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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

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Front. Earth Sci.    2022, Vol. 16 Issue (2) : 248-264    https://doi.org/10.1007/s11707-021-0883-z
RESEARCH ARTICLE
A rain-type adaptive optical flow method and its application in tropical cyclone rainfall nowcasting
Jiakai ZHU1, Jianhua DAI2()
1. Shanghai Meteorological Information and Technological Support Center, China Meteorological Administration, Shanghai 200030, China
2. Shanghai Central Meteorological Observatory, China Meteorological Administration, Shanghai 200030, China
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Abstract

A rain-type adaptive pyramid Kanade–Lucas–Tomasi (A-PKLT) optical flow method for radar echo extrapolation is proposed. This method introduces a rain-type classification algorithm that can classify radar echoes into six types: convective, stratiform, surrounding convective, isolated convective core, isolated convective fringe, and weak echoes. Then, new schemes are designed to optimize specific parameters of the PKLT optical flow based on the rain type of the echo. At the same time, the gradients of radar reflectivity in the fringe positions corresponding to all types of rain echoes are increased. As a result, corner points that are characteristic points used for PKLT optical flow tracking in the surrounding area will be increased. Therefore, more motion vectors are purposefully obtained in the whole radar echo area. This helps to describe the motion characteristics of the precipitation more precisely. Then, the motion vectors corresponding to each type of rain echo are merged, and a denser motion vector field is generated by an interpolation algorithm on the basis of merged motion vectors. Finally, the dense motion vectors are used to extrapolate rain echoes into 0–60-min nowcasts by a semi-Lagrangian scheme. Compared with other nowcasting methods for four landfalling typhoons in or near Shanghai, the new optical flow method is found to be more accurate than the traditional cross-correlation and optical flow methods, particularly showing a clear improvement in the nowcasting of convective echoes on the spiral rainbands of typhoons.
Keywords optical flow method      radar echo classification      adaptive      typhoon      nowcasting     
Corresponding Author(s): Jianhua DAI   
About author: Tongcan Cui and Yizhe Hou contributed equally to this work.
Online First Date: 01 June 2021    Issue Date: 26 August 2022
 Cite this article:   
Jiakai ZHU,Jianhua DAI. A rain-type adaptive optical flow method and its application in tropical cyclone rainfall nowcasting[J]. Front. Earth Sci., 2022, 16(2): 248-264.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-021-0883-z
https://academic.hep.com.cn/fesci/EN/Y2022/V16/I2/248
Fig.1  Schematic flow diagram of the A-PKLT optical flow radar echo extrapolation method. The procedure of traditional PKLT optical flow method is shown in the dashed rectangle.
Typhoon Name (ID) Ampil (1810) Jongdari (1812) Rumbia (1818) Lekima (1909)
Landfall date/Time 22 July, 2018
0430 UTC		 03 August, 2018
0335 UTC		 16 August, 2018
2005 UTC		 9 August, 2019
1745 UTC
Landfall location Chongming, Shanghai Jinshan,
Shanghai		 Pudong,
Shanghai		 Wenling,
Zhejiang
Landfall center Pressure/hPa 982 988 982 930
Landfall max wind speed/(m·s-1) 28 23 23 52
Max rainfall in Shanghai/mm 118.1 104.4 154.4 276.1
Max hourly rainfall in Shanghai/mm 46.5 29.1 46.6 112.2
Data period 1107 UTC 21 Jul
1759 UTC 22 Jul		 0204 UTC 02 Aug
1055 UTC 03 Aug		 0030 UTC 16 Aug
1706 UTC 17 Aug		 0000 UTC 9 Aug
0000 UTC 11 Aug
Radar scans 317 356 407 481
Tab.1  Summary of typhoon cases
Fig.2  0600-0700 UTC 1-h rainfall (a) and 0500–0800 UTC 3-h rainfall (b) in Shanghai on 10 August, 2019.
Fig.3  Nanhui radar 0.5° elevation angle reflectivity (dBZ, color shading) images from 0609 UTC on 9 August, to 1210 UTC on 10 August, 2019.
Fig.4  Diagram of declustering of the corner points in one box.
Fig.5  Nanhui radar reflectivity (dBZ, color shading) at a 0.5° elevation angle at 1259 UTC 9 August, 2019, overlaid with motion vectors (blue arrows) from (a) the PKLT and (b) A-PKLT optical flow methods. More motion vectors are captured in the interior areas of two spiral rainbands of Typhoon Lekima using the A-PKLT method than the traditional PKLT method.
Fig.6  Mean CSI scores of 6–60-min (lead time) nowcasts at 20–55 dBZ reflectivity levels based on the A-PKLT, PKLT, and TREC methods for four typhoon cases: a) Ampil, b) Jongdari, c) Rumbia, and d) Lekima.
Fig.7  Nanhui radar (a) reflectivity (dBZ, color shading) at a 0.5° elevation angle at 0027 UTC 22 July, 2018 and the 60-min reflectivity extrapolation at this time of (b) TREC, (c) PKLT, and (d) A-PKLT for Typhoon Ampil.
Fig.8  (a) Nanhui radar reflectivity (dBZ, color shading) at a 0.5° elevation angle at 1634 UTC on 2 August, 2018 for Typhoon Jongdari and (b) Qingpu radar reflectivity at a 0.5° elevation angle at 0130 UTC on 17 August, 2018 for Typhoon Rumbia.
Lead time min 20
dBZ		 25
dBZ		 30
dBZ		 35
dBZ		 40
dBZ		 45
dBZ		 50
dBZ		 55
dBZ		 Mean
6 0.85 0.81 0.75 0.64 0.49 0.36 0.19 0.08 0.52
12 0.80 0.76 0.68 0.57 0.41 0.27 0.13 0.04 0.46
18 0.77 0.71 0.64 0.51 0.35 0.22 0.09 0.03 0.42
24 0.73 0.68 0.60 0.47 0.31 0.18 0.07 0.02 0.38
30 0.71 0.65 0.56 0.44 0.27 0.15 0.05 0.01 0.36
36 0.68 0.62 0.53 0.40 0.24 0.13 0.04 0.01 0.33
42 0.66 0.60 0.50 0.38 0.22 0.11 0.03 0.01 0.31
48 0.64 0.57 0.48 0.35 0.20 0.10 0.03 0.00 0.30
54 0.61 0.55 0.45 0.33 0.18 0.08 0.02 0.00 0.28
60 0.59 0.53 0.43 0.30 0.17 0.08 0.02 0.00 0.27
Mean 0.70 0.65 0.56 0.44 0.28 0.17 0.07 0.02 0.36
Tab.2  Average CSI of the A-PKLT 6~60-min reflectivity nowcasts for Typhoon Lekima during 0011 UTC 9 August, – 0010 UTC 11 August, 2019
Fig.9  Same as in Fig. 7 but for Typhoon Lekima at 0641 UTC on 10 August, 2019.
Lead time min 20
dBZ		 25
dBZ		 30
dBZ		 35
dBZ		 40
dBZ		 45
dBZ		 50
dBZ		 55
dBZ		 Mean
6 0.00 0.01 0.01 0.02 0.04 0.05 0.03 0.02 0.02
12 0.00 0.01 0.01 0.03 0.05 0.06 0.04 0.01 0.03
18 0.01 0.00 0.02 0.02 0.05 0.06 0.02 0.01 0.02
24 0.00 0.01 0.02 0.02 0.05 0.05 0.02 0.01 0.02
30 0.00 0.01 0.01 0.03 0.04 0.04 0.01 0.00 0.02
36 0.00 0.00 0.00 0.01 0.03 0.04 0.01 0.00 0.01
42 0.00 0.00 0.00 0.02 0.03 0.03 0.01 0.01 0.01
48 0.00 -0.01 0.00 0.01 0.02 0.03 0.01 0.00 0.01
54 -0.01 -0.01 -0.01 0.01 0.02 0.02 0.00 0.00 0.00
60 -0.01 -0.01 -0.01 -0.01 0.02 0.03 0.01 0.00 0.00
Mean 0.00 0.00 0.01 0.02 0.04 0.04 0.02 0.01 0.02
Tab.3  As in Table 2, but for average CSI gain of A-PKLT against PKLT
Fig.10  a) As in Fig. 6(d), but for the period of 0423 – 0807 UTC on 10 August, 2019, and b) hourly CSI gains of the A-PKLT 40–50 dBZ reflectivity nowcasts against the PKLT method for Typhoon Lekima from 0000 UTC on 9 August, – 2300 UTC on 10 August, 2019.
Lead time min 20
dBZ		 25
dBZ		 30
dBZ		 35
dBZ		 40
dBZ		 45
dBZ		 50
dBZ		 55
dBZ		 Mean
6 0.01 0.01 0.02 0.04 0.05 0.06 0.06 0.04 0.04
12 0.00 0.02 0.03 0.04 0.06 0.08 0.07 0.06 0.05
18 0.01 0.02 0.02 0.04 0.07 0.07 0.08 0.05 0.05
24 0.01 0.01 0.02 0.04 0.06 0.07 0.09 0.04 0.04
30 0.01 0.02 0.02 0.04 0.06 0.07 0.09 0.04 0.04
36 0.01 0.01 0.01 0.03 0.06 0.08 0.09 0.03 0.04
42 0.00 0.01 0.01 0.03 0.05 0.08 0.08 0.02 0.04
48 0.00 0.01 0.01 0.03 0.05 0.08 0.08 0.03 0.04
54 0.00 0.00 0.01 0.03 0.05 0.07 0.07 0.02 0.03
60 -0.01 0.00 0.00 0.02 0.05 0.07 0.06 0.01 0.03
Mean 0.00 0.01 0.02 0.03 0.06 0.07 0.08 0.03 0.04
Tab.4  As in Table 3, but for the period during 0423–0807 UTC 10 August, 2019.
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