Yuan Mei, Yin Honggang, Shang Jian, et al. Validation and evaluation of ocean calibration accuracy of FY-3G precipitation measurement radar. J Appl Meteor Sci, 2024, 35(5): 526-537. DOI:   10.11898/1001-7313.20240502.
Citation: Yuan Mei, Yin Honggang, Shang Jian, et al. Validation and evaluation of ocean calibration accuracy of FY-3G precipitation measurement radar. J Appl Meteor Sci, 2024, 35(5): 526-537. DOI:   10.11898/1001-7313.20240502.

Validation and Evaluation of Ocean Calibration Accuracy of FY-3G Precipitation Measurement Radar

DOI: 10.11898/1001-7313.20240502
  • Received Date: 2024-03-17
  • Rev Recd Date: 2024-05-06
  • Publish Date: 2024-09-30
  • FY-3G precipitation satellite launched in April 2023 is the first dedicated precipitation measurement satellite in China. The dual-frequency precipitation measurement radar (PMR) is the core instrument on the satellite. Because the backscattering performance of the vast ocean area is relatively stable, the calibration accuracy of the on-orbit radar can be tested by studying the backscattering cross-section of the sea surface. FY-3G PMR level 1 data in July 2023 and GPM DPR (global precipitation measurement, dual-frequency precipitation radar) level 2A data are used to analyze the mean value and mean square error of the global sea surface backscattering cross section under no-rain conditions to evaluate the radar performance. At the same time, the theoretical model of ocean surface backscattering is studied to simulate the sea surface backscattering cross-section under the condition of no rain, and the sea surface backscattering cross-section is compared with the actual radar measurement, so as to realize the preliminary evaluation of FY-3G PMR calibration accuracy. Furthermore, the accuracy of FY-3G PMR calibration is evaluated by the ocean calibration test results of GPM DPR data. Test results of ocean calibration accuracy show that when the incidence angle of FY-3G PMR Ku-band is less than 15°, the deviation between the observed value and the model simulation value is small. The deviation of FY-3G PMR ranges from 1.65 to 2.73 dB, while the standard deviation ranges from 0.74 to 1.82 dB. The deviation of FY-3G PMR Ka-band at an 18° incidence is less than 0.27 dB, and the standard deviation of the deviation is 3.49 dB. The calibration deviation of FY-3G PMR and GPM DPR is relatively constant, with the difference is primarily attributed to the backscattering statistical characteristics of the data itself. The stability of the backscattering data of FY-3G PMR Ku- and Ka-band sea surfaces at each incidence angle is comparable to that of GPM DPR. Gas attenuation is not considered at the moment. In the future, the impact of gas attenuation on the Ku- and Ka-band ocean calibration accuracy validation will be further evaluated, and the systematic deviation of FY-3G PMR will be corrected.
  • Fig. 1  Monthly mean of sea surface backscattering cross section in Jul 2023

    Fig. 2  Statistical histogram of sea surface backscattering cross section at 0° incidence angle of FY-3G PMR and GPM DPR in Jul 2023

    Fig. 3  Probability density of different sea surface backscattering intensity of FY-3G PMR and GPM DPR in Jul 2023

    Fig. 4  Mean square errors of monthly and orbit mean of sea surface backscattering cross section in Jul 2023

    Fig. 5  Ocean calibration results of FY-3G PMR and GPM DPR at different wind speed intervals in Jul 2023

    Table  1  Main performance indexes of FY-3G PMR

    参数 Ku波段 Ka波段
    工作中心频率 13.35 ± 0.01 GHz 35.55 ± 0.01 GHz
    极化 HH HH
    脉冲体制 短脉冲 短脉冲/脉冲压缩
    扫描方式 交轨方向一维扫描 交轨方向一维扫描
    距离方向观测范围 -5~18 km(海拔) -5~18 km(海拔)
    6 dB距离分辨率 ≤ 250 m ≤ 250 m
    单程3 dB波束宽度 0.7°±0.02° 0.7°±0.02°
    观测刈幅 300 km 300 km
    最小可检测降水强度 0.5 mm·h-1 (18 dBZ) 0.2 mm·h-1 (12 dBZ)
    辐射精度 ≤ ±1 dB (3σ) ≤ ±1 dB (3σ)
    DownLoad: Download CSV

    Table  1  Main performance indexes of FY-3G PMR

    参数 Ku波段 Ka波段
    工作中心频率 13.35 ± 0.01 GHz 35.55 ± 0.01 GHz
    极化 HH HH
    脉冲体制 短脉冲 短脉冲/脉冲压缩
    扫描方式 交轨方向一维扫描 交轨方向一维扫描
    距离方向观测范围 -5~18 km(海拔) -5~18 km(海拔)
    6 dB距离分辨率 ≤ 250 m ≤ 250 m
    单程3 dB波束宽度 0.7°±0.02° 0.7°±0.02°
    观测刈幅 300 km 300 km
    最小可检测降水强度 0.5 mm·h-1 (18 dBZ) 0.2 mm·h-1 (12 dBZ)
    辐射精度 ≤ ±1 dB (3σ) ≤ ±1 dB (3σ)
    DownLoad: Download CSV

    Table  1  Main performance indexes of FY-3G PMR

    参数 Ku波段 Ka波段
    工作中心频率 13.35 ± 0.01 GHz 35.55 ± 0.01 GHz
    极化 HH HH
    脉冲体制 短脉冲 短脉冲/脉冲压缩
    扫描方式 交轨方向一维扫描 交轨方向一维扫描
    距离方向观测范围 -5~18 km(海拔) -5~18 km(海拔)
    6 dB距离分辨率 ≤ 250 m ≤ 250 m
    单程3 dB波束宽度 0.7°±0.02° 0.7°±0.02°
    观测刈幅 300 km 300 km
    最小可检测降水强度 0.5 mm·h-1 (18 dBZ) 0.2 mm·h-1 (12 dBZ)
    辐射精度 ≤ ±1 dB (3σ) ≤ ±1 dB (3σ)
    DownLoad: Download CSV

    Table  2  FY-3G PMR and GPM DPR ocean calibration evaluation results (Ku-band typical incidence angle) in Jul 2023

    仪器 入射角/(°) 观测值/dB 模拟值/dB 平均偏差/dB 偏差标准差/dB
    FY-3G PMR -18 0.37 -2.37 2.74 3.20
    -15 3.72 2.07 1.65 1.82
    -10 9.33 7.63 1.70 1.68
    -5 12.04 10.36 1.68 0.74
    0 13.71 11.48 2.23 1.26
    5 12.77 10.36 2.41 0.74
    10 10.32 7.58 2.73 1.74
    15 4.62 2.06 2.55 1.82
    18 2.98 -2.38 5.36 3.17
    GPM DPR -18 -0.69 -3.39 2.70 3.41
    -15 2.65 1.39 1.26 2.08
    -10 7.98 7.39 0.59 2.27
    -5 11.45 10.39 1.06 1.24
    0 12.93 11.63 1.30 1.95
    5 11.53 10.45 1.09 1.21
    10 8.12 7.49 0.63 2.23
    15 2.67 1.54 1.13 2.10
    18 -0.58 -3.22 2.64 3.39
    DownLoad: Download CSV

    Table  2  FY-3G PMR and GPM DPR ocean calibration evaluation results (Ku-band typical incidence angle) in Jul 2023

    仪器 入射角/(°) 观测值/dB 模拟值/dB 平均偏差/dB 偏差标准差/dB
    FY-3G PMR -18 0.37 -2.37 2.74 3.20
    -15 3.72 2.07 1.65 1.82
    -10 9.33 7.63 1.70 1.68
    -5 12.04 10.36 1.68 0.74
    0 13.71 11.48 2.23 1.26
    5 12.77 10.36 2.41 0.74
    10 10.32 7.58 2.73 1.74
    15 4.62 2.06 2.55 1.82
    18 2.98 -2.38 5.36 3.17
    GPM DPR -18 -0.69 -3.39 2.70 3.41
    -15 2.65 1.39 1.26 2.08
    -10 7.98 7.39 0.59 2.27
    -5 11.45 10.39 1.06 1.24
    0 12.93 11.63 1.30 1.95
    5 11.53 10.45 1.09 1.21
    10 8.12 7.49 0.63 2.23
    15 2.67 1.54 1.13 2.10
    18 -0.58 -3.22 2.64 3.39
    DownLoad: Download CSV

    Table  2  FY-3G PMR and GPM DPR ocean calibration evaluation results (Ku-band typical incidence angle) in Jul 2023

    仪器 入射角/(°) 观测值/dB 模拟值/dB 平均偏差/dB 偏差标准差/dB
    FY-3G PMR -18 0.37 -2.37 2.74 3.20
    -15 3.72 2.07 1.65 1.82
    -10 9.33 7.63 1.70 1.68
    -5 12.04 10.36 1.68 0.74
    0 13.71 11.48 2.23 1.26
    5 12.77 10.36 2.41 0.74
    10 10.32 7.58 2.73 1.74
    15 4.62 2.06 2.55 1.82
    18 2.98 -2.38 5.36 3.17
    GPM DPR -18 -0.69 -3.39 2.70 3.41
    -15 2.65 1.39 1.26 2.08
    -10 7.98 7.39 0.59 2.27
    -5 11.45 10.39 1.06 1.24
    0 12.93 11.63 1.30 1.95
    5 11.53 10.45 1.09 1.21
    10 8.12 7.49 0.63 2.23
    15 2.67 1.54 1.13 2.10
    18 -0.58 -3.22 2.64 3.39
    DownLoad: Download CSV

    Table  3  FY-3G PMR and GPM DPR ocean calibration evaluation results (Ka-band typical incidence angle) in Jul 2023

    仪器 入射角/(°) 观测值/dB 模拟值/dB 平均偏差/dB 偏差标准差/dB
    FY-3G PMR -18 -3.59 -2.30 -1.29 3.51
    -15 -0.45 2.06 -2.51 2.00
    -10 4.83 7.63 -2.80 2.02
    -5 8.28 10.38 -2.10 1.02
    0 9.52 11.49 -1.97 1.57
    5 8.86 10.38 -1.52 1.02
    10 5.33 7.62 -2.29 2.01
    15 1.13 2.13 -1.00 2.01
    18 -1.98 -2.25 0.27 3.49
    GPM DPR -18 -1.72 -2.85 1.13 3.40
    -15 1.56 1.73 -0.17 1.99
    -10 6.94 7.46 -0.52 2.04
    -5 10.09 10.32 -0.23 1.04
    0 11.21 11.47 -0.26 1.46
    5 10.15 10.35 -0.20 1.03
    10 6.90 7.51 -0.61 2.02
    15 1.72 1.81 -0.09 1.98
    18 -1.44 -2.77 1.33 3.36
    DownLoad: Download CSV

    Table  3  FY-3G PMR and GPM DPR ocean calibration evaluation results (Ka-band typical incidence angle) in Jul 2023

    仪器 入射角/(°) 观测值/dB 模拟值/dB 平均偏差/dB 偏差标准差/dB
    FY-3G PMR -18 -3.59 -2.30 -1.29 3.51
    -15 -0.45 2.06 -2.51 2.00
    -10 4.83 7.63 -2.80 2.02
    -5 8.28 10.38 -2.10 1.02
    0 9.52 11.49 -1.97 1.57
    5 8.86 10.38 -1.52 1.02
    10 5.33 7.62 -2.29 2.01
    15 1.13 2.13 -1.00 2.01
    18 -1.98 -2.25 0.27 3.49
    GPM DPR -18 -1.72 -2.85 1.13 3.40
    -15 1.56 1.73 -0.17 1.99
    -10 6.94 7.46 -0.52 2.04
    -5 10.09 10.32 -0.23 1.04
    0 11.21 11.47 -0.26 1.46
    5 10.15 10.35 -0.20 1.03
    10 6.90 7.51 -0.61 2.02
    15 1.72 1.81 -0.09 1.98
    18 -1.44 -2.77 1.33 3.36
    DownLoad: Download CSV

    Table  3  FY-3G PMR and GPM DPR ocean calibration evaluation results (Ka-band typical incidence angle) in Jul 2023

    仪器 入射角/(°) 观测值/dB 模拟值/dB 平均偏差/dB 偏差标准差/dB
    FY-3G PMR -18 -3.59 -2.30 -1.29 3.51
    -15 -0.45 2.06 -2.51 2.00
    -10 4.83 7.63 -2.80 2.02
    -5 8.28 10.38 -2.10 1.02
    0 9.52 11.49 -1.97 1.57
    5 8.86 10.38 -1.52 1.02
    10 5.33 7.62 -2.29 2.01
    15 1.13 2.13 -1.00 2.01
    18 -1.98 -2.25 0.27 3.49
    GPM DPR -18 -1.72 -2.85 1.13 3.40
    -15 1.56 1.73 -0.17 1.99
    -10 6.94 7.46 -0.52 2.04
    -5 10.09 10.32 -0.23 1.04
    0 11.21 11.47 -0.26 1.46
    5 10.15 10.35 -0.20 1.03
    10 6.90 7.51 -0.61 2.02
    15 1.72 1.81 -0.09 1.98
    18 -1.44 -2.77 1.33 3.36
    DownLoad: Download CSV
  • [1]
    McKee J L, Binns A D. A review of gauge-radar merging methods for quantitative precipitation estimation in hydrology. Canadian Water Resources Journal/Revue Canadienne Des Ressources Hydriques, 2016, 41(1/2): 186-203.
    [2]
    Trenberth K E, Smith L, Qian T T, et al. Estimates of the global water budget and its annual cycle using observational and model data. J Hydrometeorol, 2007, 8(4): 758-769. doi:  10.1175/JHM600.1
    [3]
    Li Q K. Research on the Algorithm of Three-Dimensional Precipitation Structure Inversion with GPM/DPR and CINRAD Data. Hefei: University of Science and Technology of China, 2021.
    [4]
    Jiang Y F, Kou L L, Chen A J, et al. Comparison of reflectivity factor of dual polarization radar and dual-frequency precipitation radar. J Appl Meteor Sci, 2020, 31(5): 608-619. doi:  10.11898/1001-7313.20200508
    [5]
    Dong G H, Liu L P. Correlation analysis on estimating rainfall using radar-rain gauge calibration. J Appl Meteor Sci, 2012, 23(1): 30-39. doi:  10.3969/j.issn.1001-7313.2012.01.004
    [6]
    Zhou B X, Zhu L F, Wu H, et al. Accuracy of atmospheric profiles retrieved from microwave radiometer and its application to precipitation forecast. J Appl Meteor Sci, 2023, 34(6): 717-728. doi:  10.11898/1001-7313.20230607
    [7]
    Wang H, Zhou H F, Wang C, et al. Accuracy validation of FY-4A temperature profile based on microwave radiometer and radiosonde. J Appl Meteor Sci, 2023, 34(3): 295-308. doi:  10.11898/1001-7313.20230304
    [8]
    Li R. Study on Structure Characteristics of Tropical Precipitation and Passive Microwave Retrieval of Precipitation with TRMM Rain Measuring Radar. Hefei: University of Science and Technology of China, 2005.
    [9]
    Wang C G. Research on Precipitation Detection by TRMM PR and Precipitation Estimation by Weather Radar. Nanjing: Nanjing University, 2003.
    [10]
    Mao D Y, Cheng M H. Study on Typhoon Sam in 1999 with TRMM data. Meteor Sci Technol, 2001, 29(2): 37-40. doi:  10.3969/j.issn.1671-6345.2001.02.005
    [11]
    Wen J Q, Wang G L, Zhou R R, et al. Vertical structure characteristics of precipitation in Mêdog area of southeastern Tibet during the monsoon period. J Appl Meteor Sci, 2023, 34(5): 562-573. doi:  10.11898/1001-7313.20230505
    [12]
    Fu Y F, Yu R C, Xu Y P, et al. Analysis on precipitation structures of two heavy rain cases by using TRMM PR and IMI. Acta Meteor Sinica, 2003, 61(4): 421-431. doi:  10.3321/j.issn:0577-6619.2003.04.004
    [13]
    Li W B, Chen Y, Zhu Y J, et al. Retrieval of rain over land by using TRMM/TMI measurements. Acta Meteor Sinica, 2001, 59(5): 591-601. doi:  10.3321/j.issn:0577-6619.2001.05.009
    [14]
    Shang J, Guo Y, Wu Q, et al. Airborne field campaign results of Ka-band precipitation measuring radar in China. J Appl Meteor Sci, 2011, 22(5): 590-596. doi:  10.3969/j.issn.1001-7313.2011.05.009
    [15]
    Wu Q M, Cheng M H, Miao C S. Study of microwave characteristics of rainfall over South China and Yangtze River Basin using TRMM data. J Appl Meteor Sci, 2003, 14(2): 206-214. doi:  10.3969/j.issn.1001-7313.2003.02.008
    [16]
    Chiu L, Serafino G, Teng W L. Applications of Tropical Rainfall Measuring Mission(TRMM) Data//IGARSS 2001. Scanning the Present and Resolving the Future. IEEE 2001 International Geoscience and Remote Sensing Symposium. Sydney, NSW, Australia. IEEE, 2001: 2118-2120.
    [17]
    Chiu L S, Liu Z, Rui H L, et al. Tropical Rainfall Measuring Mission Data and Access Tools//Earth Science Satellite Remote Sensing. Berlin, Heidelberg: Springer, 2006: 202-219.
    [18]
    Kojima M, Miura T, Furukawa K, et al. Dual-frequency Precipitation radar(DPR) Development on the Global Precipitation Measurement(GPM) Core Observatory//Earth Observing Missions and Sensors: Development, Implementation, and Characterization Ⅱ. Kyoto, Japan. SPIE, 2012, 8528: 234-243.
    [19]
    Masaki T, Kubota T, Oki R, et al. Current status of GPM/DPR Level 1 Algorithm Development and DPR Calibration//2015 IEEE International Geoscience and Remote Sensing Symposium(IGARSS). Milan, Italy. IEEE, 2015: 2615-2618.
    [20]
    Zhang P, Gu S, Chen L, et al. FY-3G satellite instruments and precipitation products: First report of China's Fengyun rainfall mission in-orbit. J Remote Sensing, 2023, 3. DOI:  10.34133/remotesensing.0097.
    [21]
    Shang J, Yang H, Yin H G, et al. Performance analysis of China dual-frequency airborne precipitation radar. IEEE Aerosp Electron Syst Mag, 2013, 28(4): 16-27. doi:  10.1109/MAES.2013.6506825
    [22]
    Hossan A, Jones W L. Ku- and Ka-band ocean surface radar backscatter model functions at low-incidence angles using full-swath GPM DPR data. Remote Sens, 2021, 13(8). DOI:  10.3390/rs13081569.
    [23]
    Barrick D. Wind dependence of quasi-specular microwave sea scatter. IEEE Trans Anntenas Propag, 1974, 22(1): 135-136. doi:  10.1109/TAP.1974.1140736
    [24]
    Brown G S. Quasi-specular Scattering from the Air-sea IKnterface//Geernaert G L, Plant W L. Surface Waves and Fluxes. Dordrecht: Springer, 1990: 1-39.
    [25]
    Freilich M H, Vanhoff B A. The relationship between winds, surface roughness, and radar backscatter at low incidence angles from TRMM precipitation radar measurements. J Atmos Oceanic Technol, 2003, 20(4): 549-562. doi:  10.1175/1520-0426(2003)20<549:TRBWSR>2.0.CO;2
    [26]
    Tanelli S, Durden S L, Im E. Simultaneous measurements of Ku- and Ka-band sea surface cross sections by an airborne Radar. IEEE Geosci Remote Sens Lett, 2006, 3(3): 359-363. doi:  10.1109/LGRS.2006.872929
    [27]
    Valenzuela G R. Theories for the interaction of electromagnetic and oceanic waves-A review. Bound Layer Meteor, 1978, 13(1): 61-85.
    [28]
    Liao M, Zhang P, Liu J, et al. Accuracy and stability of radio occultation dry temperature profiles from Fengyun satellites. J Appl Meteor Sci, 2023, 34(3): 270-281. doi:  10.11898/1001-7313.20230302
    [29]
    Xing C Y, Wu S A, Zhu J J. Comparison on the circulation background of tropical cyclone affecting the South China Sea based upon different reanalysis datasets. J Appl Meteor Sci, 2023, 34(2): 179-192. doi:  10.11898/1001-7313.20230205
    [30]
    Yang R F, Yu Y, Li L H, et al. Characteristics of surface NRCS and the effect on the spaceborne precipitation radar system design. J Electron Inf Technol, 2013, 35(11): 2721-2727.
    [31]
    Holliday D, St-Cyr G, Woods N E. A radar ocean imaging model for small to moderate incidence angles. Int J Remote Sens, 1986, 7(12): 1809-1834. doi:  10.1080/01431168608948971
    [32]
    Liu Q H, Weng F Z, English S J. An improved fast microwave water emissivity model. IEEE Trans Geosci Remote Sens, 2011, 49(4): 1238-1250. doi:  10.1109/TGRS.2010.2064779
    [33]
    Stephen J, Hewison T J. A Fast Generic Millimetre-wave Emissivity Model//Proc of SPIE, 1998, 3503. DOI: 10.1117/12.319490.
    [34]
    Wu J. Mean square slopes of the wind-disturbed water surface, their magnitude, directionality, and composition. Radio Sci, 1990, 25(1): 37-48. doi:  10.1029/RS025i001p00037
    [35]
    Nouguier F, Mouche A, Rascle N, et al. Analysis of dual-frequency ocean backscatter measurements at Ku- and Ka-bands using near-nadir incidence GPM radar data. IEEE Geosci Remote Sens Lett, 2016, 13(9): 1310-1314. doi:  10.1109/LGRS.2016.2583198
    [36]
    Walsh E, Vandemark D, Friehe C, et al. Measuring sea surface mean square slope with a 36-GHz scanning. J Geophys Res Atmos, 1998, 1031(C6): 12613-12628.
  • 加载中
  • -->

Catalog

    Figures(5)  / Tables(9)

    Article views (422) PDF downloads(48) Cited by()
    • Received : 2024-03-17
    • Accepted : 2024-05-06
    • Published : 2024-09-30

    /

    DownLoad:  Full-Size Img  PowerPoint