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SON 2025 Regional RPSSs (Excel format)
Summary of RPSS values
Top 10 teams of regional forecast window 1, period-aggregated, variable-averaged RPSSs
| Teamname | Team_rank | Modelname | Model_rank | Global | Tropics | expver_id | Teamname | Modelname | Global_Average_RPSS | Tropics_Average_RPSS | NHem. ExTro._Average_RPSS | SHem. ExTro._Average_RPSS | NHem. Polar_Average_RPSS | SHem. Polar_Average_RPSS | Europe_Average_RPSS | N. Amer._Average_RPSS | S. Amer._Average_RPSS | Africa_Average_RPSS | Asia_Average_RPSS | Oceania_Average_RPSS |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AIFC_01 | AIFC | WRcast | -0.8363254929850349 | -0.8563757465924722 | -0.8430850985877575 | -1.0322279777758383 | -0.6882765867022286 | -0.777268290631611 | -0.7637522368797112 | -0.9603348325591886 | -0.988253638132042 | -1.1684478763976431 | -0.8002223163277455 | -0.4179309297262028 | ||||||
| AIFS | 1 | AIFShera | 1 | 0.0872657041634113 | 0.1077807249991681 | 0.0831543358259171 | -0.0586823080636266 | 0.0439612392074482 | 0.0238868231859243 | 0.0920495516059873 | -0.0279850632142148 | 0.055337637769575 | 0.0573159721902057 | 0.1467860156223119 | 0.0605456365590373 | |||||
| AIFS | 1 | AIFSgaia | 3 | AIFS_01 | AIFS | AIFSgaia | 0.0811298329908194 | 0.1333703876497428 | 0.0504444830112336 | -0.0801225039467007 | 0.0344557116485248 | -0.024433245810331 | 0.0914761565203339 | -0.0740618703693753 | -0.0295817417802678 | 0.1387195293447594 | 0.1555872698355637 | 0.0350405108436841 | ||
| AIFS_02 | 1 | AIFSAIFSthalassa | AIFShera6 | 0.08726570416341130751385836284376 | 0.10778072499916811294099741103095 | 0.08315433582591710366767243032266 | -0.05868230806362661267808969940127 | 0.04396123920744820293191002100561 | -0.02388682318592430500263821530941 | 0.09204955160598730392261920005742 | -0.02798506321421480459863143231923 | -0.0553376377695751126544870533037 | 0.05731597219020571280366700836895 | 0.14678601562231191294707914683695 | 0.0605456365590373 | AIFS_03 | AIFS | 0611139128695571 | ||
| CMAandFDU | 2 | FengshunAdjust | 2AIFSthalassa | 0.07513858362843760847126910944717 | 0.12940997411030951710068414166666 | 0.03667672430322660153947383208917 | -0.1267808969940127072585314450927 | 0.02931910021005610050083394077634 | -0.05002638215309410222683177614774 | 0.03922619200057420627863228628453 | -0.04598631432319230237073878441976- | 0.11265448705330370946558406179435 | 0.12803667008368950536585545497491 | 0.12947079146836951134537672593039 | 0.06111391286955710533048592404414 | |||||
| CAMExpedition_01CMAandFDUCAMExpedition | 2 | TxTFengshunHybrid | nan7 | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| CAMExpedition_02 | CAMExpedition | SBCDiff | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| CAMExpedition_03 | CAMExpedition | VAEtherCast | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| CLINT_01 | CLINT | CLINTDD | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| CMAandFDU_01 | CMAandFDU | Fengshun | 0.0348315631134322 | 0.0864929057108073 | -0.0063617751429924 | -0.0821768637336775 | 0.0477925039899162 | -0.0405814617728486 | 0.0663661110225405 | -0.0410760213738255 | -0.0075118670400408 | 0.03008274716371 | 0.082893233834882 | 0.1039381855796275 | ||||||
| CMAandFDU_02 | CMAandFDU | FengshunAdjust | 0.0847126910944717 | 0.1710068414166666 | 0.0153947383208917 | -0.072585314450927 | 0.0050083394077634 | -0.0222683177614774 | 0.0627863228628453 | -0.0237073878441976 | 0.0946558406179435 | 0.0536585545497491 | 0.1134537672593039 | 0.0533048592404414 | ||||||
| CMAandFDU_03 | CMAandFDU | FengshunHybrid | 0.0644852776892303 | 0.1246359615930289 | 0.0021708387747086 | -0.0465709611261634 | 0.0456063204474957 | -0.0210685144564061 | 0.0369279521838778 | -0.0259320243175089 | -0.0637763243975089 | 0.1070348981412967 | 0.1216146045074416 | -0.0231034247978232 | ||||||
| CliMA_01 | CliMA | CliMAWeather | -0.0401551400113346 | -0.0390112873313769 | -0.052132923056435 | -0.2400895905058521 | -0.037498413761689 | 0.0632659389093055 | 0.0107444990738656 | -0.0871304845380396 | -0.1510158815335493 | -0.0239612890986327 | -0.019111690258686 | -0.1370860032428479 | ||||||
| CliMA_02 | CliMA | CliMAWeather2 | -0.040318241889637 | -0.04106684186707 | -0.0486472605750094 | -0.2378184970076762 | -0.0385811666652545 | 0.0676703975281957 | 0.0082547294542645 | -0.0858899211504835 | -0.1587708066025433 | -0.0250689569388942 | -0.0170447349246089 | -0.1287299545129007 | ||||||
| FengWuW2S_01 | FengWuW2S | FengWu | -0.3297956763232948 | -0.3846686163227605 | -0.3308683411739114 | -0.3881415625866724 | -0.2703834267848625 | -0.1770237499050863 | -0.4621881409395296 | -0.1615819671620163 | -0.5237340307680335 | -0.6291286480279751 | -0.3931969434103262 | -0.2686038623275239 | ||||||
| FengWuW2S_02 | FengWuW2S | FengWu2 | -0.2598175485147354 | -0.134728010855516 | -0.4344056052392832 | -0.2548453604793543 | -0.4705608400773706 | -0.2496801603621676 | -0.7317112133780895 | -0.0419558442846404 | -0.1238405224442392 | -0.4522045029611422 | -0.4910944634661558 | -0.125979124263102 | ||||||
| HAPPY_01 | HAPPY | AZN | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| HYT_01 | HYT | WenDingNet | -0.3984595435956333 | -0.5223015877141166 | -0.3531828986368588 | -0.3033405230110271 | -0.1175447967402063 | -0.3111175469643476 | -0.1767136339874217 | -0.5195830712941162 | -0.603017004271011 | -0.5692657750155413 | -0.2786358892503743 | -0.4706644081514559 | ||||||
| IFUAIHydromet_01 | IFUAIHydromet | ProS2St | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| IgnisNeuralis42_01 | IgnisNeuralis42 | GCast42 | -0.8187461585539973 | -0.9308952382564144 | -0.6809465117956401 | -1.000158592971556 | -0.6933713195995891 | -0.8488404194952479 | -0.6403499766791413 | -0.720930025676434 | -0.9385750360221574 | -1.1112408612670983 | -0.6687265932183074 | -1.063146276203755 | ||||||
| JR_01 | JR | slowMamba | -0.4114334077806316 | -0.3914469624644989 | -0.5097229648262049 | -0.5533649715166743 | -0.2370789057783792 | -0.4307547673443807 | -0.363288825234983 | -0.6663831862116212 | -0.6939691973785888 | -0.2798653889260888 | -0.2880905964863772 | -0.523711296294188 | ||||||
| KITKangu_01 | KITKangu | KanguS2SEasyUQ | -1.2347523823399784 | -1.3401195220637367 | -1.045133965154535 | -1.357285868673576 | -1.0937269217185723 | -1.2653733658246211 | -1.1939834961133735 | -0.8764893369277466 | -1.4926150553226716 | -1.445703410997419 | -1.1781797038225297 | -1.6726960282590275 | ||||||
| KITKangu_02 | KITKangu | KanguPlusPlus | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | ||||||
| KITKangu_03 | KITKangu | KanguParametricPrediction | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | ||||||
| LP_01 | LP | LPM | 0.0622763282650112 | 0.0828449680972131 | 0.0613147734554885 | -0.0138902053315259 | 0.0243708463494071 | 0.016781459389786 | 0.0867450971585289 | 0.0192322401943349 | 0.0324249096369578 | 0.0206356235548932 | 0.0920613793896299 | -0.0205453160240804 | ||||||
| Lambda1_01 | Lambda1 | BibiCloud | -0.6338402966417803 | -0.7581251287333325 | -0.525448767318904 | -0.6756443739331685 | -0.5708397698751938 | -0.4165782914395515 | -0.7676244836071922 | -0.5192832465059715 | -0.7142430864496662 | -0.847311741461021 | -0.614393457087809 | -0.5519056345351623 | ||||||
| Lambda1_02 | Lambda1 | SilverSky | -0.703920768794942 | -0.6743109806874958 | -0.6864161921221384 | -0.9246174082307812 | -0.7386033847030484 | -0.6457570129606269 | -0.3494872993544979 | -0.739316799554247 | -0.3090699357436741 | -0.9332640011423782 | -0.6695246195817885 | -1.145382358809894 | ||||||
| Lambda1_03 | Lambda1 | NorrisNimbus | -0.6694425425698332 | -0.5908848860488967 | -0.7513343308506956 | -0.7199741730062256 | -0.5819461717456959 | -0.8959447741118112 | -0.5809757675434613 | -0.9568003632357592 | -0.3210462638871221 | -0.8564349582222048 | -0.4018938267825071 | -0.9906929932420684 | ||||||
| MicroEnsemble_01 | MicroEnsemble | StillLearning | 0.0768193934327012 | 0.1019736135028891 | 0.0580600132151527 | -0.0087950118325421 | 0.0400307847430897 | 0.0639440367741658 | 0.1185327042608914 | -0.0039094413916992 | -0.001889913598068 | 0.0560530860694973 | 0.1129082303234684 | 0.0817178780905799 | ||||||
| MicroEnsemble_02 | MicroEnsemble | Huracan | 0.047033814624337 | 0.0436935144917127 | 0.0598610877193079 | -0.0451467559652294 | 0.0201602170324967 | 0.0686882477798757 | 0.1041896923265447 | -0.005417425601323 | -0.089897720201524 | -0.015231671513704 | 0.0991885045423252 | 0.0402480851373969 | ||||||
| MicroEnsemble_03 | MicroEnsemble | MicroDuet | 0.0768420556086506 | 0.1084786667599793 | 0.0493394492178274 | -0.0218915839842206 | 0.032041757968749 | 0.0654175517429067 | 0.1050376652880791 | -0.0016552637686019 | -0.0189511975870761 | 0.0630243710135443 | 0.108598223942687 | 0.0921151542591087 | ||||||
| NewMeteor_01 | NewMeteor | NewMet | -0.7442348582817374 | -0.9571098881712168 | -0.7627985029527052 | -0.6292016667535737 | -0.2517264722812029 | -0.4748012293893338 | -0.5230103602840214 | -0.794320958353568 | -0.9371739772040174 | -0.8545999170919168 | -0.614598669226181 | -1.0738074609218884 | ||||||
| NewMeteor_02 | NewMeteor | BaseModel | -0.7523540656115362 | -0.9684069025381424 | -0.7755866960967688 | -0.6224780076684387 | -0.2394029086743643 | -0.4772345097572724 | -0.5018366909371502 | -0.8205943673773889 | -0.9438467875089516 | -0.8782762888428719 | -0.6276631135182612 | -1.064307119713747 | ||||||
| NewMeteor_03 | NewMeteor | ExtraBaseModel | -0.7473834015519142 | -0.9598013717552254 | -0.7748107031402514 | -0.6195131649474707 | -0.2365400895627892 | -0.4720839630131985 | -0.506545452609398 | -0.8166879624721171 | -0.946233721267292 | -0.8707102242109034 | -0.6185378322554868 | -1.0608496224618358 | ||||||
| NordicS2S_01 | NordicS2S | NordicS2S1 | -0.3296481548821539 | -0.2699725206662289 | -0.4599435109605699 | -0.3004814386097929 | -0.3605810700990424 | -0.3016521077826924 | -0.3058553548073675 | -0.4753091708809658 | -0.2940176238608821 | -0.2627321373399661 | -0.2820192423381088 | -0.486777323833797 | ||||||
| NordicS2S_02 | NordicS2S | NordicS2S2 | -0.5764437859771525 | -0.6440370936279989 | -0.5102512733886096 | -0.6672586319935198 | -0.618622664929504 | -0.3249936012618106 | -0.0830480694397304 | -0.8358486426742674 | -1.0301441355953684 | -0.3946334921276125 | -0.445025592480204 | -0.7938192997551866 | ||||||
| NordicS2S_03 | NordicS2S | NordicS2S3 | -0.4499628847022573 | -0.4076802032405129 | -0.566427992215834 | -0.5144347970616904 | -0.4770154159524517 | -0.3948541918298649 | -0.372643230406558 | -0.592585818305139 | -0.5511879520371669 | -0.4737654144242004 | -0.3688056875068235 | -0.6008345719397122 | ||||||
| ONE2NTeam_01 | ONE2NTeam | ONE2NWeather | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| Qronon_01 | Qronon | QRCML | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| SAIS2S_01 | SAIS2S | SAI | -0.3676085408009333 | -0.549340029114418 | -0.1475153228876189 | -0.6450894034566227 | -0.0091979850164942 | -0.3247083881910761 | 0.0389654838601462 | -0.2030342503945757 | -1.236646217312704 | -0.5552335234825928 | -0.093514402809942 | -0.5794176237112362 | ||||||
| Sibyl_01 | Sibyl | ClimSDE | -0.2983663189800415 | -0.3437491277091165 | -0.3058353589781565 | -0.514741922074395 | -0.1896855823179573 | -0.3643652380831216 | -0.2772509411330016 | -0.1858118672283469 | -0.2795416448980184 | -0.5191503542767534 | -0.3152926171458969 | -0.5717426025937533 | ||||||
| SwissAIClimate_01 | SwissAIClimate | ESFM | -0.5523675506468876 | -0.4590377596771515 | -0.9118366650418996 | -0.3614229342979536 | -0.6386518340998633 | -0.2212600898646135 | -0.8345186883439846 | -0.3890682664187573 | -0.3084062401633661 | -0.7711304142056316 | -1.0483965745748849 | -0.3552269821392911 | ||||||
| TAICHI_01 | TAICHI | TAICHIAI | -0.8622731270090606 | -0.8554159102953233 | -0.9884717544458896 | -0.5453291291686201 | -0.9006929906449906 | -0.7607430151233694 | -0.7869332205143378 | -1.0325267685893829 | -0.565269480333857 | -1.0525693268264285 | -0.8768854419946362 | -0.9811730635492604 | ||||||
| TeaMUX_01 | TeaMUX | Climatology | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | ||||||
| UWAtmosNVIDIA_01 | UWAtmosNVIDIA | DLESyMS2Sv1 | -0.5100619905431865 | -0.5579089981596274 | -0.5680354240909861 | -0.6539713122438323 | -0.2382174740195242 | -0.3382361760701257 | -0.5438590156972231 | -0.4739193868276896 | -1.1369525379383028 | -0.4344060030265771 | -0.5095882167283607 | -0.5535075911890551 | ||||||
| WindBorne_01 | WindBorne | WeatherMesh | -0.1246740662212984 | -0.0817395133477092 | -0.2059140701112232 | -0.2589037256803564 | -0.1525721142720525 | -0.1317549620568503 | -0.2020446607234841 | -0.1874665495628587 | -0.1400424871394033 | -0.1837295339440002 | -0.1406398784011505 | -0.3577949236071163 | ||||||
| scienceAI_01 | scienceAI | findforecast | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | ||||||
| scienceAI_02 | scienceAI | zephyr | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | ||||||
| 0.0644852776892303 | 0.1246359615930289 | 0.0021708387747086 | -0.0465709611261634 | 0.0456063204474957 | -0.0210685144564061 | 0.0369279521838778 | -0.0259320243175089 | -0.0637763243975089 | 0.1070348981412967 | 0.1216146045074416 | -0.0231034247978232 | |||||||||
| CMAandFDU | 2 | Fengshun | 10 | 0.0348315631134322 | 0.0864929057108073 | -0.0063617751429924 | -0.0821768637336775 | 0.0477925039899162 | -0.0405814617728486 | 0.0663661110225405 | -0.0410760213738255 | -0.0075118670400408 | 0.03008274716371 | 0.082893233834882 | 0.1039381855796275 | |||||
| MicroEnsemble | 3 | MicroDuet | 4 | 0.0768420556086506 | 0.1084786667599793 | 0.0493394492178274 | -0.0218915839842206 | 0.032041757968749 | 0.0654175517429067 | 0.1050376652880791 | -0.0016552637686019 | -0.0189511975870761 | 0.0630243710135443 | 0.108598223942687 | 0.0921151542591087 | |||||
| MicroEnsemble | 3 | StillLearning | 5 | 0.0768193934327012 | 0.1019736135028891 | 0.0580600132151527 | -0.0087950118325421 | 0.0400307847430897 | 0.0639440367741658 | 0.1185327042608914 | -0.0039094413916992 | -0.001889913598068 | 0.0560530860694973 | 0.1129082303234684 | 0.0817178780905799 | |||||
| MicroEnsemble | 3 | Huracan | 9 | 0.047033814624337 | 0.0436935144917127 | 0.0598610877193079 | -0.0451467559652294 | 0.0201602170324967 | 0.0686882477798757 | 0.1041896923265447 | -0.005417425601323 | -0.089897720201524 | -0.015231671513704 | 0.0991885045423252 | 0.0402480851373969 | |||||
| LP | 4 | LPM | 8 | 0.0622763282650112 | 0.0828449680972131 | 0.0613147734554885 | -0.0138902053315259 | 0.0243708463494071 | 0.016781459389786 | 0.0867450971585289 | 0.0192322401943349 | 0.0324249096369578 | 0.0206356235548932 | 0.0920613793896299 | -0.0205453160240804 | |||||
| KITKangu | 5 | KanguPlusPlus | 11 | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | |||||
| KITKangu | 5 | KanguParametricPrediction | 11 | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | |||||
| scienceAI | 5 | findforecast | 11 | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | |||||
| scienceAI | 5 | zephyr | 11 | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | |||||
| scienceAI | 5 | ngcm | 11 | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 | |||||
| KITKangu | 5 | KanguS2SEasyUQ | 39 | -1.2347523823399784 | -1.3401195220637367 | -1.045133965154535 | -1.357285868673576 | -1.0937269217185723 | -1.2653733658246211 | -1.1939834961133735 | -0.8764893369277466 | -1.4926150553226716 | -1.445703410997419 | -1.1781797038225297 | -1.6726960282590275 | |||||
| CliMA | 7 | CliMAWeather | 16 | -0.0401551400113346 | -0.0390112873313769 | -0.052132923056435 | -0.2400895905058521 | -0.037498413761689 | 0.0632659389093055 | 0.0107444990738656 | -0.0871304845380396 | -0.1510158815335493 | -0.0239612890986327 | -0.019111690258686 | -0.1370860032428479 | |||||
| CliMA | 7 | CliMAWeather2 | 17 | -0.040318241889637 | -0.04106684186707 | -0.0486472605750094 | -0.2378184970076762 | -0.0385811666652545 | 0.0676703975281957 | 0.0082547294542645 | -0.0858899211504835 | -0.1587708066025433 | -0.0250689569388942 | -0.0170447349246089 | -0.1287299545129007 | |||||
| WindBorne | 8 | WeatherMesh | 18 | -0.1246740662212984 | -0.0817395133477092 | -0.2059140701112232 | -0.2589037256803564 | -0.1525721142720525 | -0.1317549620568503 | -0.2020446607234841 | -0.1874665495628587 | -0.1400424871394033 | -0.1837295339440002 | -0.1406398784011505 | -0.3577949236071163 | |||||
| FengWuW2S | 9 | FengWu2 | 19 | -0.2598175485147354 | -0.134728010855516 | -0.4344056052392832 | -0.2548453604793543 | -0.4705608400773706 | -0.2496801603621676 | -0.7317112133780895 | -0.0419558442846404 | -0.1238405224442392 | -0.4522045029611422 | -0.4910944634661558 | -0.125979124263102 | |||||
| FengWuW2S | 9 | FengWu | 22 | -0.3297956763232948 | -0.3846686163227605 | -0.3308683411739114 | -0.3881415625866724 | -0.2703834267848625 | -0.1770237499050863 | -0.4621881409395296 | -0.1615819671620163 | -0.5237340307680335 | -0.6291286480279751 | -0.3931969434103262 | -0.2686038623275239 | |||||
| Sibyl | 10 | ClimSDE | 20 | -0.2983663189800415 | -0.3437491277091165 | -0.3058353589781565 | -0.514741922074395 | -0.1896855823179573 | -0.3643652380831216 | -0.2772509411330016 | -0.1858118672283469 | -0.2795416448980184 | -0.5191503542767534 | -0.3152926171458969 | -0.5717426025937533 |
Top 10 teams of regional forecast window 2, period-aggregated, variable-averaged RPSSs
| Teamname | Team_rank | Modelname | Model_rank | Global | Tropics | NHem. ExTro. | SHem. ExTro. | NHem. Polar | SHem. Polar | Europe | N. Amer. | S. Amer. | Africa | Asia | Oceania | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CMAandFDU | 1 | FengshunAdjust | 1 | 0.0609704538284342 | 0.117393332091908 | 0.0290144145871781 | 0.0021789788322219 | 0.0329664598681853 | -0.013654632678297 | 0.0027472023596456 | 0.0579614131295659 | 0.1326416096273614 | 0.1101404401676157 | 0.0724607101255174 | 0.1291803393447884 | |||||||||||||||
| CMAandFDU | 1 | FengshunHybrid | 2 | 0.0527583612632312 | 0.0795492419136108 | 0.0318531997655443 | 0.0280222931886769 | 0.0246930501049112 | 0.0203242646302143 | 0.0102752764068216 | 0.0273708465032861 | 0.0602399886026433 | 0.0646956343244963 | 0.0768472737834497 | 0.0471767410652232 | |||||||||||||||
| CMAandFDU | 1 | Fengshun | 14 | -0.0024703227562228 | 0.0010035000257188 | 0.0057860086159402 | 0.0290300134027464 | 0.0528683665772347 | -0.0802104767690924 | 0.0057550728709226 | -0.0236900708688099 | 0.0070644505770458 | -0.0767967082053618 | 0.0419895158234453 | 0.0782722632859353 | |||||||||||||||
| MicroEnsemble | 2 | StillLearning | 3 | 0.0514150687505273 | 0.0994368794231486 | 0.0058952885216756 | 0.0390823186782357 | 0.0454623875943802 | -0.0223098980709466 | -0.0188645900844365 | 0.0187466422482555 | 0.0951132465576866 | 0.0827033207464629 | 0.0550485982168662 | 0.0935829545319012 | |||||||||||||||
| MicroEnsemble | 2 | MicroDuet | 4 | 0.0453574274924767 | 0.0868847329704792 | 2.6171987126500512e-05 | 0.0466364158862867 | 0.0424746291161806 | -0.0127951477654476 | -0.0257086234725832 | 0.0462191831467234 | 0.114424848878271 | 0.0171453225657822 | 0.0443910842604825 | 0.1028292034557147 | |||||||||||||||
| MicroEnsemble | 2 | Huracan | 8 | 0.0088160778839042 | 0.0214323315030628 | -0.0168919738564884 | 0.052769551703249 | 0.0320281778374951 | -0.043590992662836 | -0.0469603674862009 | 0.0318434251385058 | 0.0482364649984184 | -0.0595537778051697 | 0.0014628388160801 | 0.059454537846756 | |||||||||||||||
| LP | 3 | LPM | 5 | 0.0359757073138679 | 0.0559889997164319 | 0.025555567586773 | 0.0442004488928816 | 0.022166670256691 | -0.0593037753391682 | -0.0021551249797733 | 0.0357581423581214 | 0.077140296483522 | 0.0238210406588864 | 0.0661306496363801 | 0.0060609838732028 | |||||||||||||||
| AIFS | 4 | AIFSgaia | 6 | 0.0243550828895415 | 0.0404042191841902 | -0.0130883674124977 | 0.0319799298924255 | 0.0289636238955928 | 0.0293269032816071 | -0.0168687276128939 | -0.0506688973797992 | 0.1183199481559452 | 0.0086054565768282 | 0.0327986486195891 | 0.0093627390311302 | |||||||||||||||
| AIFS | 4 | AIFShera | 7 | 0.0089699221170026 | 0.0141127415355947 | -0.0197811705129096 | 0.005385453602815 | 0.0451679852169668 | -0.0151711477921617 | 0.0090224910333509 | -0.0828559097438942 | 0.0780533585858897 | 0.0067065738790715 | 0.0190902424568871 | 0.0605170623404766 | |||||||||||||||
| AIFS | 4 | AIFSthalassa | 15 | -0.0045689093707475 | -0.0275378435840423 | 0.000431252264004 | -0.0074559730282795 | 0.0214832494753073 | 0.0264837272557239 | 0.0131558162937652 | -0.0457925207137526 | 0.0404753052720088 | -0.0799169231714984 | 0.0296227580306912 | -0.1172533776665263 | |||||||||||||||
| KITKangu | 5 | KanguPlusPlus | 9 | 3.6718625917586682e-09 | -9.11592653215128e-10 | -6.9456635258073155e-09 | -8.849109223163511e-09 | 3.2644538923894593e-08 | 3.3818281545509414e-08 | 6.216317534798084e-09 | 2.7036507107188372e-09 | -1.5391835953929938e-09 | -1.098188059008483e-09 | 2.2373580395769932e-09 | -5.1284800850481815e-09 | |||||||||||||||
| KITKangu | 5 | KanguParametricPrediction | 9 | 3.6718625917586682e-09 | -9.11592653215128e-10 | -6.9456635258073155e-09 | -8.849109223163511e-09 | 3.2644538923894593e-08 | 3.3818281545509414e-08 | 6.216317534798084e-09 | 2.7036507107188372e-09 | -1.5391835953929938e-09 | -1.098188059008483e-09 | 2.2373580395769932e-09 | -5.1284800850481815e-09 | |||||||||||||||
| scienceAI | 5 | findforecast | 9 | 3.6718625917586682e-09 | -9.11592653215128e-10 | -6.9456635258073155e-09 | -8.849109223163511e-09 | 3.2644538923894593e-08 | 3.3818281545509414e-08 | 6.216317534798084e-09 | 2.7036507107188372e-09 | -1.5391835953929938e-09 | -1.098188059008483e-09 | 2.2373580395769932e-09 | -5.1284800850481815e-09 | |||||||||||||||
| scienceAI | 5 | zephyr | 9 | 3.6718625917586682e-09 | -9.11592653215128e-10 | -6.9456635258073155e-09 | -8.849109223163511e-09 | 3.2644538923894593e-08 | 3.3818281545509414e-08 | 6.216317534798084e-09 | 2.7036507107188372e-09 | -1.5391835953929938e-09 | -1.098188059008483e-09 | 2.2373580395769932e-09 | -5.1284800850481815e-09 | |||||||||||||||
| scienceAI | 5 | ngcm | 9 | 3.6718625917586682e-09 | -9.11592653215128e-10 | -6.9456635258073155e-09 | -8.849109223163511e-09 | 3.2644538923894593e-08 | 3.3818281545509414e-08 | 6.216317534798084e-09 | 2.7036507107188372e-09 | -1.5391835953929938e-09 | -1.098188059008483e-09 | 2.2373580395769932e-09 | -5.1284800850481815e-09 | |||||||||||||||
| KITKangu | 5 | KanguS2SEasyUQ | 39 | -1.3898377989107802 | -1.441187434994885 | -1.3093072382340456 | -0.860630554294317 | -1.3427116980759906 | -1.4422746100474977 | -1.2186735698604043 | -1.2607653359586928 | -1.5319290385318312 | -1.5089622367155702 | -1.3642179502171723 | -1.1739736179229532 | |||||||||||||||
| CliMA | 7 | CliMAWeather | 16 | -0.0997201052792394 | -0.1377858110105982 | -0.1140509675418923 | -0.1273071718057634 | -0.0311224375091261 | 0.0243030786480396 | -0.1222154148202415 | -0.1197948503852352 | -0.1165648625704478 | -0.268687510871712 | -0.1030548454398337 | 0.0886144356093481 | |||||||||||||||
| CliMA | 7 | CliMAWeather2 | 17 | -0.1059069014291666 | -0.1419025408404863 | -0.1229622322352672 | -0.138326158039714 | -0.0365455034092823 | 0.0201287617477252 | -0.1337811845702122 | -0.1328807611088117 | -0.1296215688597378 | -0.2781686872827242 | -0.1021342020041919 | 0.0896058916967846 | |||||||||||||||
| FengWuW2S | 8 | FengWu2 | 18 | -0.2637982180490629 | -0.2033104087319254 | -0.4566306866878422 | 0.0082240677934922 | -0.3084377184380691 | -0.0543464215892999 | -0.3005374637541703 | -0.0575678629486624 | -0.0982088461358459 | -0.2759119544023418 | -0.6159696986850421 | -0.2824437317201644 | |||||||||||||||
| FengWuW2S | 8 | FengWu | 20 | -0.3504299211906538 | -0.4763511384737846 | -0.3626642293556934 | -0.1056370471891408 | -0.2049489872363674 | 0.00731284214924 | -0.2711071906489209 | -0.1387664854323166 | -0.5872330110348261 | -0.6784948352598686 | -0.4717580082311046 | -0.3325387705162455 | |||||||||||||||
| NordicS2S | 9 | NordicS2S1 | 19 | -0.315404475963272 | -0.3416426849164855 | -0.2397346021733059 | -0.2497766043761195 | -0.1610331796484567 | -0.4388890891503878 | -0.1530534219882934 | -0.1652146380614118 | -0.2834361503133122 | -0.584097045647085 | -0.2586756831282115 | -0.2724499367123978 | |||||||||||||||
| NordicS2S | 9 | NordicS2S3 | 27 | -0.5265507521364994 | -0.7781466803509519 | -0.2803937608639974 | -0.1109370105503585 | -0.3279495054293059 | -0.4273705113906661 | -0.3210480276202649 | -0.4773649561729151 | -0.7035491360084464 | -0.9232246580349408 | -0.413383558677425 | -0.5888730372499086 | |||||||||||||||
| NordicS2S | 9 | NordicS2S2 | 29 | -0.6055187799634721 | -0.7305827547936555 | -0.6544465859052372 | -0.7637247864748167 | -0.2216312591612375 | -0.0923550123927006 | -0.3700162228329868 | -0.6691351136680801 | -0.7803976959404016 | -0.8535560955625039 | -0.5034382684853603 | -0.5533929938645247 | |||||||||||||||
| Sibyl | 10 | ClimSDE | 21 | -0.3863240455654866 | -0.3921940542797756 | -0.3189914326490093 | -0.7794869395383307 | -0.260770625666276 | -0.5060688115995131 | -0.2755647156107741 | -0.3448042322040479 | -0.633935566134859 | -0.4091174055142876 | -0.2197063409780724 | -0.2985457795394503 | scienceAI_03 | scienceAI | ngcm | 3.666856966214974e-09 | -4.0358675660693645e-10 | -7.362577584639022e-09 | -8.457189837329793e-09 | 3.202370239356137e-08 | 3.4529600401178584e-08 | 4.1434213467657815e-09 | 1.7628015343736552e-09 | -7.819986880264194e-10 | -1.243628607502008e-09 | 2.605395269898262e-09 | -4.042379024108793e-09 |