research article rainfall estimation using specific differential...

Research ArticleRainfall Estimation Using Specific Differential Phase forthe First Operational Polarimetric Radar in Korea

Cheol-Hwan You1 Dong-In Lee2 and Mi-Young Kang1

1 Hydrospheric Atmospheric Research Center Nagoya University Furo-cho Chikusa-ku Nagoya 464-8601 Japan2Department of Environmental Atmospheric Sciences Pukyong National University Yongso-ro Nam-guBusan 608-737 Republic of Korea

Correspondence should be addressed to Dong-In Lee leedipknuackr

Received 25 November 2013 Revised 14 January 2014 Accepted 15 January 2014 Published 24 February 2014

Academic Editor Hiroyuki Hashiguchi

Copyright copy 2014 Cheol-Hwan You et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

To assess the performance of rainfall estimation using specific differential phase observed by Bislsan radar the first polarimetricradar inKorea three rainfall cases occurring in 2011 were selected each caused by different conditions the first is theChangma frontand typhoon the second is only theChangma front and the third is only a typhoon For quantitative use of specific differential phase(119870DP) a data quality algorithm was developed for differential phase shift (ΦDP) composed of two steps the first involves removalof scattered noise and the second is unfolding of ΦDP This order of the algorithm is necessary so as not to remove unfolded areaswhich are the realmeteorological target All noise was removed and the foldedΦDP were unfolded successfully for this study119877(119870DP)relations for S-band radar were calculated for 84754 samples of observed drop size distribution (DSD) using different drop shapeassumptionsThe relation for the Bringi drop shape showed the best statistics 028 for normalized error and 67mm for root meansquare error for rainfall heavier than 10mmhminus1 Because the drop shape assumption affects the accuracy of rainfall estimationdifferently for different rainfall types such characteristics should be taken into account to estimate rainfall more accurately usingpolarimetric variables

1 IntroductionWeather radar is a very useful remote sensing tool forestimating rainfall amount because of its high spatial and timeresolution compared with other instruments Measurementsof rainfall by radar are generally based on the relationshipbetween the reflectivity factor (119885) and rain rate (119877) termedthe 119885-119877 relation (hereafter 119877(119885)) Experimentally measuredDSDs have been extensively used to calculate both radarreflectivity and rain rate [1] It can be shown that thereis no unique global 119877(119885) relation because DSDs can varyfrom storm to storm and within the storm itself [2] Manyresearchers have noted that radar rainfall estimation iscontaminated by a number of uncertainties such as hardwarecalibration partial beamfilling rain attenuation bright bandand nonweather echoes [3 4] Several studies in Korea havecalculated the 119877(119885) relationship using disdrometer data fordifferent rainfall types and calirated rainfall amount with raingages for operational Doppler weather radars [5ndash7]

Numerous studies have investigated the implementationof polarimetric radar for operational use A particle identi-fication algorithmhas been developed to improve data qualitycontrol and rainfall estimates by distinguishing nonmete-orological artifacts such as anomalous propagation birdsinsects second-trip echo and melting-layer detection [8ndash10]The improvement of quantitative precipitation estimation(QPE) accuracy is one of the major advantages of polari-metric radar [11ndash15] Cifelli et al [16] recently comparedthe performance of two rainfall algorithms in a high plainsenvironment the CSU-HIDRO (Colorado State University-Hydrometeor IDentification of Rainfall) and one based on theJPOLE (Joint Polarization Experiment) Based on these the-oretical and other experimental studies many countries arereplacing or modifying their radars to provide polarimetricradar for operational use The specific differential phase is avery useful parameter for rainfall estimation because it is notsusceptible to radar calibration beam attenuation or beam

Hindawi Publishing CorporationAdvances in MeteorologyVolume 2014 Article ID 413717 10 pageshttpdxdoiorg1011552014413717

2 Advances in Meteorology

40

38

36

34

32

Latit

ude (

nort

h)

Latit

ude (

nort

h)

122 124 126 128 130 132

Longitude (east)

Longitude (east)

BISL

POSS

3650

36

3550

35

3650

36

3550

35

12750 128 12850 129 12950

12750 128 12850 129 12950

(a) (b)Figure 1 The location of the Bislsan radar (solid rectangle) the POSS disdrometer (open rectangle) and rain gages (plus signs) distributedwithin the area of radar coverage (100 km radius)

blockage It is also closely related to rain intensity even in thepresence of dry tumbling hail [17 18]

Three major agencies use radars to monitor and forecastsevere weather and flash floods operationally in Korea theMinistry of National Defense (MND) the Ministry of LandInfrastructure and Transportation (MOLIT) and the KoreaMeteorological Administration (KMA) MOLIT installedpolarimetric radars for the first time in Korea in 2009and 2012 The successful implementation of these radarsfor operational use requires studies of rainfall estimationhydrometeor classification and DSD retrieval Howeverthere are few studies on these polarimetric related issuesother than for deriving relationships using long perioddisdrometer data assessing each relation after applying a verysimple quality control for differential phase shift [19] Theaccuracy of rainfall estimation using 119877(119870DP) was found to beworse than that of 119877(119885 119885

119863119877

)This paper discusses how the accuracy of rainfall esti-

mation can be improved using specific differential phasemeasured by the first polarimetric radar installed in KoreaSection 2 describes the data used in this study the calculationof the relationship between specific differential phase and rainrate the data quality control of differential phase shift andthe statistical validation Section 3 gives results for rainfallestimation using specific differential phase and describes theeffect of quality control of differential phase shift includingthe unfolding algorithm Finally Section 4 summarizes theresults and provides some concluding remarks

2 Data and Methodology

21 Rain Gage and Radar Dataset The rainfall data fromrain gages operated by the KMA were used to evaluate theaccuracy of radar rainfall Rain gages located at distances of5 km to 100 km from the radar are included in the analysisFigure 1 shows the location of all instruments used in this

study The circle represents the radar coverage the solidrectangle is the center of the Bislsan radar plus signs show thedistributed rain gageswithin the radar coverage and the openrectangle is the position of a POSS (Precipitation OccurrenceSensor System) disdrometer whichwas located around 82 kmfrom the radar The POSS disdrometer will be described inmore detail in the next section

Radar data were collected by the Bislsan S-band polari-metric radar which was installed and operated by MOLITin Korea from 2009 The transmitted peak power is 750 kWbeam width is 095∘ and frequency is about 28GHz Hori-zontal and vertical reflectivity (119885

ℎ

119885V) radial velocity (VR)spectrumwidth (SW) differential reflectivity (119885DR) differen-tial phase shift (ΦDP) specific differential phase (119870DP) andcross correlation coefficient (120588

ℎV) are estimated with a gatesize of 0125 kmThe scan strategy is composed of 6 elevationangles with a 25-minute update interval The values of ΦDPand 119870DP for 05∘ elevation angle were extracted from thevolume data every 25 minutes

The quality control algorithm consists of aΦDP unfoldingstage and a noise removal stage It is applied to improverainfall estimates The maximum observable value of ΦDP is180∘ for the Bislsan radar in 2011 If the real ΦDP exceeds thisvalue in the case of heavy rainfallΦDP may be folded (aliased)and should be unfolded for quantitative useThe procedure tounfold ΦDP is as follows

(1) Check for folding by comparing the difference bet-ween the current gate value of ΦDP and the medianofΦDP for the previous 24 gates

(2) The gage is designated as a folded gate if the differencesatisfies the conditions shown in Figure 2

(3) If it is folded add 180∘ to the folded valueNoise removal is performed after unfolding as follows(1) calculation of standard deviation ofΦDP using 9 gates

centered on the target gate

Advances in Meteorology 3

Last gate

No

No

The profile was unfolded phase

No

Last ray

Yes

No

No

j = j + 1

Start from the 1st ray j = 1

120588hv gt 09 more than 5 gates

Start from the 1st gate i = 1

f = ff from i to i + 299 gatesf = unfolded differential phase ff = folded differential phase

i = i + 1i = 300 maximum bin number


fmed = median of differential phase overthe last 24 gates from i gate

f = ff + 180∘ f = ff

df1 = abs (ff minus fmed )

df2 lt df1 and df minus df2 gt 100∘

df2 = abs minus fmed) + 180∘(ff

Figure 2 Flowchart of differential phase shift-unfolding algorithm

(2) remove gate as noise if the standard deviation of ΦDPat the gate is more than 15 degrees

(3) remove remaining noise by checking the number ofmissing gates in the 25 neighbor gates

(4) use the average value of the 9 neighbor gates to replacethe removed gate value

119870DP is calculated from the slope of 9 and 25 gates ofquality-controlledΦDP If a reflectivity is higher (lower) than40 dBZ it is lightly (heavily) filtered These 119870DP are used tocalculate rainfall amount Figures 2 and 3 show the details ofthe ΦDP unfolding algorithm and noise removal procedure

22 Calculation of R(119870DP) and Validation Relations forconverting radar variables into rain rate are required becauseradar does not observe the rainfall directly In order to calcu-late these relations disdrometer data which can measure theDSDs are needed A POSS is a low power continuous waveX-band bistatic system here the transmitter and receiver arehoused separately and mounted on a frame 45 cm apart [20]

One-minute DSDs obtained fromMarch 2001 to Septem-ber 2004 were processed to remove unreliable data as shownin You et al [19] After quality control there were 84574DSDsamples available for calculating the relationshipsMost of thedata are distributed over a wide range with a maximum rainrate of about 199mmhminus1 (Figure 4)119870DP was calculated for this study using T-matrix scatter-

ing techniques derived byWaterman [21] and later developed

Count the number of missing data around 25 neighboring gates

Filling of gap

If data is not missing in a raw fill the gap using 9 gate-averaged data

using neighboring 9 gates which are 4 gates backward and forward direction

along with the radial

Calculation of standard deviation for ΦDP

Remove noise ΦDP

If Std phi gt 15 remove ΦDP at the gate

Calculation of N25

Remove residual ΦDP

If N25 gt 18 remove ΦDP at that gate

Std phi calculation

ΦDP processing for noise data

KDP calculation

Figure 3 Noise removal flowchart for differential phase shift

0 50 100 150 200

Rain rate (mmhr)

Tota

l tim

e (m

inut

es)

105

104

103

102

101

100

10minus1

Figure 4 Histogram of rain rate calculated using 84574 samples of1 min DSD after quality control


Table 1 Rainfall cases and different source conditions used in the study

Items Period SourcesCase 1 2011 6 25 0000 LSTsim6 26 1400 LST Changma front and typhoonCase 2 2011 7 09 0000 LSTsim7 10 2200 LST Changma frontCase 3 2011 8 07 1800 LSTsim8 08 0300 LST Typhoon

further by Mishchenko et al [22] The shape of a fallingraindrop in air is determined by a balance of three typesof forces working on the drop surface hydrostatic pressuresurface tension and aerodynamic pressure To obtain thespecific differential phase using DSDs three raindrop shapeassumptions are used as described in Ryzhkov et al [23]The numerical model of Beard and Chuang [24] whichagrees well with wind tunnel measurements suggests that theequilibrium values of the raindrop axis ratio 119903 are related tothe equivolume diameter in mm119863 by

119903 = 10048 + 0500057119863 minus 0026281198632

+ 00036821198633

minus 000016771198634

(1)

(hereafter EQU) The actual shapes of raindrops in turbulentflow are expected to be different from the equilibrium shapedue to drop oscillation Oscillating drops appear to be morespherical on average than the drops with equilibrium shapesas shown by Andsager et al [25] in laboratory studies Theyshowed that the shape of raindrops between 11 and 44mmis better explained by the following formula

119903 = 1012 minus 001445119863 minus 0010281198632

(2)

Bringi et al [26] [hereafter BRI] suggested using (2)for drops with sizes smaller than 44mm and (1) for largersizes Another shape-diameter relation recently proposed byBrandes et al [14] [hereafter BRA] combines the observationsof different authors

119903 = 09951 + 0025119863 minus 0036441198632

+ 00053031198633

+ 000024921198634

(3)

Another parameter in the T-matrix calculations is thetemperature which is assumed to be 20∘C in this study It isalso necessary to take the canting angle into considerationbecause it can account for a 6 reduction in the coefficient ofthe 119877(119870DP) relation [27] and may give small negative biasesin the estimators [28] The distribution of canting anglesof raindrops is Gaussian with a mean of 0∘ and a standarddeviation of 10∘ and these values have been used commonlyin previous studies [27 29]

To validate each relationship the normalized error (NE)fractional root mean square error (RMSE) and correlationcoefficients (CC) are used

NE =(1119873)sum

119873

119894=1

(1003816100381610038161003816119877119877119894 minus 119877119866119894

1003816100381610038161003816)

119877119866

(4)

RMSE = [ 1119873

119873

sum

119894=1

(119877119877119894

minus 119877119866119894

)2

]

12

(5)

CC =sum119873

119894=1

(119877119877119894

minus 119877119877

) (119877119866119894

minus 119877119866

)

[sum119873

119894=1

(119877119877119894

minus 119877119877

)]12

[sum119873

119894=1

119877119866119894

minus 119877119866

]12

(6)

Here119873 is the number of 119877119877

and 119877119866

pairs and 119877119877

and 119877119866

are the averaged rain rate for 1 hour for the radar and gagerespectively The above measures are calculated using hourlyrainfall amount for the radar and gage at the point Negative119870DP is set to 0 in calculating 119877(119870DP) The point rainfall fromradar was obtained by averaging rainfall over a small area(500m times 1∘) centered on each rain gage

3 Results

31 Rainfall Case Studies and Quality Control of DifferentialPhase Shift

311 Rainfall Distributions In this study three precipitationsystems in 2011 were analyzed one associated with theChangma front and a typhoon from 0000 LST on June 25 to1400 LST on June 26 a second only with the Changma frontfrom 0000 LST on July 9 to 2000 LST on July 10 and a thirdonly with a typhoon from 2100 LST on August 7 to 0300 LSTon August 8 (Table 1)

Figure 5 shows the time series of total rainfall amountobserved by the ground rain gages in each case obtained bysumming the amount of rainfall observed by all the rain gageswithin the radius of the radar In Case 1 there are two peaksof rainfall the first due to the Changma front and the secondto the typhoon There are three peaks associated with theChangma front in Case 2 The third case was a precipitationsystem caused by the typhoon but of relatively short duration

312 Quality Control of Differential Phase Shift Differentialphase shift is defined as the difference between the verticaland horizontal phases of the precipitation particles andis used to calculate 119870DP If the processing of ΦDP is notsuccessful the calculation of 119870DP and rainfall estimationis affected The maximum observable value of ΦDP is 180degrees for the Bislsan radar in 2011 If the real ΦDP exceedsthis value in heavy rainfall ΦDP may be folded and shouldbe unfolded for quantitative use There is also considerablenoise in the observed ΦDP and this should be removedFigure 6 shows the results of noise removal and unfolding ofdifferential phase shift for observations on 1330 LST on June26 and 0246 LST on August 8 in 2011 respectively

Considerable noise was observed to the west of the radarcenter and this has clearly been removed by the noise removal


1200

900

600

300

01 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

Tota

l rai

nfal

l am

ount

(mm

)

(a)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(b)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(c)

Figure 5 Time series of total rainfall amount defined as rainfall summed over all rain gages within the radar coverage for (a) Case 1 (b)Case 2 and (c) Case 3

algorithm (Figures 6(a) and 6(b)) Folding ofΦDP occurs at adistance of 60 km south of the center of the radar coveragethe algorithm successfully recovers ΦDP (Figures 6(c) and6(d)) It is necessary to apply the noise removal algorithmafter unfolding so that it does not remove the unfoldingregion which is an area of real echo Folding of the differentialphase shift occurred from 0215 LST onAugust 8 in Case 3 andall events were successfully unfolded (not shown here)

32 119877(119870DP) Relations and Validation Relations between rainrate and 119870DP 119877(119870DP) were determined using a standardweighted least square polynomial fit 119870DP and rain rate werecalculated using the observed DSDs from 84574 samples

Equations (7) (8) and (9) were obtained by assumingEQU BRI and BRA drop shapes respectively Their corre-lation coefficients were 087 086 and 084 respectively The119877(119870DP) BSC referred to below is the 119877(119870DP) calculated fromDSD data observed at Busan in Korea

119877 = 509119870DP0827 (7)

119877 = 614119870DP0833 (8)

119877 = 534119870DP0787

(9)

Table 2 List of different relations used for validation

Number Relationship Drop shape1 119877 = 364 times 10

minus2

1198850625 Marshall Palmer

2 119877 = 440119870DP0822

Measured DSDs at OklahomaEQU shape

3 119877 = 503119870DP0812

Measured DSDs at OklahomaBRI shape

4 119877 = 473119870DP0791

Measured DSDs at OklahomaBRA shape

5 119877 = 509119870DP0827

Measured DSDs at Busan EQUshape

6 119877 = 614119870DP0833

Measured DSDs at Busan BRIshape

7 119877 = 534119870DP0787

Measured DSDs at Busan BRAshape

The accuracies of these relationships were compared withthose of the 119877(119870DP) based on DSDs observed in OklahomaCity (hereafter 119877(119870DP)OKC) [30] and 119877 = 200119877

16 (Table 2)Only the times for which gages have rainfall greater than01mm were selected and there are 2891 3051 and 423 pairsfor Cases 1ndash3 respectively


Differential phase shift (deg) 20110626 133051 KST EL 046

300

240

200

180

160

140

120

100

80

60

40

20

10

1BSL range 101 km Bin size 0125 km Bins 813 Sweep rate 180 (degs)

(a)

Differential phase shift (deg) 20110626 133051 KST EL 046QCD

300

240

200

180

160

140

120

100

80

60

40

20

10


(b)

Differential phase shift (deg)

300

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1

20110808 2464 KST EL 050

BSL range 101 km Bin size 0125 km Bins 813 Sweep rate 180 (degs)

(c)

Differential phase shift (deg) QCD

300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(d)

Figure 6 The results of noise removal and unfolding of differential phase shift (a) Raw ΦDP observed at 1330 LST on June 26 2011 beforenoise removal and (b) after noise removal (c) RawΦDP observed at 0246 LST on August 8 2011 before unfolding and (d) after unfolding

Figure 7 shows scatterplots of gage rainfall against radarrainfall obtained from the Marshall Palmer (MP) 119877(119885)119877(119870DP) OKC and 119877(119870DP) BSC

Blue triangles are for equilibrium drop shape red circlesfor the Brandes drop shape and black crosses for the Bringidrop shape In Case 1 the statistics of the radar rainfalldetermined from 119877(119885) were NE = 054 RMSE = 43mmand CC = 082 Regardless of the drop shape the statisticsfor rainfall obtained by 119877(119870DP) OKC and BSC were similarBetter values of CC and NE were obtained with 119877(119885) thanwith 119877(119870DP) but the RMSE of 119877(119870DP) was a little better thanthat of 119877(119885) Case 2 shows a similar pattern to Case 1 butthe RMSE of the 119877(119870DP) with EQU drop shape was good

in 119877(119870DP) BSC In Case 3 119877(119885) showed good results in allstatistics and the RMSE of 119877(119870DP) BSC was lower than thatof119877(119870DP)OKCThe quality control algorithm for differentialphase shift has resulted inmuch better results for119877(119870DP) thanin the previous study [19]119870DP is susceptible to fluctuations of DSD and is noisy in

light precipitation In all cases used in this study there is alarge proportion of light precipitation and the performanceof the 119877(119870DP) is either no better or worse than the perfor-mance of 119877(119885) Therefore only samples with gage rainfallintensity greater than 10mmhminus1 in all caseswere selected andanalyzed The number of samples with heavier rainfall was1072


60

50

40

30

20

10

06050403020100

Gage total AWS (mm)

NE RMSE CCMP 039 31 080

Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)

NE RMSE CCEQU 056 39 066

BRA 056 38 066

BRI 057 38 066

Rada

r tot

alR

(KD

P) O

KC(b)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 059 38 066

BRI 061 38 066

Rada

r tot

alR

(KD

P) B

SC

(c)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(d)

6050403020100

Gage total AWS (mm)


BRA 047 44 081

BRI 048 44 081

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(e)

6050403020100

081

081081

Gage total AWS (mm)

NE RMSE CCEQU 047 43

BRA 051 45

BRI 056 49

60

50

40

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20

10

0

Rada

r tot

alR

(KD

P) B

SC

(f)

Gage total AWS (mm)


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01009080706050403020100

Rada

r tot

alR

(Z)

(g)

Gage total AWS (mm)


BRA 044 73 091

BRI 043 69 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(h)

Gage total AWS (mm)


BRA 044 68 091

BRI 046 68 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC

(i)Figure 7 Scatterplots of gage rainfall against radar rainfall estimated by theMP 119877(119885) 119877(119870DP)OKC and 119877(119870DP) BSC relations for Cases 1ndash3(a) (b) and (c) are for Case 1 (d) (e) and (f) are for Case 2 and (g) (h) and (i) are for Case 3 Blue triangles are for equilibrium drop shapered diamond for the Brandes drop shape and black crosses for the Bringi drop shape

Values of RMSE increase when only heavy rain samplesare selected With the exception of the CC the results of119877(119870DP) are greatly improved comparedwith119877(119885)The resultsof119877(119870DP) BSC are better than those of119877(119870DP)OKC with theBRI shape performing the best giving NE = 027 and RMSE= 67 (Table 3)

33 Discussion For rainfall heavier than 10mmhminus1 119877(119870DP)BSC BRI was most accurate but its normalized error is still

27 There could be many sources of error but the differingaccuracy of the different rainfall relations was first examinedby using the tropical 119877(119885) relation used in next generationradar (NEXRAD) in USA

119877 = 121 times 10minus2

1198850833

(10)

Figure 8 shows the comparison of gage and radar rainfallestimated for the NEXRAD 119877(119885) relation In Case 1 whererainfall was caused by the Changma front and typhoon


60

50

40

30

20

10

0

Gage total AWS (mm)

NE RMSE CCNEX 039 31 080

6050403020100

Rada

r tot

alR

(Z)

(a)

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Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(b)

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0

Gage total AWS (mm)


1009080706050403020100

Rada

r tot

alR

(Z)

(c)

Figure 8 Scatterplots of gage rainfall against radar rainfall obtained using the tropical 119877(119885) relation derived from the US NEXRAD networkfor (a) Case 1 (b) Case 2 and (c) Case 3

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(a)

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(b)

3

2

1

0

minus1

ZD

R(d

B)20 30 40 50

Z (dBZ)

(c)

Figure 9 Scatterplots of average 119885 against 119885DR for (a) Case 1 (b) Case 2 and (c) Case 3

Table 3 Rainfall statistics for the different relations for high rainfallrate conditions for all three cases combined

Number Relation NE RMSE CC1 119877 = 364 times 10

minus2

1198850625 052 115 078

2 119877 = 440119870DP0822 039 92 078

3 119877 = 503119870DP0812 032 80 078

4 119877 = 473119870DP0791 034 84 077

5 119877 = 509119870DP0827 033 80 078

6 119877 = 614119870DP0833 027 67 078

7 119877 = 534119870DP0787 029 74 078

NE = 039 RMSE = 31 and CC = 08 and its performanceis much better than that of 119877(119870DP) In the other two caseswith either only the Changma front or only the typhoon theradar rainfall was not in good agreement with the gage Thiswas particularly so in Case 3 with RMSE = 240mmhminus1 eventhough it was typhoon rainfall The difference in accuracywith each rainfall case was greater than that of 119877(119870DP) Itis believed that 119870DP is less sensitive to the DSD variationassociated with different precipitation types than is thereflectivity

Secondly average 119885 and 119885DR were calculated for therainfall periods in each case (Figure 9) Small raindrops with

119885DR less than 1 dB were dominant in all cases but therewere significant differences in the reflectivity The 119885-119885DRscattering distribution is also different from the general onein which 119885DR increases with 119885 and this would affect theaccuracy of 119877(119870DP) Accordingly it may be necessary tocalculate the 119877(119870DP) only for rainfall caused by the typhoon

4 Summary and Conclusions

Within several years polarimetric radars will be the maintools to monitor and forecast severe weather and flash floo-ding in Korea To assess the performance of rainfall estima-tion using specific differential phase observed from the Bis-lsan radar the first polarimetric radar installed inKorea threerainfall cases were selected for 2011 These were associatedwith different conditions the Changma front and typhoononly the Changma front and only a typhoon

For quantitative use of 119870DP a data quality algorithmfor differential phase shift was developed The algorithmis composed of two steps the unfolding of ΦDP and theremoval of scattered noise This order is important to ensurethat areas of folded ΦDP which are part of the real mete-orological target are not removed as noise All noise wasremoved and folded ΦDP were unfolded This algorithm isessential for the use of 119870DP for many applications such as


rainfall estimation hydrometeor classification and numeri-cal modeling

The 119877(119870DP) relations for S-band polarimetric radar werecalculated using 84754 samples of observed DSD data withthree different drop shape assumptions equilibrium shapethe Brandes drop shape and the Bringi drop shape To assessthe performance of these relationships we compared themwith the results of theMP119877(119885) relation and119877(119870DP) obtainedat Oklahoma in the USA

For Case 1 (the rainfall caused by the Changma front andtyphoon) the values of NE RMSE and CC for radar rainfalldetermined by 119877(119885) were 054mm 43mm and 082mmrespectively Rainfall obtained using the 119877(119870DP) OKC andBSChad similar statistics regardless of the drop shapeValuesof CC and NE determined by 119877(119885)were better than those for119877(119870DP) but the RMSE of 119877(119870DP) was slightly better Case 2showed a similar pattern to Case 1 but the RMSE of 119877(119870DP)with EQUdrop shapewas the best of the119877(119870DP)BSC InCase3 119877(119885) showed good results in all statistics and the RMSE of119877(119870DP) BSC showed better performance than that of 119877(119870DP)OKC

To compare the performance of each relation for heavierrainfall the gage rainfall samples with intensity greater than10mmhminus1 in all cases were selected and analyzed With theexception of the CC the results of 119877(119870DP) improved consi-derably compared with those of 119877(119885) The 119877(119870DP) BSC gavebetter results than the 119877(119870DP) OKC Of the results from119877(119870DP) BSC the relation using the BRI drop shape showedthe best statistics with NE = 027 and RMSE = 67mm

Finally quality control of differential phase shift is essen-tial to obtain reliable119870DP which is an important polarimetricvariable for many purposes The relation 119877(119870DP) should becalculated using a DSD that reflects the characteristics ofthe region Further since the accuracy of rainfall estimationis affected by the drop shape assumption this assumptionshould be considered in developing an optimal rainfall esti-mation algorithm using other polarimetric variables Altho-ugh further research is required the results of this study areexpected to contribute to various fields such as hydrometeorclassification and to improve the operational accuracy ofrainfall estimation from polarimetric radar in Korea

Conflict of Interests

The authors declare that they have no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors acknowledge the provision of radar data andAWS data for this work by the Ministry of Land Trans-portation and the Korea Meteorological AdministrationTheauthors also acknowledge the code for simulating scatteringprovided by Professor V N Bringi at Colorado State Univer-sity This research was supported by the National ResearchFoundation of Korea (NRF) through a Grant provided bythe Korean Ministry of Education Science amp Technology(MEST) in 2014 (no K200603874)Thisworkwas also funded

by the Korea Meteorological Administration Research andDevelopment Program under Grant CATER 2012-2071 andJSTCREST

References

[1] E Campos and I Zawadzki ldquoInstrumental uncertainties in Z-R relationsrdquo Journal of Applied Meteorology vol 39 no 7 pp1088ndash1102 2000

[2] C-H You D-I Lee S-M Jang et al ldquoCharacteristics of rain-fall systems accompanied with Changma front at Chujado inKoreardquo Asia-Pacific Journal of Atmospheric Sciences vol 46 no1 pp 41ndash51 2010

[3] J W Wilson and E A Brandes ldquoRadar measurement of rain-fallmdasha summaryrdquo Bulletin of the American Meteorological Soci-ety vol 60 no 9 pp 1048ndash1058 1979

[4] P M Austin ldquoRelations between measured radar reflectivityand surface rainfallrdquo Monthly Weather Review vol 115 no 5pp 1053ndash1070 1987

[5] C You D Lee M Jang K Seo K Kim and B Kim ldquoThecharacteristics of rain drop size distributions using a POSS inBusan areardquo Journal of the Korean Meteorological Society vol40 no 6 pp 713ndash724 2004

[6] M JangD Lee andC You ldquoZ-R relationship andDSDanalysesusing a POSSdisdrometermdashpart I precipitation cases in BusanrdquoJournal of the Korean Meteorological Society vol 40 pp 557ndash570 2004

[7] M Suk K Nam Y Kim and S Oh ldquoEstimation of quantitativerain intensity from radar reflectivities using a wind probabilitymatchingmethodrdquo Journal of the KoreanMeteorological Societyvol 41 pp 123ndash138 2005

[8] J Vivekanandan D S Zrnic S M Ellis R Oye A V Ryzhkovand J Straka ldquoCloud microphysics retrieval using S-band dual-polarization radar measurementsrdquo Bulletin of the AmericanMeteorological Society vol 80 no 3 pp 381ndash388 1999

[9] A V Ryzhkov and D S Zrnic ldquoDiscrimination between rainand snow with a polarimetric radarrdquo Journal of Applied Meteo-rology vol 37 no 10 pp 1228ndash1240 1998

[10] S E Giangrande and A V Ryzhkov ldquoEstimation of rainfallbased on the results of polarimetric echo classificationrdquo Journalof AppliedMeteorology and Climatology vol 47 no 9 pp 2445ndash2462 2008

[11] A V Ryzhkov and D S Zrnic ldquoAssessment of rainfall measure-ment that uses specific differential phaserdquo Journal of AppliedMeteorology vol 35 no 11 pp 2080ndash2090 1996

[12] P T May T D Keenan D S Zrnic L D Carey and S ARutledge ldquoPolarimetric radar measurements of tropical rain ata 5-cm wavelengthrdquo Journal of Applied Meteorology vol 38 no6 pp 750ndash765 1999

[13] V N Bringi and V Chandrasekar The Polarimetric Basisfor Characterizing Precipitation Polarimetric Doppler WeatherRadar Principles and Applications CambridgeUniversity PressCambridge UK 2001

[14] E A Brandes G Zhang and J Vivekanandan ldquoExperimentsin rainfall estimation with a polarimetric radar in a subtropicalenvironmentrdquo Journal of Applied Meteorology vol 41 pp 674ndash685 2002

[15] A V Ryzhkov T J Schuur D W Burgess P L Heinselman SE Giangrande and D S Zrnic ldquoThe joint polarization exper-iment polarimetric rainfall measurements and hydrometeor


classificationrdquo Bulletin of the American Meteorological Societyvol 86 no 6 pp 809ndash824 2005

[16] R Cifelli V Chandrasekar S Lim P C Kennedy Y Wangand S A Rutledge ldquoA new dual-polarization radar rainfall algo-rithm application in Colorado precipitation eventsrdquo Journal ofAtmospheric andOceanic Technology vol 28 no 3 pp 352ndash3642011

[17] N Balakrishnan and D S Zrnic ldquoEstimation of rain and hailrates in mixed-phase precipitationrdquo Journal of the AtmosphericSciences vol 47 no 5 pp 565ndash583 1990

[18] K Aydin V N Bringi and L Liu ldquoRain-rate estimation in thepresence of hail using S-band specific differential phase andother radar parametersrdquo Journal of AppliedMeteorology vol 34no 2 pp 404ndash410 1995

[19] C You M Kang D Lee and H Uyeda ldquoRainfall estimation byS-band polarimetricradar in Koreamdashpart I preprocessing andpreliminary resultsrdquoMeteorological Applications In press

[20] B E Sheppard ldquoThe measurement of raindrop size distribu-tions using a small Doppler radarrdquo Journal of Atmospheric andOceanic Technology vol 7 pp 255ndash268 1990

[21] P CWaterman ldquoSymmetry unitarity and geometry in electro-magnetic scatteringrdquo Physical Review D vol 3 no 4 pp 825ndash839 1971

[22] M IMishchenko LD Travis andDWMackowski ldquoT-matrixcomputations of light scattering by nonspherical particles areviewrdquo Journal of Quantitative Spectroscopy and RadiativeTransfer vol 55 no 5 pp 535ndash575 1996

[23] A V Ryzhkov S E Giangrande V M Melnikov and T JSchuur ldquoCalibration issues of dual-polarization radar measure-mentsrdquo Journal of Atmospheric and Oceanic Technology vol 22no 8 pp 1138ndash1155 2005

[24] K V Beard andC C Chuang ldquoA newmodel for the equilibriumshape of raindropsrdquo Journal of the Atmospheric Sciences vol 44pp 1509ndash1524 1987

[25] K Andsager K V Beard andN F Laird ldquoLaboratorymeasure-ments of axis ratios for large raindropsrdquo Journal of the Atmo-spheric Sciences vol 56 no 15 pp 2673ndash2683 1999

[26] V N Bringi V Chandrasekar J Hubbert E Gorgucci W LRandeu and M Schoenhuber ldquoRaindrop size distribution indifferent climatic regimes from disdrometer and dual-polarizedradar analysisrdquo Journal of the Atmospheric Sciences vol 60 no2 pp 354ndash365 2003

[27] A V Ryzhkov D S Zrnic J C Hubbert V N Bringi J Vive-kanandan and E A Brandes ldquoPolarimetric radar observationsand interpretation of co-cross-polar correlation coefficientsrdquoJournal of Atmospheric and Oceanic Technology vol 19 no 3pp 340ndash354 2002

[28] S YMatrosov KAClark B EMartner andA Tokay ldquoX-bandpolarimetric radar measurements of rainfallrdquo Journal of AppliedMeteorology vol 41 no 9 pp 941ndash952 2002

[29] T D Keenan D S Zrnic L Carey and P May ldquoSensitivityof 5-cm wavelength polarimetric radar variables to raindropaxial ratio anddrop size distributionsrdquo Journal of AppliedMeteo-rology vol 40 pp 526ndash545 2001

[30] A V Ryzhkov S E Giangrande and T J Schuur ldquoRainfall esti-mation with a polarimetric prototype of WSR-88Drdquo Journal ofApplied Meteorology vol 44 no 4 pp 502ndash515 2005

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

EcologyInternational Journal of


EarthquakesJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Mining


Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

OceanographyInternational Journal of


Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal ofPetroleum Engineering


GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Atmospheric SciencesInternational Journal of


OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in


MineralogyInternational Journal of


MeteorologyAdvances in

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Geological ResearchJournal of


Geology Advances in


40

38

36

34

32

Latit

ude (

nort

h)

Latit

ude (

nort

h)

122 124 126 128 130 132

Longitude (east)

Longitude (east)

BISL

POSS

3650

36

3550

35

3650

36

3550

35

12750 128 12850 129 12950

12750 128 12850 129 12950

(a) (b)Figure 1 The location of the Bislsan radar (solid rectangle) the POSS disdrometer (open rectangle) and rain gages (plus signs) distributedwithin the area of radar coverage (100 km radius)

blockage It is also closely related to rain intensity even in thepresence of dry tumbling hail [17 18]

Three major agencies use radars to monitor and forecastsevere weather and flash floods operationally in Korea theMinistry of National Defense (MND) the Ministry of LandInfrastructure and Transportation (MOLIT) and the KoreaMeteorological Administration (KMA) MOLIT installedpolarimetric radars for the first time in Korea in 2009and 2012 The successful implementation of these radarsfor operational use requires studies of rainfall estimationhydrometeor classification and DSD retrieval Howeverthere are few studies on these polarimetric related issuesother than for deriving relationships using long perioddisdrometer data assessing each relation after applying a verysimple quality control for differential phase shift [19] Theaccuracy of rainfall estimation using 119877(119870DP) was found to beworse than that of 119877(119885 119885

119863119877

)This paper discusses how the accuracy of rainfall esti-

mation can be improved using specific differential phasemeasured by the first polarimetric radar installed in KoreaSection 2 describes the data used in this study the calculationof the relationship between specific differential phase and rainrate the data quality control of differential phase shift andthe statistical validation Section 3 gives results for rainfallestimation using specific differential phase and describes theeffect of quality control of differential phase shift includingthe unfolding algorithm Finally Section 4 summarizes theresults and provides some concluding remarks

2 Data and Methodology

21 Rain Gage and Radar Dataset The rainfall data fromrain gages operated by the KMA were used to evaluate theaccuracy of radar rainfall Rain gages located at distances of5 km to 100 km from the radar are included in the analysisFigure 1 shows the location of all instruments used in this

study The circle represents the radar coverage the solidrectangle is the center of the Bislsan radar plus signs show thedistributed rain gageswithin the radar coverage and the openrectangle is the position of a POSS (Precipitation OccurrenceSensor System) disdrometer whichwas located around 82 kmfrom the radar The POSS disdrometer will be described inmore detail in the next section

Radar data were collected by the Bislsan S-band polari-metric radar which was installed and operated by MOLITin Korea from 2009 The transmitted peak power is 750 kWbeam width is 095∘ and frequency is about 28GHz Hori-zontal and vertical reflectivity (119885

ℎ

119885V) radial velocity (VR)spectrumwidth (SW) differential reflectivity (119885DR) differen-tial phase shift (ΦDP) specific differential phase (119870DP) andcross correlation coefficient (120588

ℎV) are estimated with a gatesize of 0125 kmThe scan strategy is composed of 6 elevationangles with a 25-minute update interval The values of ΦDPand 119870DP for 05∘ elevation angle were extracted from thevolume data every 25 minutes

The quality control algorithm consists of aΦDP unfoldingstage and a noise removal stage It is applied to improverainfall estimates The maximum observable value of ΦDP is180∘ for the Bislsan radar in 2011 If the real ΦDP exceeds thisvalue in the case of heavy rainfallΦDP may be folded (aliased)and should be unfolded for quantitative useThe procedure tounfold ΦDP is as follows

(1) Check for folding by comparing the difference bet-ween the current gate value of ΦDP and the medianofΦDP for the previous 24 gates

(2) The gage is designated as a folded gate if the differencesatisfies the conditions shown in Figure 2

(3) If it is folded add 180∘ to the folded valueNoise removal is performed after unfolding as follows(1) calculation of standard deviation ofΦDP using 9 gates

centered on the target gate


Last gate

No

No


No

Last ray

Yes

No

No

j = j + 1








f = ff + 180∘ f = ff













Filling of gap





Remove noise ΦDP


Calculation of N25



Std phi calculation


KDP calculation


0 50 100 150 200

Rain rate (mmhr)

Tota

l tim

e (m

inut

es)

105

104

103

102

101

100

10minus1






119903 = 10048 + 0500057119863 minus 0026281198632

+ 00036821198633

minus 000016771198634

(1)


119903 = 1012 minus 001445119863 minus 0010281198632

(2)


119903 = 09951 + 0025119863 minus 0036441198632

+ 00053031198633

+ 000024921198634

(3)



NE =(1119873)sum

119873

119894=1

(1003816100381610038161003816119877119877119894 minus 119877119866119894

1003816100381610038161003816)

119877119866

(4)

RMSE = [ 1119873

119873

sum

119894=1

(119877119877119894

minus 119877119866119894

)2

]

12

(5)

CC =sum119873

119894=1

(119877119877119894

minus 119877119877

) (119877119866119894

minus 119877119866

)

[sum119873

119894=1

(119877119877119894

minus 119877119877

)]12

[sum119873

119894=1

119877119866119894

minus 119877119866

]12

(6)


and 119877119866

pairs and 119877119877

and 119877119866


3 Results







1200

900

600

300

01 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

Tota

l rai

nfal

l am

ount

(mm

)

(a)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(b)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(c)





119877 = 509119870DP0827 (7)

119877 = 614119870DP0833 (8)

119877 = 534119870DP0787

(9)



minus2


2 119877 = 440119870DP0822


3 119877 = 503119870DP0812


4 119877 = 473119870DP0791


5 119877 = 509119870DP0827


6 119877 = 614119870DP0833


7 119877 = 534119870DP0787






300

240

200

180

160

140

120

100

80

60

40

20

10


(a)


300

240

200

180

160

140

120

100

80

60

40

20

10


(b)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(c)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(d)







60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 056 38 066

BRI 057 38 066

Rada

r tot

alR

(KD

P) O

KC(b)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 059 38 066

BRI 061 38 066

Rada

r tot

alR

(KD

P) B

SC

(c)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(d)

6050403020100

Gage total AWS (mm)


BRA 047 44 081

BRI 048 44 081

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(e)

6050403020100

081

081081

Gage total AWS (mm)


BRA 051 45

BRI 056 49

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC

(f)

Gage total AWS (mm)


100

90

80

70

60

50

40

30

20

10

01009080706050403020100

Rada

r tot

alR

(Z)

(g)

Gage total AWS (mm)


BRA 044 73 091

BRI 043 69 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(h)

Gage total AWS (mm)


BRA 044 68 091

BRI 046 68 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC





119877 = 121 times 10minus2

1198850833

(10)



60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(b)

100

90

80

70

60

50

40

30

20

10

0

Gage total AWS (mm)


1009080706050403020100

Rada

r tot

alR

(Z)

(c)


3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(a)

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(b)

3

2

1

0

minus1

ZD

R(d

B)20 30 40 50

Z (dBZ)

(c)




minus2

1198850625 052 115 078

2 119877 = 440119870DP0822 039 92 078

3 119877 = 503119870DP0812 032 80 078

4 119877 = 473119870DP0791 034 84 077

5 119877 = 509119870DP0827 033 80 078

6 119877 = 614119870DP0833 027 67 078

7 119877 = 534119870DP0787 029 74 078















Acknowledgments



References










































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


Last gate

No

No


No

Last ray

Yes

No

No

j = j + 1








f = ff + 180∘ f = ff













Filling of gap





Remove noise ΦDP


Calculation of N25



Std phi calculation


KDP calculation


0 50 100 150 200

Rain rate (mmhr)

Tota

l tim

e (m

inut

es)

105

104

103

102

101

100

10minus1






119903 = 10048 + 0500057119863 minus 0026281198632

+ 00036821198633

minus 000016771198634

(1)


119903 = 1012 minus 001445119863 minus 0010281198632

(2)


119903 = 09951 + 0025119863 minus 0036441198632

+ 00053031198633

+ 000024921198634

(3)



NE =(1119873)sum

119873

119894=1

(1003816100381610038161003816119877119877119894 minus 119877119866119894

1003816100381610038161003816)

119877119866

(4)

RMSE = [ 1119873

119873

sum

119894=1

(119877119877119894

minus 119877119866119894

)2

]

12

(5)

CC =sum119873

119894=1

(119877119877119894

minus 119877119877

) (119877119866119894

minus 119877119866

)

[sum119873

119894=1

(119877119877119894

minus 119877119877

)]12

[sum119873

119894=1

119877119866119894

minus 119877119866

]12

(6)


and 119877119866

pairs and 119877119877

and 119877119866


3 Results







1200

900

600

300

01 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

Tota

l rai

nfal

l am

ount

(mm

)

(a)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(b)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(c)





119877 = 509119870DP0827 (7)

119877 = 614119870DP0833 (8)

119877 = 534119870DP0787

(9)



minus2


2 119877 = 440119870DP0822


3 119877 = 503119870DP0812


4 119877 = 473119870DP0791


5 119877 = 509119870DP0827


6 119877 = 614119870DP0833


7 119877 = 534119870DP0787






300

240

200

180

160

140

120

100

80

60

40

20

10


(a)


300

240

200

180

160

140

120

100

80

60

40

20

10


(b)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(c)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(d)







60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 056 38 066

BRI 057 38 066

Rada

r tot

alR

(KD

P) O

KC(b)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 059 38 066

BRI 061 38 066

Rada

r tot

alR

(KD

P) B

SC

(c)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(d)

6050403020100

Gage total AWS (mm)


BRA 047 44 081

BRI 048 44 081

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(e)

6050403020100

081

081081

Gage total AWS (mm)


BRA 051 45

BRI 056 49

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC

(f)

Gage total AWS (mm)


100

90

80

70

60

50

40

30

20

10

01009080706050403020100

Rada

r tot

alR

(Z)

(g)

Gage total AWS (mm)


BRA 044 73 091

BRI 043 69 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(h)

Gage total AWS (mm)


BRA 044 68 091

BRI 046 68 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC





119877 = 121 times 10minus2

1198850833

(10)



60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(b)

100

90

80

70

60

50

40

30

20

10

0

Gage total AWS (mm)


1009080706050403020100

Rada

r tot

alR

(Z)

(c)


3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(a)

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(b)

3

2

1

0

minus1

ZD

R(d

B)20 30 40 50

Z (dBZ)

(c)




minus2

1198850625 052 115 078

2 119877 = 440119870DP0822 039 92 078

3 119877 = 503119870DP0812 032 80 078

4 119877 = 473119870DP0791 034 84 077

5 119877 = 509119870DP0827 033 80 078

6 119877 = 614119870DP0833 027 67 078

7 119877 = 534119870DP0787 029 74 078















Acknowledgments



References










































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in





119903 = 10048 + 0500057119863 minus 0026281198632

+ 00036821198633

minus 000016771198634

(1)


119903 = 1012 minus 001445119863 minus 0010281198632

(2)


119903 = 09951 + 0025119863 minus 0036441198632

+ 00053031198633

+ 000024921198634

(3)



NE =(1119873)sum

119873

119894=1

(1003816100381610038161003816119877119877119894 minus 119877119866119894

1003816100381610038161003816)

119877119866

(4)

RMSE = [ 1119873

119873

sum

119894=1

(119877119877119894

minus 119877119866119894

)2

]

12

(5)

CC =sum119873

119894=1

(119877119877119894

minus 119877119877

) (119877119866119894

minus 119877119866

)

[sum119873

119894=1

(119877119877119894

minus 119877119877

)]12

[sum119873

119894=1

119877119866119894

minus 119877119866

]12

(6)


and 119877119866

pairs and 119877119877

and 119877119866


3 Results







1200

900

600

300

01 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

Tota

l rai

nfal

l am

ount

(mm

)

(a)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(b)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(c)





119877 = 509119870DP0827 (7)

119877 = 614119870DP0833 (8)

119877 = 534119870DP0787

(9)



minus2


2 119877 = 440119870DP0822


3 119877 = 503119870DP0812


4 119877 = 473119870DP0791


5 119877 = 509119870DP0827


6 119877 = 614119870DP0833


7 119877 = 534119870DP0787






300

240

200

180

160

140

120

100

80

60

40

20

10


(a)


300

240

200

180

160

140

120

100

80

60

40

20

10


(b)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(c)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(d)







60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 056 38 066

BRI 057 38 066

Rada

r tot

alR

(KD

P) O

KC(b)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 059 38 066

BRI 061 38 066

Rada

r tot

alR

(KD

P) B

SC

(c)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(d)

6050403020100

Gage total AWS (mm)


BRA 047 44 081

BRI 048 44 081

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(e)

6050403020100

081

081081

Gage total AWS (mm)


BRA 051 45

BRI 056 49

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC

(f)

Gage total AWS (mm)


100

90

80

70

60

50

40

30

20

10

01009080706050403020100

Rada

r tot

alR

(Z)

(g)

Gage total AWS (mm)


BRA 044 73 091

BRI 043 69 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(h)

Gage total AWS (mm)


BRA 044 68 091

BRI 046 68 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC





119877 = 121 times 10minus2

1198850833

(10)



60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(b)

100

90

80

70

60

50

40

30

20

10

0

Gage total AWS (mm)


1009080706050403020100

Rada

r tot

alR

(Z)

(c)


3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(a)

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(b)

3

2

1

0

minus1

ZD

R(d

B)20 30 40 50

Z (dBZ)

(c)




minus2

1198850625 052 115 078

2 119877 = 440119870DP0822 039 92 078

3 119877 = 503119870DP0812 032 80 078

4 119877 = 473119870DP0791 034 84 077

5 119877 = 509119870DP0827 033 80 078

6 119877 = 614119870DP0833 027 67 078

7 119877 = 534119870DP0787 029 74 078















Acknowledgments



References










































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


1200

900

600

300

01 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

Tota

l rai

nfal

l am

ount

(mm

)

(a)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(b)

1 3 6 9 12 15 18 21 00 3 6 9 12 15 18 21 24

Time (hour LST)

1200

900

600

300

0

Tota

l rai

nfal

l am

ount

(mm

)

(c)





119877 = 509119870DP0827 (7)

119877 = 614119870DP0833 (8)

119877 = 534119870DP0787

(9)



minus2


2 119877 = 440119870DP0822


3 119877 = 503119870DP0812


4 119877 = 473119870DP0791


5 119877 = 509119870DP0827


6 119877 = 614119870DP0833


7 119877 = 534119870DP0787






300

240

200

180

160

140

120

100

80

60

40

20

10


(a)


300

240

200

180

160

140

120

100

80

60

40

20

10


(b)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(c)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(d)







60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 056 38 066

BRI 057 38 066

Rada

r tot

alR

(KD

P) O

KC(b)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 059 38 066

BRI 061 38 066

Rada

r tot

alR

(KD

P) B

SC

(c)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(d)

6050403020100

Gage total AWS (mm)


BRA 047 44 081

BRI 048 44 081

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(e)

6050403020100

081

081081

Gage total AWS (mm)


BRA 051 45

BRI 056 49

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC

(f)

Gage total AWS (mm)


100

90

80

70

60

50

40

30

20

10

01009080706050403020100

Rada

r tot

alR

(Z)

(g)

Gage total AWS (mm)


BRA 044 73 091

BRI 043 69 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(h)

Gage total AWS (mm)


BRA 044 68 091

BRI 046 68 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC





119877 = 121 times 10minus2

1198850833

(10)



60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(b)

100

90

80

70

60

50

40

30

20

10

0

Gage total AWS (mm)


1009080706050403020100

Rada

r tot

alR

(Z)

(c)


3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(a)

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(b)

3

2

1

0

minus1

ZD

R(d

B)20 30 40 50

Z (dBZ)

(c)




minus2

1198850625 052 115 078

2 119877 = 440119870DP0822 039 92 078

3 119877 = 503119870DP0812 032 80 078

4 119877 = 473119870DP0791 034 84 077

5 119877 = 509119870DP0827 033 80 078

6 119877 = 614119870DP0833 027 67 078

7 119877 = 534119870DP0787 029 74 078















Acknowledgments



References










































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



300

240

200

180

160

140

120

100

80

60

40

20

10


(a)


300

240

200

180

160

140

120

100

80

60

40

20

10


(b)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(c)


300

240

200

180

160

140

120

100

80

60

40

20

10

1

20110808 2464 KST EL 050


(d)







60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 056 38 066

BRI 057 38 066

Rada

r tot

alR

(KD

P) O

KC(b)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 059 38 066

BRI 061 38 066

Rada

r tot

alR

(KD

P) B

SC

(c)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(d)

6050403020100

Gage total AWS (mm)


BRA 047 44 081

BRI 048 44 081

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(e)

6050403020100

081

081081

Gage total AWS (mm)


BRA 051 45

BRI 056 49

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC

(f)

Gage total AWS (mm)


100

90

80

70

60

50

40

30

20

10

01009080706050403020100

Rada

r tot

alR

(Z)

(g)

Gage total AWS (mm)


BRA 044 73 091

BRI 043 69 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(h)

Gage total AWS (mm)


BRA 044 68 091

BRI 046 68 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC





119877 = 121 times 10minus2

1198850833

(10)



60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(b)

100

90

80

70

60

50

40

30

20

10

0

Gage total AWS (mm)


1009080706050403020100

Rada

r tot

alR

(Z)

(c)


3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(a)

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(b)

3

2

1

0

minus1

ZD

R(d

B)20 30 40 50

Z (dBZ)

(c)




minus2

1198850625 052 115 078

2 119877 = 440119870DP0822 039 92 078

3 119877 = 503119870DP0812 032 80 078

4 119877 = 473119870DP0791 034 84 077

5 119877 = 509119870DP0827 033 80 078

6 119877 = 614119870DP0833 027 67 078

7 119877 = 534119870DP0787 029 74 078















Acknowledgments



References










































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 056 38 066

BRI 057 38 066

Rada

r tot

alR

(KD

P) O

KC(b)

60

50

40

30

20

10

06050403020100

Gage total AWS (mm)


BRA 059 38 066

BRI 061 38 066

Rada

r tot

alR

(KD

P) B

SC

(c)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(d)

6050403020100

Gage total AWS (mm)


BRA 047 44 081

BRI 048 44 081

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(e)

6050403020100

081

081081

Gage total AWS (mm)


BRA 051 45

BRI 056 49

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC

(f)

Gage total AWS (mm)


100

90

80

70

60

50

40

30

20

10

01009080706050403020100

Rada

r tot

alR

(Z)

(g)

Gage total AWS (mm)


BRA 044 73 091

BRI 043 69 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) O

KC

(h)

Gage total AWS (mm)


BRA 044 68 091

BRI 046 68 091

1009080706050403020100

100

90

80

70

60

50

40

30

20

10

0

Rada

r tot

alR

(KD

P) B

SC





119877 = 121 times 10minus2

1198850833

(10)



60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(b)

100

90

80

70

60

50

40

30

20

10

0

Gage total AWS (mm)


1009080706050403020100

Rada

r tot

alR

(Z)

(c)


3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(a)

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(b)

3

2

1

0

minus1

ZD

R(d

B)20 30 40 50

Z (dBZ)

(c)




minus2

1198850625 052 115 078

2 119877 = 440119870DP0822 039 92 078

3 119877 = 503119870DP0812 032 80 078

4 119877 = 473119870DP0791 034 84 077

5 119877 = 509119870DP0827 033 80 078

6 119877 = 614119870DP0833 027 67 078

7 119877 = 534119870DP0787 029 74 078















Acknowledgments



References










































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(a)

60

50

40

30

20

10

0

Gage total AWS (mm)


6050403020100

Rada

r tot

alR

(Z)

(b)

100

90

80

70

60

50

40

30

20

10

0

Gage total AWS (mm)


1009080706050403020100

Rada

r tot

alR

(Z)

(c)


3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(a)

3

2

1

0

minus1

ZD

R(d

B)

20 30 40 50

Z (dBZ)

(b)

3

2

1

0

minus1

ZD

R(d

B)20 30 40 50

Z (dBZ)

(c)




minus2

1198850625 052 115 078

2 119877 = 440119870DP0822 039 92 078

3 119877 = 503119870DP0812 032 80 078

4 119877 = 473119870DP0791 034 84 077

5 119877 = 509119870DP0827 033 80 078

6 119877 = 614119870DP0833 027 67 078

7 119877 = 534119870DP0787 029 74 078















Acknowledgments



References










































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in









Acknowledgments



References










































Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



























Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in

research article rainfall estimation using specific differential...

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