A Method for Predicting High-Resolution 3D Variations in Temperature and Salinity Fields Using Multi-Source Ocean Data
<p>Data partitioning for prediction and inversion. Figure (<b>a</b>) shows the division of forecast data, and figure (<b>b</b>) shows the division of inversion data.</p> "> Figure 2
<p>SimVP-gsta model. Figure (<b>a</b>) shows the SimVP–gsta model, and figure (<b>b</b>) shows the gsta module.</p> "> Figure 3
<p>M-ViT model. Figure (<b>a</b>) shows the M–ViT model, and figure (<b>b</b>) shows the Mobile–ViT module.</p> "> Figure 4
<p>Three-dimensional prediction model.</p> "> Figure 5
<p>Bilinear interpolation model.</p> "> Figure 6
<p>Loss function settings in the inversion experiment.</p> "> Figure 7
<p>Visualization of the average SST prediction error over 20 days in the Coastal Waters of China. The MAE chart is on the left, and the RMSE chart is on the right.</p> "> Figure 8
<p>Visualization of the average SST prediction error over 20 days in the Northwest Pacific. The MAE chart is on the left, and the RMSE chart is on the right.</p> "> Figure 9
<p>Visualization of the average SLA prediction error over 20 days in the Coastal Waters of China. The MAE chart is on the left, and the RMSE chart is on the right.</p> "> Figure 10
<p>Visualization of the average SLA prediction error over 20 days in the Northwest Pacific. The MAE chart is on the left, and the RMSE chart is on the right.</p> "> Figure 11
<p>Visualization of errors in 48-layer temperature and salinity inversion in the Coastal Waters of China. Figure (<b>a</b>) represents the temperature error, with the MAE chart on the left and the RMSE chart on the right. Figure (<b>b</b>) represents the salinity error, with the MAE chart on the left and the RMSE chart on the right.</p> "> Figure 12
<p>Visualization of errors in 48-layer temperature and salinity inversion in the Northwest Pacific. Figure (<b>a</b>) represents the temperature error, with the MAE chart on the left and the RMSE chart on the right. Figures (<b>b</b>) represents the salinity error, with the MAE chart on the left and the RMSE chart on the right.</p> "> Figure 13
<p>Three-dimensional sea temperature prediction error curves in the Coastal Waters of China. Figures (<b>a</b>–<b>d</b>) show the average MAE for temperature every 5 days from 1 to 20 days, and figures (<b>e</b>–<b>h</b>) show the average RMSE for temperature.</p> "> Figure 14
<p>Three-dimensional salinity prediction error curves in the Coastal Waters of China. Figures (<b>a</b>–<b>d</b>) show the average MAE for salinity, and figures (<b>e</b>–<b>h</b>) show the average RMSE for salinity.</p> "> Figure 15
<p>Visualization of the 3D temperature and salinity predictions for day 1 in the Coastal Waters of China. (<b>a</b>) Temperature, (<b>b</b>) salinity.</p> "> Figure 16
<p>Visualization of the 3D temperature and salinity predictions for day 20 in the Coastal Waters of China. (<b>a</b>) Temperature, (<b>b</b>) salinity.</p> "> Figure 17
<p>Three-dimensional sea temperature prediction error curves in the Northwest Pacific. Figures (<b>a</b>–<b>d</b>) show the average MAE for temperature every 5 days from 1 to 20 days, and figures (<b>e</b>–<b>h</b>) show the average RMSE for temperature.</p> "> Figure 18
<p>Three-dimensional sea salinity prediction error curves in the Northwest Pacific. Figures (<b>a</b>–<b>d</b>) show the average MAE for salinity, and figures (<b>e</b>–<b>h</b>) show the average RMSE for salinity.</p> "> Figure 19
<p>Visualization of the 3D temperature and salinity predictions for day 1 in the Northwest Pacific. (<b>a</b>) Temperature, (<b>b</b>) salinity.</p> "> Figure 20
<p>Visualization of the 3D temperature and salinity predictions for day 20 in the Northwest Pacific. (<b>a</b>) Temperature, (<b>b</b>) salinity.</p> "> Figure 21
<p>Visualization of temperature and salinity prediction errors. The areas highlighted in the figure are the regions with larger forecast errors in this instance.</p> "> Figure 22
<p>The RMSE curves for temperature with different methods. Figures (<b>a</b>–<b>d</b>) show the errors averaged every 5 days for the 20-day temperature and salinity forecasts. Orange and red box indicate the positions where error changes are noticeably variable over time.</p> "> Figure 23
<p>The RMSE curves for salinity with different methods. Figures (<b>a</b>–<b>d</b>) show the errors averaged every 5 days for the 20-day temperature and salinity forecasts. Orange and red box indicate the positions where error changes are noticeably variable over time.</p> ">
Abstract
:1. Introduction
2. Dataset
3. Method
3.1. Model Construction
3.2. Construction of the 3D Prediction Model
4. Parameter Settings and Evaluation Metrics
4.1. Parameter Settings
4.2. Evaluation Metrics
5. Experimental Results
5.1. SST Prediction
5.1.1. Coastal Waters of China
5.1.2. Northwest Pacific
5.2. SLA Prediction
5.2.1. Coastal Waters of China
5.2.2. Northwest Pacific
5.3. Ocean Subsurface Temperature and Salinity Vertical Inversion
5.3.1. Coastal Waters of China
5.3.2. Northwest Pacific
5.4. Three-Dimensional Temperature and Salinity Prediction
5.4.1. Coastal Waters of China
5.4.2. Northwest Pacific
5.4.3. Error Analysis of Prediction
5.4.4. Sensitivity Analysis
6. Discussion
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Layer | Depth | Layer | Depth | Layer | Depth | Layer | Depth |
---|---|---|---|---|---|---|---|
1 | 1 m | 13 | 25 m | 25 | 185 m | 37 | 1452 m |
2 | 2 m | 14 | 29 m | 26 | 222 m | 38 | 1684 m |
3 | 3 m | 15 | 34 m | 27 | 216 m | 39 | 1941 m |
4 | 5 m | 16 | 40 m | 28 | 318 m | 40 | 2225 m |
5 | 6 m | 17 | 47 m | 29 | 380 m | 41 | 2533 m |
6 | 7 m | 18 | 55 m | 30 | 453 m | 42 | 2865 m |
7 | 9 m | 19 | 65 m | 31 | 541 m | 43 | 3220 m |
8 | 11 m | 20 | 77 m | 32 | 643 m | 44 | 3597 m |
9 | 13 m | 21 | 92 m | 33 | 763 m | 45 | 3992 m |
10 | 15 m | 22 | 109 m | 34 | 902 m | 46 | 4405 m |
11 | 18 m | 23 | 130 m | 35 | 1062 m | 47 | 4833 m |
12 | 21 m | 24 | 155 m | 36 | 1245 m | 48 | 5274 m |
Parameter | Model | Data | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
SimVP-gsta | M-ViT | B | T(in, out) | L(in, out) | E(in, out) | |||||
dim | N_T | N_S | C | L | P | |||||
NWP | 512 | 6 | 6 | 1024 | 6 | (7, 5) | 8 | (30, 20) | (1, 48) | (2, 2) |
CWOC | 512 | 6 | 8 | 1024 | 6 | (15, 9) | 8 | (30, 20) | (1, 48) | (2, 2) |
Time | Average-MAE (↓) | Average-RMSE (↓) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Simvp-gsta | UNet | M-ViT | L-R | ConvFormer | ViT | Simvp-gsta | UNet | M-ViT | L-R | ConvFormer | ViT | |
1∼5 days | 0.3896 | 0.6806 | 0.3201 | 0.3457 | 0.4348 | 0.3843 | 0.5365 | 0.8299 | 0.4471 | 0.4754 | 0.5749 | 0.5292 |
6∼10 days | 0.4934 | 0.7585 | 0.4639 | 0.5386 | 0.5583 | 0.4894 | 0.6715 | 0.9496 | 0.6423 | 0.7525 | 0.7450 | 0.6683 |
11∼15 days | 0.5344 | 0.8093 | 0.5273 | 0.6840 | 0.6545 | 0.5819 | 0.7277 | 1.0182 | 0.7282 | 0.9505 | 0.8537 | 0.7720 |
16∼20 days | 0.5829 | 0.8554 | 0.5541 | 0.8223 | 0.6549 | 0.6454 | 0.7917 | 1.0764 | 0.7484 | 1.1411 | 0.8728 | 0.8511 |
Average | 0.5001 | 0.7760 | 0.4664 | 0.5977 | 0.5756 | 0.5253 | 0.6819 | 0.9685 | 0.6465 | 0.8299 | 0.7616 | 0.7052 |
Time | Average-MAE (↓) | Average-RMSE (↓) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Simvp-gsta | UNet | M-ViT | L-R | ConvFormer | ViT | Simvp-gsta | UNet | M-ViT | L-R | ConvFormer | ViT | |
1∼5 days | 0.2972 | 0.5027 | 0.2782 | 0.2989 | 0.6730 | 0.3286 | 0.4368 | 0.6538 | 0.4793 | 0.4529 | 0.8441 | 0.4902 |
6∼10 days | 0.4347 | 0.5829 | 0.4182 | 0.4960 | 0.7463 | 0.4446 | 0.6441 | 0.7810 | 0.6279 | 0.7432 | 0.9737 | 0.6556 |
11∼15 days | 0.5099 | 0.6422 | 0.4884 | 0.6297 | 0.7899 | 0.5093 | 0.7537 | 0.8681 | 0.7314 | 0.9408 | 1.0542 | 0.7467 |
16∼20 days | 0.5698 | 0.7034 | 0.5425 | 0.7603 | 0.8438 | 0.5642 | 0.8452 | 0.9491 | 0.8156 | 1.1395 | 1.1062 | 0.8261 |
Average | 0.4529 | 0.6078 | 0.4318 | 0.5462 | 0.7558 | 0.4617 | 0.6700 | 0.8130 | 0.6486 | 0.8191 | 0.9946 | 0.6797 |
Time | Average-MAE (↓) | Average-RMSE (↓) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Simvp-gsta | UNet | M-ViT | L-R | ConvFormer | ViT | Simvp-gsta | UNet | M-ViT | L-R | ConvFormer | ViT | |
1∼5 days | 0.0229 | 0.0429 | 0.0224 | 0.0327 | 0.0327 | 0.0281 | 0.0320 | 0.0546 | 0.0317 | 0.0385 | 0.0431 | 0.0378 |
6∼10 days | 0.0368 | 0.0523 | 0.0363 | 0.0506 | 0.0455 | 0.0441 | 0.0510 | 0.0674 | 0.0507 | 0.0687 | 0.0601 | 0.0587 |
11∼15 days | 0.0441 | 0.0589 | 0.0431 | 0.0619 | 0.0524 | 0.0548 | 0.0602 | 0.0761 | 0.0593 | 0.0816 | 0.0692 | 0.0715 |
16∼20 days | 0.0484 | 0.0647 | 0.0476 | 0.0694 | 0.0563 | 0.0614 | 0.0658 | 0.0829 | 0.0652 | 0.0903 | 0.0745 | 0.0797 |
Average | 0.0381 | 0.0547 | 0.0374 | 0.0526 | 0.0467 | 0.0471 | 0.0523 | 0.0703 | 0.0517 | 0.0698 | 0.0617 | 0.0619 |
Time | Average-MAE (↓) | Average-RMSE (↓) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Simvp-gsta | UNet | M-ViT | L-R | ConvFormer | ViT | Simvp-gsta | UNet | M-ViT | L-R | ConvFormer | ViT | |
1∼5 days | 0.0213 | 0.0402 | 0.0235 | 0.0214 | 0.0507 | 0.0203 | 0.0303 | 0.0504 | 0.0326 | 0.0354 | 0.0544 | 0.0300 |
6∼10 days | 0.0327 | 0.0466 | 0.0327 | 0.0396 | 0.0507 | 0.0329 | 0.0470 | 0.0608 | 0.0464 | 0.0636 | 0.0648 | 0.0467 |
11∼15 days | 0.0416 | 0.0527 | 0.0408 | 0.0521 | 0.0568 | 0.0429 | 0.0606 | 0.0714 | 0.0587 | 0.0813 | 0.0756 | 0.0609 |
16∼20 days | 0.0476 | 0.0578 | 0.0467 | 0.0607 | 0.0611 | 0.0503 | 0.0702 | 0.0801 | 0.0680 | 0.0932 | 0.0840 | 0.0715 |
Average | 0.0351 | 0.0493 | 0.0359 | 0.0435 | 0.0548 | 0.0366 | 0.0520 | 0.0657 | 0.0514 | 0.0684 | 0.0697 | 0.0523 |
Element | Depth | Average-MAE (↓) | Average-RMSE (↓) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Simvp-gsta | UNet | M-ViT | Atten-UNet | ConvFormer | ViT | Simvp-gsta | UNet | M-ViT | Atten-UNet | ConvFormer | ViT | ||
Temp | <600 m | 0.4969 | 0.7577 | 0.5099 | 0.6807 | 0.7933 | 0.5391 | 0.6968 | 1.0916 | 0.7192 | 0.9986 | 1.0385 | 0.7881 |
>600 m | 0.1017 | 0.1605 | 0.1086 | 0.1565 | 0.1550 | 0.1368 | 0.1467 | 0.2686 | 0.1535 | 0.2678 | 0.2171 | 0.1929 | |
Sal | <600 m | 0.2106 | 0.4183 | 0.2393 | 0.3512 | 0.3725 | 0.3282 | 0.3261 | 0.9422 | 0.3865 | 0.8816 | 0.5516 | 0.6021 |
>600 m | 0.0690 | 0.4586 | 0.1162 | 0.2295 | 0.3714 | 0.2361 | 0.0937 | 1.0096 | 0.3063 | 0.9580 | 0.5176 | 0.4784 |
Element | Depth | Average-MAE (↓) | Average-RMSE (↓) | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Simvp-gsta | UNet | M-ViT | Atten-UNet | ConvFormer | ViT | Simvp-gsta | UNet | M-ViT | Atten-UNet | ConvFormer | ViT | ||
Temp | <600 m | 0.5134 | 0.6684 | 0.5761 | 0.7873 | 0.8208 | 0.8823 | 0.7587 | 0.9567 | 0.8438 | 1.1241 | 1.1698 | 1.3008 |
>600 m | 0.0975 | 0.1201 | 0.1101 | 0.1785 | 0.1585 | 0.1735 | 0.1377 | 0.1786 | 0.1590 | 0.3003 | 0.2503 | 0.2826 | |
Sal | <600 m | 0.1935 | 0.2661 | 0.2440 | 0.4037 | 0.3960 | 0.3935 | 0.3192 | 0.3682 | 0.4244 | 0.7596 | 0.6607 | 0.6035 |
>600 m | 0.1025 | 0.1311 | 0.2381 | 0.3208 | 0.2585 | 0.3357 | 0.2443 | 0.2527 | 0.4647 | 0.7050 | 0.5442 | 0.6079 |
Time | Element | Depth | Average-MAE (↓) | Average-RMSE (↓) | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Winter | Spring | Summer | Autumn | Winter | Spring | Summer | Autumn | |||
1∼5 days | Temp | <600 m | 0.5697 | 0.5463 | 0.6002 | 0.4950 | 0.7392 | 0.7420 | 0.7135 | 0.6989 |
>600 m | 0.1088 | 0.1107 | 0.1045 | 0.1043 | 0.1529 | 0.1562 | 0.1513 | 0.1536 | ||
Sal | <600 m | 0.2018 | 0.1897 | 0.1945 | 0.2485 | 0.3358 | 0.2998 | 0.2893 | 0.3664 | |
>600 m | 0.0609 | 0.0622 | 0.0587 | 0.0565 | 0.0829 | 0.0838 | 0.0791 | 0.0765 | ||
6∼10 days | Temp | <600 m | 0.5818 | 0.5745 | 0.5231 | 0.5160 | 0.7611 | 0.7782 | 0.7432 | 0.7269 |
>600 m | 0.1106 | 0.1104 | 0.1042 | 0.1052 | 0.1554 | 0.1561 | 0.1511 | 0.1551 | ||
Sal | <600 m | 0.2047 | 0.1916 | 0.1967 | 0.2479 | 0.3392 | 0.3024 | 0.2958 | 0.3711 | |
>600 m | 0.0584 | 0.0599 | 0.0567 | 0.0564 | 0.0790 | 0.0810 | 0.0766 | 0.0764 | ||
11∼15 days | Temp | <600 m | 0.5926 | 0.5954 | 0.5454 | 0.5333 | 0.7836 | 0.8042 | 0.7743 | 0.7495 |
>600 m | 0.1124 | 0.1107 | 0.1044 | 0.1061 | 0.1577 | 0.1567 | 0.1515 | 0.1564 | ||
Sal | <600 m | 0.2075 | 0.1924 | 0.2010 | 0.2496 | 0.3420 | 0.3026 | 0.3035 | 0.3754 | |
>600 m | 0.0581 | 0.0592 | 0.0560 | 0.0555 | 0.0786 | 0.0802 | 0.0758 | 0.0753 | ||
16∼20 days | Temp | <600 m | 0.6116 | 0.6136 | 0.5660 | 0.5531 | 0.8135 | 0.8225 | 0.8027 | 0.7775 |
>600 m | 0.1143 | 0.1225 | 0.1051 | 0.1062 | 0.1598 | 0.1711 | 0.1526 | 0.1565 | ||
Sal | <600 m | 0.2104 | 0.1930 | 0.2068 | 0.2537 | 0.3461 | 0.3036 | 0.3117 | 0.3797 | |
>600 m | 0.0582 | 0.0585 | 0.0559 | 0.0562 | 0.0790 | 0.0792 | 0.0758 | 0.0763 |
Time | Element | Depth | Average-MAE (↓) | Average-RMSE (↓) | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Winter | Spring | Summer | Autumn | Winter | Spring | Summer | Autumn | |||
1∼5 days | Temp | <600 m | 0.4834 | 0.4777 | 0.5532 | 0.5583 | 0.7002 | 0.6896 | 0.8197 | 0.8370 |
>600 m | 0.0842 | 0.0836 | 0.0850 | 0.0883 | 0.1165 | 0.1164 | 0.1174 | 0.1226 | ||
Sal | <600 m | 0.1759 | 0.1609 | 0.1872 | 0.2088 | 0.2600 | 0.2381 | 0.2668 | 0.2996 | |
>600 m | 0.0820 | 0.0765 | 0.0796 | 0.0934 | 0.1280 | 0.1252 | 0.1229 | 0.1416 | ||
6∼10 days | Temp | <600 m | 0.4980 | 0.5042 | 0.5787 | 0.5808 | 0.7264 | 0.7241 | 0.8539 | 0.8653 |
>600 m | 0.0850 | 0.0844 | 0.0854 | 0.0887 | 0.1178 | 0.1177 | 0.1180 | 0.1231 | ||
Sal | <600 m | 0.1746 | 0.1609 | 0.1888 | 0.2081 | 0.2590 | 0.2384 | 0.2704 | 0.3002 | |
>600 m | 0.0827 | 0.0765 | 0.0792 | 0.0896 | 0.1286 | 0.1246 | 0.1254 | 0.1376 | ||
11∼15 days | Temp | <600 m | 0.5176 | 0.5360 | 0.6083 | 0.6059 | 0.7570 | 0.7702 | 0.8997 | 0.9013 |
>600 m | 0.0862 | 0.0858 | 0.0863 | 0.0895 | 0.1199 | 0.1200 | 0.1195 | 0.1244 | ||
Sal | <600 m | 0.1732 | 0.1618 | 0.1913 | 0.2085 | 0.2580 | 0.2392 | 0.2745 | 0.3016 | |
>600 m | 0.0818 | 0.0768 | 0.0785 | 0.0867 | 0.1283 | 0.1224 | 0.1249 | 0.1338 | ||
16∼20 days | Temp | <600 m | 0.5378 | 0.5655 | 0.6385 | 0.6310 | 0.7910 | 0.8146 | 0.9503 | 0.9429 |
>600 m | 0.0876 | 0.0872 | 0.0875 | 0.0904 | 0.1225 | 0.1229 | 0.1216 | 0.1261 | ||
Sal | <600 m | 0.1724 | 0.1636 | 0.1941 | 0.2097 | 0.2576 | 0.2417 | 0.2786 | 0.3044 | |
>600 m | 0.0806 | 0.0780 | 0.0783 | 0.0850 | 0.1270 | 0.1249 | 0.1233 | 0.1357 |
Inputs | Method 1 | Method 2 | Method 3 | Method 4 |
---|---|---|---|---|
SST-True | ✓ | ✓ | ||
SST-Pred | ✓ | ✓ | ✓ | |
SLA-True | ✓ | ✓ | ||
SLA-Pred | ✓ |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Cao, X.; Liu, C.; Zhang, S.; Gao, F. A Method for Predicting High-Resolution 3D Variations in Temperature and Salinity Fields Using Multi-Source Ocean Data. J. Mar. Sci. Eng. 2024, 12, 1396. https://doi.org/10.3390/jmse12081396
Cao X, Liu C, Zhang S, Gao F. A Method for Predicting High-Resolution 3D Variations in Temperature and Salinity Fields Using Multi-Source Ocean Data. Journal of Marine Science and Engineering. 2024; 12(8):1396. https://doi.org/10.3390/jmse12081396
Chicago/Turabian StyleCao, Xiaohu, Chang Liu, Shaoqing Zhang, and Feng Gao. 2024. "A Method for Predicting High-Resolution 3D Variations in Temperature and Salinity Fields Using Multi-Source Ocean Data" Journal of Marine Science and Engineering 12, no. 8: 1396. https://doi.org/10.3390/jmse12081396