Application of Doppler Radar Data to the Landfalling Typhoon Saomai Simulation

Shi Lijuan; Xu Xiaofeng; Li Bai; Yang Hongping; Xu Fengwen

Vol.20, NO.3, 2009

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2009 > 20(3): 257-266

Shi Lijuan, Xu Xiaofeng, Li Bai, et al. Application of Doppler radar data to the landfalling Typhoon Saomai simulation. J Appl Meteor Sci, 2009, 20(3): 257-266.

Citation:

Shi Lijuan, Xu Xiaofeng, Li Bai, et al. Application of Doppler radar data to the landfalling Typhoon Saomai simulation. J Appl Meteor Sci, 2009, 20(3): 257-266.

Shi Lijuan, Xu Xiaofeng, Li Bai, et al. Application of Doppler radar data to the landfalling Typhoon Saomai simulation. J Appl Meteor Sci, 2009, 20(3): 257-266.

Citation:

Shi Lijuan, Xu Xiaofeng, Li Bai, et al. Application of Doppler radar data to the landfalling Typhoon Saomai simulation. J Appl Meteor Sci, 2009, 20(3): 257-266.

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Application of Doppler Radar Data to the Landfalling Typhoon Saomai Simulation

1.
Chinese Academy of Meteorological Sciences, Beijing 100081
2.
CMA Meteorological Observation Center, Beijing 100081
3.
China Meteorological Administration, Beijing 100081
4.
National Meteorological Center, Beijing 100081

Received Date: 2008-03-04
Rev Recd Date: 2009-02-16
Publish Date: 2009-06-30

Abstract

Abstract

The mesoscale model ARPS and its data analyzing system ARPS 3DVar developed by CAPS of Oklahoma university has a good potential to utilize in China. Using ARPS and its 3DVar assimilation system, the Doppler weather radar (CINRAD SA) reflectivity and radial velocity are assimilated. In order to test the effects of Doppler radar data on the initial field and on the forecast field, numeric study is carried out on super typhoon Saomai (0608) which lands at east China and causes a large damage. Comparison between experiments with and without radar data assimilation shows that Doppler radar assimilation can help obtain more realistic precipitation, wind and reflectivity structures within 6 hour initial time windows. The radar assimilation by ARPS 3DVar has the ability to improve the forecast on the mesoscale rain cell position and intensity. The improvement on typhoon track forecast is due to the effective adjustment of the typhoon vortex and eye structure by radar data assimilation. The result of precipitation forecast is improved significantly, mainly because of the physical quantities in assimilation test displaying typical characteristics of mesoscale system. However, there are some inadequate aspects still needing improvements in the stimulation of typhoon intensity.
- ARPS model;
- Doppler radar data;
- 3D variational assimilation;
- initial field;
- landfalling typhoon

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References(34)

Figures and Tables

图 1 同化窗口内2006年8月10日06:00 1 h降水量（单位:mm）（a）雷达反演，（b）同化试验，（c）控制试验

Fig. 1 1-hour precipitation in the initial time windows at 06:00 10 Aug 2006(unit:mm)(a) retrieved rainfall fromr adar observation, (b) assimilation test, (c) control test

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图 2 同化窗口内2006年8月10日06:00海平面的流场和全风速（阴影，单位:m/s）（a）控制试验，（b）同化试验

Fig. 2 Streamline filed and wind speed (shadow, unit: m/s) in the initial time windows at 06:00 10 Aug 2006(a) control test, (b) assimilation test

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图 3 2006年8月10日06:00温州多普勒天气雷达径向风速度（单位:m/s）

Fig. 3 Radial velocity observed by Wenzhou radar at 06:00 10 Aug 2006(unit:m/s)

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图 4 同化窗口内雷达同化试验、控制试验模拟台风路径与实况台风路径

Fig. 4 The track of typhoon Saomai in the initial time windows simulated by radar assimilation test, by control tset and observation

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图 5 同化窗口内2008年8月10日06:00组合反射率（单位:dBz）（a）同化试验，（b）温州雷达观测，（c）控制试验

Fig. 5 The composite reflectivity in the initial time windows at 06:00 10 Aug 2006(unit:dBz) (a) assimilationtest, (b) observed by Wenzhou radar, (c) controltes

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图 6 同化窗口内2006年8月10日06:00沿台风中心垂直径向剖面上的物理量（a）同化试验涡度（阴影，单位:10^-5s^-1）和散度（等值线，单位:10^-3s^-1），（b）控制试验涡度（阴影，单位:10^-5s^-1）和散度（等值线，单位:10^-3s^-1），（c）同化试验q_c（阴影，单位:g/kg）和uv-w风场（矢量，单位:m/s），（d）控制试验q_c（阴影，单位:g/kg）和uv-w风场（矢量，单位:m/s），（e）同化试验θ_e（单位:K），（f）控制试验θ_e（单位:K）

Fig. 6 The cross section of physical variables along typhoon center at 06:00 10 Aug 2006, vorticity (shadow, unit:10^-5s^-1), divergence (contour, unit:10^-3s^-1) in assimilation test (a) and in control test (b), q_c(shadow, unit:g/kg), uv-w wind (vector, unit:m/s) in assimilation test (c) and in control test (d), θ_e(unit:K) in assimilation test (e) and in control test (f)

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图 7 1 h降水量（单位：mm）

Fig. 7 1-hour precipitation (unit:mm)

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图 8 同化试验、控制试验模拟的“桑美”台风路径预报与实况路径

Fig. 8 The track of typhoon Saomai simulated by radar assimilation test, by control tset and the observation

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