Horizontal Validation results comparing model output against observations.
Experiment Information
Area: AMM7 Experiment: Baseline Validation Type: Horizontal Validation Variables: SALT_SURFACE, TEMP_SURFACE
Overview
| Metric | SALT_SURFACE / CCI-SSS | TEMP_SURFACE / OSTIA | TEMP_SURFACE / CCI-SST |
|---|---|---|---|
| RMSE | 1.0030 | 0.9160 | 0.9018 |
| Bias | 0.2756 | 0.3920 | 0.3841 |
| Corr | 0.6019 | 0.9651 | 0.9649 |
| N points | 195,106,513 | 151,821,276 | 197,655,640 |
Annual Statistics Trends
Salinity (surface) — annual statistics timeseries (RMSE, bias, correlation)
Temperature (surface) — annual statistics timeseries (RMSE, bias, correlation)
Horizontal Validation
Statistics
SALT_SURFACE
| Metric | CCI-SSS |
|---|---|
| RMSE | 1.0030 |
| Bias | +0.2756 |
| MAE | 0.4414 |
| Corr | 0.6019 |
| Model mean | 35.1719 |
| Obs mean | 34.9009 |
View Full Statistics Report
################################################################################
SALT_SURFACE Validation Statistics
################################################################################
Format: 1.1
Created: 2026-04-30 16:58:50
Author: RT
Project: OceanICU
Institute: BB
Area: AMM7
Experiment: Baseline
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 1.0030
Bias: +0.2756
MAE: 0.4414
Correlation: 0.6019
N points: 195,106,513
Model mean: 35.1719
Obs mean: 34.9009
Model std: 0.9339
Obs std: 1.1772
Error distribution:
Min: -32.4635
5th pct: -0.2833
25th pct: +0.0023
Median: +0.1464
75th pct: +0.3972
95th pct: +1.2992
Max: +16.3415
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 0.8386 +0.2295 0.3850 0.6247
Feb 0.9104 +0.2222 0.3944 0.5860
Mar 1.0133 +0.2442 0.4368 0.5628
Apr 1.0604 +0.2677 0.4626 0.5683
May 1.0807 +0.2840 0.4606 0.6037
Jun 1.1435 +0.3240 0.4916 0.6028
Jul 1.1168 +0.3159 0.4775 0.6042
Aug 1.0866 +0.3145 0.4735 0.5962
Sep 1.0521 +0.3070 0.4613 0.5998
Oct 0.9783 +0.2872 0.4341 0.6148
Nov 0.9261 +0.2809 0.4301 0.6060
Dec 0.8481 +0.2275 0.3871 0.6223
--------------------------------------------
All 1.0030 +0.2756 0.4414 0.6019
================================================================================
Period: 2016 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 0.9593
Bias: +0.3249
MAE: 0.4501
Correlation: 0.6329
N points: 24,460,506
Model mean: 35.2095
Obs mean: 34.8875
Model std: 0.8423
Obs std: 1.1664
Error distribution:
Min: -25.8268
5th pct: -0.2306
25th pct: +0.0545
Median: +0.1943
75th pct: +0.4087
95th pct: +1.3440
Max: +16.3415
================================================================================
Period: 2017 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 1.0460
Bias: +0.2893
MAE: 0.4306
Correlation: 0.5489
N points: 24,395,369
Model mean: 35.2131
Obs mean: 34.9268
Model std: 0.8926
Obs std: 1.1686
Error distribution:
Min: -28.2579
5th pct: -0.2065
25th pct: +0.0251
Median: +0.1375
75th pct: +0.3621
95th pct: +1.3496
Max: +16.3139
================================================================================
Period: 2018 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 0.9921
Bias: +0.2380
MAE: 0.4117
Correlation: 0.5912
N points: 24,338,489
Model mean: 35.1741
Obs mean: 34.9407
Model std: 0.9086
Obs std: 1.1622
Error distribution:
Min: -29.9102
5th pct: -0.2936
25th pct: -0.0085
Median: +0.1277
75th pct: +0.3523
95th pct: +1.1403
Max: +15.5873
================================================================================
Period: 2019 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 0.9992
Bias: +0.2882
MAE: 0.4403
Correlation: 0.5874
N points: 24,377,458
Model mean: 35.1845
Obs mean: 34.8998
Model std: 0.8905
Obs std: 1.1549
Error distribution:
Min: -28.8293
5th pct: -0.2543
25th pct: +0.0162
Median: +0.1563
75th pct: +0.3962
95th pct: +1.2861
Max: +14.6536
================================================================================
Period: 2020 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 1.0207
Bias: +0.2902
MAE: 0.4547
Correlation: 0.5980
N points: 24,422,636
Model mean: 35.1712
Obs mean: 34.8879
Model std: 0.9276
Obs std: 1.1916
Error distribution:
Min: -29.0632
5th pct: -0.2690
25th pct: -0.0063
Median: +0.1350
75th pct: +0.4119
95th pct: +1.3924
Max: +14.6794
================================================================================
Period: 2021 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 1.0191
Bias: +0.2595
MAE: 0.4307
Correlation: 0.6044
N points: 24,370,685
Model mean: 35.1348
Obs mean: 34.8807
Model std: 0.9723
Obs std: 1.2061
Error distribution:
Min: -28.0755
5th pct: -0.2896
25th pct: +0.0035
Median: +0.1401
75th pct: +0.3896
95th pct: +1.2146
Max: +15.6121
================================================================================
Period: 2022 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 0.9968
Bias: +0.2628
MAE: 0.4543
Correlation: 0.6181
N points: 24,370,685
Model mean: 35.1515
Obs mean: 34.8939
Model std: 1.0260
Obs std: 1.1594
Error distribution:
Min: -32.4635
5th pct: -0.3304
25th pct: -0.0181
Median: +0.1445
75th pct: +0.4339
95th pct: +1.2720
Max: +12.9008
================================================================================
Period: 2023 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:58:50
--- CCI-SSS ---
RMSE: 0.9914
Bias: +0.2515
MAE: 0.4584
Correlation: 0.6351
N points: 24,370,685
Model mean: 35.1362
Obs mean: 34.8901
Model std: 0.9941
Obs std: 1.2056
Error distribution:
Min: -29.5309
5th pct: -0.3829
25th pct: -0.0531
Median: +0.1321
75th pct: +0.4246
95th pct: +1.3064
Max: +15.3259
📄 Download Statistics Report (txt) · 📄 YAML
TEMP_SURFACE
| Metric | OSTIA | CCI-SST |
|---|---|---|
| RMSE | 0.9160 | 0.9018 |
| Bias | +0.3920 | +0.3841 |
| MAE | 0.7266 | 0.7152 |
| Corr | 0.9651 | 0.9649 |
| Model mean | 12.2628 | 12.4600 |
| Obs mean | 11.8707 | 12.0759 |
View Full Statistics Report
################################################################################
TEMP_SURFACE Validation Statistics
################################################################################
Format: 1.1
Created: 2026-04-30 16:22:30
Author: RT
Project: OceanICU
Institute: BB
Area: AMM7
Experiment: Baseline
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.9160
Bias: +0.3920
MAE: 0.7266
Correlation: 0.9651
N points: 151,821,276
Model mean: 12.2628
Obs mean: 11.8707
Model std: 4.0162
Obs std: 3.8133
Error distribution:
Min: -9.7834
5th pct: -0.8868
25th pct: -0.0976
Median: +0.3996
75th pct: +0.8998
95th pct: +1.6521
Max: +10.0921
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 0.9340 +0.3050 0.7263 0.9555
Feb 0.9121 +0.2936 0.6972 0.9589
Mar 0.8415 +0.2331 0.6405 0.9637
Apr 0.7604 +0.1807 0.5835 0.9705
May 0.8391 +0.3735 0.6565 0.9716
Jun 1.2281 +0.7980 0.9955 0.9552
Jul 1.3036 +0.8952 1.0867 0.9534
Aug 1.0455 +0.6093 0.8451 0.9626
Sep 0.7555 +0.2528 0.5822 0.9765
Oct 0.6902 +0.1415 0.5374 0.9778
Nov 0.7899 +0.2486 0.6275 0.9688
Dec 0.9270 +0.3613 0.7343 0.9595
--------------------------------------------
All 0.9160 +0.3920 0.7266 0.9651
--- CCI-SST ---
RMSE: 0.9018
Bias: +0.3841
MAE: 0.7152
Correlation: 0.9649
N points: 197,655,640
Model mean: 12.4600
Obs mean: 12.0759
Model std: 3.8903
Obs std: 3.7509
Error distribution:
Min: -11.0026
5th pct: -0.8721
25th pct: -0.1136
Median: +0.3811
75th pct: +0.8884
95th pct: +1.6397
Max: +8.8265
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 0.8997 +0.2875 0.6939 0.9561
Feb 0.8773 +0.2977 0.6676 0.9598
Mar 0.8263 +0.2625 0.6305 0.9636
Apr 0.7444 +0.2077 0.5751 0.9700
May 0.8260 +0.3887 0.6490 0.9703
Jun 1.1845 +0.7575 0.9614 0.9544
Jul 1.2591 +0.8469 1.0452 0.9536
Aug 1.0436 +0.6036 0.8462 0.9628
Sep 0.7678 +0.2521 0.5932 0.9760
Oct 0.7131 +0.1326 0.5564 0.9766
Nov 0.7939 +0.2235 0.6293 0.9675
Dec 0.9218 +0.3378 0.7267 0.9574
--------------------------------------------
All 0.9018 +0.3841 0.7152 0.9649
================================================================================
Period: 2016 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.8768
Bias: +0.1957
MAE: 0.6889
Correlation: 0.9610
N points: 19,016,628
Model mean: 12.0692
Obs mean: 11.8735
Model std: 3.9886
Obs std: 3.7392
Error distribution:
Min: -8.4243
5th pct: -1.0961
25th pct: -0.2904
Median: +0.2150
75th pct: +0.7203
95th pct: +1.4537
Max: +6.9846
--- CCI-SST ---
RMSE: 0.8298
Bias: +0.1936
MAE: 0.6514
Correlation: 0.9638
N points: 24,757,704
Model mean: 12.2449
Obs mean: 12.0513
Model std: 3.8616
Obs std: 3.7266
Error distribution:
Min: -8.9750
5th pct: -1.0402
25th pct: -0.2701
Median: +0.2129
75th pct: +0.6939
95th pct: +1.3793
Max: +7.1261
================================================================================
Period: 2017 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.8807
Bias: +0.3935
MAE: 0.7007
Correlation: 0.9662
N points: 18,964,670
Model mean: 12.2909
Obs mean: 11.8974
Model std: 3.8412
Obs std: 3.6558
Error distribution:
Min: -6.1325
5th pct: -0.8441
25th pct: -0.0802
Median: +0.4026
75th pct: +0.8828
95th pct: +1.6333
Max: +8.6925
--- CCI-SST ---
RMSE: 0.8524
Bias: +0.3655
MAE: 0.6785
Correlation: 0.9671
N points: 24,690,059
Model mean: 12.4918
Obs mean: 12.1263
Model std: 3.7457
Obs std: 3.6290
Error distribution:
Min: -6.5475
5th pct: -0.8617
25th pct: -0.1087
Median: +0.3653
75th pct: +0.8458
95th pct: +1.5749
Max: +6.7065
================================================================================
Period: 2018 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.9849
Bias: +0.4776
MAE: 0.7812
Correlation: 0.9629
N points: 18,964,670
Model mean: 12.1215
Obs mean: 11.6439
Model std: 4.1821
Obs std: 3.9844
Error distribution:
Min: -9.7834
5th pct: -0.8793
25th pct: -0.0494
Median: +0.4812
75th pct: +1.0063
95th pct: +1.8040
Max: +8.3029
--- CCI-SST ---
RMSE: 0.9695
Bias: +0.5086
MAE: 0.7647
Correlation: 0.9651
N points: 24,690,050
Model mean: 12.3127
Obs mean: 11.8041
Model std: 4.0178
Obs std: 3.8476
Error distribution:
Min: -10.7811
5th pct: -0.7440
25th pct: -0.0015
Median: +0.4971
75th pct: +1.0093
95th pct: +1.8266
Max: +8.2242
================================================================================
Period: 2019 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.9111
Bias: +0.4732
MAE: 0.7328
Correlation: 0.9687
N points: 18,964,670
Model mean: 12.2363
Obs mean: 11.7631
Model std: 3.9060
Obs std: 3.6817
Error distribution:
Min: -7.1780
5th pct: -0.7480
25th pct: -0.0108
Median: +0.4761
75th pct: +0.9800
95th pct: +1.6861
Max: +7.3279
--- CCI-SST ---
RMSE: 0.9227
Bias: +0.5084
MAE: 0.7423
Correlation: 0.9670
N points: 24,690,060
Model mean: 12.4605
Obs mean: 11.9521
Model std: 3.7935
Obs std: 3.6177
Error distribution:
Min: -8.6994
5th pct: -0.6930
25th pct: +0.0024
Median: +0.5044
75th pct: +1.0226
95th pct: +1.7321
Max: +6.9408
================================================================================
Period: 2020 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.8991
Bias: +0.4208
MAE: 0.7118
Correlation: 0.9673
N points: 19,016,628
Model mean: 12.2002
Obs mean: 11.7794
Model std: 3.8771
Obs std: 3.6783
Error distribution:
Min: -8.2411
5th pct: -0.8051
25th pct: -0.0540
Median: +0.4241
75th pct: +0.9163
95th pct: +1.6575
Max: +8.3450
--- CCI-SST ---
RMSE: 0.8976
Bias: +0.4669
MAE: 0.7145
Correlation: 0.9679
N points: 24,757,704
Model mean: 12.3851
Obs mean: 11.9182
Model std: 3.7680
Obs std: 3.6279
Error distribution:
Min: -9.9685
5th pct: -0.7210
25th pct: -0.0109
Median: +0.4606
75th pct: +0.9506
95th pct: +1.6736
Max: +7.1809
================================================================================
Period: 2021 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.9805
Bias: +0.4560
MAE: 0.7747
Correlation: 0.9601
N points: 18,964,670
Model mean: 12.1911
Obs mean: 11.7351
Model std: 4.0802
Obs std: 3.8776
Error distribution:
Min: -8.5194
5th pct: -0.8656
25th pct: -0.0653
Median: +0.4509
75th pct: +0.9944
95th pct: +1.8046
Max: +8.3180
--- CCI-SST ---
RMSE: 0.9625
Bias: +0.4274
MAE: 0.7556
Correlation: 0.9598
N points: 24,689,971
Model mean: 12.4060
Obs mean: 11.9786
Model std: 3.9558
Obs std: 3.8267
Error distribution:
Min: -10.7180
5th pct: -0.8792
25th pct: -0.1153
Median: +0.3999
75th pct: +0.9553
95th pct: +1.7966
Max: +7.8217
================================================================================
Period: 2022 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.8457
Bias: +0.3520
MAE: 0.6691
Correlation: 0.9713
N points: 18,964,670
Model mean: 12.4037
Obs mean: 12.0517
Model std: 4.0073
Obs std: 3.8585
Error distribution:
Min: -6.4934
5th pct: -0.8451
25th pct: -0.1163
Median: +0.3536
75th pct: +0.8264
95th pct: +1.5326
Max: +6.9722
--- CCI-SST ---
RMSE: 0.8367
Bias: +0.3027
MAE: 0.6635
Correlation: 0.9688
N points: 24,690,060
Model mean: 12.6041
Obs mean: 12.3015
Model std: 3.8767
Obs std: 3.7716
Error distribution:
Min: -7.8750
5th pct: -0.9148
25th pct: -0.1883
Median: +0.2948
75th pct: +0.7911
95th pct: +1.5135
Max: +7.0232
================================================================================
Period: 2023 | Model: pyGETM
================================================================================
Analysed: 2026-04-30 16:22:30
--- OSTIA ---
RMSE: 0.9464
Bias: +0.3678
MAE: 0.7539
Correlation: 0.9640
N points: 18,964,670
Model mean: 12.5899
Obs mean: 12.2221
Model std: 4.2069
Obs std: 3.9821
Error distribution:
Min: -8.7341
5th pct: -1.0365
25th pct: -0.1473
Median: +0.3920
75th pct: +0.9128
95th pct: +1.6738
Max: +10.0921
--- CCI-SST ---
RMSE: 0.9404
Bias: +0.2997
MAE: 0.7511
Correlation: 0.9601
N points: 24,690,032
Model mean: 12.7754
Obs mean: 12.4757
Model std: 4.0655
Obs std: 3.9041
Error distribution:
Min: -11.0026
5th pct: -1.1399
25th pct: -0.2606
Median: +0.3086
75th pct: +0.8701
95th pct: +1.6717
Max: +8.8265
📄 Download Statistics Report (txt) · 📄 YAML
Plots
Full Period
SALT_SURFACE
Salinity (surface) — monthly by year
Salinity (surface) — monthly statistics
CCI-SSS
Salinity (surface) — CCI-SSS comparison
Salinity (surface) — CCI-SSS monthly maps
Salinity (surface) — CCI-SSS monthly taylor
Salinity (surface) — CCI-SSS pdf annual
Salinity (surface) — CCI-SSS pdf monthly
Salinity (surface) — CCI-SSS spatial stats
TEMP_SURFACE
Temperature (surface) — monthly by year CCI-SST
Temperature (surface) — monthly by year OSTIA
Temperature (surface) — monthly statistics
CCI-SST
Temperature (surface) — CCI-SST comparison
Temperature (surface) — CCI-SST monthly maps
Temperature (surface) — CCI-SST monthly taylor
Temperature (surface) — CCI-SST pdf annual
Temperature (surface) — CCI-SST pdf monthly
Temperature (surface) — CCI-SST spatial stats
OSTIA
Temperature (surface) — OSTIA comparison
Temperature (surface) — OSTIA monthly maps
Temperature (surface) — OSTIA monthly taylor
Temperature (surface) — OSTIA pdf annual
Temperature (surface) — OSTIA pdf monthly
Temperature (surface) — OSTIA spatial stats
Taylor diagram
Gridded 3D Validation
Statistics
SALT_3D
| Metric | WOA |
|---|---|
| RMSE | 0.3919 |
| Bias | -0.0277 |
| MAE | 0.1981 |
| Corr | 0.6007 |
| Model mean | 35.2548 |
| Obs mean | 35.2825 |
View Full Statistics Report
################################################################################
SALT Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-07 08:29:01
Author: RT
Project: OceanICU
Institute: BB
Area: AMM7
Experiment: Baseline
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 19:16:30
--- WOA ---
RMSE: 0.3919
Bias: -0.0277
MAE: 0.1981
Correlation: 0.6007
N points: 115,638,048
Model mean: 35.2548
Obs mean: 35.2825
Model std: 0.3798
Obs std: 0.4743
Error distribution:
Min: -14.4854
5th pct: -0.6332
25th pct: -0.1051
Median: +0.0088
75th pct: +0.1072
95th pct: +0.3166
Max: +14.9160
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 0.3221 -0.0210 0.1835 0.6372
Feb 0.3699 -0.0106 0.1941 0.5878
Mar 0.3995 -0.0144 0.1933 0.6024
Apr 0.3947 -0.0258 0.1962 0.6051
May 0.4179 -0.0283 0.2017 0.5929
Jun 0.4413 -0.0385 0.2081 0.5725
Jul 0.4210 -0.0327 0.2098 0.5934
Aug 0.4182 -0.0345 0.2063 0.5841
Sep 0.3742 -0.0381 0.1985 0.6114
Oct 0.4534 -0.0156 0.2118 0.6040
Nov 0.3411 -0.0348 0.1895 0.6370
Dec 0.3212 -0.0377 0.1842 0.6364
--------------------------------------------
All 0.3919 -0.0277 0.1981 0.6007
📄 Download Statistics Report (txt) · 📄 YAML
TEMP_3D
| Metric | WOA |
|---|---|
| RMSE | 2.6073 |
| Bias | -1.0462 |
| MAE | 1.8039 |
| Corr | 0.8408 |
| Model mean | 8.1345 |
| Obs mean | 9.1808 |
View Full Statistics Report
################################################################################
TEMP Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-07 08:00:00
Author: RT
Project: OceanICU
Institute: BB
Area: AMM7
Experiment: Baseline
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 18:47:19
--- WOA ---
RMSE: 2.6073
Bias: -1.0462
MAE: 1.8039
Correlation: 0.8408
N points: 115,638,048
Model mean: 8.1345
Obs mean: 9.1808
Model std: 4.4103
Obs std: 3.7631
Error distribution:
Min: -8.7417
5th pct: -5.7957
25th pct: -2.2220
Median: -0.4773
75th pct: +0.3474
95th pct: +1.9338
Max: +12.5807
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 2.5164 -1.1156 1.7042 0.8091
Feb 2.4962 -1.1176 1.6789 0.8018
Mar 2.4812 -1.1143 1.6618 0.7988
Apr 2.4727 -1.1298 1.6499 0.8055
May 2.5160 -1.0494 1.7057 0.8158
Jun 2.7101 -0.8669 1.9320 0.8265
Jul 2.8396 -0.8163 2.0355 0.8463
Aug 2.8265 -0.8624 2.0408 0.8634
Sep 2.7131 -1.0045 1.9416 0.8716
Oct 2.6079 -1.1622 1.8211 0.8674
Nov 2.5519 -1.1486 1.7503 0.8476
Dec 2.5181 -1.1673 1.7247 0.8325
--------------------------------------------
All 2.6073 -1.0462 1.8039 0.8408
📄 Download Statistics Report (txt) · 📄 YAML
Plots
Full Period
Salinity at 5 m depth — model vs observations comparison
Salinity at 5 m depth — spatial distribution of statistics
Salinity at 50 m depth — model vs observations comparison
Salinity at 50 m depth — spatial distribution of statistics
Salinity at 100 m depth — model vs observations comparison
Salinity at 100 m depth — spatial distribution of statistics
Salinity at 200 m depth — model vs observations comparison
Salinity at 200 m depth — spatial distribution of statistics
Salinity at 500 m depth — model vs observations comparison
Salinity at 500 m depth — spatial distribution of statistics
Salinity — monthly 3D profile statistics
Salinity — monthly 3D Taylor diagram
Taylor diagram
Temperature at 5 m depth — model vs observations comparison
Temperature at 5 m depth — spatial distribution of statistics
Temperature at 50 m depth — model vs observations comparison
Temperature at 50 m depth — spatial distribution of statistics
Temperature at 100 m depth — model vs observations comparison
Temperature at 100 m depth — spatial distribution of statistics
Temperature at 200 m depth — model vs observations comparison
Temperature at 200 m depth — spatial distribution of statistics
Temperature at 500 m depth — model vs observations comparison
Temperature at 500 m depth — spatial distribution of statistics
Temperature — monthly 3D profile statistics
Temperature — monthly 3D Taylor diagram
ICES Point Profiles
Statistics
PSAL
| Metric | ICES point observations |
|---|---|
| RMSE | 1.0428 |
| Bias | +0.2043 |
| MAE | 0.3132 |
| Corr | 0.6842 |
| Model mean | 34.9848 |
| Obs mean | 34.7805 |
View Full Statistics Report
################################################################################
PSAL Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-04-30 21:16:02
Area: AMM7
Experiment: Baseline
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:26:03
--- ICES point observations ---
RMSE: 1.0428
Bias: +0.2043
MAE: 0.3132
Correlation: 0.6842
N points: 4,479,562
N profiles: 32,134
Model mean: 34.9848
Obs mean: 34.7805
Model std: 0.7657
Obs std: 1.3806
Error distribution:
Min: -34.5193
5th pct: -0.2809
25th pct: -0.0032
Median: +0.0935
75th pct: +0.2111
95th pct: +0.6663
Max: +34.4219
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 288,164 +1.2476 3.6108 0.5618
10-25m 420,745 +0.4439 1.4158 0.6849
25-50m 567,989 +0.1566 0.5095 0.7681
50-100m 763,824 +0.1100 0.2829 0.8003
100-200m 681,882 +0.0646 0.1713 0.8172
200-500m 782,467 +0.0923 0.1351 0.8450
500-1000m 586,611 +0.0644 0.1334 0.8939
📄 Download Statistics Report (txt) · 📄 YAML
TEMP
| Metric | ICES point observations |
|---|---|
| RMSE | 1.1857 |
| Bias | +0.1009 |
| MAE | 0.8000 |
| Corr | 0.9567 |
| Model mean | 7.7389 |
| Obs mean | 7.6380 |
View Full Statistics Report
################################################################################
TEMP Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-04-30 21:13:47
Area: AMM7
Experiment: Baseline
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:24:06
--- ICES point observations ---
RMSE: 1.1857
Bias: +0.1009
MAE: 0.8000
Correlation: 0.9567
N points: 4,488,796
N profiles: 28,989
Model mean: 7.7389
Obs mean: 7.6380
Model std: 3.9448
Obs std: 4.0496
Error distribution:
Min: -10.1696
5th pct: -1.6426
25th pct: -0.4082
Median: +0.0595
75th pct: +0.6308
95th pct: +2.0384
Max: +9.2800
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 286,658 +0.3111 1.2264 0.9639
10-25m 422,418 -0.1907 1.4237 0.9271
25-50m 570,518 -0.2559 1.3481 0.8649
50-100m 766,720 +0.0922 0.8780 0.8731
100-200m 684,363 +0.1123 0.7826 0.8729
200-500m 783,657 +0.1348 1.3744 0.8557
500-1000m 586,581 +0.2550 1.2684 0.9583
📄 Download Statistics Report (txt) · 📄 YAML
Plots
Practical Salinity — statistics vs depth profile
Temperature — statistics vs depth profile
Argo Float Profiles
Statistics
PSAL
| Metric | ARGO floats |
|---|---|
| RMSE | 4.3342 |
| Bias | +0.6646 |
| MAE | 0.7583 |
| Corr | 0.1743 |
| Model mean | 35.3563 |
| Obs mean | 34.6917 |
View Full Statistics Report
################################################################################
PSAL Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-05 10:00:29
Area: AMM7
Experiment: Baseline
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-05 10:00:29
--- ARGO floats ---
RMSE: 4.3342
Bias: +0.6646
MAE: 0.7583
Correlation: 0.1743
N points: 4,905,728
N profiles: 18,473
Model mean: 35.3563
Obs mean: 34.6917
Model std: 0.3082
Obs std: 4.3259
Error distribution:
Min: -26.4433
5th pct: -0.2453
25th pct: -0.0128
Median: +0.0608
75th pct: +0.1838
95th pct: +0.4500
Max: +36.8896
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 97,572 +0.5546 3.2684 0.1719
10-25m 146,016 +0.7025 3.6024 0.1580
25-50m 232,397 +0.7747 3.7305 0.1229
50-100m 425,227 +0.7950 3.8506 0.1004
100-200m 495,254 +0.7208 4.4644 0.1627
200-500m 1,075,494 +0.7137 4.6168 0.2005
500-1000m 1,117,739 +0.6148 4.5117 0.2520
📄 Download Statistics Report (txt) · 📄 YAML
TEMP
| Metric | ARGO floats |
|---|---|
| RMSE | 1.2648 |
| Bias | +0.2033 |
| MAE | 0.9381 |
| Corr | 0.9624 |
| Model mean | 8.2875 |
| Obs mean | 8.0842 |
View Full Statistics Report
################################################################################
TEMP Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-05 09:57:30
Area: AMM7
Experiment: Baseline
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-05 09:57:30
--- ARGO floats ---
RMSE: 1.2648
Bias: +0.2033
MAE: 0.9381
Correlation: 0.9624
N points: 4,906,063
N profiles: 18,473
Model mean: 8.2875
Obs mean: 8.0842
Model std: 4.5916
Obs std: 4.4683
Error distribution:
Min: -49.6595
5th pct: -1.6005
25th pct: -0.5229
Median: +0.0218
75th pct: +0.9589
95th pct: +2.3211
Max: +20.4119
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 97,583 +0.4029 1.0456 0.9741
10-25m 146,026 +0.0600 1.1311 0.9573
25-50m 232,410 +0.3038 1.2722 0.9241
50-100m 425,244 +0.7066 1.5131 0.9069
100-200m 495,283 +0.3951 1.4952 0.9112
200-500m 1,075,630 +0.1414 1.3630 0.9361
500-1000m 1,117,875 -0.2909 1.0199 0.9690
📄 Download Statistics Report (txt) · 📄 YAML
Plots
Amm7 Argo Argo Overview
AMM7_ARGO — Hovmöller diagram
Practical Salinity — statistics vs depth profile
Temperature — statistics vs depth profile
Observations
ARGO Observations — 2016-2023
ARGO Station Map
ARGO Observation Density
ARGO Hovmoller
ICES Observations — 2016-2022
ICES Station Map
ICES Observation Density
ICES Alk Hovmoller
ICES Amon Hovmoller
ICES Doxy Hovmoller
ICES Ntra Hovmoller
ICES Ph Hovmoller
ICES Phos Hovmoller
ICES PSAL Hovmoller
ICES Slca Hovmoller
ICES TEMP Hovmoller
ICES Observations — 2016-2023
ICES Station Map
ICES Observation Density
ICES Alk Hovmoller
ICES Amon Hovmoller
ICES Cphl Hovmoller
ICES Doxy Hovmoller
ICES Ntra Hovmoller
ICES Ph Hovmoller
ICES Phos Hovmoller
ICES PSAL Hovmoller
ICES Slca Hovmoller
ICES TEMP Hovmoller
Methodology
Horizontal Validation
Model surface fields compared against gridded satellite products and in-situ observations.
Statistics: RMSE, Bias, MAE, Pearson correlation.
Spatial statistics show the error distribution across the domain.
Gridded 3D Validation
Model vertical profiles compared against gridded 3D climatologies.
Statistics: RMSE and Bias at each depth level.
ICES Point Profiles
Quality-controlled hydrographic profiles from the ICES data portal (temperature, salinity, biogeochemical variables).
Argo Float Profiles
Autonomous profiling floats providing temperature and salinity profiles to 2000 m depth (Ifremer ERDDAP).