################################################################################ TEMP_SURFACE Validation Statistics ################################################################################ Format: 1.1 Created: 2026-04-30 16:22:30 Author: RT Project: OceanICU Institute: BB Area: AMM7 Experiment: Baseline ################################################################################ ================================================================================ Period: 2016-2023 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.9160 Bias: +0.3920 MAE: 0.7266 Correlation: 0.9651 N points: 151,821,276 Model mean: 12.2628 Obs mean: 11.8707 Model std: 4.0162 Obs std: 3.8133 Error distribution: Min: -9.7834 5th pct: -0.8868 25th pct: -0.0976 Median: +0.3996 75th pct: +0.8998 95th pct: +1.6521 Max: +10.0921 Monthly breakdown: Month RMSE Bias MAE Corr -------------------------------------------- Jan 0.9340 +0.3050 0.7263 0.9555 Feb 0.9121 +0.2936 0.6972 0.9589 Mar 0.8415 +0.2331 0.6405 0.9637 Apr 0.7604 +0.1807 0.5835 0.9705 May 0.8391 +0.3735 0.6565 0.9716 Jun 1.2281 +0.7980 0.9955 0.9552 Jul 1.3036 +0.8952 1.0867 0.9534 Aug 1.0455 +0.6093 0.8451 0.9626 Sep 0.7555 +0.2528 0.5822 0.9765 Oct 0.6902 +0.1415 0.5374 0.9778 Nov 0.7899 +0.2486 0.6275 0.9688 Dec 0.9270 +0.3613 0.7343 0.9595 -------------------------------------------- All 0.9160 +0.3920 0.7266 0.9651 --- CCI-SST --- RMSE: 0.9018 Bias: +0.3841 MAE: 0.7152 Correlation: 0.9649 N points: 197,655,640 Model mean: 12.4600 Obs mean: 12.0759 Model std: 3.8903 Obs std: 3.7509 Error distribution: Min: -11.0026 5th pct: -0.8721 25th pct: -0.1136 Median: +0.3811 75th pct: +0.8884 95th pct: +1.6397 Max: +8.8265 Monthly breakdown: Month RMSE Bias MAE Corr -------------------------------------------- Jan 0.8997 +0.2875 0.6939 0.9561 Feb 0.8773 +0.2977 0.6676 0.9598 Mar 0.8263 +0.2625 0.6305 0.9636 Apr 0.7444 +0.2077 0.5751 0.9700 May 0.8260 +0.3887 0.6490 0.9703 Jun 1.1845 +0.7575 0.9614 0.9544 Jul 1.2591 +0.8469 1.0452 0.9536 Aug 1.0436 +0.6036 0.8462 0.9628 Sep 0.7678 +0.2521 0.5932 0.9760 Oct 0.7131 +0.1326 0.5564 0.9766 Nov 0.7939 +0.2235 0.6293 0.9675 Dec 0.9218 +0.3378 0.7267 0.9574 -------------------------------------------- All 0.9018 +0.3841 0.7152 0.9649 ================================================================================ Period: 2016 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.8768 Bias: +0.1957 MAE: 0.6889 Correlation: 0.9610 N points: 19,016,628 Model mean: 12.0692 Obs mean: 11.8735 Model std: 3.9886 Obs std: 3.7392 Error distribution: Min: -8.4243 5th pct: -1.0961 25th pct: -0.2904 Median: +0.2150 75th pct: +0.7203 95th pct: +1.4537 Max: +6.9846 --- CCI-SST --- RMSE: 0.8298 Bias: +0.1936 MAE: 0.6514 Correlation: 0.9638 N points: 24,757,704 Model mean: 12.2449 Obs mean: 12.0513 Model std: 3.8616 Obs std: 3.7266 Error distribution: Min: -8.9750 5th pct: -1.0402 25th pct: -0.2701 Median: +0.2129 75th pct: +0.6939 95th pct: +1.3793 Max: +7.1261 ================================================================================ Period: 2017 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.8807 Bias: +0.3935 MAE: 0.7007 Correlation: 0.9662 N points: 18,964,670 Model mean: 12.2909 Obs mean: 11.8974 Model std: 3.8412 Obs std: 3.6558 Error distribution: Min: -6.1325 5th pct: -0.8441 25th pct: -0.0802 Median: +0.4026 75th pct: +0.8828 95th pct: +1.6333 Max: +8.6925 --- CCI-SST --- RMSE: 0.8524 Bias: +0.3655 MAE: 0.6785 Correlation: 0.9671 N points: 24,690,059 Model mean: 12.4918 Obs mean: 12.1263 Model std: 3.7457 Obs std: 3.6290 Error distribution: Min: -6.5475 5th pct: -0.8617 25th pct: -0.1087 Median: +0.3653 75th pct: +0.8458 95th pct: +1.5749 Max: +6.7065 ================================================================================ Period: 2018 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.9849 Bias: +0.4776 MAE: 0.7812 Correlation: 0.9629 N points: 18,964,670 Model mean: 12.1215 Obs mean: 11.6439 Model std: 4.1821 Obs std: 3.9844 Error distribution: Min: -9.7834 5th pct: -0.8793 25th pct: -0.0494 Median: +0.4812 75th pct: +1.0063 95th pct: +1.8040 Max: +8.3029 --- CCI-SST --- RMSE: 0.9695 Bias: +0.5086 MAE: 0.7647 Correlation: 0.9651 N points: 24,690,050 Model mean: 12.3127 Obs mean: 11.8041 Model std: 4.0178 Obs std: 3.8476 Error distribution: Min: -10.7811 5th pct: -0.7440 25th pct: -0.0015 Median: +0.4971 75th pct: +1.0093 95th pct: +1.8266 Max: +8.2242 ================================================================================ Period: 2019 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.9111 Bias: +0.4732 MAE: 0.7328 Correlation: 0.9687 N points: 18,964,670 Model mean: 12.2363 Obs mean: 11.7631 Model std: 3.9060 Obs std: 3.6817 Error distribution: Min: -7.1780 5th pct: -0.7480 25th pct: -0.0108 Median: +0.4761 75th pct: +0.9800 95th pct: +1.6861 Max: +7.3279 --- CCI-SST --- RMSE: 0.9227 Bias: +0.5084 MAE: 0.7423 Correlation: 0.9670 N points: 24,690,060 Model mean: 12.4605 Obs mean: 11.9521 Model std: 3.7935 Obs std: 3.6177 Error distribution: Min: -8.6994 5th pct: -0.6930 25th pct: +0.0024 Median: +0.5044 75th pct: +1.0226 95th pct: +1.7321 Max: +6.9408 ================================================================================ Period: 2020 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.8991 Bias: +0.4208 MAE: 0.7118 Correlation: 0.9673 N points: 19,016,628 Model mean: 12.2002 Obs mean: 11.7794 Model std: 3.8771 Obs std: 3.6783 Error distribution: Min: -8.2411 5th pct: -0.8051 25th pct: -0.0540 Median: +0.4241 75th pct: +0.9163 95th pct: +1.6575 Max: +8.3450 --- CCI-SST --- RMSE: 0.8976 Bias: +0.4669 MAE: 0.7145 Correlation: 0.9679 N points: 24,757,704 Model mean: 12.3851 Obs mean: 11.9182 Model std: 3.7680 Obs std: 3.6279 Error distribution: Min: -9.9685 5th pct: -0.7210 25th pct: -0.0109 Median: +0.4606 75th pct: +0.9506 95th pct: +1.6736 Max: +7.1809 ================================================================================ Period: 2021 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.9805 Bias: +0.4560 MAE: 0.7747 Correlation: 0.9601 N points: 18,964,670 Model mean: 12.1911 Obs mean: 11.7351 Model std: 4.0802 Obs std: 3.8776 Error distribution: Min: -8.5194 5th pct: -0.8656 25th pct: -0.0653 Median: +0.4509 75th pct: +0.9944 95th pct: +1.8046 Max: +8.3180 --- CCI-SST --- RMSE: 0.9625 Bias: +0.4274 MAE: 0.7556 Correlation: 0.9598 N points: 24,689,971 Model mean: 12.4060 Obs mean: 11.9786 Model std: 3.9558 Obs std: 3.8267 Error distribution: Min: -10.7180 5th pct: -0.8792 25th pct: -0.1153 Median: +0.3999 75th pct: +0.9553 95th pct: +1.7966 Max: +7.8217 ================================================================================ Period: 2022 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.8457 Bias: +0.3520 MAE: 0.6691 Correlation: 0.9713 N points: 18,964,670 Model mean: 12.4037 Obs mean: 12.0517 Model std: 4.0073 Obs std: 3.8585 Error distribution: Min: -6.4934 5th pct: -0.8451 25th pct: -0.1163 Median: +0.3536 75th pct: +0.8264 95th pct: +1.5326 Max: +6.9722 --- CCI-SST --- RMSE: 0.8367 Bias: +0.3027 MAE: 0.6635 Correlation: 0.9688 N points: 24,690,060 Model mean: 12.6041 Obs mean: 12.3015 Model std: 3.8767 Obs std: 3.7716 Error distribution: Min: -7.8750 5th pct: -0.9148 25th pct: -0.1883 Median: +0.2948 75th pct: +0.7911 95th pct: +1.5135 Max: +7.0232 ================================================================================ Period: 2023 | Model: pyGETM ================================================================================ Analysed: 2026-04-30 16:22:30 --- OSTIA --- RMSE: 0.9464 Bias: +0.3678 MAE: 0.7539 Correlation: 0.9640 N points: 18,964,670 Model mean: 12.5899 Obs mean: 12.2221 Model std: 4.2069 Obs std: 3.9821 Error distribution: Min: -8.7341 5th pct: -1.0365 25th pct: -0.1473 Median: +0.3920 75th pct: +0.9128 95th pct: +1.6738 Max: +10.0921 --- CCI-SST --- RMSE: 0.9404 Bias: +0.2997 MAE: 0.7511 Correlation: 0.9601 N points: 24,690,032 Model mean: 12.7754 Obs mean: 12.4757 Model std: 4.0655 Obs std: 3.9041 Error distribution: Min: -11.0026 5th pct: -1.1399 25th pct: -0.2606 Median: +0.3086 75th pct: +0.8701 95th pct: +1.6717 Max: +8.8265