This page provides an overview of regional forecast skill for the JJA 2026 period. Forecast scores are updated automatically every week throughout the competitive period. The current data includes 5 forecasts initialized between Thursday 14th May 2026 and Thursday 11th June 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:

JJA 2026 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
CMAandFDU1FengshunAdjust10.1260.2010.0430.0440.0490.0920.0540.0770.130.2150.0910.199
CMAandFDU1FengshunHybrid30.1120.1840.0290.0630.0360.0750.0580.0610.1120.1730.0810.237
CMAandFDU1Fengshun80.1110.1750.0330.0360.0410.0850.050.0590.120.1780.0890.152
LP2LPM20.1190.2120.0410.064-0.0170.0560.0890.0560.1030.180.0910.243
AIFS3AIFShera40.1110.1880.020.072-0.0020.1010.0150.0870.1060.1940.060.177
AIFS3AIFSthalassa90.110.1880.0160.082-0.0030.0970.0220.0680.1060.1640.0680.208
AIFS3AIFSgaia120.0880.1570.0060.05-0.0270.0940.0210.0380.060.1170.0690.172
MicroEnsemble4MicroDuet50.1110.1830.0460.0770.020.0560.080.0790.1110.1520.0860.219
MicroEnsemble4StillLearning100.1070.1730.0490.0720.0270.0450.080.0760.1040.1390.0870.212
MicroEnsemble4Huracan150.0720.1280.0160.0880.00.0210.0530.0450.050.070.0570.197
CLINT5CLINTDD60.1110.1780.0420.0430.0290.0720.1080.0620.0710.150.1010.201
CLINT5CLINTMF70.1110.180.0390.0470.020.0780.1090.0610.0750.150.0970.198
CLINT5CLINTSE190.0590.119-0.0190.008-0.0360.1150.0850.011-0.030.050.0270.185
SBUHybrid6HybridStillDeveloping110.1010.1750.0360.0320.0260.0240.0540.0260.080.1690.0930.183
SBUHybrid6HybridPPx200.0570.1040.019-0.0020.0130.0090.029-0.021-0.0430.1460.0740.131
SBUHybrid6HybridAC250.0360.0610.024-0.0190.010.0190.039-0.037-0.0940.1040.0530.11
scienceAI7zephyr130.0780.1290.0280.0090.0320.0480.0370.040.0070.1070.0850.14
scienceAI7ngcm180.0650.1090.0260.0240.020.0190.0270.035-0.0030.0960.0590.137
scienceAI7findforecast270.0310.0470.0130.0220.0320.0090.0060.0090.0410.0710.0280.034
MetaCarbon30608PuyunEnsemble140.0780.15-0.0110.033-0.00.0450.0070.0340.1360.10.0310.164
MetaCarbon30608PuyunWeather170.0650.1280.0020.0210.0150.0180.0630.0530.0450.0880.0320.174
MetaCarbon30608PuyunLDM230.040.11-0.0640.025-0.020.032-0.0680.010.1080.042-0.0360.149
UWAtmosNVIDIA9DLESyMS2Sv1160.0680.127-0.00.027-0.0060.0570.029-0.0090.0150.1030.0650.141
CliMA10CliMAWeather210.0460.0810.0220.0180.006-0.0190.0110.0280.0250.0740.0450.108
CliMA10CliMAWeather2220.0450.0820.0220.01-0.001-0.0380.0090.029-0.0020.0750.0520.132
Team nameTeam rankModel nameModel rankGlobalTropicsNHem. ExTro.SHem. ExTro.NHem. PolarSHem. PolarEuropeN. Amer.S. Amer.AfricaAsiaOceania
CMAandFDU1FengshunAdjust10.1340.2170.063-0.0050.0410.0750.0680.0820.1450.2270.1050.148
CMAandFDU1Fengshun20.1190.1970.056-0.0280.0330.0610.060.0710.1370.1970.1080.084
CMAandFDU1FengshunHybrid30.1170.1970.0540.0050.0330.040.0740.0590.1430.1690.10.186
LP2LPM40.1090.2060.0380.01-0.0190.0020.0790.0140.1530.1480.1080.174
MicroEnsemble3MicroDuet50.1060.1830.0480.0210.0080.0330.060.0510.1450.1330.0940.165
MicroEnsemble3StillLearning70.1020.1750.0510.0210.0080.0080.0610.0520.1470.1270.0950.162
MicroEnsemble3Huracan150.0670.1380.0190.019-0.02-0.0260.0420.0050.0850.0520.0690.158
CLINT4CLINTDD60.1040.1780.042-0.0040.0250.0260.0960.0290.1280.1140.1170.158
CLINT4CLINTMF80.1010.1770.039-0.010.0180.0230.0950.0240.1290.1110.1160.153
CLINT4CLINTSE220.050.114-0.012-0.059-0.020.0560.065-0.0270.043-0.0060.0570.126
AIFS5AIFShera90.0960.1830.012-0.017-0.0030.0330.020.0340.1140.1640.0860.099
AIFS5AIFSthalassa100.0940.1760.0080.015-0.0080.0420.0180.0320.1310.1360.0720.118
AIFS5AIFSgaia120.0760.1520.004-0.007-0.0310.0270.0140.0240.1170.1180.0540.061
SBUHybrid6HybridStillDeveloping110.0870.1670.024-0.0180.006-0.0080.0380.0230.080.1480.0860.137
SBUHybrid6HybridPPx160.0650.1340.013-0.019-0.016-0.0340.016-0.0280.010.1150.0860.136
SBUHybrid6HybridAC240.0430.0890.002-0.027-0.005-0.0380.011-0.051-0.0330.0750.050.123
scienceAI7zephyr130.0740.1290.027-0.0130.0280.0240.0440.0260.040.090.090.115
scienceAI7ngcm180.0630.110.0230.0130.0060.0110.0340.0230.0220.0840.0540.119
scienceAI7findforecast280.0320.0530.0190.0040.026-0.0130.0140.0160.0430.0690.030.043
MetaCarbon30608PuyunWeather140.0720.140.0130.006-0.0060.0070.0560.0270.120.0670.0570.097
MetaCarbon30608PuyunEnsemble170.0630.1260.005-0.001-0.0350.0240.0130.0110.1180.10.020.122
MetaCarbon30608PuyunLDM300.0230.083-0.052-0.011-0.0660.013-0.044-0.0130.0880.056-0.060.095
UWAtmosNVIDIA9DLESyMS2Sv1190.0620.1310.005-0.056-0.0160.0130.023-0.0120.0040.0820.070.109
CliMA10CliMAWeather2200.0540.1010.024-0.017-0.008-0.0270.0050.0210.0190.0890.0570.134
CliMA10CliMAWeather210.0530.0950.024-0.0020.001-0.0110.0090.0230.0390.0850.0490.11

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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