Comparison of Reflectivity Factor of Dual Polarization Radar and Dual-frequency Precipitation Radar

Jiang Yinfeng; Kou Leilei; Chen Aijun; Wang Zhenhui; Chu Zhigang; Hu Hanfeng

doi:10.11898/1001-7313.20200508

Vol.31, NO.5, 2020

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Jiang Yinfeng, Kou Leilei, Chen Aijun, 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.

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Jiang Yinfeng, Kou Leilei, Chen Aijun, 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.

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Comparison of Reflectivity Factor of Dual Polarization Radar and Dual-frequency Precipitation Radar

DOI: 10.11898/1001-7313.20200508

1.
School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044
2.
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044

Received Date: 2020-04-15
Rev Recd Date: 2020-06-15
Publish Date: 2020-09-30

Abstract

Abstract

To find the root cause of the difference between spaceborne radar and ground-based radar data, their similarities and differences are quantitatively analyzed using GPM (Global Precipitation Measurement Mission) DPR (dual-frequency precipitation radar) and C-band dual-polarization radar (CDP) at Nanjing University of Information Science & Technology with respect to reflectivity factor classification of hydrometeor types by spatial-temporal matchup. The comparison reveals a high correlation of 0.86 between reflectivity factor detected by GPM DPR and CDP from 2015 to 2017 and a small root mean square error(RMSE) of 3.33 dB after attenuation correction and band correction, and the correlation passes the test of 0.001 level. The band correction formulas for detecting different hydrometeors reflectivity factor in C- and Ku-band are fitted by T-matrix method, applied the formula of dry snow to dry snow and graupel, applied the formula of wet snow is applicable to wet snow and rain hail, applied the formula of water to moderate rain, applied big drop and heavy rain and the band correction formula of ice to ice crystal. Band correction is carried out for different hydrometeors echoes after attenuation correction, the echo consistency of wet snow, graupel, big drops and moderate rain is well, and the correlation coefficient is over 0.85, the RMSE is less than 4 dB and echo differences of wet snow, graupel, big drops and moderate rain are small. The echo correlation coefficient of dry snow is relatively less than 0.8 due to the complex shape of dry snow which leads to difference between horizontal and vertical directions of CDP and difference between Mie scattering simulation and actual situation of dry snow, and further study on simulation of dry snow reflectivity factor is deserved. Due to the detection resolution of DPR and insufficient effective irradiation volume of CDP, the echo correlation coefficient of heavy rain and ice crystal is less than 0.4, and the reflectivity factor of heavy rain and ice crystal detected by DPR is less than CDP. The difference of reflectivity factor between DPR and CDP is mainly caused by dry snow, heavy rain and ice crystal. The amount of band correction is less than the amount of attenuation correction, then attenuation is the main factor. Band correction improves the matching situation on the basis of attenuation correction. NS mode and HS mode in DPR are different. NS mode can detect high reflectivity factor and is sensitive to strong echo, but is weak in detecting small reflectivity factor, while HS mode can detect small reflectivity factor and is sensitive to weak echo, but is weak in detecting high reflectivity factor.
- GPM DPR;
- spatial-temporal matchup;
- classification of hydrometeor types;
- band correction;
- reflectivity factor difference

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References(28)

Figures and Tables

Fig. 1 Scatter plot and difference scatter plot of reflectivity factor of DPR and GR

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Fig. 2 Z, Z_DR, ρ, hydrometeor distribution of CDP at NUIST with different degrees at 0025 UTC 26 Oct 2016(the distance between adjacent range rings is 30 km)

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Fig. 3 D_FR of different hydrometeors varing with Z_Ku

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Fig. 4 Scatter plot and probability density function of different hydrometeors after band correction

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Fig. 5 Curves of statistical parameters of different hydrometeors after band correction

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Table 1 Distribution of hydrometeors

高度	水凝物类型
低于零度层亮带底部	中雨、大滴、大雨、雨雹混合物
零度层亮带底部—零度层亮带	湿雪、霰、中雨、大滴、大雨、雨雹混合物
零度层亮带—零度层亮带顶部	干雪、湿雪、霰、冰晶、大滴、雨雹混合物
高于零度层亮带顶部	干雪、霰、冰晶、雨雹混合物

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Table 2 Fitted curve coefficients

类别	a₀	a₁	a₂	a₃	a₄	a₅
冰	0.0120	0.0111	-0.0020	6.8441×10^-5	-7.8862×10^-7	3.0245×10^-9
水	-0.0377	0.0530	-0.0020	-7.5728×10^-7	1.5135×10^-7
湿雪	0.0165	-0.0189		-4.2491×10^-5	2.4098×10^-7
干雪	0.0088	-0.1131	0.0077	-1.9627×10^-4	2.2309×10^-6	-9.3026×10^-9

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