################################################################################ TEMP_SURFACE Validation Statistics ################################################################################ Format: 1.1 Created: 2026-05-05 08:37:50 Author: RT Project: OceanICU Institute: BB Area: AMM7 Experiment: ObsKd ################################################################################ ================================================================================ Period: 2016-2023 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 0.9880 Bias: +0.5735 MAE: 0.8000 Correlation: 0.9654 N points: 151,821,276 Model mean: 12.4442 Obs mean: 11.8707 Model std: 3.9169 Obs std: 3.8133 Error distribution: Min: -9.6203 5th pct: -0.7238 25th pct: +0.1134 Median: +0.5970 75th pct: +1.0669 95th pct: +1.7970 Max: +9.2727 Monthly breakdown: Month RMSE Bias MAE Corr -------------------------------------------- Jan 1.0808 +0.5484 0.8596 0.9505 Feb 1.0457 +0.5221 0.8125 0.9546 Mar 0.9707 +0.4758 0.7581 0.9597 Apr 0.8691 +0.4305 0.6980 0.9681 May 0.8722 +0.5290 0.7171 0.9733 Jun 1.1068 +0.7263 0.9085 0.9626 Jul 1.1429 +0.7507 0.9392 0.9620 Aug 1.0290 +0.6233 0.8285 0.9653 Sep 0.8612 +0.4850 0.6872 0.9761 Oct 0.8464 +0.4941 0.6820 0.9765 Nov 0.9771 +0.6104 0.8016 0.9672 Dec 1.1088 +0.6802 0.9057 0.9570 -------------------------------------------- All 0.9880 +0.5735 0.8000 0.9654 --- CCI-SST --- RMSE: 0.9801 Bias: +0.5491 MAE: 0.7916 Correlation: 0.9639 N points: 197,655,640 Model mean: 12.6250 Obs mean: 12.0759 Model std: 3.8098 Obs std: 3.7509 Error distribution: Min: -10.7849 5th pct: -0.7569 25th pct: +0.0527 Median: +0.5712 75th pct: +1.0612 95th pct: +1.7903 Max: +9.4216 Monthly breakdown: Month RMSE Bias MAE Corr -------------------------------------------- Jan 1.0498 +0.5102 0.8247 0.9498 Feb 1.0191 +0.5066 0.7879 0.9542 Mar 0.9667 +0.4847 0.7566 0.9585 Apr 0.8656 +0.4342 0.6941 0.9664 May 0.8757 +0.5291 0.7179 0.9710 Jun 1.0867 +0.6945 0.8938 0.9609 Jul 1.1134 +0.7199 0.9158 0.9623 Aug 1.0294 +0.6107 0.8306 0.9653 Sep 0.8765 +0.4594 0.6977 0.9745 Oct 0.8658 +0.4523 0.6938 0.9739 Nov 0.9715 +0.5530 0.7898 0.9641 Dec 1.1040 +0.6290 0.8932 0.9523 -------------------------------------------- All 0.9801 +0.5491 0.7916 0.9639 ================================================================================ Period: 2016 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 0.8748 Bias: +0.3147 MAE: 0.6865 Correlation: 0.9631 N points: 19,016,628 Model mean: 12.1882 Obs mean: 11.8735 Model std: 3.9222 Obs std: 3.7392 Error distribution: Min: -8.3486 5th pct: -0.9606 25th pct: -0.1295 Median: +0.3515 75th pct: +0.8365 95th pct: +1.5323 Max: +6.8076 --- CCI-SST --- RMSE: 0.8355 Bias: +0.3022 MAE: 0.6571 Correlation: 0.9655 N points: 24,757,704 Model mean: 12.3535 Obs mean: 12.0513 Model std: 3.8110 Obs std: 3.7266 Error distribution: Min: -8.7668 5th pct: -0.9364 25th pct: -0.1267 Median: +0.3387 75th pct: +0.8059 95th pct: +1.4647 Max: +7.2398 ================================================================================ Period: 2017 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 0.9663 Bias: +0.5792 MAE: 0.7845 Correlation: 0.9656 N points: 18,964,670 Model mean: 12.4767 Obs mean: 11.8974 Model std: 3.7331 Obs std: 3.6558 Error distribution: Min: -5.9293 5th pct: -0.6806 25th pct: +0.1242 Median: +0.6063 75th pct: +1.0789 95th pct: +1.8037 Max: +9.2727 --- CCI-SST --- RMSE: 0.9406 Bias: +0.5303 MAE: 0.7611 Correlation: 0.9652 N points: 24,690,059 Model mean: 12.6566 Obs mean: 12.1263 Model std: 3.6549 Obs std: 3.6290 Error distribution: Min: -6.1345 5th pct: -0.7521 25th pct: +0.0481 Median: +0.5517 75th pct: +1.0438 95th pct: +1.7568 Max: +7.2300 ================================================================================ Period: 2018 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 1.0824 Bias: +0.6773 MAE: 0.8737 Correlation: 0.9629 N points: 18,964,670 Model mean: 12.3212 Obs mean: 11.6439 Model std: 4.0814 Obs std: 3.9844 Error distribution: Min: -9.4665 5th pct: -0.6763 25th pct: +0.1719 Median: +0.6902 75th pct: +1.1974 95th pct: +2.0127 Max: +8.7800 --- CCI-SST --- RMSE: 1.0759 Bias: +0.6882 MAE: 0.8656 Correlation: 0.9638 N points: 24,690,050 Model mean: 12.4923 Obs mean: 11.8041 Model std: 3.9335 Obs std: 3.8476 Error distribution: Min: -10.3517 5th pct: -0.5921 25th pct: +0.1738 Median: +0.6925 75th pct: +1.2065 95th pct: +2.0252 Max: +7.5133 ================================================================================ Period: 2019 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 0.9843 Bias: +0.6340 MAE: 0.8057 Correlation: 0.9685 N points: 18,964,670 Model mean: 12.3971 Obs mean: 11.7631 Model std: 3.7751 Obs std: 3.6817 Error distribution: Min: -7.0930 5th pct: -0.5967 25th pct: +0.1798 Median: +0.6533 75th pct: +1.1225 95th pct: +1.8523 Max: +7.7173 --- CCI-SST --- RMSE: 1.0096 Bias: +0.6536 MAE: 0.8229 Correlation: 0.9658 N points: 24,690,060 Model mean: 12.6057 Obs mean: 11.9521 Model std: 3.6856 Obs std: 3.6177 Error distribution: Min: -8.5255 5th pct: -0.5823 25th pct: +0.1513 Median: +0.6740 75th pct: +1.1688 95th pct: +1.8993 Max: +7.0687 ================================================================================ Period: 2020 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 0.9518 Bias: +0.5647 MAE: 0.7737 Correlation: 0.9679 N points: 19,016,628 Model mean: 12.3441 Obs mean: 11.7794 Model std: 3.7702 Obs std: 3.6783 Error distribution: Min: -7.6856 5th pct: -0.6763 25th pct: +0.1366 Median: +0.6018 75th pct: +1.0492 95th pct: +1.7369 Max: +7.8931 --- CCI-SST --- RMSE: 0.9687 Bias: +0.6044 MAE: 0.7908 Correlation: 0.9680 N points: 24,757,704 Model mean: 12.5226 Obs mean: 11.9182 Model std: 3.6886 Obs std: 3.6279 Error distribution: Min: -10.7849 5th pct: -0.6166 25th pct: +0.1420 Median: +0.6357 75th pct: +1.0976 95th pct: +1.7724 Max: +7.5468 ================================================================================ Period: 2021 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 1.0638 Bias: +0.6675 MAE: 0.8654 Correlation: 0.9609 N points: 18,964,670 Model mean: 12.4026 Obs mean: 11.7351 Model std: 3.9754 Obs std: 3.8776 Error distribution: Min: -9.1434 5th pct: -0.6720 25th pct: +0.1952 Median: +0.6937 75th pct: +1.1853 95th pct: +1.9373 Max: +8.9868 --- CCI-SST --- RMSE: 1.0515 Bias: +0.6251 MAE: 0.8490 Correlation: 0.9593 N points: 24,689,971 Model mean: 12.6037 Obs mean: 11.9786 Model std: 3.8708 Obs std: 3.8267 Error distribution: Min: -10.2151 5th pct: -0.7470 25th pct: +0.0937 Median: +0.6473 75th pct: +1.1651 95th pct: +1.9422 Max: +8.3632 ================================================================================ Period: 2022 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 0.9530 Bias: +0.5761 MAE: 0.7734 Correlation: 0.9708 N points: 18,964,670 Model mean: 12.6277 Obs mean: 12.0517 Model std: 3.9532 Obs std: 3.8585 Error distribution: Min: -5.7222 5th pct: -0.6563 25th pct: +0.1339 Median: +0.6022 75th pct: +1.0516 95th pct: +1.7514 Max: +7.0574 --- CCI-SST --- RMSE: 0.9373 Bias: +0.5041 MAE: 0.7565 Correlation: 0.9665 N points: 24,690,060 Model mean: 12.8056 Obs mean: 12.3015 Model std: 3.8320 Obs std: 3.7716 Error distribution: Min: -7.4294 5th pct: -0.7955 25th pct: +0.0064 Median: +0.5314 75th pct: +1.0156 95th pct: +1.7358 Max: +7.6121 ================================================================================ Period: 2023 | Model: pyGETM ================================================================================ Analysed: 2026-05-05 08:37:50 --- OSTIA --- RMSE: 1.0252 Bias: +0.5751 MAE: 0.8375 Correlation: 0.9641 N points: 18,964,670 Model mean: 12.7972 Obs mean: 12.2221 Model std: 4.0758 Obs std: 3.9821 Error distribution: Min: -9.6203 5th pct: -0.8713 25th pct: +0.1036 Median: +0.6249 75th pct: +1.1112 95th pct: +1.8592 Max: +7.6242 --- CCI-SST --- RMSE: 1.0198 Bias: +0.4853 MAE: 0.8302 Correlation: 0.9580 N points: 24,690,032 Model mean: 12.9610 Obs mean: 12.4757 Model std: 3.9570 Obs std: 3.9041 Error distribution: Min: -10.1614 5th pct: -1.0397 25th pct: -0.0825 Median: +0.5423 75th pct: +1.0797 95th pct: +1.8586 Max: +9.4216