Horizontal Validation results comparing model output against observations.
Experiment Information
Area: NS Experiment: CMEMS Validation Type: Horizontal Validation Variables: SALT_BOTTOM, TEMP_BOTTOM, SALT_SURFACE, TEMP_SURFACE
Overview
| Metric | SALT_BOTTOM / NWS-salinity | TEMP_BOTTOM / NWS-bottomT | SALT_SURFACE / CCI-SSS | TEMP_SURFACE / OSTIA | TEMP_SURFACE / CCI-SST |
|---|---|---|---|---|---|
| RMSE | 0.4879 | 1.4122 | 2.2332 | 0.8598 | 0.8541 |
| Bias | 0.0749 | -0.6136 | -0.1010 | 0.1970 | 0.4024 |
| Corr | 0.8398 | 0.9208 | 0.9219 | 0.9010 | 0.9213 |
| N points | 58,068 | 58,068 | 16,531,480 | 2,003,850 | 17,213,415 |
Annual Statistics Trends
Salinity (surface) — annual statistics timeseries (RMSE, bias, correlation)
Temperature (surface) — annual statistics timeseries (RMSE, bias, correlation)
Horizontal Validation
Statistics
SALT_BOTTOM
| Metric | NWS-salinity |
|---|---|
| RMSE | 0.4879 |
| Bias | +0.0749 |
| MAE | 0.2796 |
| Corr | 0.8398 |
| Model mean | 34.7384 |
| Obs mean | 34.6636 |
View Full Statistics Report
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SALT_BOTTOM Validation Statistics
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Format: 1.1
Created: 2026-05-04 08:38:02
Author: KB
Project: OceanICU
Institute: BB
Area: NS
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-04 09:24:44
--- NWS-salinity ---
RMSE: 0.4879
Bias: +0.0749
MAE: 0.2796
Correlation: 0.8398
N points: 58,068
Model mean: 34.7384
Obs mean: 34.6636
Model std: 0.8816
Obs std: 0.7989
Error distribution:
Min: -10.1723
5th pct: -0.6296
25th pct: -0.0285
Median: +0.1144
75th pct: +0.2671
95th pct: +0.5230
Max: +9.7811
================================================================================
Period: 2016 | Model: pyGETM
================================================================================
Analysed: 2026-05-04 09:24:44
--- NWS-salinity ---
RMSE: 0.4879
Bias: +0.0749
MAE: 0.2796
Correlation: 0.8398
N points: 58,068
Model mean: 34.7384
Obs mean: 34.6636
Model std: 0.8816
Obs std: 0.7989
Error distribution:
Min: -10.1723
5th pct: -0.6296
25th pct: -0.0285
Median: +0.1144
75th pct: +0.2671
95th pct: +0.5230
Max: +9.7811
📄 Download Statistics Report (txt) · 📄 YAML
TEMP_BOTTOM
| Metric | NWS-bottomT |
|---|---|
| RMSE | 1.4122 |
| Bias | -0.6136 |
| MAE | 0.9115 |
| Corr | 0.9208 |
| Model mean | 8.6424 |
| Obs mean | 9.2560 |
View Full Statistics Report
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TEMP_BOTTOM Validation Statistics
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Format: 1.1
Created: 2026-05-04 08:37:40
Author: KB
Project: OceanICU
Institute: BB
Area: NS
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-04 09:24:22
--- NWS-bottomT ---
RMSE: 1.4122
Bias: -0.6136
MAE: 0.9115
Correlation: 0.9208
N points: 58,068
Model mean: 8.6424
Obs mean: 9.2560
Model std: 3.0763
Obs std: 3.2540
Error distribution:
Min: -10.2789
5th pct: -3.1284
25th pct: -1.1299
Median: -0.2392
75th pct: +0.1677
95th pct: +0.7904
Max: +3.4116
================================================================================
Period: 2016 | Model: pyGETM
================================================================================
Analysed: 2026-05-04 09:24:22
--- NWS-bottomT ---
RMSE: 1.4122
Bias: -0.6136
MAE: 0.9115
Correlation: 0.9208
N points: 58,068
Model mean: 8.6424
Obs mean: 9.2560
Model std: 3.0763
Obs std: 3.2540
Error distribution:
Min: -10.2789
5th pct: -3.1284
25th pct: -1.1299
Median: -0.2392
75th pct: +0.1677
95th pct: +0.7904
Max: +3.4116
📄 Download Statistics Report (txt) · 📄 YAML
SALT_SURFACE
| Metric | CCI-SSS |
|---|---|
| RMSE | 2.2332 |
| Bias | -0.1010 |
| MAE | 1.1942 |
| Corr | 0.9219 |
| Model mean | 32.8099 |
| Obs mean | 33.0738 |
View Full Statistics Report
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SALT_SURFACE Validation Statistics
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Format: 1.1
Created: 2026-05-04 09:23:50
Author: KB
Project: OceanICU
Institute: BB
Area: NS
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:56
--- CCI-SSS ---
RMSE: 2.2332
Bias: -0.1010
MAE: 1.1942
Correlation: 0.9219
N points: 16,531,480
Model mean: 32.8099
Obs mean: 33.0738
Model std: 5.2758
Obs std: 3.4437
Error distribution:
Min: -29.0710
5th pct: -3.8999
25th pct: -0.2426
Median: +0.3087
75th pct: +0.8127
95th pct: +1.9089
Max: +14.4447
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 2.1798 -0.2397 1.0593 0.9282
Feb 2.2350 -0.2855 1.0608 0.9246
Mar 2.3084 -0.1893 1.2082 0.9161
Apr 2.2102 -0.1710 1.2224 0.9223
May 2.1402 -0.1545 1.2026 0.9322
Jun 2.2213 -0.0484 1.2728 0.9200
Jul 2.1491 +0.0124 1.1709 0.9158
Aug 2.2884 +0.0322 1.2516 0.9107
Sep 2.3792 +0.0195 1.3232 0.9052
Oct 2.2765 +0.0627 1.2447 0.9086
Nov 2.3256 -0.0463 1.1993 0.9140
Dec 2.2576 -0.2154 1.1097 0.9236
--------------------------------------------
All 2.2332 -0.1010 1.1942 0.9219
================================================================================
Period: 2016 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:56
--- CCI-SSS ---
RMSE: 1.9624
Bias: +0.2410
MAE: 1.1387
Correlation: 0.9311
N points: 2,077,414
Model mean: 33.1862
Obs mean: 33.0758
Model std: 4.9788
Obs std: 3.4872
Error distribution:
Min: -28.1718
5th pct: -2.6694
25th pct: +0.0530
Median: +0.4876
75th pct: +1.0103
95th pct: +2.1139
Max: +14.4447
================================================================================
Period: 2017 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:56
--- CCI-SSS ---
RMSE: 2.3162
Bias: -0.0157
MAE: 1.2143
Correlation: 0.9213
N points: 2,072,303
Model mean: 32.9092
Obs mean: 33.0686
Model std: 5.3606
Obs std: 3.4696
Error distribution:
Min: -28.7901
5th pct: -4.1259
25th pct: -0.0723
Median: +0.3841
75th pct: +0.8888
95th pct: +2.0032
Max: +10.7868
================================================================================
Period: 2018 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:56
--- CCI-SSS ---
RMSE: 2.4018
Bias: -0.3460
MAE: 1.1842
Correlation: 0.9236
N points: 2,056,640
Model mean: 32.7733
Obs mean: 33.2477
Model std: 5.4681
Obs std: 3.5455
Error distribution:
Min: -28.7730
5th pct: -4.5800
25th pct: -0.4082
Median: +0.1207
75th pct: +0.5730
95th pct: +1.6785
Max: +11.3631
================================================================================
Period: 2019 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:56
--- CCI-SSS ---
RMSE: 2.2862
Bias: -0.1992
MAE: 1.1727
Correlation: 0.9280
N points: 2,067,322
Model mean: 32.7883
Obs mean: 33.1263
Model std: 5.3341
Obs std: 3.4295
Error distribution:
Min: -29.0710
5th pct: -4.0607
25th pct: -0.2776
Median: +0.2493
75th pct: +0.7198
95th pct: +1.7417
Max: +10.1715
================================================================================
Period: 2020 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:57
--- CCI-SSS ---
RMSE: 2.2408
Bias: -0.0968
MAE: 1.1719
Correlation: 0.9241
N points: 2,065,576
Model mean: 32.7542
Obs mean: 33.0527
Model std: 5.3567
Obs std: 3.3748
Error distribution:
Min: -25.6755
5th pct: -4.1724
25th pct: -0.1958
Median: +0.2821
75th pct: +0.8102
95th pct: +1.9192
Max: +9.7343
================================================================================
Period: 2021 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:57
--- CCI-SSS ---
RMSE: 2.2624
Bias: -0.2819
MAE: 1.1847
Correlation: 0.9244
N points: 2,064,075
Model mean: 32.5380
Obs mean: 33.0125
Model std: 5.4038
Obs std: 3.4872
Error distribution:
Min: -22.7722
5th pct: -4.3368
25th pct: -0.3992
Median: +0.2634
75th pct: +0.6940
95th pct: +1.5447
Max: +11.4668
================================================================================
Period: 2022 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:57
--- CCI-SSS ---
RMSE: 2.3936
Bias: -0.2133
MAE: 1.3453
Correlation: 0.9175
N points: 2,064,075
Model mean: 32.6184
Obs mean: 33.0241
Model std: 5.4198
Obs std: 3.3329
Error distribution:
Min: -27.6209
5th pct: -4.6468
25th pct: -0.3855
Median: +0.3520
75th pct: +0.8736
95th pct: +1.8849
Max: +8.5417
================================================================================
Period: 2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 08:04:57
--- CCI-SSS ---
RMSE: 2.0031
Bias: +0.1006
MAE: 1.1422
Correlation: 0.9044
N points: 2,064,075
Model mean: 32.9091
Obs mean: 32.9830
Model std: 4.8238
Obs std: 3.4115
Error distribution:
Min: -26.5762
5th pct: -2.8086
25th pct: -0.2291
Median: +0.3301
75th pct: +0.8974
95th pct: +2.2094
Max: +11.4691
📄 Download Statistics Report (txt) · 📄 YAML
TEMP_SURFACE
| Metric | OSTIA | CCI-SST |
|---|---|---|
| RMSE | 0.8598 | 0.8541 |
| Bias | +0.1970 | +0.4024 |
| MAE | 0.6761 | 0.6755 |
| Corr | 0.9010 | 0.9213 |
| Model mean | 11.1727 | 11.4266 |
| Obs mean | 10.9757 | 11.0242 |
View Full Statistics Report
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TEMP_SURFACE Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-04 08:37:10
Author: KB
Project: OceanICU
Institute: BB
Area: NS
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:54
--- OSTIA ---
RMSE: 0.8598
Bias: +0.1970
MAE: 0.6761
Correlation: 0.9010
N points: 2,003,850
Model mean: 11.1727
Obs mean: 10.9757
Model std: 4.2401
Obs std: 3.9426
Error distribution:
Min: -7.1744
5th pct: -0.9853
25th pct: -0.2768
Median: +0.1666
75th pct: +0.6310
95th pct: +1.4022
Max: +7.9395
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 0.7229 -0.2550 0.5449 0.9400
Feb 0.6042 -0.0340 0.4493 0.9239
Mar 0.6149 -0.0170 0.4606 0.8878
Apr 0.5382 -0.0852 0.3939 0.8233
May 0.8404 +0.3031 0.6237 0.9041
Jun 1.7251 +1.2612 1.4524 0.8453
Jul 1.3257 +0.8365 1.1079 0.8695
Aug 0.9577 +0.4789 0.7655 0.9295
Sep 0.8016 +0.1034 0.6220 0.9606
Oct 0.7823 -0.1480 0.6267 0.9310
Nov 0.7145 -0.0471 0.5509 0.9065
Dec 0.6757 -0.0334 0.5113 0.8896
--------------------------------------------
All 0.8598 +0.1970 0.6761 0.9010
--- CCI-SST ---
RMSE: 0.8541
Bias: +0.4024
MAE: 0.6755
Correlation: 0.9213
N points: 17,213,415
Model mean: 11.4266
Obs mean: 11.0242
Model std: 4.2066
Obs std: 3.9824
Error distribution:
Min: -7.8403
5th pct: -0.7046
25th pct: -0.0363
Median: +0.3916
75th pct: +0.8270
95th pct: +1.5552
Max: +8.4914
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 0.6262 +0.1690 0.4699 0.9359
Feb 0.6282 +0.1686 0.4586 0.9399
Mar 0.5890 +0.1997 0.4302 0.9425
Apr 0.5680 +0.2267 0.4290 0.9313
May 0.9602 +0.6022 0.7531 0.9152
Jun 1.4925 +1.0823 1.2532 0.8952
Jul 1.3847 +0.9859 1.1698 0.9011
Aug 1.0726 +0.6578 0.8646 0.9273
Sep 0.8148 +0.1911 0.6194 0.9500
Oct 0.7477 +0.0475 0.5751 0.9360
Nov 0.6801 +0.1772 0.5137 0.9259
Dec 0.7516 +0.3026 0.5539 0.9111
--------------------------------------------
All 0.8541 +0.4024 0.6755 0.9213
================================================================================
Period: 2016 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:54
--- OSTIA ---
RMSE: 0.8598
Bias: +0.1970
MAE: 0.6761
Correlation: 0.9010
N points: 2,003,850
Model mean: 11.1727
Obs mean: 10.9757
Model std: 4.2401
Obs std: 3.9426
Error distribution:
Min: -7.1744
5th pct: -0.9853
25th pct: -0.2768
Median: +0.1666
75th pct: +0.6310
95th pct: +1.4022
Max: +7.9395
--- CCI-SST ---
RMSE: 0.8271
Bias: +0.2944
MAE: 0.6560
Correlation: 0.9258
N points: 2,156,106
Model mean: 11.3043
Obs mean: 11.0099
Model std: 4.2196
Obs std: 3.9205
Error distribution:
Min: -6.8646
5th pct: -0.7895
25th pct: -0.1504
Median: +0.2648
75th pct: +0.7036
95th pct: +1.4293
Max: +7.5252
================================================================================
Period: 2017 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:54
--- CCI-SST ---
RMSE: 0.8032
Bias: +0.3863
MAE: 0.6358
Correlation: 0.9264
N points: 2,150,199
Model mean: 11.3208
Obs mean: 10.9345
Model std: 4.0051
Obs std: 3.7916
Error distribution:
Min: -6.4653
5th pct: -0.6456
25th pct: -0.0430
Median: +0.3705
75th pct: +0.7915
95th pct: +1.4407
Max: +7.2120
================================================================================
Period: 2018 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:54
--- CCI-SST ---
RMSE: 0.9637
Bias: +0.4715
MAE: 0.7590
Correlation: 0.9241
N points: 2,150,213
Model mean: 11.2432
Obs mean: 10.7718
Model std: 4.7218
Obs std: 4.5159
Error distribution:
Min: -7.8403
5th pct: -0.7636
25th pct: -0.0196
Median: +0.4534
75th pct: +0.9389
95th pct: +1.7693
Max: +7.1265
================================================================================
Period: 2019 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:54
--- CCI-SST ---
RMSE: 0.8462
Bias: +0.4463
MAE: 0.6805
Correlation: 0.9271
N points: 2,150,215
Model mean: 11.3664
Obs mean: 10.9201
Model std: 4.0471
Obs std: 3.7613
Error distribution:
Min: -5.5929
5th pct: -0.6113
25th pct: +0.0056
Median: +0.4199
75th pct: +0.8461
95th pct: +1.5285
Max: +7.5057
================================================================================
Period: 2020 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:55
--- CCI-SST ---
RMSE: 0.7883
Bias: +0.3926
MAE: 0.6278
Correlation: 0.9227
N points: 2,156,106
Model mean: 11.4934
Obs mean: 11.1007
Model std: 3.8711
Obs std: 3.6252
Error distribution:
Min: -7.8276
5th pct: -0.6280
25th pct: -0.0231
Median: +0.3705
75th pct: +0.7808
95th pct: +1.4419
Max: +7.4337
================================================================================
Period: 2021 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:55
--- CCI-SST ---
RMSE: 0.9056
Bias: +0.4168
MAE: 0.7069
Correlation: 0.9044
N points: 2,150,176
Model mean: 11.2643
Obs mean: 10.8476
Model std: 4.3819
Obs std: 4.1594
Error distribution:
Min: -6.4133
5th pct: -0.7551
25th pct: -0.0254
Median: +0.4099
75th pct: +0.8400
95th pct: +1.6379
Max: +6.6665
================================================================================
Period: 2022 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:55
--- CCI-SST ---
RMSE: 0.7620
Bias: +0.2979
MAE: 0.5932
Correlation: 0.9306
N points: 2,150,215
Model mean: 11.6401
Obs mean: 11.3423
Model std: 4.1089
Obs std: 3.9947
Error distribution:
Min: -6.0376
5th pct: -0.7399
25th pct: -0.0999
Median: +0.2869
75th pct: +0.6851
95th pct: +1.3830
Max: +7.7539
================================================================================
Period: 2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:54:55
--- CCI-SST ---
RMSE: 0.9326
Bias: +0.5140
MAE: 0.7450
Correlation: 0.9144
N points: 2,150,185
Model mean: 11.7807
Obs mean: 11.2667
Model std: 4.2088
Obs std: 3.9895
Error distribution:
Min: -7.3122
5th pct: -0.6414
25th pct: +0.0481
Median: +0.5039
75th pct: +0.9512
95th pct: +1.6932
Max: +8.4914
📄 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
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
SALT_BOTTOM
Salinity (bottom) — monthly by year
NWS-salinity
Salinity (bottom) — NWS-salinity comparison
Salinity (bottom) — NWS-salinity monthly maps
Salinity (bottom) — NWS-salinity pdf annual
Salinity (bottom) — NWS-salinity pdf monthly
Salinity (bottom) — NWS-salinity spatial stats
TEMP_BOTTOM
Temperature (bottom) — monthly by year
NWS-bottomT
Temperature (bottom) — NWS-bottomT comparison
Temperature (bottom) — NWS-bottomT monthly maps
Temperature (bottom) — NWS-bottomT pdf annual
Temperature (bottom) — NWS-bottomT pdf monthly
Temperature (bottom) — NWS-bottomT spatial stats
Taylor diagram
Taylor diagram
Gridded 3D Validation
Statistics
SALT_3D
| Metric | WOA |
|---|---|
| RMSE | 1.8657 |
| Bias | -0.4047 |
| MAE | 0.6013 |
| Corr | 0.8484 |
| Model mean | 34.2831 |
| Obs mean | 34.6877 |
View Full Statistics Report
################################################################################
SALT Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-04 08:56:01
Author: KB
Project: OceanICU
Institute: BB
Area: NS
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:47:04
--- WOA ---
RMSE: 1.8657
Bias: -0.4047
MAE: 0.6013
Correlation: 0.8484
N points: 13,890,240
Model mean: 34.2831
Obs mean: 34.6877
Model std: 2.9459
Obs std: 1.5586
Error distribution:
Min: -24.5625
5th pct: -1.8974
25th pct: -0.3434
Median: -0.0322
75th pct: +0.1224
95th pct: +0.4691
Max: +3.3153
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 1.7050 -0.3468 0.5380 0.8623
Feb 1.7717 -0.3784 0.5559 0.8529
Mar 1.8752 -0.4176 0.6083 0.8424
Apr 1.9813 -0.4203 0.6472 0.8255
May 2.0577 -0.4902 0.6740 0.8301
Jun 2.0936 -0.5069 0.6727 0.8243
Jul 1.8502 -0.4147 0.6128 0.8580
Aug 1.8730 -0.3900 0.6055 0.8505
Sep 1.8779 -0.3860 0.6026 0.8536
Oct 1.7620 -0.3621 0.5784 0.8582
Nov 1.7447 -0.3609 0.5628 0.8665
Dec 1.7492 -0.3820 0.5578 0.8667
--------------------------------------------
All 1.8657 -0.4047 0.6013 0.8484
📄 Download Statistics Report (txt) · 📄 YAML
TEMP_3D
| Metric | WOA |
|---|---|
| RMSE | 1.6707 |
| Bias | +1.0188 |
| MAE | 1.2186 |
| Corr | 0.9159 |
| Model mean | 10.0176 |
| Obs mean | 8.9989 |
View Full Statistics Report
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TEMP Validation Statistics
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Format: 1.1
Created: 2026-05-04 08:53:34
Author: KB
Project: OceanICU
Institute: BB
Area: NS
Experiment: CMEMS
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================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:44:30
--- WOA ---
RMSE: 1.6707
Bias: +1.0188
MAE: 1.2186
Correlation: 0.9159
N points: 13,890,240
Model mean: 10.0176
Obs mean: 8.9989
Model std: 3.2017
Obs std: 2.6140
Error distribution:
Min: -6.6442
5th pct: -0.7176
25th pct: +0.2210
Median: +0.8370
75th pct: +1.5528
95th pct: +3.5470
Max: +13.1985
Monthly breakdown:
Month RMSE Bias MAE Corr
--------------------------------------------
Jan 1.1679 +0.9188 0.9935 0.8086
Feb 1.0994 +0.7241 0.9076 0.7966
Mar 1.1261 +0.7865 0.9587 0.7863
Apr 1.1238 +0.8775 0.9654 0.7850
May 1.6636 +1.2549 1.3121 0.7386
Jun 2.5178 +1.7070 1.8241 0.8487
Jul 2.7206 +1.8489 2.0350 0.9015
Aug 2.3442 +1.5336 1.8193 0.9308
Sep 1.7704 +1.0528 1.3980 0.9272
Oct 1.2028 +0.5534 0.9266 0.8983
Nov 1.1107 +0.6937 0.8757 0.8433
Dec 0.7579 +0.2738 0.6068 0.7978
--------------------------------------------
All 1.6707 +1.0188 1.2186 0.9159
📄 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 | 2.9193 |
| Bias | -0.8519 |
| MAE | 1.1703 |
| Corr | 0.9527 |
| Model mean | 31.3225 |
| Obs mean | 32.1743 |
View Full Statistics Report
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PSAL Profile Validation Statistics
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Format: 1.1
Created: 2026-05-04 08:33:44
Area: NS
Experiment: CMEMS
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================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:47:45
--- ICES point observations ---
RMSE: 2.9193
Bias: -0.8519
MAE: 1.1703
Correlation: 0.9527
N points: 2,237,954
N profiles: 27,972
Model mean: 31.3225
Obs mean: 32.1743
Model std: 8.1132
Obs std: 6.4210
Error distribution:
Min: -25.9221
5th pct: -7.5945
25th pct: -0.3312
Median: -0.0157
75th pct: +0.1035
95th pct: +0.6890
Max: +34.1564
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 389,613 -2.4538 4.8389 0.9367
10-25m 412,998 -1.9975 4.5901 0.9273
25-50m 407,979 -0.3030 1.7006 0.9215
50-100m 463,619 -0.0292 0.3479 0.7667
100-200m 324,278 +0.0198 0.1800 0.6268
200-500m 224,657 +0.0208 0.0845 0.3426
500-1000m 14,810 +0.0429 0.0607 0.2832
📄 Download Statistics Report (txt) · 📄 YAML
TEMP
| Metric | ICES point observations |
|---|---|
| RMSE | 1.3532 |
| Bias | +0.0862 |
| MAE | 0.8901 |
| Corr | 0.9249 |
| Model mean | 9.4227 |
| Obs mean | 9.3365 |
View Full Statistics Report
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TEMP Profile Validation Statistics
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Format: 1.1
Created: 2026-05-04 08:32:26
Area: NS
Experiment: CMEMS
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================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:46:28
--- ICES point observations ---
RMSE: 1.3532
Bias: +0.0862
MAE: 0.8901
Correlation: 0.9249
N points: 2,247,321
N profiles: 25,948
Model mean: 9.4227
Obs mean: 9.3365
Model std: 3.4961
Obs std: 3.4722
Error distribution:
Min: -11.0420
5th pct: -1.9490
25th pct: -0.4677
Median: +0.0784
75th pct: +0.6593
95th pct: +2.1014
Max: +10.4338
Statistics by depth:
Depth N Bias RMSE Corr
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0-10m 389,474 +0.3763 1.5207 0.9614
10-25m 415,226 -0.0822 1.7830 0.9127
25-50m 410,379 -0.3621 1.6032 0.8250
50-100m 466,017 +0.1302 0.9960 0.7561
100-200m 325,997 +0.1971 0.8095 0.5620
200-500m 225,418 +0.4180 0.8186 0.4674
500-1000m 14,810 +0.7216 0.9221 0.2511
📄 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 | 0.4500 |
| Bias | -0.1398 |
| MAE | 0.2464 |
| Corr | 0.8794 |
| Model mean | 34.6889 |
| Obs mean | 34.8287 |
View Full Statistics Report
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PSAL Profile Validation Statistics
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Format: 1.1
Created: 2026-05-04 14:14:33
Area: NS
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:47:09
--- ARGO floats ---
RMSE: 0.4500
Bias: -0.1398
MAE: 0.2464
Correlation: 0.8794
N points: 9,278
N profiles: 38
Model mean: 34.6889
Obs mean: 34.8287
Model std: 0.8658
Obs std: 0.8759
Error distribution:
Min: -3.7714
5th pct: -0.8425
25th pct: -0.1965
Median: -0.0896
75th pct: -0.0238
95th pct: +0.2093
Max: +4.0651
Statistics by depth:
Depth N Bias RMSE Corr
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0-10m 190 -0.1729 1.5569 0.7362
10-25m 537 -0.0585 1.0630 0.7689
25-50m 861 -0.1621 0.5930 0.7992
50-100m 1,730 -0.2388 0.4535 0.5422
100-200m 2,809 -0.1459 0.1991 0.6350
200-500m 2,940 -0.0912 0.1190 -0.1755
500-1000m 211 -0.0105 0.0134 -0.4413
📄 Download Statistics Report (txt) · 📄 YAML
TEMP
| Metric | ARGO floats |
|---|---|
| RMSE | 1.0344 |
| Bias | +0.1992 |
| MAE | 0.6657 |
| Corr | 0.8754 |
| Model mean | 8.8561 |
| Obs mean | 8.6569 |
View Full Statistics Report
################################################################################
TEMP Profile Validation Statistics
################################################################################
Format: 1.1
Created: 2026-05-04 14:14:31
Area: NS
Experiment: CMEMS
################################################################################
================================================================================
Period: 2016-2023 | Model: pyGETM
================================================================================
Analysed: 2026-05-07 07:47:07
--- ARGO floats ---
RMSE: 1.0344
Bias: +0.1992
MAE: 0.6657
Correlation: 0.8754
N points: 9,278
N profiles: 38
Model mean: 8.8561
Obs mean: 8.6569
Model std: 1.7953
Obs std: 2.0977
Error distribution:
Min: -4.2178
5th pct: -1.6228
25th pct: -0.0857
Median: +0.1423
75th pct: +0.6191
95th pct: +1.9013
Max: +4.9314
Statistics by depth:
Depth N Bias RMSE Corr
------------------------------------------------------
0-10m 190 -0.3018 1.0140 0.9402
10-25m 537 -0.1033 1.5451 0.7958
25-50m 861 -0.2594 1.9319 0.6892
50-100m 1,730 +0.2955 1.4590 0.5229
100-200m 2,809 +0.3043 0.6051 0.6492
200-500m 2,940 +0.2119 0.3411 0.6579
500-1000m 211 +0.9276 0.9310 -0.4030
📄 Download Statistics Report (txt) · 📄 YAML
Plots
Argo float profile overview (NE Atlantic)
NA_ARGO — Hovmöller diagram
Na 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 — 2016-2023
ICES Station Map
ICES Observation Density
ICES PSAL 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).