Clear-Air Turbulence (CAT) Identification with X-Band Dual Polarimetric Radar Based on Bayesian Approach
Abstract
:1. Introduction
2. Data and Methods
2.1. Instruments and Data
2.2. Methodology
2.2.1. Bayesian Approach for the Identification of CATs
2.2.2. The Prior Distribution of Polarimetric Parameters
2.2.3. Evaluation Metrics
3. Results
3.1. Verification by a Case Study
3.2. Performance of the Bayesian Method
3.3. Comparisons between Bayesian and Fuzzy Logic Method
4. Summary and Conclusions
- (1)
- The characteristics of CATs observed by the Beijing X-band polarimetric radar show that the high-frequency concentration area of turbulent echoes is within 15 km from radar. The P3 value of the total echo proportion of each range database is high. After the elimination of non-meteorological echoes, the P2 value of ME proportion is maintained within 16%, indicating that the filtering method of CAT echoes is good.
- (2)
- The Bayesian method can filter the edge of MEs with SNR < 15 dB. When the SNR of ME is < 15 dB, the values of Sd(Z), Sd(ZDR), Sd(ρHV), and Sd(ΦDP) are higher, causing it to filter out as a CAT.
- (3)
- Compared to traditional fuzzy-logic classification, the Performance of the Bayesian approach is slightly better in identifying the CATs.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Transmitting Frequency | 9.3–9.5 GHz (X-Band) |
---|---|
Wavelength | 3.2 cm |
Peak power | 70 kw |
Average Power | 112 w |
Max. Duty Cycle | 0.16% |
Antenna type (diameter) | Front-fed parabolic (2.4 m) |
3-dB beam width | 0.94° |
Polarization | Dual linear, H and V channel |
Range resolution | 75 m |
Maximum pulse width | 1 μs |
Variables | Z, V, W, ZDR, ρHV, KDP, ФDP, SNR |
Radars | N | Nb | Nf | Pb | Pf |
---|---|---|---|---|---|
Changping | 33612 | 373 | 977 | 98.8% | 97.1% |
Fangshan | 21856 | 143 | 494 | 99.3% | 97.7% |
Miyun | 26344 | 213 | 624 | 99.1% | 97.6% |
Shunyi | 27239 | 151 | 601 | 99.4% | 97.8% |
Tongzhou | 14335 | 224 | 605 | 98.4% | 95.8% |
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Ma, J.; Luo, L.; Chen, M.; Li, S. Clear-Air Turbulence (CAT) Identification with X-Band Dual Polarimetric Radar Based on Bayesian Approach. Atmosphere 2021, 12, 1691. https://doi.org/10.3390/atmos12121691
Ma J, Luo L, Chen M, Li S. Clear-Air Turbulence (CAT) Identification with X-Band Dual Polarimetric Radar Based on Bayesian Approach. Atmosphere. 2021; 12(12):1691. https://doi.org/10.3390/atmos12121691
Chicago/Turabian StyleMa, Jianli, Li Luo, Mingxuan Chen, and Siteng Li. 2021. "Clear-Air Turbulence (CAT) Identification with X-Band Dual Polarimetric Radar Based on Bayesian Approach" Atmosphere 12, no. 12: 1691. https://doi.org/10.3390/atmos12121691