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

Team nameTeam rankModel nameModel rankGlobalTropicsNHem. ExTro.SHem. ExTro.NHem. PolarSHem. PolarEuropeN. Amer.S. Amer.AfricaAsiaOceania
AIFS1AIFShera10.160.1830.0810.2680.0910.160.0190.10.1320.2160.0950.194
AIFS1AIFSthalassa20.1480.1540.0950.3080.0860.1360.0320.0960.1080.1240.1220.196
AIFS1AIFSgaia30.1460.170.070.2780.060.1470.0210.1180.1790.1910.0360.194
LP2LPM40.140.1640.0530.2360.0620.2230.0210.0650.0830.220.0710.169
MicroEnsemble3StillLearning50.1340.1540.0680.2310.0390.2190.050.0590.1040.1770.0930.137
MicroEnsemble3MicroDuet60.1280.1580.0520.2250.0260.1920.0410.0450.0950.1980.0850.118
MicroEnsemble3Huracan80.1040.1260.0020.235-0.010.238-0.0240.0450.040.218-0.0010.111
CMAandFDU4FengshunHybrid70.1140.1680.0050.1980.0310.172-0.015-0.0360.1070.1970.0950.161
CMAandFDU4FengshunAdjust100.090.157-0.0040.1350.0240.029-0.022-0.0470.1030.2110.0530.121
CMAandFDU4Fengshun140.0070.0080.048-0.0070.01-0.1050.053-0.0370.0430.238-0.025-0.249
UWAtmosNVIDIA5DLESyMS2Sv190.0920.1410.0130.1880.0160.0650.015-0.0160.0940.1810.0570.176
JR6slowMamba110.0640.118-0.0060.095-0.0240.038-0.073-0.0020.140.0390.060.073
scienceAI7zephyr120.0570.0540.0070.1420.0180.110.009-0.012-0.030.0260.0490.089
scienceAI7ngcm130.0250.050.010.11-0.013-0.134-0.019-0.0160.003-0.0210.0530.095
scienceAI7findforecast20-0.001-0.005-0.0090.06-0.0250.010.071-0.049-0.0530.0030.026-0.035
IgnisNeuralis428GCast42150.0020.027-0.006-0.041-0.0040.0040.084-0.0740.0150.0380.054-0.103
CelestScience9Tellus160.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu9KanguS2SEasyUQ160.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu9KanguPlusPlus160.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu9KanguParametricPrediction160.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
Team nameTeam rankModel nameModel rankGlobalTropicsNHem. ExTro.SHem. ExTro.NHem. PolarSHem. PolarEuropeN. Amer.S. Amer.AfricaAsiaOceania
MicroEnsemble1Huracan10.0640.0520.1030.060.0170.0670.0740.126-0.0350.0080.1280.049
MicroEnsemble1MicroDuet20.0630.0610.0930.0910.0070.0520.080.085-0.0150.1020.1220.005
MicroEnsemble1StillLearning30.0580.050.1030.0920.0090.0550.0780.092-0.0220.0920.104-0.015
LP2LPM40.0540.0460.0890.0540.010.0280.0220.0920.0030.0450.121-0.02
IgnisNeuralis423GCast4250.0480.0890.0350.07-0.042-0.0430.074-0.0030.0230.0570.0830.074
AIFS4AIFShera60.022-0.0550.1330.0050.0610.0690.090.12-0.1680.0850.127-0.122
AIFS4AIFSgaia80.017-0.0590.1290.0330.062-0.0030.0930.148-0.1140.0210.095-0.058
AIFS4AIFSthalassa15-0.002-0.0850.1060.0120.0420.0220.070.141-0.132-0.0590.079-0.034
UWAtmosNVIDIA5DLESyMS2Sv170.018-0.0130.0960.037-0.0460.0360.0790.052-0.0470.0590.085-0.013
scienceAI6zephyr90.0-0.0420.0450.003-0.0080.0670.1110.002-0.025-0.0420.026-0.035
scienceAI6findforecast16-0.005-0.0080.0230.03-0.038-0.0550.059-0.0180.015-0.0010.011-0.032
scienceAI6ngcm21-0.049-0.0870.007-0.0150.002-0.0990.057-0.026-0.069-0.038-0.011-0.073
CelestScience7Tellus100.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu7KanguS2SEasyUQ100.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu7KanguPlusPlus100.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu7KanguParametricPrediction100.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
CliMA9CliMAWeather214-0.001-0.0040.0220.031-0.024-0.0170.061-0.053-0.0370.0150.0690.011
CliMA9CliMAWeather20-0.037-0.0770.008-0.018-0.0970.1260.055-0.074-0.160.0040.014-0.097
JR10slowMamba17-0.008-0.0780.0690.0530.0120.1080.091-0.045-0.137-0.0060.0650.022

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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