144 30, [ 1-3 ],,,, h, 151 mm, 50 a,,,,, Xue [ 4 ] ARPS, W SR (09 12, 98D,, ) 1 h ( 1), sp in2up, 10 Zhang [ 5 ] 2,,, Rogers [ 6 ] 60

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1 30 2 Vol. 30, No SC IENTIA METEOROLOGICA SIN ICA Ap r., 2010,,.., 2010, 30 (2) : Zhi Xiefei, Gao J ie, Zhang Xiaoling. An app lication of the Dopp ler radar data in the nowcasting using mesoscale model. Scientia Meteorologic Sinica, 2010, 30 (2) : (1, ) (2, ) Lev2 9 ARPS( the Advanced Regional Prediction System), ,,,, sp in2up,,,,,,,, ARPS P41512 A An application of the Doppler radar data in the nowcasting using mesoscale model Zh i X iefe i 1 Gao J ie 1 Zhang X iaoling 2 ( 1 Key Laboratory of M eteorological D isaster of M inistry of Education, NU IST, N anjing , China) ( 2 N ational M eteorological Center, B eijing , China) Abstract In order to test the effect of the Dopp ler radar data on the mesoscale model forecasting, a heavy rain event occurred on 18 July 2007 has been studied by app lying the new generation Dopp ler raw radar data in China which contains 9 levels reflectivity and radial velocities in the ARPS ( the Advanced Regional Prediction System) model. The results show that the initialization of both radar reflectivity and radial w ind may significantly imp rove short2term quantitative p recip itation forecasting by using m esoscale model. It was found that the radar radial w ind adjustment may cause the small2 and m edium scale charac2 teristics in the initial field and reduce the model sp in2up time. A s integral goes on, vapor adjustment has also an influence on the p recip itation forecasting, but less significantly compared w ith the w ind adjust2 m ent. Radar reflectivity m ainly imp roves the hum idity parameter and increases the cloud water content in the initial field. A s integral begins it leads to a considerable w ind adjustm ent. In this study, the distribu2 tion of radar echoes and water vapor centers have been p redicted noticeably in the control run. The distri2 bution of the forecasted p recip itation is sim ilar to that of the observations, but p redicted radar echo inten2 sity and correspondingly p recip itation in the mesoscale model seemed to be larger. Key words ARPS model Radar radial velocity Radar reflectivity : ; : : (2720), ( ) : (19652),,,,. zhi@ nuist. edu. cn

144 30, [ 1-3 ],,,, 2007 7 18 1h, 151 mm, 50 a,,,,, Xue [ 4 ] ARPS, W SR2 7 18 (09 12, 98D,, ) 1 h ( 1), sp in2up, 10 Zhang [ 5 ] 2,,, Rogers [ 6 ] 60 mm /h 11, 6 Gao [ 728 ] ARPS23DVAR,, 60 mm /h,,

2 144 30, [ 1-3 ],,,, h, 151 mm, 50 a,,,,, Xue [ 4 ] ARPS, W SR (09 12, 98D,, ) 1 h ( 1), sp in2up, 10 Zhang [ 5 ] 2,,, Rogers [ 6 ] 60 mm /h 11, 6 Gao [ 728 ] ARPS23DVAR,, 60 mm /h,, 60 mm /h,, [ 9 ], 50 mm /h,, 30 mm /h,, 20 mm /h 12,, [ 16 ],,, ARPS,, , 1,, sp in2up [ ], 50 mm /h h ( 10mm), (3617 N, E), ( a) ; ( b) ; ( c) Fig. 1 The distribution of the hourly p recip itation ( unit: mm) during the period 09: 00 12: 00 UTC July 18, 2007 taken from AW S in Shandong p rovince, where the station Jinan is depicted as a black triangle. The contour interval is 10 mm. ( a) 09: 00 10: 00 UTC; ( b) 10: 00 11: 00 UTC; ( c) 11: 00 12: 00 UTC

3 2, : ARPS ARPS (Advanced Regional Prediction System) A rakawa2c [ 17 ], [ 18 ] Hu [ ], ARPS, (ADAS), 3DVAR ARPS23DVAR, ARPS,, km 3 km, (3617 N, E), 32, 650 m, 6 s, 1 km Kain2Fritsch,, 6 h NCEP 1 1 GR IB, 06 15, 09 12, 09 C INRAD2SA ARPS, ARPS23DVAR,, 3 h ; : : ; : :,, 311 (09 ), ( 2) ( 2a) ( 2c),,,, ( 2d) ( 2b), 1 h, ( 3a), 15 km, 150 mm /h,, 50 mm /h,,, ( 3b) ( 3c), 100 mm /h, 25 mm /h ( 3d ), 150 mm /h,,,,,,,,,,,, 40 km, 2 h, ( 4a),, 100 mm /h ( 4b), ( 4c), 50 mm /h ( 4d),

146 30 2 3 km 7 18 09 ( : mm) ( a) ; ( b) ; ( c) ; ( d) Fig.

resolution of 3 km, where the station Jinan is depicted as a black triangle.

4 km ( : mm) ( a) ; ( b) ; ( c) ; ( d) Fig. 2 The distribution of the simulated precipitation (unit: mm) and surface wind fields during the period 09: 00 UTC July 18, 2007 with a resolution of 3 km, where the station Jinan is depicted as a black triangle. (a) control run; (b) experiment I; (c) experiment II; (d) experiment III h ( :mm) (a) ; (b) ; (c) ; (d) Fig. 3 Same as Fig. 2, excep t for the period 09: 00 10: 00 UTC July 18, 2007 ( a) control run; ( b) experiment I; ( c) experiment II; ( d) experiment III

2, : 147 45 km,, 100 mm /h, 150 mm /h,,,, 312,, 5, 3 h ( ),,,,, 46 dbz,,,,,,,,, NCEP 1 h ( 6 ),,,,,,, 60 dbz,,,,,,,,,,, 59 dbz 4 7 18 10 11 1 h ( : mm) ( a) ; ( b) ;

5 2, : km,, 100 mm /h, 150 mm /h,,,, 312,, 5, 3 h ( ),,,,, 46 dbz,,,,,,,,, NCEP 1 h ( 6 ),,,,,,, 60 dbz,,,,,,,,,,, 59 dbz h ( : mm) ( a) ; ( b) ; ( c) ; ( d) Fig. 4 Same as Fig. 2, excep t for the period 10: 00 11: 00 UTC July 18, 2007 ( a) control run; ( b) experiment I; ( c) experiment II; ( d) experiment III

148 30 5 3 km 7 18 09 1 500 m ( : dbz) ( a) ; ( b) ; ( c) ; ( d) Fig.

resolution of 3 km, where rep resents the station Jinan.

6 km m ( : dbz) ( a) ; ( b) ; ( c) ; ( d) Fig. 5 The distribution of the simulated radar echoes at the altitude of 1500m ( unit: dbz) at 09: 00 UTC July 18, 2007 with a resolution of 3 km, where rep resents the station Jinan. ( a) control run; ( b) experiment I; ( c) experiment II; ( d) experiment III m ( : dbz) Fig. 6 Same as Fig. 5, excep t for 10: 00 UTC July 18, 2007 ( a) control run; ( b) experiment I; ( c) experiment II; ( d) experiment III

2, : 149 7 7 18 11 1 500 m ( : dbz) Fig. 7 Same as Fig.

7 2, : m ( : dbz) Fig. 7 Same as Fig. 5, excep t for 11: 00 UTC July 18, 2007 ( a) control run; ( b) experiment I; ( c) experiment II; ( d) experiment III,, 25 dbz 2 h ( 7),,, 60 dbz,,,, 25 dbz,, 30 km, 40 dbz, 3 h ( ),, 50 dbz,,, 58 dbz,,, 3h,,, 4 ARPS 3DVAR,, , : (1) (2),, sp in2up,,, (3),,,,,,,,

8 150 30,,,,,,,, :, [ 1 ],,.., 2007, 30 (3) : [ 2 ],,, , 2008, 31 (4) : [ 3 ],.., 2008, 28 (3) : [ 4 ] Xue M and Coauthors. The advanced regional p rediction system (ARPS), storm2scale numericalweather p rediction and data assim2 ilation. Meteor. A tmos. Phys., 2003, 82: [ 5 ] Zhang J. Moisture and diabatic initialization based on radar and satellite observations[ Ph. D. D issertation ]. University of Oklaho2 ma, [ 6 ] Rogers R F and Coauthors. A simp le technique for using radar data in the dynamic initialization of a mesoscale model. Mon. W ea. Rev., 2000, 128: [ 7 ] Gao J D and B rewster K. A three2dimensional variational data anal2 ysis method with recursive filter for Doppler radars. J. A tmos. Ocea. Tech., 2004, 21 (3) : [ 8 ] Gao J D and Coauthors. Multip le Dopp lerwind analysis and assim i2 lation via 3DVAR using Simulated observations of the Planned Case Network and W SR288D radars 32nd. Conf. Radar Mete2 or.. A lbuquerque, NM: Amer. Meteor. Soc., [ 9 ],.., 2000, 58 (2) : [ 10 ],,.., 2006, 30 (1) : [ 11 ],.., 2008, 13 (3) : [ 12 ],,,.., 2008, 34 (6) : [ 13 ],,,.., 2008, 31 ( 5) : [ 14 ],,,. 3., 2008, 28 (2) : [ 15 ],,,. 7 8., 2008, 28 (3) : [ 16 ],,, , 24 (1) : [ 17 ] Xue M and D roegemeier K K. ARPS userπs guide (Version410 ). Center for Analysis and Prediction of Storm s, [ 18 ] Xue M and D roegemeier K K, Wong V. The advanced regional p rediction system (ARPS) A multiscale nonhydrostatic atmos2 pheric simulation and p rediction tool, Part : Model Physics and App lications. Meteor. A tmos. Physics, 2001, 76: [ 19 ] Hu M and Xue M. 3DVAR and cloud analysis with W SR288D lev2 el2 data for the p rediction of the Fort Worth tornadic thunder2 storm s. Part : Cloud analysis and its impact. Mon. W ea. Rev., 2006, 134 (2) : [ 20 ] Hu M and Xue M. 3DVAR and cloud analysis with W SR288D lev2 el2 data for the p rediction of the Fort Worth tornadic thunder2 storm s. Part : Impact of radial velocity analysis via 3DVAR. Mon. W ea. Rev., 2006, 134 (2) :

408 30,, [ 225 ],,,,, [ 629 ],, , 2008,,,,, mm, mm, 3115 mm /h, (34193 N, E), mm, 8511 mm /h,, :,, (5 1

408 30,, [ 225 ],,,,, [ 629 ],, , 2008,,,,, mm, mm, 3115 mm /h, (34193 N, E), mm, 8511 mm /h,, :,, (5 1 30 3 Vol. 30, No. 3 2010 6 SC IENTIA METEOROLOGICA SIN ICA Jun., 2010,,,.., 2010, 30 ( 3) : 4072413. Zhang J ingying, Chen J inm in, L iu Yingjie, et al. Analysis of mechanism s of short2time rainfall