################################################################################ SALT_SURFACE Validation Statistics ################################################################################ Format: 1.1 Created: 2026-05-28 10:10:48 Author: RT Project: OceanICU Institute: BB Area: AMM7 Experiment: CMEMS_prof ################################################################################ ================================================================================ Period: 2016-2023 | Model: pyGETM ================================================================================ Analysed: 2026-05-28 10:10:48 --- CCI-SSS --- RMSE: 0.8866 Bias: +0.0802 MAE: 0.4354 Correlation: 0.8318 N points: 170,735,828 Model mean: 34.9782 Obs mean: 34.9024 Model std: 1.5983 Obs std: 1.1730 Error distribution: Min: -32.5268 5th pct: -0.9079 25th pct: -0.0452 Median: +0.1136 75th pct: +0.3249 95th pct: +1.0717 Max: +12.1194 Monthly breakdown: Month RMSE Bias MAE Corr -------------------------------------------- Jan 0.8112 +0.0827 0.3839 0.8069 Feb 0.8535 +0.0700 0.3771 0.7989 Mar 0.9450 +0.0863 0.4155 0.7862 Apr 0.9278 +0.0960 0.4410 0.8093 May 0.8897 +0.0859 0.4387 0.8607 Jun 0.9593 +0.0753 0.4681 0.8666 Jul 0.9033 +0.0406 0.4585 0.8695 Aug 0.9457 +0.0509 0.4830 0.8482 Sep 0.9395 +0.0624 0.4751 0.8444 Oct 0.8564 +0.0994 0.4451 0.8262 Nov 0.8517 +0.1303 0.4371 0.8054 Dec 0.8201 +0.0830 0.3991 0.8226 -------------------------------------------- All 0.8866 +0.0802 0.4354 0.8318 ================================================================================ Period: 2016 | Model: pyGETM ================================================================================ Analysed: 2026-05-28 10:10:48 --- CCI-SSS --- RMSE: 0.8573 Bias: +0.1151 MAE: 0.4303 Correlation: 0.8510 N points: 24,460,506 Model mean: 34.9999 Obs mean: 34.8875 Model std: 1.6039 Obs std: 1.1664 Error distribution: Min: -26.0535 5th pct: -0.7276 25th pct: -0.0254 Median: +0.1326 75th pct: +0.3537 95th pct: +1.0593 Max: +12.1194 ================================================================================ Period: 2017 | Model: pyGETM ================================================================================ Analysed: 2026-05-28 10:10:48 --- CCI-SSS --- RMSE: 0.8426 Bias: +0.0559 MAE: 0.3956 Correlation: 0.8414 N points: 24,395,369 Model mean: 34.9800 Obs mean: 34.9268 Model std: 1.5603 Obs std: 1.1686 Error distribution: Min: -28.1669 5th pct: -0.8372 25th pct: -0.0640 Median: +0.0754 75th pct: +0.2645 95th pct: +1.0164 Max: +9.1506 ================================================================================ Period: 2018 | Model: pyGETM ================================================================================ Analysed: 2026-05-28 10:10:48 --- CCI-SSS --- RMSE: 0.8267 Bias: +0.0868 MAE: 0.3953 Correlation: 0.8333 N points: 24,338,489 Model mean: 35.0231 Obs mean: 34.9407 Model std: 1.4832 Obs std: 1.1622 Error distribution: Min: -29.8683 5th pct: -0.7027 25th pct: -0.0497 Median: +0.1082 75th pct: +0.3062 95th pct: +0.9578 Max: +12.0495 ================================================================================ Period: 2019 | Model: pyGETM ================================================================================ Analysed: 2026-05-28 10:10:48 --- CCI-SSS --- RMSE: 0.8217 Bias: +0.1100 MAE: 0.4197 Correlation: 0.8286 N points: 24,377,458 Model mean: 35.0064 Obs mean: 34.8998 Model std: 1.4717 Obs std: 1.1549 Error distribution: Min: -29.5824 5th pct: -0.7546 25th pct: -0.0424 Median: +0.1198 75th pct: +0.3381 95th pct: +1.0921 Max: +9.2627 ================================================================================ Period: 2020 | Model: pyGETM ================================================================================ Analysed: 2026-05-28 10:10:48 --- CCI-SSS --- RMSE: 0.8968 Bias: +0.1029 MAE: 0.4377 Correlation: 0.8103 N points: 24,422,636 Model mean: 34.9837 Obs mean: 34.8879 Model std: 1.5705 Obs std: 1.1916 Error distribution: Min: -29.1297 5th pct: -0.8224 25th pct: -0.0397 Median: +0.1052 75th pct: +0.3198 95th pct: +1.1681 Max: +8.9942 ================================================================================ Period: 2021 | Model: pyGETM ================================================================================ Analysed: 2026-05-28 10:10:48 --- CCI-SSS --- RMSE: 0.9505 Bias: +0.0201 MAE: 0.4721 Correlation: 0.8403 N points: 24,370,685 Model mean: 34.8953 Obs mean: 34.8807 Model std: 1.7522 Obs std: 1.2061 Error distribution: Min: -28.1046 5th pct: -1.3029 25th pct: -0.0504 Median: +0.1216 75th pct: +0.3274 95th pct: +1.0076 Max: +11.7662 ================================================================================ Period: 2022 | Model: pyGETM ================================================================================ Analysed: 2026-05-28 10:10:48 --- CCI-SSS --- RMSE: 1.0083 Bias: +0.0705 MAE: 0.4971 Correlation: 0.8180 N points: 24,370,685 Model mean: 34.9590 Obs mean: 34.8939 Model std: 1.7211 Obs std: 1.1594 Error distribution: Min: -32.5268 5th pct: -1.1393 25th pct: -0.0446 Median: +0.1252 75th pct: +0.3552 95th pct: +1.1837 Max: +10.7502