Horizontal Validation results comparing model output against observations.
Experiment Information
Area: AMM7 Experiment: CMEMS Validation Type: Horizontal Validation Variables: SALT_SURFACE, TEMP_SURFACE
Overview
| Metric | SALT_SURFACE / CCI-SSS | TEMP_SURFACE / OSTIA | TEMP_SURFACE / CCI-SST |
|---|---|---|---|
| RMSE | 1.0607 | 1.1413 | 1.0988 |
| Bias | -0.0323 | 0.6880 | 0.6777 |
| Corr | 0.8367 | 0.9610 | 0.9630 |
| 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 | 1.0607 |
| Bias | -0.0323 |
| MAE | 0.4797 |
| Corr | 0.8367 |
| Model mean | 34.8636 |
| Obs mean | 34.9009 |
View Full Statistics Report
################################################################################
SALT_SURFACE Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-08 17:11:33
Author: RT
Project: OceanICU
Institute: BB
Area: AMM7
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 1.0607
Bias: -0.0323
MAE: 0.4797
Correlation: 0.8367
N points: 195,106,513
Model mean: 34.8636
Obs mean: 34.9009
Model std: 1.8646
Obs std: 1.1772
Error distribution:
Min: -32.4903
5th pct: -1.6169
25th pct: -0.0780
Median: +0.0726
75th pct: +0.3042
95th pct: +0.9452
Max: +12.3821
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 0.8388 +0.0465 0.3902 0.8231
Feb 0.8943 +0.0328 0.3982 0.8177
Mar 1.0006 +0.0175 0.4404 0.8135
Apr 1.0966 -0.0119 0.4801 0.8213
May 1.1882 -0.0753 0.5071 0.8507
Jun 1.3549 -0.1180 0.5677 0.8442
Jul 1.3352 -0.1511 0.5715 0.8304
Aug 1.2628 -0.1154 0.5641 0.8259
Sep 1.1832 -0.0716 0.5217 0.8386
Oct 0.9864 -0.0010 0.4560 0.8338
Nov 0.9272 +0.0507 0.4408 0.8239
Dec 0.9134 +0.0137 0.4142 0.8311
--------------------------------------------
All 1.0607 -0.0323 0.4797 0.8367
================================================================================
Period: 2016 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 1.0796
Bias: +0.0085
MAE: 0.5070
Correlation: 0.8303
N points: 24,460,506
Model mean: 34.8929
Obs mean: 34.8875
Model std: 1.8572
Obs std: 1.1664
Error distribution:
Min: -25.9802
5th pct: -1.3326
25th pct: -0.0760
Median: +0.1063
75th pct: +0.3527
95th pct: +1.0101
Max: +12.3821
================================================================================
Period: 2017 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 0.9894
Bias: -0.0370
MAE: 0.4350
Correlation: 0.8368
N points: 24,395,369
Model mean: 34.8868
Obs mean: 34.9268
Model std: 1.7528
Obs std: 1.1686
Error distribution:
Min: -28.0616
5th pct: -1.4195
25th pct: -0.0959
Median: +0.0304
75th pct: +0.2517
95th pct: +0.9291
Max: +9.1558
================================================================================
Period: 2018 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 0.8767
Bias: -0.0191
MAE: 0.3859
Correlation: 0.8657
N points: 24,338,489
Model mean: 34.9172
Obs mean: 34.9407
Model std: 1.6709
Obs std: 1.1622
Error distribution:
Min: -29.8512
5th pct: -0.9527
25th pct: -0.1005
Median: +0.0411
75th pct: +0.2498
95th pct: +0.7908
Max: +7.9468
================================================================================
Period: 2019 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 0.9390
Bias: -0.0089
MAE: 0.4355
Correlation: 0.8454
N points: 24,377,458
Model mean: 34.8873
Obs mean: 34.8998
Model std: 1.7062
Obs std: 1.1549
Error distribution:
Min: -29.7854
5th pct: -1.2546
25th pct: -0.0857
Median: +0.0595
75th pct: +0.2879
95th pct: +0.9240
Max: +8.0505
================================================================================
Period: 2020 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 0.9259
Bias: +0.0438
MAE: 0.4365
Correlation: 0.8375
N points: 24,422,636
Model mean: 34.9239
Obs mean: 34.8879
Model std: 1.6997
Obs std: 1.1916
Error distribution:
Min: -28.9147
5th pct: -1.0658
25th pct: -0.0615
Median: +0.0694
75th pct: +0.3168
95th pct: +1.0586
Max: +8.9942
================================================================================
Period: 2021 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 1.0742
Bias: -0.0618
MAE: 0.4787
Correlation: 0.8473
N points: 24,370,685
Model mean: 34.8130
Obs mean: 34.8807
Model std: 1.9232
Obs std: 1.2061
Error distribution:
Min: -27.8038
5th pct: -1.7676
25th pct: -0.0616
Median: +0.0734
75th pct: +0.2906
95th pct: +0.8820
Max: +11.8472
================================================================================
Period: 2022 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 1.1325
Bias: -0.0067
MAE: 0.5116
Correlation: 0.8296
N points: 24,370,685
Model mean: 34.8814
Obs mean: 34.8939
Model std: 1.9137
Obs std: 1.1594
Error distribution:
Min: -32.4903
5th pct: -1.5464
25th pct: -0.0589
Median: +0.1012
75th pct: +0.3480
95th pct: +1.0333
Max: +10.7502
================================================================================
Period: 2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 17:11:33
--- CCI-SSS ---
RMSE: 1.4686
Bias: -0.1778
MAE: 0.6473
Correlation: 0.8015
N points: 24,370,685
Model mean: 34.7064
Obs mean: 34.8901
Model std: 2.3031
Obs std: 1.2056
Error distribution:
Min: -28.9906
5th pct: -3.2024
25th pct: -0.0828
Median: +0.0953
75th pct: +0.3439
95th pct: +0.9217
Max: +6.5050
📄 Download Statistics Report (txt) · 📄 YAML
TEMP_SURFACE
| Metric | OSTIA | CCI-SST |
|---|---|---|
| RMSE | 1.1413 | 1.0988 |
| Bias | +0.6880 | +0.6777 |
| MAE | 0.9304 | 0.8850 |
| Corr | 0.9610 | 0.9630 |
| Model mean | 12.5587 | 12.7536 |
| Obs mean | 11.8707 | 12.0759 |
View Full Statistics Report
################################################################################
TEMP_SURFACE Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-08 16:35:31
Author: RT
Project: OceanICU
Institute: BB
Area: AMM7
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.1413
Bias: +0.6880
MAE: 0.9304
Correlation: 0.9610
N points: 151,821,276
Model mean: 12.5587
Obs mean: 11.8707
Model std: 4.1250
Obs std: 3.8133
Error distribution:
Min: -8.7641
5th pct: -0.7154
25th pct: +0.1569
Median: +0.6938
75th pct: +1.2403
95th pct: +2.0577
Max: +10.3511
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 1.0662 +0.4158 0.8314 0.9516
Feb 1.0342 +0.3996 0.8026 0.9569
Mar 0.9865 +0.3976 0.7682 0.9601
Apr 0.9751 +0.5232 0.7787 0.9659
May 1.2053 +0.8779 0.9908 0.9657
Jun 1.6858 +1.3275 1.4104 0.9443
Jul 1.6447 +1.2961 1.3954 0.9472
Aug 1.3229 +0.9866 1.1060 0.9599
Sep 0.9637 +0.6132 0.7732 0.9750
Oct 0.8301 +0.4060 0.6628 0.9755
Nov 0.9600 +0.4646 0.7669 0.9634
Dec 1.0871 +0.5277 0.8676 0.9553
--------------------------------------------
All 1.1413 +0.6880 0.9304 0.9610
--- CCI-SST ---
RMSE: 1.0988
Bias: +0.6777
MAE: 0.8850
Correlation: 0.9630
N points: 197,655,640
Model mean: 12.7536
Obs mean: 12.0759
Model std: 3.9975
Obs std: 3.7509
Error distribution:
Min: -8.6116
5th pct: -0.6143
25th pct: +0.1526
Median: +0.6576
75th pct: +1.2001
95th pct: +2.0247
Max: +9.8150
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 1.0157 +0.4205 0.7832 0.9547
Feb 0.9874 +0.4259 0.7585 0.9594
Mar 0.9561 +0.4372 0.7413 0.9619
Apr 0.9438 +0.5342 0.7480 0.9670
May 1.1622 +0.8527 0.9451 0.9657
Jun 1.5979 +1.2445 1.3184 0.9449
Jul 1.5647 +1.2205 1.3068 0.9489
Aug 1.2921 +0.9643 1.0655 0.9621
Sep 0.9516 +0.6128 0.7562 0.9763
Oct 0.8124 +0.4098 0.6375 0.9775
Nov 0.9186 +0.4568 0.7226 0.9669
Dec 1.0494 +0.5349 0.8258 0.9579
--------------------------------------------
All 1.0988 +0.6777 0.8850 0.9630
================================================================================
Period: 2016 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.0372
Bias: +0.4304
MAE: 0.8261
Correlation: 0.9554
N points: 19,016,628
Model mean: 12.3040
Obs mean: 11.8735
Model std: 4.0874
Obs std: 3.7392
Error distribution:
Min: -7.7802
5th pct: -1.0101
25th pct: -0.1190
Median: +0.4481
75th pct: +0.9985
95th pct: +1.7915
Max: +7.7702
--- CCI-SST ---
RMSE: 0.9632
Bias: +0.3896
MAE: 0.7552
Correlation: 0.9596
N points: 24,757,704
Model mean: 12.4409
Obs mean: 12.0513
Model std: 3.9888
Obs std: 3.7266
Error distribution:
Min: -7.4719
5th pct: -0.9291
25th pct: -0.1327
Median: +0.3825
75th pct: +0.9264
95th pct: +1.6953
Max: +9.1459
================================================================================
Period: 2017 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.0966
Bias: +0.6580
MAE: 0.9017
Correlation: 0.9622
N points: 18,964,670
Model mean: 12.5554
Obs mean: 11.8974
Model std: 3.9457
Obs std: 3.6558
Error distribution:
Min: -6.9771
5th pct: -0.7381
25th pct: +0.1152
Median: +0.6584
75th pct: +1.2008
95th pct: +2.0068
Max: +9.7926
--- CCI-SST ---
RMSE: 1.0432
Bias: +0.6303
MAE: 0.8485
Correlation: 0.9657
N points: 24,690,059
Model mean: 12.7566
Obs mean: 12.1263
Model std: 3.8655
Obs std: 3.6290
Error distribution:
Min: -6.6356
5th pct: -0.6719
25th pct: +0.1014
Median: +0.6084
75th pct: +1.1446
95th pct: +1.9419
Max: +7.0723
================================================================================
Period: 2018 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.2056
Bias: +0.7522
MAE: 0.9871
Correlation: 0.9592
N points: 18,964,670
Model mean: 12.3961
Obs mean: 11.6439
Model std: 4.3034
Obs std: 3.9844
Error distribution:
Min: -7.2633
5th pct: -0.7586
25th pct: +0.1792
Median: +0.7505
75th pct: +1.3270
95th pct: +2.1497
Max: +10.3511
--- CCI-SST ---
RMSE: 1.1715
Bias: +0.7576
MAE: 0.9490
Correlation: 0.9625
N points: 24,690,050
Model mean: 12.5617
Obs mean: 11.8041
Model std: 4.1404
Obs std: 3.8476
Error distribution:
Min: -8.6116
5th pct: -0.5983
25th pct: +0.1919
Median: +0.7296
75th pct: +1.3061
95th pct: +2.1444
Max: +9.8150
================================================================================
Period: 2019 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.1243
Bias: +0.6977
MAE: 0.9248
Correlation: 0.9637
N points: 18,964,670
Model mean: 12.4609
Obs mean: 11.7631
Model std: 4.0079
Obs std: 3.6817
Error distribution:
Min: -6.5304
5th pct: -0.6951
25th pct: +0.1702
Median: +0.6967
75th pct: +1.2440
95th pct: +2.0405
Max: +8.0854
--- CCI-SST ---
RMSE: 1.1028
Bias: +0.7171
MAE: 0.8960
Correlation: 0.9638
N points: 24,690,060
Model mean: 12.6692
Obs mean: 11.9521
Model std: 3.8779
Obs std: 3.6177
Error distribution:
Min: -6.3594
5th pct: -0.5700
25th pct: +0.1848
Median: +0.6976
75th pct: +1.2419
95th pct: +2.0499
Max: +8.3861
================================================================================
Period: 2020 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.1024
Bias: +0.6864
MAE: 0.8956
Correlation: 0.9635
N points: 19,016,628
Model mean: 12.4657
Obs mean: 11.7794
Model std: 3.9567
Obs std: 3.6783
Error distribution:
Min: -7.2009
5th pct: -0.6766
25th pct: +0.1720
Median: +0.6812
75th pct: +1.2070
95th pct: +2.0251
Max: +8.5298
--- CCI-SST ---
RMSE: 1.0867
Bias: +0.7214
MAE: 0.8823
Correlation: 0.9658
N points: 24,757,704
Model mean: 12.6396
Obs mean: 11.9182
Model std: 3.8510
Obs std: 3.6279
Error distribution:
Min: -6.3426
5th pct: -0.5347
25th pct: +0.2166
Median: +0.6932
75th pct: +1.2070
95th pct: +2.0145
Max: +9.5877
================================================================================
Period: 2021 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.2379
Bias: +0.8245
MAE: 1.0207
Correlation: 0.9564
N points: 18,964,670
Model mean: 12.5596
Obs mean: 11.7351
Model std: 4.1881
Obs std: 3.8776
Error distribution:
Min: -8.7641
5th pct: -0.6137
25th pct: +0.2571
Median: +0.8179
75th pct: +1.3941
95th pct: +2.2158
Max: +9.7990
--- CCI-SST ---
RMSE: 1.1927
Bias: +0.7983
MAE: 0.9645
Correlation: 0.9581
N points: 24,689,971
Model mean: 12.7768
Obs mean: 11.9786
Model std: 4.0635
Obs std: 3.8267
Error distribution:
Min: -7.9634
5th pct: -0.5196
25th pct: +0.2233
Median: +0.7550
75th pct: +1.3390
95th pct: +2.2036
Max: +9.3973
================================================================================
Period: 2022 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.1100
Bias: +0.6975
MAE: 0.9016
Correlation: 0.9672
N points: 18,964,670
Model mean: 12.7492
Obs mean: 12.0517
Model std: 4.1292
Obs std: 3.8585
Error distribution:
Min: -6.6134
5th pct: -0.6229
25th pct: +0.2163
Median: +0.6883
75th pct: +1.2038
95th pct: +1.9885
Max: +8.5413
--- CCI-SST ---
RMSE: 1.0662
Bias: +0.6858
MAE: 0.8585
Correlation: 0.9680
N points: 24,690,060
Model mean: 12.9873
Obs mean: 12.3015
Model std: 3.9735
Obs std: 3.7716
Error distribution:
Min: -6.5446
5th pct: -0.5330
25th pct: +0.2123
Median: +0.6609
75th pct: +1.1515
95th pct: +1.9579
Max: +8.7850
================================================================================
Period: 2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 16:35:31
--- OSTIA ---
RMSE: 1.2137
Bias: +0.7578
MAE: 0.9860
Correlation: 0.9615
N points: 18,964,670
Model mean: 12.9799
Obs mean: 12.2221
Model std: 4.3244
Obs std: 3.9821
Error distribution:
Min: -7.2034
5th pct: -0.7201
25th pct: +0.1704
Median: +0.7421
75th pct: +1.3253
95th pct: +2.1965
Max: +9.3188
--- CCI-SST ---
RMSE: 1.1607
Bias: +0.7219
MAE: 0.9262
Correlation: 0.9611
N points: 24,690,032
Model mean: 13.1976
Obs mean: 12.4757
Model std: 4.1556
Obs std: 3.9041
Error distribution:
Min: -7.4871
5th pct: -0.6567
25th pct: +0.1460
Median: +0.6806
75th pct: +1.2591
95th pct: +2.1728
Max: +8.8208
📄 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 | 0.6193 |
| Bias | -0.1212 |
| MAE | 0.2435 |
| Corr | 0.6861 |
| Model mean | 35.1620 |
| Obs mean | 35.2832 |
View Full Statistics Report
################################################################################
SALT Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-08 11:03:44
Author: RT
Project: OceanICU
Institute: BB
Area: AMM7
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-29 09:47:15
--- WOA ---
RMSE: 0.6193
Bias: -0.1212
MAE: 0.2435
Correlation: 0.6861
N points: 115,591,776
Model mean: 35.1620
Obs mean: 35.2832
Model std: 0.8246
Obs std: 0.4709
Error distribution:
Min: -21.7550
5th pct: -0.7287
25th pct: -0.1577
Median: -0.0102
75th pct: +0.0807
95th pct: +0.2843
Max: +8.2900
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 0.4203 -0.0804 0.2070 0.7145
Feb 0.4360 -0.0730 0.2139 0.7043
Mar 0.4725 -0.0870 0.2154 0.7278
Apr 0.5372 -0.1114 0.2264 0.7436
May 0.6766 -0.1353 0.2551 0.7110
Jun 0.8148 -0.1676 0.2833 0.6716
Jul 0.8060 -0.1699 0.2855 0.6858
Aug 0.7756 -0.1632 0.2818 0.6600
Sep 0.7362 -0.1515 0.2717 0.6524
Oct 0.5654 -0.1050 0.2399 0.7048
Nov 0.4945 -0.1054 0.2237 0.7140
Dec 0.4942 -0.1044 0.2184 0.6892
--------------------------------------------
All 0.6193 -0.1212 0.2435 0.6861
📄 Download Statistics Report (txt) · 📄 YAML
TEMP_3D
| Metric | WOA |
|---|---|
| RMSE | 2.7734 |
| Bias | -0.9734 |
| MAE | 1.9600 |
| Corr | 0.8239 |
| Model mean | 8.2057 |
| Obs mean | 9.1791 |
View Full Statistics Report
################################################################################
TEMP Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-08 10:23:23
Author: RT
Project: OceanICU
Institute: BB
Area: AMM7
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-29 09:16:59
--- WOA ---
RMSE: 2.7734
Bias: -0.9734
MAE: 1.9600
Correlation: 0.8239
N points: 115,591,776
Model mean: 8.2057
Obs mean: 9.1791
Model std: 4.5821
Obs std: 3.7598
Error distribution:
Min: -8.9458
5th pct: -6.0645
25th pct: -2.3487
Median: -0.3765
75th pct: +0.6248
95th pct: +2.2991
Max: +12.3648
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 2.6594 -1.0959 1.8427 0.7916
Feb 2.6465 -1.1075 1.8264 0.7832
Mar 2.6406 -1.0936 1.8154 0.7767
Apr 2.6424 -1.0603 1.8125 0.7793
May 2.7017 -0.9281 1.8904 0.7898
Jun 2.9208 -0.7361 2.1203 0.8063
Jul 3.0226 -0.7164 2.1948 0.8325
Aug 2.9924 -0.7712 2.1892 0.8521
Sep 2.8715 -0.9111 2.0885 0.8604
Oct 2.7603 -1.0841 1.9632 0.8536
Nov 2.7061 -1.0730 1.9017 0.8306
Dec 2.6759 -1.1035 1.8745 0.8129
--------------------------------------------
All 2.7734 -0.9734 1.9600 0.8239
📄 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 | 0.8693 |
| Bias | -0.0790 |
| MAE | 0.3571 |
| Corr | 0.8309 |
| Model mean | 34.7325 |
| Obs mean | 34.8115 |
View Full Statistics Report
################################################################################
PSAL Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-29 12:50:20
Area: AMM7
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2022 | Model: pyGETM
================================================================================
Analysed: 2026-05-29 12:50:20
--- ICES point observations ---
RMSE: 0.8693
Bias: -0.0790
MAE: 0.3571
Correlation: 0.8309
N points: 3,994,080
N profiles: 28,533
Model mean: 34.7325
Obs mean: 34.8115
Model std: 1.5534
Obs std: 1.2408
Error distribution:
Min: -16.0520
5th pct: -1.5073
25th pct: -0.0131
Median: +0.0862
75th pct: +0.1968
95th pct: +0.3995
Max: +35.3630
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 253,019 -0.6167 2.4318 0.8036
10-25m 378,314 -0.5078 1.4665 0.8190
25-50m 515,654 -0.2435 0.9340 0.8092
50-100m 694,512 -0.0481 0.5144 0.8011
100-200m 607,268 +0.0528 0.2300 0.7756
200-500m 686,298 +0.1196 0.1642 0.7857
500-1000m 509,815 +0.0762 0.1375 0.9011
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-29 15:32:24
--- ICES point observations ---
RMSE: 1.0209
Bias: -0.1258
MAE: 0.4010
Correlation: 0.8191
N points: 4,478,542
N profiles: 32,071
Model mean: 34.6560
Obs mean: 34.7818
Model std: 1.7615
Obs std: 1.3717
Error distribution:
Min: -34.9143
5th pct: -1.7766
25th pct: -0.0276
Median: +0.0780
75th pct: +0.1949
95th pct: +0.3946
Max: +35.3630
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 287,144 -0.7661 2.7377 0.7952
10-25m 420,745 -0.6664 1.8033 0.7947
25-50m 567,989 -0.3483 1.1759 0.7783
50-100m 763,824 -0.0879 0.5991 0.7810
100-200m 681,882 +0.0481 0.2392 0.7674
200-500m 782,467 +0.1191 0.1669 0.7668
500-1000m 586,611 +0.0641 0.1384 0.8677
📄 Download Statistics Report (txt) · 📄 YAML
TEMP
| Metric | ICES point observations |
|---|---|
| RMSE | 1.3146 |
| Bias | +0.4313 |
| MAE | 0.9325 |
| Corr | 0.9535 |
| Model mean | 8.0082 |
| Obs mean | 7.5769 |
View Full Statistics Report
################################################################################
TEMP Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-29 12:48:28
Area: AMM7
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2022 | Model: pyGETM
================================================================================
Analysed: 2026-05-29 12:48:28
--- ICES point observations ---
RMSE: 1.3146
Bias: +0.4313
MAE: 0.9325
Correlation: 0.9535
N points: 4,003,593
N profiles: 25,653
Model mean: 8.0082
Obs mean: 7.5769
Model std: 4.0734
Obs std: 4.0727
Error distribution:
Min: -11.0577
5th pct: -1.4014
25th pct: -0.1323
Median: +0.4438
75th pct: +1.0757
95th pct: +2.2245
Max: +10.2527
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 251,709 +0.5441 1.2650 0.9667
10-25m 379,993 +0.0030 1.4262 0.9238
25-50m 518,214 +0.0796 1.3802 0.8467
50-100m 697,441 +0.5071 1.0608 0.8460
100-200m 609,761 +0.6690 1.1249 0.8282
200-500m 687,489 +0.6365 1.7041 0.8223
500-1000m 509,785 +0.3650 1.2749 0.9580
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-29 15:30:25
--- ICES point observations ---
RMSE: 1.3309
Bias: +0.4152
MAE: 0.9451
Correlation: 0.9511
N points: 4,487,747
N profiles: 28,918
Model mean: 8.0521
Obs mean: 7.6368
Model std: 4.0375
Obs std: 4.0486
Error distribution:
Min: -11.0577
5th pct: -1.5032
25th pct: -0.1472
Median: +0.4304
75th pct: +1.0734
95th pct: +2.2273
Max: +10.2527
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 285,609 +0.5162 1.2835 0.9660
10-25m 422,418 -0.0113 1.4414 0.9236
25-50m 570,518 +0.0700 1.3988 0.8455
50-100m 766,720 +0.5109 1.0671 0.8419
100-200m 684,363 +0.6834 1.1348 0.8224
200-500m 783,657 +0.6413 1.7283 0.8155
500-1000m 586,581 +0.2694 1.2916 0.9570
📄 Download Statistics Report (txt) · 📄 YAML
Plots
Practical Salinity — statistics vs depth profile
Temperature — statistics vs depth profile
Practical Salinity — statistics vs depth profile
Temperature — statistics vs depth profile
Argo Float Profiles
Statistics
PSAL
| Metric | ARGO floats |
|---|---|
| RMSE | 4.3279 |
| Bias | +0.6360 |
| MAE | 0.7451 |
| Corr | 0.1770 |
| Model mean | 35.3282 |
| Obs mean | 34.6922 |
View Full Statistics Report
################################################################################
PSAL Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-08 11:09:22
Area: AMM7
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 11:09:22
--- ARGO floats ---
RMSE: 4.3279
Bias: +0.6360
MAE: 0.7451
Correlation: 0.1770
N points: 4,904,713
N profiles: 18,472
Model mean: 35.3282
Obs mean: 34.6922
Model std: 0.3125
Obs std: 4.3252
Error distribution:
Min: -26.4725
5th pct: -0.2923
25th pct: -0.0239
Median: +0.0314
75th pct: +0.1434
95th pct: +0.4283
Max: +36.9164
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 96,557 +0.5205 3.2047 0.1672
10-25m 146,016 +0.6579 3.6003 0.1402
25-50m 232,397 +0.7302 3.7176 0.1271
50-100m 425,227 +0.7562 3.8331 0.1305
100-200m 495,254 +0.6813 4.4494 0.1906
200-500m 1,075,494 +0.6730 4.6080 0.2194
500-1000m 1,117,739 +0.5876 4.5106 0.2577
📄 Download Statistics Report (txt) · 📄 YAML
TEMP
| Metric | ARGO floats |
|---|---|
| RMSE | 1.2432 |
| Bias | +0.2704 |
| MAE | 0.8965 |
| Corr | 0.9662 |
| Model mean | 8.3531 |
| Obs mean | 8.0826 |
View Full Statistics Report
################################################################################
TEMP Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-08 11:07:35
Area: AMM7
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-08 11:07:35
--- ARGO floats ---
RMSE: 1.2432
Bias: +0.2704
MAE: 0.8965
Correlation: 0.9662
N points: 4,905,048
N profiles: 18,472
Model mean: 8.3531
Obs mean: 8.0826
Model std: 4.7007
Obs std: 4.4672
Error distribution:
Min: -49.4755
5th pct: -1.5465
25th pct: -0.3753
Median: +0.1166
75th pct: +0.9699
95th pct: +2.2558
Max: +20.7322
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 96,568 +0.7477 1.2123 0.9749
10-25m 146,026 +0.4453 1.1846 0.9602
25-50m 232,410 +0.6373 1.4017 0.9237
50-100m 425,244 +0.9959 1.6562 0.9122
100-200m 495,283 +0.6026 1.5595 0.9199
200-500m 1,075,630 +0.1888 1.2823 0.9479
500-1000m 1,117,875 -0.2711 0.9465 0.9734
📄 Download Statistics Report (txt) · 📄 YAML
Plots
Amm7 Argo Overview
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).