Raw model output on the native 0.25° grid — no MOS, no bias correction, no post-processing. Scores understate operational forecast quality. Read the fairness statement →

CastCheck methodology v0.2 · data through 2026-08-30

KTTN — Trenton Mercer

40.2764, -74.8164 · 64 m· standard offset UTC-5 h · truth product CLITTN

These pages are always bilinear interpolation, the headline method. The nearest-node variant, and every other window/initialization/interpolation/variable combination, is published on each permanent link below — follow any number.

Daily maximum temperature — MAE °F

the last 30 days, 00Z, bilinear. MAE with the bias and n underneath; every cell links to its permanent page. The sparkline shows the same model across lead days 1–9 on a scale shared within this table.
Modeld0d1d2d3d4d5d6d7d8d9lead 1–9
ECMWF AIFS Singleaifs_single 1.83+0.70 · n=30 1.75+0.67 · n=29 2.34+0.54 · n=28 1.63+0.80 · n=27 1.76+0.05 · n=26 1.68+0.41 · n=25 1.92+0.13 · n=24 1.59-0.32 · n=23 2.19-1.05 · n=22 3.91-1.70 · n=21 ECMWF AIFS Single MAE by lead day 1 to 9, tmax
Aurora (GFS init)aurora_gfs 1.62-1.62 · n=2 2.43-2.43 · n=1 Aurora (GFS init) MAE by lead day 1 to 9, tmax
Aurora (IFS init)aurora_ifs 0.96-0.89 · n=3 0.54-0.54 · n=2 0.31+0.31 · n=1 Aurora (IFS init) MAE by lead day 1 to 9, tmax
FourCastNet v2 (GFS init)fourcastnet_gfs 2.60-1.17 · n=2 1.20-1.20 · n=1 FourCastNet v2 (GFS init) MAE by lead day 1 to 9, tmax
FourCastNet v2 (IFS init)fourcastnet_ifs 2.72-1.90 · n=3 2.66+0.67 · n=2 1.07-1.07 · n=1 FourCastNet v2 (IFS init) MAE by lead day 1 to 9, tmax
NCEP GFSgfs 1.88+0.73 · n=30 2.94+0.58 · n=29 3.08-0.26 · n=28 2.53+0.71 · n=27 3.15+1.01 · n=26 4.27+0.56 · n=25 3.70+1.18 · n=24 3.29+0.62 · n=23 4.79+0.57 · n=22 5.33+1.40 · n=21 NCEP GFS MAE by lead day 1 to 9, tmax
GraphCast (GFS init)graphcast_gfs 1.76-1.76 · n=2 3.44-3.44 · n=1 GraphCast (GFS init) MAE by lead day 1 to 9, tmax
GraphCast (IFS init)graphcast_ifs 2.06-2.05 · n=28 2.41-2.38 · n=27 2.58-2.20 · n=26 2.47-1.80 · n=25 2.61-1.85 · n=25 2.33-1.45 · n=25 2.25-1.58 · n=24 2.37-1.36 · n=23 3.44-0.95 · n=22 4.15-0.28 · n=21 GraphCast (IFS init) MAE by lead day 1 to 9, tmax
ECMWF IFS HRESifs_hres 1.55+0.16 · n=24 2.66-0.76 · n=23 2.44+0.10 · n=22 2.35-0.18 · n=22 3.42+0.52 · n=20 3.04+0.87 · n=18 4.18+1.89 · n=19 2.74+1.02 · n=18 2.67+1.14 · n=17 4.51+1.96 · n=16 ECMWF IFS HRES MAE by lead day 1 to 9, tmax
Pangu-Weather (GFS init)pangu_gfs 2.25+2.25 · n=2 2.46+2.46 · n=1 Pangu-Weather (GFS init) MAE by lead day 1 to 9, tmax
Pangu-Weather (IFS init)pangu_ifs 1.59+1.59 · n=3 2.81+2.81 · n=2 2.11+2.11 · n=1 Pangu-Weather (IFS init) MAE by lead day 1 to 9, tmax
Persistence (baseline)persistence 2.33+0.13 · n=30 2.83+0.23 · n=30 3.43+0.23 · n=30 3.60+0.33 · n=30 3.63+0.50 · n=30 3.53+0.73 · n=30 3.83+0.77 · n=30 4.20+0.80 · n=30 4.53+0.80 · n=30 Persistence (baseline) MAE by lead day 1 to 9, tmax

Up to 1 of the scored days in this table carry a QC flag on the observation (a CLI value that disagreed with the hourly observations, or a fallback source). They are kept in the scores and counted here rather than dropped — see methodology.

+ model too warm · − model too cold · bias interval includes zero · ★ lowest MAE · = not distinguishable from the leader · ▼ significantly worse · n < 30 greyed and unranked · CI is a 95 % moving-block bootstrap interval.

Daily minimum temperature — MAE °F

the last 30 days, 00Z, bilinear. MAE with the bias and n underneath; every cell links to its permanent page. The sparkline shows the same model across lead days 1–9 on a scale shared within this table.
Modeld0d1d2d3d4d5d6d7d8d9lead 1–9
ECMWF AIFS Singleaifs_single 3.66+3.66 · n=30 4.00+4.00 · n=29 4.43+4.43 · n=28 4.54+4.49 · n=27 4.15+4.11 · n=26 4.21+3.92 · n=25 4.12+3.86 · n=24 4.46+4.40 · n=23 4.09+3.73 · n=22 4.31+3.89 · n=21 ECMWF AIFS Single MAE by lead day 1 to 9, tmin
Aurora (GFS init)aurora_gfs 4.25+4.25 · n=2 6.21+6.21 · n=1 Aurora (GFS init) MAE by lead day 1 to 9, tmin
Aurora (IFS init)aurora_ifs 3.28+3.28 · n=3 4.56+4.56 · n=2 5.28+5.28 · n=1 Aurora (IFS init) MAE by lead day 1 to 9, tmin
FourCastNet v2 (GFS init)fourcastnet_gfs 4.88+4.88 · n=2 9.37+9.37 · n=1 FourCastNet v2 (GFS init) MAE by lead day 1 to 9, tmin
FourCastNet v2 (IFS init)fourcastnet_ifs 3.75+3.75 · n=3 8.43+8.43 · n=2 10.97+10.97 · n=1 FourCastNet v2 (IFS init) MAE by lead day 1 to 9, tmin
NCEP GFSgfs 3.35+3.34 · n=30 3.63+3.39 · n=29 3.34+3.01 · n=28 4.42+4.24 · n=27 4.05+3.49 · n=26 4.05+3.01 · n=25 4.60+3.44 · n=24 5.05+3.23 · n=23 4.60+3.47 · n=22 5.67+3.29 · n=21 NCEP GFS MAE by lead day 1 to 9, tmin
GraphCast (GFS init)graphcast_gfs 3.99+3.99 · n=2 6.61+6.61 · n=1 GraphCast (GFS init) MAE by lead day 1 to 9, tmin
GraphCast (IFS init)graphcast_ifs 3.32+3.32 · n=28 3.31+3.27 · n=27 3.55+3.46 · n=26 3.91+3.91 · n=25 3.95+3.75 · n=25 4.08+3.73 · n=25 4.18+4.02 · n=24 4.32+3.85 · n=23 4.57+3.54 · n=22 4.46+3.60 · n=21 GraphCast (IFS init) MAE by lead day 1 to 9, tmin
ECMWF IFS HRESifs_hres 3.69+3.69 · n=24 3.34+3.26 · n=23 4.34+4.34 · n=22 4.89+4.89 · n=22 5.05+4.94 · n=20 4.57+4.32 · n=18 4.77+4.77 · n=19 5.33+5.33 · n=18 5.98+5.65 · n=17 6.09+5.93 · n=16 ECMWF IFS HRES MAE by lead day 1 to 9, tmin
Pangu-Weather (GFS init)pangu_gfs 5.53+5.53 · n=2 6.42+6.42 · n=1 Pangu-Weather (GFS init) MAE by lead day 1 to 9, tmin
Pangu-Weather (IFS init)pangu_ifs 4.87+4.87 · n=3 5.95+5.95 · n=2 7.57+7.57 · n=1 Pangu-Weather (IFS init) MAE by lead day 1 to 9, tmin
Persistence (baseline)persistence 2.97+0.23 · n=30 3.93+0.53 · n=30 3.97+0.57 · n=30 3.10+0.57 · n=30 3.00+0.80 · n=30 3.83+0.77 · n=30 4.47+0.87 · n=30 5.23+0.70 · n=30 5.00+0.53 · n=30 Persistence (baseline) MAE by lead day 1 to 9, tmin

Up to 1 of the scored days in this table carry a QC flag on the observation (a CLI value that disagreed with the hourly observations, or a fallback source). They are kept in the scores and counted here rather than dropped — see methodology.

Month-by-month slices, model availability and the observed-truth table live on the canonical page: they do not depend on the window, initialization or interpolation selected here.

All scores as JSON scores_latest.csv daily_errors.csv.gz data & licences