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 2 forecasts initialized between Thursday 13th November 2025 and Thursday 20th 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
MicroEnsemble1StillLearning10.0960.1030.1050.1530.0140.1180.0760.104-0.0020.1650.0990.054
MicroEnsemble1MicroDuet20.0950.1120.0890.1480.0080.0970.0660.095-0.010.1740.1070.064
MicroEnsemble1Huracan60.0810.0910.0670.13-0.0020.1090.0290.112-0.0550.1430.0710.093
AIFS2AIFSthalassa30.0830.0610.0910.1710.0940.0740.080.098-0.0410.0880.1120.113
AIFS2AIFShera40.0810.0610.1050.0870.080.0770.010.148-0.0780.1560.095-0.033
AIFS2AIFSgaia70.0740.0590.0970.0930.0580.0470.070.127-0.0610.1510.0770.007
LP3LPM50.0810.0810.0890.120.0050.120.0390.112-0.0680.180.0680.039
CMAandFDU4FengshunHybrid80.0480.0470.0420.0890.0270.080.0240.02-0.0260.1410.082-0.004
CMAandFDU4FengshunAdjust100.0440.0570.0280.0740.0210.010.0250.014-0.0150.1480.0520.029
CMAandFDU4Fengshun21-0.015-0.0390.029-0.0110.043-0.0950.056-0.049-0.0280.1280.014-0.15
UWAtmosNVIDIA5DLESyMS2Sv190.0470.0640.0360.096-0.0260.0270.019-0.0070.0160.1250.0720.06
JR6slowMamba110.0310.050.0070.060.0160.02-0.0380.023-0.0040.0390.045-0.011
scienceAI7zephyr120.027-0.0010.0350.0630.0030.1070.0630.018-0.072-0.0030.033-0.024
scienceAI7findforecast18-0.001-0.0040.0080.046-0.033-0.0250.068-0.035-0.0180.0020.018-0.026
scienceAI7ngcm20-0.008-0.0120.020.041-0.01-0.1230.0320.005-0.061-0.0350.017-0.005
IgnisNeuralis428GCast42130.0080.035-0.012-0.003-0.026-0.0150.039-0.043-0.0030.0340.047-0.034
CelestScience9Tellus140.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu9KanguS2SEasyUQ140.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu9KanguPlusPlus140.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu9KanguParametricPrediction140.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
Team nameTeam rankModel nameModel rankGlobalTropicsNHem. ExTro.SHem. ExTro.NHem. PolarSHem. PolarEuropeN. Amer.S. Amer.AfricaAsiaOceania
MicroEnsemble1MicroDuet10.0440.0350.1010.0430.005-0.0060.0490.0540.0040.0720.112-0.06
MicroEnsemble1StillLearning20.0440.0350.1040.0510.008-0.0080.0570.0550.0090.080.11-0.072
MicroEnsemble1Huracan30.0350.0120.114-0.0120.032-0.040.0290.082-0.0160.0020.123-0.052
LP2LPM40.019-0.0110.1-0.0110.016-0.0320.0260.063-0.0130.0080.099-0.12
IgnisNeuralis423GCast4250.0170.0440.010.037-0.041-0.0550.015-0.0180.0050.0370.0410.017
CelestScience4Tellus60.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu4KanguS2SEasyUQ60.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu4KanguPlusPlus60.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
KITKangu4KanguParametricPrediction60.0-0.00.0-0.00.00.00.00.0-0.0-0.00.0-0.0
CliMA6CliMAWeather210-0.001-0.0080.0230.01-0.041-0.0030.027-0.048-0.026-0.0090.053-0.001
CliMA6CliMAWeather21-0.035-0.0620.002-0.025-0.0760.0790.016-0.066-0.153-0.0070.011-0.067
AIFS7AIFSgaia11-0.014-0.0980.116-0.0370.036-0.0230.090.09-0.099-0.0120.079-0.198
AIFS7AIFShera15-0.02-0.1090.103-0.0730.0520.0350.0830.043-0.1270.0130.09-0.254
AIFS7AIFSthalassa20-0.033-0.1420.092-0.020.066-0.0020.0440.088-0.161-0.1110.053-0.153
scienceAI8findforecast12-0.014-0.030.0240.004-0.024-0.0570.047-0.008-0.025-0.0480.002-0.04
scienceAI8zephyr17-0.024-0.0720.03-0.027-0.0050.0410.0710.003-0.048-0.08-0.01-0.103
scienceAI8ngcm22-0.052-0.1030.015-0.0370.004-0.0790.049-0.015-0.069-0.086-0.035-0.115
UWAtmosNVIDIA9DLESyMS2Sv113-0.015-0.0470.051-0.022-0.0690.0170.0090.018-0.0390.0060.023-0.093
CMAandFDU10Fengshun14-0.017-0.0480.021-0.0830.074-0.058-0.002-0.056-0.066-0.0020.063-0.095
CMAandFDU10FengshunHybrid18-0.027-0.0960.054-0.0530.0370.0160.0720.001-0.085-0.0160.026-0.199
CMAandFDU10FengshunAdjust19-0.027-0.0840.05-0.0470.025-0.0240.0750.004-0.0490.0060.037-0.189

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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