Case Study of a Retrieval Method of 3D Proxy Reflectivity from FY-4A Lightning Data and Its Impact on the Assimilation and Forecasting for Severe Rainfall Storms
Abstract
:1. Introduction
2. Lightning Data Detected by FY-4A LMI
3. Retrieval Methods
3.1. Lightning Density
3.2. Proxy Radar Reflectivity Retrieval
3.2.1. Proxy Maximum Radar Reflectivity
3.2.2. D FY-4A Proxy Reflectivity
4. Lighting Assimilation Experiments Compared with Radar Assimilation
4.1. Experiments Set Up
4.2. The Rainfall Case
4.3. Results
4.3.1. Rainfall Forecast Skill Scores
4.3.2. Precipitation Distribution
4.3.3. Analysis Increments of Hydrometers
4.3.4. Convective Available Potential Energy
5. Lighting Assimilation Experiments in Mountainous Areas
5.1. Experiments Set Up
5.2. The Rainfall Case in Mountainous Areas
5.3. Results
5.3.1. Precipitation Distribution
5.3.2. Diagnosis
5.3.3. Rainfall Forecast Skill Scores
6. Discussion
7. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Cases | Start Time (time,date,year) | End Time (time,date,year) | Duration/h |
---|---|---|---|
1 | 1100UTC, 13 July 2017 | 2100UTC, 13 July 2017 | 10 |
2 | 1400UTC, 14 July 2017 | 2300UTC, 14 July 2017 | 9 |
3 | 1700UTC, 18 July 2017 | 2300UTC, 18 July 2017 | 6 |
4 | 1200UTC, 2 August 2017 | 0000UTC, 3 August 2017 | 12 |
5 | 0400UTC, 5 August 2017 | 1400UTC, 5 August 2017 | 10 |
6 | 0600UTC, 8 August 2017 | 2100UTC, 8 August 2017 | 15 |
POD | 1000 | 2000 | 3000 | 4000 | 5000 | 6000 | 7000 | 8000 | 9000 | 10,000 |
0-35dBZ | 0.43 | 0.31 | 0.17 | 0.16 | 0.22 | 0.41 | 0.45 | 0.49 | 0.62 | 0.65 |
35-80dBZ | 0.49 | 0.49 | 0.63 | 0.64 | 0.64 | 0.58 | 0.59 | 0.39 | 0.17 | 0.11 |
BIAS | 1000 | 2000 | 3000 | 4000 | 5000 | 6000 | 7000 | 8000 | 9000 | 10,000 |
0-35dBZ | 1.33 | 1.23 | 0.89 | 0.77 | 0.90 | 0.90 | 0.86 | 0.86 | 0.89 | 0.91 |
35-80dBZ | 0.71 | 0.89 | 2.19 | 2.02 | 1.63 | 1.51 | 2.78 | 1.54 | 1.44 | 1.50 |
Model network | D01: 649 × 500 × 50, 9 km horizontal resolution (covering the mainland China region) D02: 550 × 424 × 50, 3 km horizontal resolution (covering the North China region) |
Model version | WRFDAV3.8.1 + WRFV3.8.1 |
Data assimilation | Method: 3DVAR Data resource: GTS data, observation of automatic station in the Beijing area, ground-based GNSS/ZTD in North China, radar observation of 7 Doppler weather radars in the Beijing-Tianjin-Hebei region (D02) |
Physical scheme | Boundary layer scheme: ACM2 Microphysical scheme: Thompson Long wave scheme: RRTMG Land-surface model scheme: NOAH Convection parameterization scheme: Kain–Fritsch (D01) |
Experiment Name | Additional Data for Assimilation | Initial and Boundary Conditions |
---|---|---|
CTRL | No additional data | RMAPS-ST |
RADAR_RV | Radar radial velocity | RMAPS-ST |
RADAR_RF_RV | Radar radial velocity + Radar reflectivity | RMAPS-ST |
FLASH_RF_RV | Radar radial velocity + 3D proxy reflectivity | RMAPS-ST |
Threshold: 1.5 mm | 0-1 | 1-2 | 2-3 | 3-4 | 4-5 | 5-6 |
RADAR_RV | 0.931 | 3.212 ** | 0.426 | 0.586 | 1.620 * | 1.519 |
RADAR_RF_RV | 0.791 | 4.223 ** | 7.020 ** | 3.001 ** | 1.066 | 2.067 * |
FLASH_RF_RV | 1.440 | 3.651 ** | 3.073 ** | 4.524 ** | 0.711 | 1.881 * |
Threshold: 7.0 mm | 0-1 | 1-2 | 2-3 | 3-4 | 4-5 | 5-6 |
RADAR_RV | 0.008 | 6.129 ** | 1.135 | 0.489 | 1.208 | 1.786 * |
RADAR_RF_RV | 3.618 ** | 3.454 ** | 1.164 | 1.007 | 1.837 * | 6.568 ** |
FLASH_RF_RV | 3.113 ** | 1.871 * | 0.335 | 1.125 | 2.545 ** | 7.329 ** |
Threshold: 15.0 mm | 0-1 | 1-2 | 2-3 | 3-4 | 4-5 | 5-6 |
RADAR_RV | 1.348 | 0.124 | 0.704 | 0.751 | 1.075 | 1.377 |
RADAR_RF_RV | 5.014 ** | 1.329 | 1.194 | 1.419 | 4.612 ** | 4.085 ** |
FLASH_RF_RV | 4.484 ** | 0.879 | 1.163 | 1.371 | 3.863 ** | 3.438 ** |
Threshold: 50.0 mm | 0-1 | 1-2 | 2-3 | 3-4 | 4-5 | 5-6 |
RADAR_RV | 1.664 * | 0.613 | 0.411 | 0.227 | 0.212 | 1.083 |
RADAR_RF_RV | 3.585 ** | 0.260 | 0.410 | 1.064 | 3.179 ** | 3.120 ** |
FLASH_RF_RV | 2.683 ** | 0.251 | 0.118 | 1.485 | 4.924 ** | 3.585 ** |
Experiment Name | Data for Assimilation | Domain | Time Interval |
---|---|---|---|
CTRL | - | - | - |
CONV | Conventional observations | D01 + D02 | 6 h |
CONV_FLASH | Conventional observations + 3D FY-4A proxy reflectivity | D01 + D02/D02 | 6 h/3 h |
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Chen, Y.; Yu, Z.; Han, W.; He, J.; Chen, M. Case Study of a Retrieval Method of 3D Proxy Reflectivity from FY-4A Lightning Data and Its Impact on the Assimilation and Forecasting for Severe Rainfall Storms. Remote Sens. 2020, 12, 1165. https://doi.org/10.3390/rs12071165
Chen Y, Yu Z, Han W, He J, Chen M. Case Study of a Retrieval Method of 3D Proxy Reflectivity from FY-4A Lightning Data and Its Impact on the Assimilation and Forecasting for Severe Rainfall Storms. Remote Sensing. 2020; 12(7):1165. https://doi.org/10.3390/rs12071165
Chicago/Turabian StyleChen, Yaodeng, Zheng Yu, Wei Han, Jing He, and Min Chen. 2020. "Case Study of a Retrieval Method of 3D Proxy Reflectivity from FY-4A Lightning Data and Its Impact on the Assimilation and Forecasting for Severe Rainfall Storms" Remote Sensing 12, no. 7: 1165. https://doi.org/10.3390/rs12071165