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

KAUS — Austin Bergstrom

30.1830, -97.6799 · 148 m· standard offset UTC-6 h · truth product CLIAUS

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

all available history, 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 5.27-5.27 · n=30 5.34-5.34 · n=29 5.30-5.30 · n=28 5.12-5.12 · n=27 4.87-4.87 · n=26 4.66-4.66 · n=25 4.74-4.74 · n=24 4.82-4.82 · n=23 4.67-4.67 · n=22 4.92-4.81 · n=21 ECMWF AIFS Single MAE by lead day 1 to 9, tmax
Aurora (GFS init)aurora_gfs 7.40-7.40 · n=2 9.37-9.37 · n=1 Aurora (GFS init) MAE by lead day 1 to 9, tmax
Aurora (IFS init)aurora_ifs 8.59-8.59 · n=3 7.75-7.75 · n=2 6.62-6.62 · n=1 Aurora (IFS init) MAE by lead day 1 to 9, tmax
FourCastNet v2 (GFS init)fourcastnet_gfs 5.20-5.20 · n=2 5.50-5.50 · n=1 FourCastNet v2 (GFS init) MAE by lead day 1 to 9, tmax
FourCastNet v2 (IFS init)fourcastnet_ifs 6.26-6.26 · n=3 4.75-4.75 · n=2 4.13-4.13 · n=1 FourCastNet v2 (IFS init) MAE by lead day 1 to 9, tmax
NCEP GFSgfs 1.64-1.30 · n=30 1.47-1.20 · n=29 1.55-1.11 · n=28 1.51-1.00 · n=27 1.87-1.22 · n=26 2.10-1.76 · n=25 2.82-1.92 · n=24 2.77-1.36 · n=23 2.31-1.06 · n=22 2.67-0.57 · n=21 NCEP GFS MAE by lead day 1 to 9, tmax
GraphCast (GFS init)graphcast_gfs 6.93-6.93 · n=2 8.63-8.63 · n=1 GraphCast (GFS init) MAE by lead day 1 to 9, tmax
GraphCast (IFS init)graphcast_ifs 7.34-7.34 · n=34 7.72-7.72 · n=33 7.62-7.62 · n=32 7.47-7.47 · n=31 7.22-7.22 · n=31 7.52-7.52 · n=31 7.50-7.50 · n=30 7.05-7.05 · n=29 6.26-5.90 · n=28 7.56-5.84 · n=27 GraphCast (IFS init) MAE by lead day 1 to 9, tmax
ECMWF IFS HRESifs_hres 4.69-4.59 · n=24 4.75-4.75 · n=23 4.42-4.42 · n=22 4.06-4.06 · n=22 3.83-3.83 · n=20 3.98-3.98 · n=18 4.14-4.14 · n=19 3.99-3.99 · n=18 4.10-4.10 · n=17 4.09-4.09 · n=16 ECMWF IFS HRES MAE by lead day 1 to 9, tmax
Pangu-Weather (GFS init)pangu_gfs 3.58-3.58 · n=2 4.44-4.44 · n=1 Pangu-Weather (GFS init) MAE by lead day 1 to 9, tmax
Pangu-Weather (IFS init)pangu_ifs 5.12-5.12 · n=3 5.91-5.91 · n=2 6.34-6.34 · n=1 Pangu-Weather (IFS init) MAE by lead day 1 to 9, tmax
Persistence (baseline)persistence 4.64-0.04 · n=972 6.33-0.09 · n=971 7.08-0.14 · n=970 7.39-0.19 · n=969 7.63-0.23 · n=968 7.72-0.27 · n=967 7.95-0.31 · n=966 8.11-0.34 · n=965 8.24-0.39 · n=964 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

all available history, 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 2.60+2.45 · n=30 2.94+2.74 · n=29 2.95+2.70 · n=28 2.97+2.71 · n=27 3.14+3.04 · n=26 3.26+3.23 · n=25 3.52+3.43 · n=24 3.42+3.36 · n=23 3.54+3.46 · n=22 3.27+3.23 · n=21 ECMWF AIFS Single MAE by lead day 1 to 9, tmin
Aurora (GFS init)aurora_gfs 5.95+5.95 · n=2 4.73+4.73 · n=1 Aurora (GFS init) MAE by lead day 1 to 9, tmin
Aurora (IFS init)aurora_ifs 3.05+3.05 · n=3 4.98+4.98 · n=2 4.68+4.68 · n=1 Aurora (IFS init) MAE by lead day 1 to 9, tmin
FourCastNet v2 (GFS init)fourcastnet_gfs 4.48+4.48 · n=2 3.71+3.71 · n=1 FourCastNet v2 (GFS init) MAE by lead day 1 to 9, tmin
FourCastNet v2 (IFS init)fourcastnet_ifs 2.00+0.50 · n=3 4.46+4.46 · n=2 4.42+4.42 · n=1 FourCastNet v2 (IFS init) MAE by lead day 1 to 9, tmin
NCEP GFSgfs 3.81+3.42 · n=30 3.84+3.38 · n=29 3.52+2.89 · n=28 3.28+2.83 · n=27 3.28+2.68 · n=26 3.15+2.62 · n=25 3.09+2.74 · n=24 3.13+2.30 · n=23 2.99+2.21 · n=22 2.91+2.23 · n=21 NCEP GFS MAE by lead day 1 to 9, tmin
GraphCast (GFS init)graphcast_gfs 6.49+6.49 · n=2 4.84+4.84 · n=1 GraphCast (GFS init) MAE by lead day 1 to 9, tmin
GraphCast (IFS init)graphcast_ifs 5.36+5.36 · n=34 5.58+5.55 · n=33 5.47+5.41 · n=32 5.30+5.28 · n=31 5.34+5.34 · n=31 5.16+5.16 · n=31 4.83+4.83 · n=30 4.59+4.19 · n=29 4.97+4.69 · n=28 5.74+5.46 · n=27 GraphCast (IFS init) MAE by lead day 1 to 9, tmin
ECMWF IFS HRESifs_hres 3.70+3.67 · n=24 4.12+4.05 · n=23 4.67+4.47 · n=22 4.24+4.04 · n=22 4.67+4.62 · n=20 5.04+4.95 · n=18 5.14+5.09 · n=19 5.50+5.50 · n=18 5.85+5.80 · n=17 5.44+5.44 · n=16 ECMWF IFS HRES MAE by lead day 1 to 9, tmin
Pangu-Weather (GFS init)pangu_gfs 5.39+5.39 · n=2 4.55+4.55 · n=1 Pangu-Weather (GFS init) MAE by lead day 1 to 9, tmin
Pangu-Weather (IFS init)pangu_ifs 3.49+3.49 · n=3 3.71+3.71 · n=2 2.67+2.67 · n=1 Pangu-Weather (IFS init) MAE by lead day 1 to 9, tmin
Persistence (baseline)persistence 5.02-0.03 · n=972 7.24-0.07 · n=971 8.08-0.10 · n=970 8.54-0.14 · n=969 8.77-0.18 · n=968 9.01-0.22 · n=967 9.18-0.27 · n=966 9.19-0.29 · n=965 9.27-0.33 · n=964 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