030.007-0.0050.0050.0010.0050.0350.01-0.008
CliMA6CliMAWeather16-0.013-0.012-0.014-0.035-0.008-0.012-0.016-0.018-0.047-0.001-0.016-0.024
scienceAI7zephyr130.009-0.010.0250.010.0320.0390.0110.038-0.033-0.0690.020.002
scienceAI7ngcm14-0.003-0.0160.0220.0030.017-0.0330.0130.026-0.048-0.0640.018-0.008
scienceAI7findforecast15-0.006-0.0070.0020.003-0.035-0.008-0.027-0.005-0.02-0.0050.0-0.017
FengWuW2S8FengWu217-0.022-0.0490.0180.002-0.021-0.016-0.009-0.037-0.071-0.0470.007-0.031
FengWuW2S8FengWu18-0.026-0.0490.015-0.012-0.043-0.005-0.019-0.033-0.081-0.036-0.0-0.041
FengWuW2S8FengWu319-0.027-0.0610.004-0.0180.0040.0220.005-0.027-0.081-0.086-0.001-0.033
JR9slowMamba20-0.046-0.051-0.04-0.0370.019-0.123-0.0060.009-0.088-0.062-0.054-0.057
NordicS2S10NordicS2S121-0.104-0.112-0.06-0.042-0.261-0.048-0.054-0.088-0.076-0.119-0.153-0.086
NordicS2S10NordicS2S222-0.115-0.17-0.043-0.013-0.15-0.099-0.116-0.071-0.109-0.194-0.084-0.157
NordicS2S10NordicS2S323-0.125-0.138-0.076-0.088-0.198-0.194-0.148-0.134-0.13-0.166-0.075-0.089
Team nameTeam rankModel nameModel rankGlobalTropicsNHem. ExTro.SHem. ExTro.NHem. PolarSHem. PolarEuropeN. Amer.S. Amer.AfricaAsiaOceania
MicroEnsemble1MicroDuet10.0540.0770.0550.0160.0290.010.0280.0640.0330.0910.0570.034
MicroEnsemble1StillLearning20.0440.0620.0540.0140.031-0.0150.0240.0610.020.090.0490.023
MicroEnsemble1Huracan50.0310.0270.05-0.0020.044-0.0020.0420.064-0.0020.0010.0340.027
CMAandFDU2FengshunHybrid30.0350.040.051-0.0010.051-0.010.0370.057-0.0030.0450.0480.017
CMAandFDU2FengshunAdjust60.0270.0280.0420.0040.048-0.0050.030.043-0.0020.0410.0370.003
CMAandFDU2Fengshun120.00.0010.001-0.020.035-0.007-0.022-0.023-0.034-0.0210.046-0.026
LP3LPM40.0350.0460.055-0.010.046-0.0430.0320.0590.0220.0560.0460.012
AIFS4AIFShera70.0260.0210.058-0.020.048-0.0090.0710.046-0.0270.0190.0580.002
AIFS4AIFSgaia80.0240.0240.047-0.0150.027-0.0110.0330.066-0.0180.0160.0280.02
AIFS4AIFSthalassa16-0.02-0.0670.037-0.0280.04-0.0230.0550.043-0.159-0.070.013-0.026
CliMA5CliMAWeather290.0090.0070.018-0.0040.0020.0130.0160.001-0.0140.0160.014-0.001
CliMA5CliMAWeather15-0.012-0.02-0.006-0.03-0.0080.016-0.004-0.025-0.038-0.009-0.005-0.021
UWAtmosNVIDIA6DLESyMS2Sv1100.0040.0060.016-0.0210.005-0.0230.03-0.007-0.012-0.0060.0180.005
scienceAI7zephyr110.002-0.0040.0080.0030.0050.011-0.0030.020.004-0.0490.0-0.011
scienceAI7findforecast13-0.003-0.0090.014-0.004-0.028-0.001-0.0320.012-0.012-0.0140.002-0.02
scienceAI7ngcm14-0.005-0.0180.014-0.0040.019-0.0270.0040.015-0.019-0.0480.014-0.014
FengWuW2S8FengWu317-0.031-0.04-0.001-0.022-0.056-0.052-0.0260.013-0.07-0.036-0.034-0.034
FengWuW2S8FengWu219-0.049-0.082-0.005-0.028-0.037-0.024-0.034-0.036-0.079-0.074-0.034-0.069
FengWuW2S8FengWu20-0.051-0.0890.002-0.03-0.041-0.021-0.02-0.023-0.084-0.076-0.036-0.099
NordicS2S9NordicS2S218-0.042-0.0580.014-0.035-0.022-0.126-0.0430.011-0.052-0.056-0.018-0.061
NordicS2S9NordicS2S122-0.105-0.151-0.051-0.016-0.132-0.05-0.044-0.079-0.095-0.133-0.119-0.149
NordicS2S9NordicS2S323-0.133-0.156-0.097-0.027-0.094-0.21-0.138-0.042-0.143-0.177-0.181-0.079
JR10slowMamba21-0.059-0.071-0.066-0.0320.027-0.083-0.009-0.049-0.091-0.077-0.06-0.028

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

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