A Prior Knowledge-Enhanced Deep Learning Framework for Improved Thermospheric Mass Density Prediction
Abstract
:1. Introduction
2. Data and Methods
2.1. Data Description
2.2. Deep Learning Model
2.3. DL Model Performance Evaluation
3. Results and Discussions
3.1. Convergence and Feature Extraction Performance During Training
3.2. Evaluation of DL Models on Test Data
3.3. Generalization of DL Models for TMD Prediction at Different Altitudes
3.4. Evaluating DL Models for Capturing Horizontal Variations in TMD
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Parameter Name | Parameter Value |
---|---|
Input 1–2: Local Solar Time (LST), in hours (h) | |
Input 3–4: Day of Year (DoY) | |
Input 5–6: Latitude (Lat), in degrees (°) | |
Input 7: Altitude (Alt), in kilometers (km) | |
Input 8–9: F10.7 and F10.7a, in solar flux units (sfu) | |
Input 10–16: SYM-H (with the historical information), in nanoteslas (nT) | |
Input 17–23: AE (with the historical information), in nanoteslas (nT) | |
), in kg/m3 | |
Out: Thermospheric Mass Density (TMD), in kg/m3 |
Model | Basic Environmental Parameters | Geomagnetic Indices | MSIS Density Added |
---|---|---|---|
ResNet | LST, DoY, Lat, Alt, F10.7, F10.7a | SYM-H, AE (with the historical information) | No |
ResNet-MSIS | LST, DoY, Lat, Alt, F10.7, F10.7a | SYM-H, AE (with the historical information) | Yes |
Model | Condition | Slope (k Value) | Corr | kg/m3) |
---|---|---|---|---|
ResNet-MSIS_relu | Overall | 0.9415 | 0.9078 | 0.2959 |
High solar (F10.7 > 150) | 0.7713 | 0.8444 | 0.3218 | |
Low solar (F10.7 < 100) | 0.5901 | 0.7408 | 0.2994 | |
ResNet_relu | Overall | 0.7456 | 0.8802 | 0.3352 |
High solar (F10.7 > 150) | 0.6937 | 0.8000 | 0.3885 | |
Low solar (F10.7 < 100) | 0.4190 | 0.8269 | 0.3240 | |
MSIS | Overall | 1.0187 | 0.9621 | 0.0891 |
High solar (F10.7 > 150) | 0.9508 | 0.9012 | 0.2095 | |
Low solar (F10.7 < 100) | 0.8991 | 0.9063 | 0.0605 |
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Li, L.; He, C.; Zheng, D.; Li, S.; Zhao, D. A Prior Knowledge-Enhanced Deep Learning Framework for Improved Thermospheric Mass Density Prediction. Atmosphere 2025, 16, 539. https://doi.org/10.3390/atmos16050539
Li L, He C, Zheng D, Li S, Zhao D. A Prior Knowledge-Enhanced Deep Learning Framework for Improved Thermospheric Mass Density Prediction. Atmosphere. 2025; 16(5):539. https://doi.org/10.3390/atmos16050539
Chicago/Turabian StyleLi, Ling, Changyong He, Dunyong Zheng, Shaoning Li, and Dong Zhao. 2025. "A Prior Knowledge-Enhanced Deep Learning Framework for Improved Thermospheric Mass Density Prediction" Atmosphere 16, no. 5: 539. https://doi.org/10.3390/atmos16050539
APA StyleLi, L., He, C., Zheng, D., Li, S., & Zhao, D. (2025). A Prior Knowledge-Enhanced Deep Learning Framework for Improved Thermospheric Mass Density Prediction. Atmosphere, 16(5), 539. https://doi.org/10.3390/atmos16050539