################################################################################ 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