Oceanic Mesoscale Eddies Identification Using B-Spline Surface Fitting Model Based on Along-Track SLA Data
Abstract
:1. Introduction
- Physical parameter method:
- 2.
- Sea surface geometry method:
- 3.
- Synthesis method:
2. Materials and Methods
2.1. SLA Data
2.2. Methods
2.2.1. B-Spline Surface
2.2.2. Cross-Checking
2.2.3. Surface Fitting
3. Results
3.1. Ideal Experiment I: Ideal Stationary Eddy
3.2. Ideal Experiment II: Stationary Eddy with Noise
3.3. Ideal Experiment III: Ideal Dynamic Eddy
4. Discussion
4.1. Practical Experiments with Measured Data
4.1.1. Determining the Optional Frequency Combination
4.1.2. Hypothesis Testing
4.1.3. Mesoscale Eddy Indexes
- For an (anticyclone) cyclone eddy, the SLA data points inside the eddy are all (high) below a certain value.
- For an (anticyclone) cyclone eddy, there is at least one minimum (maximum) SLA value.
- The amplitude of the eddy is not less than 7.5 cm.
- The eddy boundary is a closed contour.
- The diameter of the eddy ranges from 50 to 400 km.
4.2. Eddy Contours
4.3. Compare and Analyze the Results of Gridded Data and Along-Track Data
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Sample | Coverage | Range | Timer Series | Level | Type |
---|---|---|---|---|---|
SLA | North–West Pacific | 25–40°N 142–157°E | 2022,03,01–2022,03,09 | 3 | NRT |
Frequency n | Frequency m | |||||
---|---|---|---|---|---|---|
5 | 6 | 7 | 8 | 9 | 10 | |
7 | 5.84 | 5.34 | 6.40 | 6.70 | 7.53 | 28.01 |
8 | 5.86 | 5.03 | 5.86 | 4.95 | 5.41 | 22.79 |
9 | 5.65 | 5.04 | 6.30 | 5.52 | 7.04 | 14.18 |
10 | 5.63 | 5.02 | 6.30 | 4.93 | 5.69 | 10.32 |
11 | 6.12 | 5.00 | 6.31 | 5.12 | 8.79 | 13.95 |
Noise (cm) | Total Number | |||||
---|---|---|---|---|---|---|
10% | 20% | 40% | 60% | 80% | 100% | |
0 | 0.29 | 0.23 | 0.16 | 0.12 | 0.10 | 0.08 |
1 | 1.02 | 0.76 | 0.53 | 0.41 | 0.33 | 0.27 |
2 | 1.46 | 1.18 | 0.89 | 0.71 | 0.59 | 0.49 |
3 | 1.56 | 1.32 | 1.03 | 0.84 | 0.69 | 0.57 |
5 | 1.95 | 1.56 | 1.21 | 0.99 | 0.82 | 0.67 |
V | Total Number | |||||
---|---|---|---|---|---|---|
10% | 20% | 40% | 60% | 80% | 100% | |
0 | 0.29 | 0.23 | 0.16 | 0.12 | 0.10 | 0.08 |
2 | 5.14 | 3.56 | 2.14 | 1.50 | 1.14 | 0.91 |
4 | 6.62 | 4.74 | 2.84 | 1.97 | 1.50 | 1.20 |
6 | 8.20 | 5.82 | 3.64 | 2.58 | 1.97 | 1.58 |
8 | 9.76 | 6.87 | 4.25 | 2.98 | 2.27 | 1.82 |
10 | 11.49 | 8.14 | 4.97 | 3.48 | 2.65 | 2.12 |
12 | 13.25 | 9.47 | 5.80 | 4.07 | 3.10 | 2.49 |
Days | |||||||||
---|---|---|---|---|---|---|---|---|---|
5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | |
Data Points | 8781 | 10,042 | 12,797 | 14,763 | 16,108 | 17,746 | 19,942 | 21,413 | 23,119 |
MAE | 13.24 | 8.77 | 8.11 | 8.04 | 7.62 | 7.67 | 7.74 | 8.05 | 8.19 |
Frequency n | Frequency m | |||||
---|---|---|---|---|---|---|
11 | 12 | 13 | 14 | 15 | 16 | |
12 | 9.60 | 9.32 | 9.09 | 9.00 | 9.15 | 9.08 |
13 | 8.91 | 8.71 | 8.45 | 8.25 | 8.35 | 8.31 |
14 | 8.64 | 8.43 | 8.16 | 7.96 | 7.97 | 7.96 |
15 | 9.06 | 8.13 | 7.88 | 7.62 | 7.71 | 7.68 |
16 | 9.41 | 8.70 | 7.94 | 7.78 | 7.66 | 7.67 |
17 | 10.49 | 8.85 | 8.25 | 7.77 | 7.69 | 7.64 |
Sample | Total | Average | Skewness | Kurtosis | S–W Inspection | K–S Inspection |
---|---|---|---|---|---|---|
ERROR | 16,108 | −0.075 | 0.427 | 4.453 | 0.942 (0.000 ***) | 0.067 (0.000 ***) |
Test Value | Total | Standard Deviation | T | P |
---|---|---|---|---|
0 | 16,108 | 0.427 | −1.398 | 0.162 |
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Xu, L.; Gao, M.; Zhang, Y.; Guo, J.; Lv, X.; Zhang, A. Oceanic Mesoscale Eddies Identification Using B-Spline Surface Fitting Model Based on Along-Track SLA Data. Remote Sens. 2022, 14, 5713. https://doi.org/10.3390/rs14225713
Xu L, Gao M, Zhang Y, Guo J, Lv X, Zhang A. Oceanic Mesoscale Eddies Identification Using B-Spline Surface Fitting Model Based on Along-Track SLA Data. Remote Sensing. 2022; 14(22):5713. https://doi.org/10.3390/rs14225713
Chicago/Turabian StyleXu, Luochuan, Miao Gao, Yaorong Zhang, Junting Guo, Xianqing Lv, and Anmin Zhang. 2022. "Oceanic Mesoscale Eddies Identification Using B-Spline Surface Fitting Model Based on Along-Track SLA Data" Remote Sensing 14, no. 22: 5713. https://doi.org/10.3390/rs14225713
APA StyleXu, L., Gao, M., Zhang, Y., Guo, J., Lv, X., & Zhang, A. (2022). Oceanic Mesoscale Eddies Identification Using B-Spline Surface Fitting Model Based on Along-Track SLA Data. Remote Sensing, 14(22), 5713. https://doi.org/10.3390/rs14225713