24 2 Vol.24, No.2 2008 04 JOURNAL OF TROPICAL METEOROLOGY Apr., 2008 1004-4965(2008)02-0147-09 1 2 2 3 3 (1. 310017 2. 100081 3. 325001) Z-I A b Z I (Haitang) (Matsa) Z-I Z-I P458.1.24 A 1 [1] [2] [3] 36 Z-I (Z=A I b Z I A b ) Z-I A b Z-I [4] Z I Z-I : 2006-10-23; 2007-06-28 (2006C13025) (CMATG2006Z11) 01 (2004CB418301) (40575018) : E-mail: jichunxiao@sina.com
148 24 Z-I A b Z-I A b Z Z-I A A b Z-I Miller [5] Z i I i Z-I [6] Z-I Z-I Z-I Z-I Z I Wilson [7] 1970 [8] [9] 20.32% Sasaki [10] Nino- miya [11] [12] 100% 200% 20% 30% [13] 56% 9.9% [14] [15] Z-I A b 2 2005 (Haitang) (Matsa) 1 h( 10 ) 1 h 159 78.0 mm 205 37.2 mm
2 149 3 Z-I 3.1 CINRAD-SA Z-I ( Z=300 I 1.4 ) Z-I Z-I Z-I Z-I Z-I Z= A I b Z I Z Z-I Z-I b 5 A b Z-I (1) ( ) Z-I Z 1 > Z 2 > Z 3 > > Z n > I 1 > I 2 > I 3 > > I n > ( L L=8) [Z min Z max ] [Z 1 Z l ] [Z 2 Z 1+l ] [Z n l+1 Z n ] I [I 1 I l ] [I 2 I 1+l ] [I n l+1 I n ] Z k I k A b (2) A b Z-I I Z k Z k Z n Z k I n Z I A b 3.2 Z-I Z I Z-I Z-I Z-I Z-I Z-I Z-I Z-I Z-I 3.3 Z-I Haitang Matsa Z-I A b ( 1) 1 A b A b A b 1 Z-I A b /UTC A b 2005.7.19.17 00 324.9 1.2 2005.7.19.18 00 153.7 1.5 Haitang 2005.7.19.19 01 252.2 1.3 2005.7.19.20 01 214.0 1.3 2005.7.19.21 02 108.0 1.6 2005.8.5.19 03 17.8 1.9 2005.8.5.20 03 24.4 1.8 Matsa 2005.8.5.21 04 27.7 2.0 2005.8.5.22 04 26.1 1.9 2005.8.5.23 05 27.7 1.8
150 24 A b Z-I 1 Z-I A b 4 Z-I - R(i j) R g (i j) (i j) [11] CR (i j)= R g (i j) R(i j) CR (i j) CR(i j) J *(1) *(1) 2 2 2 J = α( CR CR ) + ε[( CR) + ( CR) ] i j x y min (1) Euler 2 2 ( ) [ α CR CR ε ( CR) + ( CR) ] = 0 (2) 2 2 x y CR(i j) R*(i j)=cr(i j)+r(i j) (3) 5 5.1 1 Haitang 5 mm 1a 2005 7 19 17 00 (UTC ) 45 dbz 20 mm 78 mm 76 mm 45 dbz 2005 7 20 00 04 ( 1b) Haitang 45 dbz 50 mm 45 dbz 2a 1 Z-I A b ( ) ( ) ( ) 2005 7 19 17 Haitang 2a 5 mm 70 mm 78 mm 60 mm 76 mm 28.5 N 120.5 E 20 mm 2b 2b 5 mm 80 mm 20 mm 20 mm 3 Haitang 2005 7 20 00 01 ( ) ( ) 1b Haitang 2005 7 20 00 3a
2 151 76 mm 50 mm 78 mm 1 Haitang (dbz ) (mm ) a. 2005 7 19 17 00 17 18 b. 2005 7 20 00 04 00 01 2 Haitang (mm ) (mm ) 2005 7 19 17 18 a. 2005 7 19 17 18 b. 2005 7 19 17 18 3 Haitang ( ) (mm ) 2005 7 20 00 01 2
152 24 35 mm 50 mm 28.0 N 120.5 E 23 mm 30 mm 27.3 N 120.3 E 3b 45 mm 28.0 N 120.5 E 30 mm 27.3 N 120.3 E 5.2 4 Matsa 2005 8 5 20 03 ( 4a) Matsa 40 dbz 35 dbz 5 mm 37 mm 45 dbz 2005 8 5 23 05 ( 4b) Matsa 4 h Matsa 32 mm Z-I Matsa A b 5 Matsa 2005 8 5 20 21 ( ) ( ) 5a 20 mm 33 mm 37.2 mm 5 mm ( 5b) 20 mm 33 mm 35 mm 6 Matsa 2005 8 5 23 6 00 ( ) ( ) 6a 10 mm 27 mm 32.4 mm ( 6b) 30 mm 5.3 7 7 Haitang 2005 7 19 17 ( 7a) 2.5 10 4 s 1 Matsa 2005 8 5 20 ( 7b) 6 10 4 s 1 28 N 119.3 E 10 mm
2 153 37 mm 32 mm 4 Matsa (dbz ) (mm ) a. 2005 8 5 20 03 20 21 b. 2005 8 5 23 05 5 23 6 00 5 Matsa ( ) (mm ) 2005 8 5 20 21 a. 2005 8 5 20 21 b. 2005 8 5 20 21 6 Matsa ( ) (mm ) 2005 8 5 23 6 00 5
154 24 7 2005 7 19 17 18 8 5 20 21 (mm ) 2 ( 10 4 s 1 ) 6 30% 2 2 /UTC 2005.7.19.17 18 2005.7.20.00 01 2005.8.5. 20 21 2005.8.5. 23 00 /mm 8.70 4.41 5.42 4.46 /mm 5.85 2.91 3.21 3.00 /mm 7.01 4.11 4.65 4.52 /mm 5.79 3.09 3.53 2.59 /mm 2.19 1.17 1.36 0.62 /% 9.50 19.76 18.30 26.28 /% 1.38 7.55 11.27 11.05 / 289 382 267 301 / 241 319 197 226 / 48 63 70 75 R gi R i R g 1 N N i = 1 = R (4) gi N 1 E = R R 100% (5) r i gi N R g i = 1 1 N ar = i gi N i = 1 E R R (6) Haitang Matsa ( 2) 2 Matsa 2005 8 5 23 6 00 2.59 0.62 26.28% 11.05% 7 Haitang Matsa Z-I A b (1) Z (2) Z-I
2 155 (3) (4) (5) [1] [J] 2006 22(1) 1-9 [2] [J] 2006 22(5) 466-472 [3] CINRAD WSR-98D [J] 2006, 22(6) 654-660 [4] [M] 2000 177-188 [5] MILLER J R A climatological Z-R relationship for convective storms in the northern Great Plains Preprints[C]//15th radar meteor conference Boston AMS 1972 153-154 [6] CINRAD [J] 2003 22(1) 96-100 [7] WILSON J W. Radar Measurement of rainfall summary[j] Bull Amer Soc 1979 60 (9) 1 048-1 058 [8] [J] 1990, 13 (4) 592-597 [9]. [J]. 2004 20(2) 192-197 [10] SASAKI Y Some basic formulas in numerical variation analysis[j] Mon Wea Rev 1970 98 875-883 [11] NINOMIYA K, AKIYAMA T. Objective analysis of heavy rainfalls based on radar and gauge measurement[j] J Meteor Soc Japan 1978 50 206-210 [12], [J] 1992 16(2) 248-256 [13] [J] 2000 11(2) 255-256 [14] [J] 1990 13 (4) 598-603 [15], [J] 2001 27(10) 3-7 A STUDY ON VARIABLE QUANTITATIVE PRECIPITATION ESTIMATION USING DOPPLER RADAR DATA JI Chun-xiao 1, CHEN Lian-shou 2, XU Xiang-de 2, ZHAO Fang 3, WU Meng-chun 3 (1. Zhejiang Institute of Meteorological Sciences, Hangzhou 310017, China; 2. Chinese Academy of Meteorological Sciences, Beijing 100081, China; 3. Wenzhou Meteorological Bureau, Wenzhou 325001, China) Abstract With the pros and cons of the traditional optimization and probability pairing methods considered, an improved optimal pairing window probability technique is developed using a dynamic relationship between the base reflectivity Z observed by radar and real time precipitation I by rain-gauge. Then, the Doppler Radar observations of base reflectivity for typhoons Haitang and Matsa in Wenzhou are employed to establish variable Z-I relationship which is subsequently used to estimate hourly precipitation of the two typhoons. Such estimations are calibrated by variational techniques. The results show that there exist significant differences in Z-I relationships for different typhoons, leading to different typhoon precipitation efficiencies. The estimated typhoon precipitation by applying radar base reflectivity is capable of exhibiting evidently the spiral rain belts and mesoscale cells, and well matches the observed rainfall. Error statistical analyses indicate that the estimated typhoon precipitation calibrated is better than the one without variational calibration. The variational calibration technique is able to maintain the characteristics of distribution of radar estimated typhoon precipitation, and to significantly reduce the error of the estimated precipitation in comparison with the observed rainfall. Key words: typhoon; radar quantitative precipitation estimation; variational calibration; verification