################################################################################ SALT_SURFACE Validation Statistics ################################################################################ Format: 1.1 Created: 2026-05-06 11:28:55 Author: RT Project: OceanICU Institute: BB Area: AMM7 Experiment: NetSW_LW ################################################################################ ================================================================================ Period: 2016-2023 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 1.0077 Bias: +0.2858 MAE: 0.4488 Correlation: 0.6003 N points: 195,106,513 Model mean: 35.1821 Obs mean: 34.9009 Model std: 0.9352 Obs std: 1.1772 Error distribution: Min: -32.4221 5th pct: -0.2771 25th pct: +0.0077 Median: +0.1546 75th pct: +0.4123 95th pct: +1.3204 Max: +16.3265 Monthly breakdown: Month RMSE Bias MAE Corr -------------------------------------------- Jan 0.8432 +0.2394 0.3926 0.6232 Feb 0.9136 +0.2317 0.4012 0.5853 Mar 1.0157 +0.2551 0.4435 0.5626 Apr 1.0651 +0.2812 0.4709 0.5669 May 1.0869 +0.2993 0.4697 0.6017 Jun 1.1483 +0.3362 0.4991 0.6016 Jul 1.1188 +0.3210 0.4819 0.6039 Aug 1.0879 +0.3178 0.4772 0.5964 Sep 1.0561 +0.3132 0.4666 0.5980 Oct 0.9856 +0.2984 0.4439 0.6115 Nov 0.9353 +0.2941 0.4415 0.6017 Dec 0.8550 +0.2402 0.3961 0.6195 -------------------------------------------- All 1.0077 +0.2858 0.4488 0.6003 ================================================================================ Period: 2016 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 0.9594 Bias: +0.3248 MAE: 0.4503 Correlation: 0.6330 N points: 24,460,506 Model mean: 35.2094 Obs mean: 34.8875 Model std: 0.8429 Obs std: 1.1664 Error distribution: Min: -25.5946 5th pct: -0.2305 25th pct: +0.0541 Median: +0.1935 75th pct: +0.4096 95th pct: +1.3452 Max: +16.3265 ================================================================================ Period: 2017 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 1.0479 Bias: +0.2937 MAE: 0.4354 Correlation: 0.5488 N points: 24,395,369 Model mean: 35.2175 Obs mean: 34.9268 Model std: 0.8948 Obs std: 1.1686 Error distribution: Min: -28.3040 5th pct: -0.2082 25th pct: +0.0260 Median: +0.1407 75th pct: +0.3729 95th pct: +1.3619 Max: +16.2470 ================================================================================ Period: 2018 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 0.9953 Bias: +0.2466 MAE: 0.4174 Correlation: 0.5908 N points: 24,338,489 Model mean: 35.1827 Obs mean: 34.9407 Model std: 0.9119 Obs std: 1.1622 Error distribution: Min: -29.8040 5th pct: -0.2883 25th pct: -0.0009 Median: +0.1349 75th pct: +0.3634 95th pct: +1.1597 Max: +15.5663 ================================================================================ Period: 2019 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 1.0044 Bias: +0.2971 MAE: 0.4474 Correlation: 0.5851 N points: 24,377,458 Model mean: 35.1933 Obs mean: 34.8998 Model std: 0.8936 Obs std: 1.1549 Error distribution: Min: -29.1627 5th pct: -0.2490 25th pct: +0.0209 Median: +0.1611 75th pct: +0.4125 95th pct: +1.3083 Max: +14.6261 ================================================================================ Period: 2020 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 1.0255 Bias: +0.3018 MAE: 0.4643 Correlation: 0.5967 N points: 24,422,636 Model mean: 35.1828 Obs mean: 34.8879 Model std: 0.9311 Obs std: 1.1916 Error distribution: Min: -29.0291 5th pct: -0.2635 25th pct: -0.0010 Median: +0.1472 75th pct: +0.4307 95th pct: +1.4081 Max: +14.5636 ================================================================================ Period: 2021 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 1.0262 Bias: +0.2771 MAE: 0.4437 Correlation: 0.6026 N points: 24,370,685 Model mean: 35.1523 Obs mean: 34.8807 Model std: 0.9750 Obs std: 1.2061 Error distribution: Min: -27.7744 5th pct: -0.2809 25th pct: +0.0145 Median: +0.1563 75th pct: +0.4129 95th pct: +1.2479 Max: +15.5230 ================================================================================ Period: 2022 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 1.0024 Bias: +0.2781 MAE: 0.4645 Correlation: 0.6167 N points: 24,370,685 Model mean: 35.1668 Obs mean: 34.8939 Model std: 1.0255 Obs std: 1.1594 Error distribution: Min: -32.4221 5th pct: -0.3130 25th pct: -0.0127 Median: +0.1576 75th pct: +0.4558 95th pct: +1.2994 Max: +12.8125 ================================================================================ Period: 2023 | Model: pyGETM ================================================================================ Analysed: 2026-05-06 11:28:55 --- CCI-SSS --- RMSE: 1.0010 Bias: +0.2671 MAE: 0.4675 Correlation: 0.6295 N points: 24,370,685 Model mean: 35.1518 Obs mean: 34.8901 Model std: 0.9913 Obs std: 1.2056 Error distribution: Min: -29.6282 5th pct: -0.3723 25th pct: -0.0433 Median: +0.1417 75th pct: +0.4433 95th pct: +1.3474 Max: +15.5347