Improved Data Processing X Band Radar Leuven

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Improved DataProcessingfor a Low-Cost Portable X-

Band Radar in Leuven Area

Promotor:Prof P !illems

"aster dissertation in partial fulfilmentof t#e re$uirements for t#e Degree of

Master of Science in Water Resources Engineeringb%: Carlos "u&o' L(pe'

)eptember *+,


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Acknowledgements

I would like to express my sincere gratitude to my promoter Prof. dr. ir. Patrick Willems for valuable

suggestions and guidance in this thesis and during the whole academic year.

I would also like to thank my advisor ir. Lipen Wang for his permanent availability and valuable comments

and advises during the development of this Master thesis.

My sincere gratitude and admiration for each of my classmates. I have learned from them and I have

always received good advises and encouragement during all this time.

Remember all the staff of IPW!R" Master Programme# for this special academic year spent in $elgium.

$esides# I would like to thank the %lemish !&uafin Water 'ompany for providing the radar and rain gauge

series.

(pecial thanks to !melia and )offre# thanks for your support and invaluable help. !nd one last personal

comment# I will always be deeply thankful to all my family members to bring me up in humility values.

'arlos Mu*o+# (eptember ,-/


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TABLE OF CONTENTS I01R23'1I20 .......................... ...................... ............................ ................... ............................... ..

. Problem 3efinition ........................... ...................... ............................ ................... ...................

., Main 2b4ectives .......................... ...................... ............................... ................... ...................... ,

.5 1hesis (ummary ......................... ....................... ........................... ...................... ...................... 5

, R!I0%!LL M"!(R"M"01( ......................... ......................... ........................... .................... ............. 5

,. 1ypes of Precipitation ....................... ...................... ............................ ................... ................... 5

,., 1ipping $ucket Rain 6auges ...................... ............................ ..................... .......................... ..... 7

,.,. Working principle of the tipping bucket rain gauge .......................... .................... ............. 7

,.,., ncertainties in rain gauge measurements. ........................ ........................... ................... 7

,.5 Weather Radars .......................... ...................... ............................... ................... ...................... 8

,.5. Working principle ......................... ......................... ........................... .................... ............. 8

,.5., Radar e&uation ........................... .......................... ........................... .................... ............. 9

,.5.5 1ypes of radar ........................... ...................... ............................ ................... ................... :

,.5./ (patial and temporal resolution in weather radars. .......................... .................... ...........

,./ L!WR ;


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8. Duality !nalysis Results !nd 3iscussions. ........................ ............................ .................... ........ ,8

8., Linear Regression Method Results and 3iscussions ..................... ........................... ................. 5-

8.5 Marshall EPalmer Paramenters 'alibration Method....................................... ................... ...... 5,

8./ FG< 'alibration MethodH Results !nd 3iscussion. ........................... .......................... ................ 55

8./. (patial resolution influence. ...................... ............................ .................... ...................... 5:

8./., 'lutter influence .......................... ......................... ........................... ............................ ... /-

8./.5 'overed area influence ...................... ........................... ........................ ....................... ... /5

8././ Maximum intensities # total amount of rainfall and duration influence .......................... . /5

9 '20'L(I20( !03 R"'2MM"03!1I20( ......................... ............................ ................... .............. /8

9. 'onclusions ........................... ................... ............................ ................... ............................... /8

9., Recommendations !nd %uture Work ......................... ............................ ................... .............. /?

? R"%"R"0'"( ............................ ...................... ............................ .................... ........................... ...... /:

LIST OF FIGURES

%ig ,. 3escribes the formation process of convective and stratiform events. ......................... ........ /

%ig ,., Working principlWorking principle of a TBRG ...................................................................... 7

%ig ,.5 Working principle of a weather Radar .................................................................................. 9%ig ,./ Scanned volume by a weather radar..................................................................................... ?

%ig ,.7 Beam filling volume correction .......................................................................................... 5

%ig. 5.. Climatological information of Leuven based on monthly averages .................................... 7

%ig 5., a Leuven location in Belgium !b "rovincieus building !c L#WR radar ............................... 8

%ig /. (tandard calibration method example ............................................................................... :

%ig 8.AaC Radar snapshots for the event took place on $th%une&Resol&'() m...................................... ,8

%ig 8.AbC Radar snapshots for the event took place on $th %une&Resol&()* m..................................... ,8

%ig 8., #ccumulation of the raw radar data of the whole events of +th and $th,une...................... ,9

%ig 8.5 @iguest reflectivities mapfor the whole events of +th and $th of ,une&............................ ... ,9

%ig 8./ 1wo clutter dry period snapshots of (-thand ($th,une are shown&......................... ........... ,?

%ig 8.7 !ccumulation of the raw radar data for the entire month of )une in a logarithmic scale .... ,:

%ig 8.8 Linear regression method for . of the rain gauges&............................................................. 5-

%ig 8.9 Range dependent curve for the 'alibration %actor to be applied to radar correction. .......... 5

%ig 8.? Radar and rain gauge rain rates time series for W/ Gauge for the event of 0th,une.............. 5


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%ig 8.: #ccumulation radar and gauge rainfall curves after applying correction 1 $th,une ............. 57

%ig. 8.-#ccumulation radar and gauge rainfall curves after applying correction 1 '*th ,une .......... 58

%ig 8. Radar and gauge rain rates time series G and linear regression method :th)une ................. 59

%ig 8., Radar and gauge rain rates time series for 5 of the gauges during the event of -th )une .... 5?

%ig 8.5 "ffect of applying the filter algortihm in the accumulated map of )une .......................... ...... /,

%ig 8./ Snapshot of the $thevent of ,une ttenuation issue............................................................. /7

LIST OF TABLES

1able ,. dB/ scale for weather radar&. ............................................................................................ :1able ,., Weather radar types ...................................................................................................... -

1able ,.5 L#WR city radar technical characteristics. ........................................................................ ,

1able 5. Characteristics of Leuven rain gauges& . ........................................................................... ?

1able 7. 2vents during ,une (*'+ and mean characteristics . ......................................................... ,5

1able 8. FaH values after applying calibration method during the events of )une ,-/. .................. 5,

1able 8., FbH values after applying calibration method during the events of )une ,-/. .................. 55

1able 8.5 G values during the events of )une ,-/ for an spatial resolution of ,7 meters. ............ 5/

1able 8./ 'oefficient of determination values during the events of )une ,-/ . 5/1able 8.7 G values for an spatial resolution of ,7- m during the events of )une ,-/ ..................... /-

1able 8.8 G values after applying clutter filter during the events of )une ,-/. ............................... /,

1able 8.9 1otal average area covered during the event# J respect the total covered by the radar.. /5

1able 8.? Maximum intensities at every gauge during each of the events . .......................... ........... //

1able 8.: Total rainfall accumulation at every gauge during each of the events . ........................ ... //


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Abstract

Rainfall estimation is a driving force in the field of hydrology in general and urban hydrology in particular.

Rain observations are used in hydrological applications as main inputs in the hydrologic


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1he results of the static calibration method showed a large variability in the parameters involved and no

tendency was found on them. %actor that might influence on the results obtained were analy+ed and some

recommendation were given in order to faces the challenges of the L!WR radar for the Leuven case study

in future works.

Keywords urban hydrology# radar# rainfall spatial variability# radar


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List of Symbols

!D!%I0 %lemish !&uafin Water 'ompany

'% 'oefficient factor lineal calibration method

3MI 3anish Meteorological Institute

3R2 3igital 2utputs Radar

3( 3iestestraat Rain 6auge

3(3 3rop (i+e 3istribution

"@ "gen@ovestraat Rain 6auge

6L" 6eneralised Likelihood ncertainty "stimation methodology for L!WR data calibration

@6 @ogeebeek Rain 6auge

IPW!R" Inter


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1111 INTRODUCTIONINTRODUCTIONINTRODUCTIONINTRODUCTION

1.1

Problem Definiion

Rainfall measurements is one of the most important topics in the field of urban hydrology. It is a very

dynamic variable and therefore# knowledge of its spatio


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!s it has been stated before# rain gauges have been used over the years and can certainly meet with the

temporal re&uirements but not with the spatial re&uirements unless a dense rain gauge network is

available# which can lead to unaffordable economic and maintenance costs.

It is here where the radar comes into play# and although it cannot replace the accuracy provided by a rain

gauge# it is considered as a good complement to know better the spatial and temporal variations on rainfall

events and improve the data input used in modelling. A"infalt et al ,--/C.

In this study# a specific ;


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1.' T(esis S)mm#ry

(& Rainfall measurements3 6ives some theoretical background about rainfall estimation# working principle

of weather radars and main differences between them# giving also the main characteristic of the L!WR

radar.

.& Leuven case study3 3escribes the case study under study.

+& Review of different calibration methods3 'overs a review of different calibration method related with

the methodology used in this study.

)& 4ethodology3 3escribes the methodology used and explains the calibration methods for the radar data

correction.

0& Results and discussionN 3iscusses the results obtained.

- &Conclusions and recommendationsN 'onclusions about the different approaches are given as well as

some recommendations for future work for this particular case study.

?. References

2222

RAINFALLMEASUREMENTSRAINFALLMEASUREMENTSRAINFALLMEASUREMENTSRAINFALLMEASUREMENTS

Rainfall is one of the main processes in the hydrological cycle and a driving force in urban hydrology field.

It is crucial thus# to estimate it as accurate as possible when urban models are used for different

applications such as sewer system designs or flood prevention structures.

Rainfall can be measured in different ways being time and space accuracy difficult to achieve. In this section

two main measuring instrument are discussed Athe tipping bucket rain gauge and the weather radarC along

with its possible uncertainties and challenges.

!.1 Ty*es of Pre%i*i#ion

Precipitation is an atmospheric phenomenon that starts with the condensation of steam contained in

clouds. It can fall in li&uid Arain and dri++leC or solid phase Ahail# snow# ice needles# graupel and sleetC.

Precipitation can be classified as orographic# convective or stratiform.


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2rographic precipitation is caused when a moist mass of air find an orographic obstacle# and ascend

upwards in such a way that the air expands and cools forming clouds that eventually can produce rain

events.

nlike orographic events# convective precipitations typically happen in flat or not high topographically

developed areas. 1hey occur when moist air rises by temperature differences due to local heating. 1hus#

the warm air becomes less dense starting to rise and forming vertical clouds AcumulonimbusC when it

reaches condensation levels# leading to rain and thunderstorms.

(tratiform precipitation are produced when two masses of air which have different characteristics Adensity#

moisture and temperatureC contact each other AfrontC in such a way that one layer of air it is forced over

the other. If the warm and moist layer is moving towards the cold air# the moist air rises over the cold air

creating clouds which might release rain. 1his phenomenon is called warm front and precipitation occurs

close to the front. !lternatively# it can happen that the cold mass moves towards the warm air Acold frontC

pushing it up and causing heavy rain and thunderstorm.

Fig.2. 5escribes the formation process of convective 6Strahler and Strahler! (**( and stratiform rainfall

events &Source 6www&ucar&edu&

It is worth noting that convective precipitations are generally more intense than stratiform but shorter in

time and with a high variability of intensities during the event A@ou+e# ::5# pp. :9


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!.! Ti**in+ B)%,e R#in G#)+es

2.2.1 Workingprincipleoftetipping!"cketr#ing#"ge

1he most used techni&ue for measuring rainfall is the rain gauge and specially the tipping bucket A1$R6sC

rain gauge type due to its easy working principle.

!s can be seen in the figure ,., the 1$R6 consist in a funnel that leads the collected water to a small

triangular double bucket Ametal or plasticC with a hinge at its midpoint. It is a system balance which varies

with the amount of water in the buckets. 1he rotation is produced when the bucket reaches a certain

amount of water# generally -., mm emptying the full bucket# while the other begins to fill. 1his movement

is recorded and therefore precipitation intensities can be computed.

1here are 1$R6s that can make the measurement even in case of snow events since the funnel is e&uipped

with a thermal resistance# which turn the snow into water.

Fig. 2.2 Working principle of a TBRG 6Wheatershack&com

!s it was mentioned above# the volume of water needed to tip it is generally , mm and this is denoted as

the resolution of the rain gauge. 1he way of registering the tips will influence on the rainfall rate

measurements leading to a certain advantages and disadvantages which will be discuss in the section ,.,.,.

2.2.2 Uncert#intie$inr#ing#"ge%e#$"re%ent$.

Measurements on rain gauges are sub4ected to uncertainties originated from errors during the

registrations. 1hese uncertainties can come either from the environmental conditions or the device itself.

Regarding the environmental conditions and according to WM2# losses might be produced by # the effect

of the wind which can lead to underestimations up to ,J


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/JC # by wetting on internal parts of the device and by splash


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When the electromagnetic wave from the radar is intercepted by a target# part of it is scattered in all

directions in a manner that a fraction is reflected back toward the radar and captured by the receiver#

which is normally located in the same antenna. 1he distance to the target is calculated by recording the

elapsed time between the emission and the reception# taking into account that electromagnetic waves are

transmitted at the speed of light. 1he working principle is shown in the figure ,.5.

Fig. 2.!Working principle of a weather Radar 6Cain! (**(

2.&.2 R#'#re("#tion

What the antenna records is actually the energy reflected back in the direction of the radar by the droplets

located within a certain volume Asee figure ,./C. 1hat energy# which is measured in the form of power# can

be expressed asN

= .|| . A,.CWhereN

Pr received power AWC

' radar constant

QGQ, refraction index.Adepend on the type of precipitationC

r distance from the radar to the target AmC

B radar reflectivity value Amm8Om5C


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Fig. 2." Scanned volume by a weather radar

1he reflectivity/is defined as the sum of the diameters of the droplets to the power of six contained within

a volume# i.e.

= A,.,C5iis the diameter of the raindrop in the volume 7. 1he reflectivity is an indirect measure of the rain rate.

(upported by experimental data it was found that the relationship between the two variables usually

responds to the following potential functionN

= . A,.5Cwhere Raccounts for the rain rate. 1he values of a and bdepend on drop si+e distribution A3(3C and

conse&uently on the type of storm that befalls. 1herefore the local conditions of the place where the radar

is working will lead to different values of the parameters. 1he relationship between Rand / was first

established by Marshall and Palmer in :/? with a ,-- and b .8# which in the following years it has

been the most used relation in this field for stratiform precipitation. Probert


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a larger concentration in space. Meanwhile# for the case of thunderstorm the opposite occurs since the

raindrops are bigger in average but with smaller concentrations.

(everal authors defend that in places where rainfall events are often a mixture of all types of rain# the

initial relation of Palmer and Marshall is the most appropriate. AMilan Slek et al# ,--/C.

1herefore# it seems that an accurate estimation of the precipitation with radar needs the use of a dynamic

relation in the Marshall and Palmer e&uation. @owever# in reality it is more common to use a fixed /


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Table 2.2 Weather radar types&

!s main concept# radars with higher wave lengths and low fre&uencies produce stronger signals# having a

larger measurement range capacity but re&uiring bigger and expensive antennas. (


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2.&.* Sp#ti#l#n'te%por#lre$ol"tionin+e#terr#'#r$.

In order to obtain better estimates of rainfall# the radar must provide an ade&uate spatio


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modelC AL!WR 'RC# A3@I#,--C. 1he model used in the study area is the L!WR 'R# whose technical

specifications are shown in the next table.

Table 2.!L#WR City Radar technical characteristics&

Parameter 'ity


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fact that the wide opening angle of the beam results in an increase of the volume targeted# which in turn#

depends on the range. 1his leads# for instance# to the fact that a relative small amount of rain drops can

be observed at a close range# while the same amount at further ranges# might escape to the observation

of the radar since this value would be averaged in a larger volume where no rain is present# leading thus

to values that might be below the cut


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nsamples 0umber of samples in a single scan line# typical value is ?---

X # ' "mpirical constants A.7 and ,--# respectivelyC

'lutter is defined as echoes in the radar not originated from precipitation. It is important in this case# to

keep in mind the opening of the radar beam# which deflects towards the ground# producing therefore a

fake signal called Fground clutterH. In this the Leuven case# the wall of the building where the radar is placed#

plays the role of a fence# in such a way that the lower part of the emission is cut


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reflectivity given by the disdrometers# the '


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calibration. !s a general rule# in this study area# the precipitations can be classified as convective or

stratiform. 3uring the summer convective storms predominates# while the stratiform type# usually occurs

more in winter# although the contrary is not as unusual. It might also happen that both types of events

may simultaneously occur in time A(teiner #::7C.

'.! Lo%#ion

1he chosen location for the radar installation AProvincieus building# fig. 5.,C and the reasons are specified

in the above section ,./.

Fig. !.2 a Leuven location in Belgium ! b "rovincieus building !c L#WR radar 65ecloedt!(*'(

3espite the low output power emitted# the radar is not allowed to broadcast electromagnetic waves

towards the airport direction upon the government authorities recommendation. 1he figure 5.5 illustrates

the situation.

Fig. !.! Rain gauges locations! and airport blocked beam area &Circles radius 6)! '* km L!WR

Leuven city radar.


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'. Le)&en R#in G#)+es

'oncerning the rain gauges involved in this study# it has been used a set of eight gauges belonging to

!D!%I0. 1he set of rain gauges are described in the table A5.C where the temporal resolution Y t!and

tipping depth resolution Aconcepts already explained in Asection R6CC are shown along with the distance to

the radar.

Table !. Characteristics of Leuven rain gauges&

'ode Location Y t AminC R AmmC 3istance AmCWB RWBIL< Leuven WW1P -., ,7:GL Geulenstraat -., 7?77@6 @ogeebeek -., 795/W( Warostraat -., 79/-3( 3iestestraat -., 5,8,"@ "gen@ovestraat -., 7,952@ 2ud@evstraat -., /,/:W$ RWBI$ < Gobeek Lo -., ,/,5

It can be seen that all rain gauges are within a range between ,./ and 7.? km. 1he specific location of the

rain gauges within the study area is shown in the figure 5.5 above.

!s mentioned in the section ,.,.,# several uncertainties exist when rainfall is estimated with tipping gauges

and therefore# they must be calibrated and corrected. 1he data obtained by !&uafin were already

calibrated# corrected for local effects of wind and validated. More information about the methodology

used for this procedure can be obtained in the Phd dissertation of 1oon 6oorsmans A,-C.

!s a first approach# in principle no strange measurements were appreciated in the rain gauges with the

exception of the Geulenstraat gauge# which from ,9th )une on# did not record any rainfall during periods

in which rainfall events actually occurred. 2f course further appreciations on the measurements might

appear when comparing measurements among different rain gauges and with the radar estimations.

Regarding the methodology used for the event selection# the criteria followed is based on the 1oon

6oorsman dissertation A,-C who performed the different calibration methods using different time

intervals when separate events. @is best results were obtained for an interval of 8- minutes# which is the

same value obtained by Pedersen et al. A,--C as a criteria to select events.


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1herefore# tipping recordings by a rain gauge belong to the same event if they are separated in time by

less than 8- minutes. In addition# a threshold of mm of total accumulated precipitation for the whole

event is established as a minimum to consider it as an event in the study.

**** RE,IEWOFDIFFERENTCALIRATIONMET/ODSRE,IEWOFDIFFERENTCALIRATIONMET/ODSRE,IEWOFDIFFERENTCALIRATIONMET/ODSRE,IEWOFDIFFERENTCALIRATIONMET/ODS

L!WR radar technology applied to hydrological purposes is relatively recent. !n evidence of this is that the

earliest studies date back to ,--,.

!mong all methods present in literature# it will be described here 4ust those which were used as a reference

for the methods applied later on in this study.

.1 #libr#ion "e(ods

1he calibration method most commonly used is the so called standard L!WR calibration method#

A1horndahl and Rasmussen#,-,C which comes from the (um 'alibration Method developed by Pedersen

A,--/C. It consists in relating by a linear regression# the total accumulated rainfall registered by a rain gauge

for each of the events with its respective accumulated R32 obtained by the radar. 1he slope of the

resulting fitting line is then considered as the final calibration factor to be applied when transforming R32

to rain rate estimations Ae&. /.-CN

= :;.


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interval affects the results# showing that# regardless the time length# the results were always improved.

@owever# it was found that short time scales gave better results.

.!

LA-R Im*ro&ed Pre*ro%essed D## 2dB3 o)*)s4

!s mentioned in section 5.5 # the new version of the L!WR radar provides outputs in d$B format# therefore

new possibilities in calibration comes into play since the Marshall


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When e&uation /.5 and /. are combined the following relation is obtainedN

= :E( *+ < ( A0 + BCD"?$ A/./C'5 'onstants '- and ',combined.

1he way to set the calibration coefficients was done by making use of the previous e&uation /./ in in such

a way that a linear regression could be fitted between 3R2 and/:(*log6rfor each of the disdrometers.

1he constant are selected by combining the results of all the regression lines obtained. 1hus# the constant

C.is therefore the y


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1he coefficients were established in basis of comparing the data with the disdrometers rainfall estimates.

'onse&uently# it was again done a comparison between results from the Fold data processedH configuration

and the Fnew Fone. In the former# the calibration factor of the linear regression was used to obtain rain

rate accumulation for every event# while in the later the Marshall


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results and discussion section .1he raw data provided by the radar are four times the value of d$B A3@I#

,--C.

5.!

6)#liy An#lysis.

!s a first step# and prior to the calibration procedure# a study of the &uality of the data provided by the

radar was carried out. 1he data output was extracted by making use of the Matlab algorithm created by

1oon 6roosmans in his dissertation thesis. 2nce it was checked that the extraction was working properly#

a &uality analysis of the radar data was performed by creating different maps and animated 6I%(# in such

a way that accumulation rainfall maps for the entire month of )une were produced# along with peak

intensities spatial distribution for each of the events. 1hus# effects such as attenuation# volume correction#

clutter effect and storm evolutions patterns were analy+ed to obtain a deep insight of how the radar was

performing for each of the events# in order to keep in mind all this factor for the calibration processes.

5.' #libr#ion "e(ods

3espite the few events presented in the data set# the first method applied was the standard calibration

method# with the difference that the data provided now consists of d$B values and thus# the Marshal 1he green triangles represent the accumulated rainfall of the radar before calibration while the red dots the accumu

'rosses shows the gauge accumulation registrations. R,represents coefficient of determination between radar and gauge a

-.--

,.--

/.--

8.--

?.--

-.--

8O:O/ :N59 8O:O/ :N/5 8O:O/ :N/? 8O:O/ :N7/ 8O:O/ -N--

mm

Time

-3 Resol)ion 1!5 m ? 1!5 m

K @ 0!.' Dis#n%e o r#d#r @ !5!: m.

Radar accum

Rain gauge !ccum

2riginal radar !cc.

-

,

/

8

?

-.-- .-- ,.-- 5.--A%%)m)l#ed

+#)+e2mm4

A%%)m)l#

oeffi%ien of de

Resol)ion 1!5

!ccumulated rainfall

Linear A!ccumulated rainfallC

-.--

7.--

-.--

7.--

,-.--

8O:O/ :N59 8O:O/ :N/- 8O:O/ :N/5 8O:O/ :N/8 8O:O/ :N/? 8O:O/ :N7 8O:O/ :N7/

mm

Time

-B R#in G#)+e Resol)ion 1!5 m ? 1!5 m

K @ 07.5 Dis#n%e o r#d#r @ !!' m.

Radar accumRain gauge !ccum2riginal radar !cc.

-

,

/

8

?

-.-- .-- ,.-- 5.-- /A%%)m

)l#ed+#)+e2mm4

A%%)m)l#e

-B oeffi%ien

Resol)ion

!cc. Rainfall

Linear A!cc. RainfallC

-.--

7.--

-.--

7.--

,-.--

8O:O/ :N5 8O:O/ :N5? 8O:O/ :N/8 8O:O/ :N75 8O:O/ -N-- 8O:O/ -N-9

mm

Time

E8 R#in G#)+e Resol)ion 1!5 m ? 1!5 m

K @ '.>> Dis#n%e o r#d#r @ 5!' m.

Radar accum

Rain gauge !ccum

2riginal radar !cc.

-

7

-

7

,-

-.-- ,.-- /.-- 8.-- ?.--A%%)

m)l#ed+#)+e2mm4

A%%)m)l#

E8 oeffi%ien o

Resol)ion 1

Rainfall !cc.

Linear ARainfall !cc.C


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Fi+. 7.1:1he green triangles represent the accumulated rainfall of the radar before calibration while the red dots the accum

constant. 'rosses shows the gauge accumulation registrations. R,represents coefficient of determination between radar an

-.--

7.--

-.--

7.--

,-.--

8O-O/ N59 8O-O/ N/5 8O-O/ N/: 8O-O/ N77 8O-O/ ,N-- 8O-O/ ,N-8 8O-O/ ,N,

mm

Time

-3 Resol)ion 1!5 m ? 1!5 m

K @ 0'.>7 Dis#n%e o r#d#r @ !5!: m.

Radar accum

6auge !cc.

2riginal radar !cc.

-

,

/

8

?

-

,

-.-- ,.-- /.--A%%)m)l#ed

+#)+e2mm4

A%%)m

oeffi

Reso

!ccum. Rainfall

Linear A!ccum. RainfallC

-.--

7.--

-.--

7.--

,-.--

,7.--

5-.--

8O-O/ N58 8O-O/ N/5 8O-O/ N7- 8O-O/ N7? 8O-O/ ,N-7 8O-O/ ,N,

mm

Time

-B R#in G#)+e Resol)ion 1!5 m ? 1!5 m

K @ 05.1 Dis#n%e o r#d#r @ !!' m.

Radar accumRain gauge !ccum2riginal radar !cc.

-

7

-

7

-.-- ,.-- /.--A%%)m)l#ed

+#)+e

2mm4

A%%)m

-B oef

ResoRainfall !cc.


-.--

,.--

/.--

8.--

?.--

-.--

,.--

/.--

8O-O/ N57 8O-O/ N/- 8O-O/ N/8 8O-O/ N7, 8O-O/ N7? 8O-O/ ,N-5

mm

Time

E8 R#in G#)+e Resol)ion 1!5 m ? 1!5 m

K @0:.77 Dis#n%e o r#d#r @ 5!' m.Radar !ccum.

Rain gauge !ccum

-

7

-

7

-.-- ,.-- /.--A%%)m)l#edr#in+#)+e2mm4

A%%)m

E8 oeffi%ien

Resol)io

Rainfall !cc.



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Fi+.7.11 Radar and gauge rain rate time series for 5 of the gauges during the event of :th)une. G method and Linear

--./

-.?

.,

.8

,

8O:O/ :N59 8O:O/ :N/ 8O:O/ :N/7 8O:O/ :N/: 8O:O/ :N7/

R#i

ninensiies

2

mm9min4

Time

-B G#)+e Dis#n%e o r#d#r@!.!' mRadar G Method

6auge 2bservations

Radar L. Regres. Method

-

-./

-.?

.,

.8

,

8O:O/ :N5 8O:O/ :N59 8O:O/ :N/5 8O:O/ :N/: 8O:O/ :N77 8O:O/

R#ininensiy

2mm9min4

Time

E8 G#)+e Dis#n%e o r#d#r@ 5!' m

Radar G Method

6auge 2bservations

Radar L. Regr. Method

-

-./

-.?

.,

.8

,

8O:O/ :N59 8O:O/ :N/5 8O:O/ :N/: 8O:O/ :N77 8O:O/ -N-- 8O:O/

R#inI

nensiy

2mm

9min4

Time

-3 G#)+e Dis#n%e o r#d#r !5!: m

Rada

6aug

Rada


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Fi+. 7.1!Radar and gauge rain rate time series for 5 of the gauges during the event of -th)une. G method and linea

-

-./

-.?

.,

.8

,

8O-O/ N5: 8O-O/ N// 8O-O/ N7- 8O-O/ N78 8O-O/ ,N-, 8O-O/ ,N

R#inInensiy

2mm9min4

Time

-3 G#)+e Dis#n%e o r#d#r !5!: m

Radar

6auge observations

-

-./

-.?

.,

.8

,

8O-O/ N59 8O-O/ N/, 8O-O/ N/? 8O-O/ N7/ 8O-O/ ,N-- 8O-O/

R#inInensiy

2mm9min4

Time

-B G#)+e Dis#n%e o r#d#r !5!: m

Rada G Method

6auge observations

-

-./

-.?

.,

.8

,

,./

,.?

5.,

8O-O/ N58 8O-O/ N/ 8O-O/ N/9 8O-O/ N75 8O-O/ N7: 8O-O

R#ininensiy

2mm9min4

Time

E8 G#)+e Dis#n%e o r#d#r@5!' m

Radar G method

6auge 2bservations

Radar L. Regres. Met


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5:

'omparing the plots of the two methods it was reali+ed that the application of the linear method

regression is based in fact on the same strategy that the G method because watching the e&uation

A7.C# one can appreciate that by multiplying each of the rain rates comig from the application of

Marshall


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corrected.1he k values obtained after extracting the values and applying the same FG calibration

methodH are shown in the next table.

Table $.#G values for spatial resol. of ,7- m during the events of )une ,-/. A\C0o rain registered

6auges WB GL @6 3( "@ 2@ R$

3istanceto radarAmC

,7,- 7?77 795/ 5,8, 7,95 /,/: ,/,5

"vent G values Res.,7- m

5


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/

1he new value for a clutter pixel would be the median of the values within a 7x7 matrix around each

of the pixel.

!s a result of applying the clutter filter it was found that it was useful but 4ust for the dry period#

cause it was not able to get rid of the clutter effect during storm events where systematically low

reflectivity values in specific values# were found with respect to the neighboring pixels. 1he

explanation for this was found by comparing original images during dry period with images during

storm events .

3uring the dry period# the areas where reflectivity values were found Asee figure 8./C# were

approximately the same ones found during the rain events. 1he reflectivity values were clearly lower

than the surroundings as shown in fig. 8. and fig 8.,. 1herefore# it seems that the reflectivity coming

from the storm for the pixels affected by this phenomenon is averaged in the whole beam volume

with those lower values coming from clutter effects.

1hus# a new condition is added by means of comparing two arrays# one with the original reflectivity

values and another after applying a 7x7 median filter to the previous one# in such a way that for

this second matrix# each pixel contains the median value of its neighbors . !fter collecting a large

data set for different pixels affected by clutter at different times# the ratios between the value of

the same pixels for each of the two arrays were computed# and after ad4usting a statistical

distribution for the whole set of ratios# that happened to be Log


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/,

1he way how the filter performed# can be seen in the next figureN

Fig $.! "ffect of applying the filter algortihm in the accumulated map during the whole month of)une ,-/.2@ gauge still not corrected by the filter.

1he k values obtained after applying the filter were the fllowingN

Table $.$ G values after applying clutter filter during the events of )une ,-/. A\C0o rain registered

"vent G values

5


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/5

by checking the effects of the application of the filter in the regression line methodbut this approach

was not performed in this study.

.*.& Co3ere'#re#infl"ence

In order to check whether there was any relationship between the area covered and the G constant

which could explain the variabilty # the average area covered in each rain event during each event

was calculated and the the following data were obtained.

Table $.' 1otal average area covered during the event# and J respect the total area covered by the

radar.

"vent !verage areal covered AGm,C J

5


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//

Table $.( Maximum intensities at every gauge during each of the events.

Max .IntensitiesAmmOminC

WB GL @6 3( "@ 2@ W$

5


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/7

!n indirect way of measure how the attenuation might be affecting the reflectivity values obtained

for an specific location# was by checking the reflectivities of the pixels located in the conecting

path from the radar to the desired location.

! first approach in this direction was made. 1hus # what was happening during the : th)une was

investigated for the gauges W$ and WB since they are placed at the same distance and the same

amount of accumulated rainfall was recorded. With this conditions # similar G values would have

been expected # but as is shown in the table 8.5 # that was not the case. 1herefore an averaged

value of the amount of reflectivity of all the pixels within the path from the radar to the gauge

was calculated# taking also into account the duration of the event at every gauge. In order to extract

the values belonged to the line# the $resenham algortihm was used AWatt#,--C.

1he values obtained indicated that more averaged reflectivity was detected in the W$ gauge path

to the radar #5.,7 d$BOmin # than in the WB path # ,7.,7 d$BOmin # and that is the reason why the

G value is different and more correction had to be done for the W$ gauge A(ee table 8.5C. 1his is

possible to appreciate more graphically in the next figure.

Fig $." .Snapshot of the $thevent of ,une in the moment the high intensity cell is passing trough

the area of interest&The colormap bar was change to apreciate more the contrasts&


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.! Re%ommend#ions #nd F))re -or,

It seems that the G calibration method used in this study leads to a very dynamic values for the FGH

factor. It is worth noting that this conclusion has been taken based on a very small set of events#

therefore a bigger data set would be need in order to corroborate it.

!nyhow# the feeling of the author is that taking into account the physical characteristics of the

rainfall events and the way they develop# at least the events presented in this study# a dynamic

approach should be done when event calibration is performed in order to represent in a more

accurate way the variability in the rain fall rates time series.

1herefore# by applying a dynamic method in such a way that the short


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/:

It also should be noted that new approaches in improving radar rainfall estimations by combining

the potentialities of the L!WR ;


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7-

"infalt# 1.# )essen# M. and Mehlig# $.# ,--7. 'omparison of radar and raingauge measurements during heavy

rainfall. Water (ci. 1echnol.# 7 A,CN :7E,-.

%ankhauser# R.# ::?. Influence of systematic errors from tipping bucket rain gauges on recorded rainfall data.

Water (cience and 1echnology# 59N ,E ,:.

%aures# ).M.# 6oodrich# 3.# Woolhiser# 3. !.# and (orooshian# (.# ::7. Impact of small


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7

Marshall# ). and Palmer# W.# :/?. 1he distribution of raindrops with si+e. )ournal of Meteorology# 7N 87E88.

Meischner# P. A"ditorC# ,--5. Weather RadarN Principles and advanced !pplications. (pringer# 6ermany# 559

pp.

Morena# %.# !ndrieu# @.# Rodrigue+# %.# and 'reutin# ).


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7,

Pedersen# L.# )ensen# 0. ".# and Madsen# @.# ,--. 'alibration of Local !rea Weather Radar. Identifying

significant factors affecting the calibration. !tmospheric Research# :9N ,:E/5.

Probert. 0ew >orkO 6reat $ritain#

8?/ pp.

1estik# %.>. and 6ebremichael# M.# ,-5. 3ual


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i4lenhoet# R.# ,--. Raindrop si+e distributions and radar reflectivity

Improved Data Processing X Band Radar Leuven

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