IRCTR has built an experimental X-band Doppler po-larimetric weather radar system aimed at obtaining high temporal and spatial resolution measurements of precipitation, with particular interest in light rain and drizzle. In this paper a first analysis of the feasibility of obtaining accurate quantitative precipitation estimation from the radar data performed using a high density network of rain gauges is presented

Beek van de, C.Z.

Figueras i Ventura, J.

Russchenberg, H.W.J.

Uijlenhoet, R.

English

Wageningen Yield 

ABSTRACT 
IRCTR has built an experimental X-band Doppler po-
larimetric weather radar system aimed at obtaining 
high temporal and spatial resolution measurements of 
precipitation, with particular interest in light rain and 
drizzle. In this paper a first analysis of the feasibility of 
obtaining accurate quantitative precipitation estimation 
from the radar data performed using a high density 
network of rain gauges is presented. 
1. INTRODUCTION 
IRCTR has built an experimental X-band Doppler-
polarimetric weather radar system called IDRA 
(IRCTR Drizzle Radar) aimed at obtaining high tempo-
ral and spatial resolution measurements of precipita-
tion with particular interest in light rain and drizzle. The 
data set obtained is meant to be used in studies of the 
dynamics of precipitation and in hydrological studies in 
general. For an explanation of the motivation of the 
system as well as its specifications refer to [1]. 
A recurrent issue in the field of radar hydrology is the 
feasibility of obtaining accurate quantitative precipita-
tion estimation from radar data. A first analysis of the 
feasibility of obtaining such measurements using IDRA 
data, using a high density network of rain gauges op-
erated by the Wageningen University as a reference, 
is performed following a similar methodology as that in 
[2]. 
In section 2 the instrumentation used for both obtain-
ing the precipitation intensity and assessing the 
weather conditions during the precipitation events is 
described. Section 3 describes the method used in the 
preliminary analysis of the data and some of the initial 
conclusions obtained. In section 4 two precipitation 
events considered to be representative of cold and 
warm periods in the Netherlands respectively are ana-
lysed in more detail. Conclusions are summarized in 
section 5.    
2. INSTRUMENTATION USED 
The IDRA radar has been operating almost continu-
ously from April 2008. It is placed on top of a 213 m 
tower situated at latitude 21.97N and longitude 4.92E. 
The most usual configuration during precipitation 
events is fully polarimetric, transmitting a 20 W signal 
with a frequency sweep of 5 MHz, which corresponds 
to a 30 m range resolution. With this configuration the 
surface covered has approximately 15 km radius. A 
scan of the total area is completed each minute. 
Wageningen University operates a network of 13 tip-
ping bucket rain gauges distributed in the area sur-
rounding the Cabauw tower (See their position in 
Table I). The rain gauges provide 1 minute-averaged 
precipitation rates. The bucket capacity is 0.2 mm and 
has a temporal resolution of 0.5 s. 
Table I. Position of the Wageningen University rain 
gauges in geographical coordinates using the WGS84 
datum and respect to the IDRA radar.The radar is lo-
cated on top of a 213 m tower at position 51.97N and 
4.92E.  
RG Latitude-longitude [°] Radar C. [m-Deg] 
1 51.97N - 4.99E 4562.8 -  92.4 
2 & 3 51.94N - 4.93E 3849.7 - 159.9 
4 51.94N - 4.88E 4604.1 - 130.7 
5 51.97N - 4.94E 840.9 - 103.2 
6 51.97N - 4.93E 285.9 - 132.0 
7 51.97N - 4.91E 1122.2 -  71.8 
8 51.97N - 4.87E 3817.9 -  96.9 
9 51.98N - 4.91E 1840.7 -  37.8 
10 51.98N - 4.84E 6091.8 -  79.3 
11 52.02N - 4.85E 7489.7 -  47.8 
12 52.02N - 4.92E 6010.7 -  19.8 
13 52.02N - 4.98E 7208.9 -  38.3 
 
Various other instruments have been used to assess 
the data quality. KNMI operates a rain gauge placed at 
the remote sensing site south of the Cabauw tower 
(close to rain gauge number 6) that provides 10 min-
ute-averaged precipitation rates with an accuracy of 
0.2 mm. This rain gauge is part of the national rain 
gauge network, currently composed of 35 elements, 
approximately one per 1000 km2. Wageningen Univer-
sity operates a present weather sensor (PWS) and a 
2-D video disdrometer located in the same site. 
Aside from the instrumentation measuring the precipi-
tation rate, other devices have been used to assess 
the meteorological situation. The wind speed and di-
rection and the temperature at various altitudes have 
been obtained from instrumentation placed on the 
meteorological tower. Temperature gradients of the 
lower part of the troposphere have been measured by 
radiosondes launched from De Bilt, 22 km away from 
Cabauw. It is assumed that the differences in average 
air temperature at such close distance are negligible. 
A 35 GHz cloud radar has provided vertical profiles of 
reflectivity, mean Doppler velocity and Doppler spec-
trum width while from a CT75 ceilometer vertical pro-
files of the backscattering attenuation coefficient have 
been obtained. Both these instruments are operated 
by KNMI. 
Preliminary Study on the Feasibility of Performing Quantitative 
Precipitation Estimation Using X-band Radar 
Jordi Figueras i Ventura1, Remco van de Beek2, Herman W.J. Russchenberg1, Remko Uijlenhoet2 
1  IRCTR-TU Delft, P.O. Box 5031, 2600GA Delft, The Netherlands, Hj.figuerasventura@tudelft.nHl
2Wageningen University, P.O. Box 47, 6700AA Wageningen, The Netherlands, HRemko.uijlenhoet@wur.nl 
© Proceedings of the 8th International Symposium on Tropospheric Profiling, ISBN 978-90-6960-233-2 
Delft, The Netherlands, October 2009. Editors, A. Apituley, H.W.J. Russchenberg, W.A.A. Monna
S11 - P04  -1
3. PRELIMINARY DATA ANALYSIS 
The data analysis was focused on a period between 
April and November 2008 for which data from the ra-
dar system was almost continuously available. How-
ever, an inspection of the rain gauge data revealed 
serious malfunctions of the tipping bucket of most of 
the rain gauges during extended periods of time. The 
rain gauges were prone to suffer from cloaking by 
leaves, seeds or mud. Moreover, some of the ones 
situated in farmland were even attacked by domestic 
animals. To guaranty a high quality data during the 
whole period an almost daily maintenance of each rain 
gauge in the network should have been performed and 
that, unfortunately, was not possible due to the lack of 
manpower.  
For this reason only data from rain gauges 1, 3, 4, 5, 
6, 9, 10 and 12 were considered appropriate for the 
study and the period were both significant data from 
the rain gauges and the radar was available was re-
duced to a short period in May and in November. Nev-
ertheless a total of 15 rainy days were encountered in 
the analysed period and from those 4 days contained 
significant precipitation events, i.e. more than 1 mm/h 
precipitation rate in a 10 minute-averaged measure-
ment. 
In a first approximation to the comparison of the radar 
data with the rain gauge data, the reflectivity factor 
values of rainy days from the radar range gate over-
lapping each rain gauge was converted to rainfall in-
tensity using the typical Marshall-Palmer Z-R relation 
and plotted as a function of time together with the rain 
rate obtained by the corresponding rain gauge. Figure 
1 shows an example of such measurement. 
 
Figure 1. Example of rain gauge 1-radar data com-
parison graph for a series of precipitation events oc-
curred the 28th of October 2008. 3 precipitation 
events can be observed. In the 1st one, lasting from 
9:30 to 10:30 UTC, there is a good agreement be-
tween both datasets; in the 2nd one, from 12:30 to 
13:30 UTC, the radar underestimates the precipita-
tion, while in the 3rd the precipitation is overesti-
mated.  
A good agreement of the precipitation pattern was 
observed between both datasets. However the actual 
precipitation intensity value was differing significantly. 
In most of the cases an underestimation of the precipi-
tation rate retrieved from the radar data respect to the 
rain gauge data was encountered but in some cases 
there was a reasonably good agreement and, in other 
cases, an overestimation was noticed.    
This initial analysis also revealed a very interesting 
feature. The radar retrieved data was able to deter-
mine the precipitation pattern of very light rain (below 
0.2 mm/h) that was not correctly measured by the rain 
gauge due to the lack of resolution of the bucket 
Therefore, radar data constitutes a very useful tool 
when studying the dynamics of drizzle and light rain. 
The origin of the lack of agreement between the pre-
cipitation intensity values measured by rain gauges 
and those retrieved from radar data is too complex to 
be determined with certainty. One possible cause has 
to do with the nature of each measurement. Radar 
provides quasi-instantaneous measurements over a 
relatively large volume whereas rain gauges provide 
time-averaged measurements over a point in space. 
Moreover, measurements of the radar take place well 
above the ground while rain gauges measure rainfall 
at the surface. Secondly, the relation between radar 
reflectivity and rainfall rate is not a direct one. It is 
based on the drop size distribution and this varies from 
rain event to rain event and even within rain events. 
The Marshall-Palmer Z-R relation was obtained for 
precipitation in North America and may not be the 
most convenient for the Netherlands. Finally, errors in 
the estimation of the radar calibration constant should 
not be discarded.         
4. CASE STUDY PRECIPITATION EVENTS 
A complete study of the weather conditions of two 
relevant precipitation events was performed to shed-
some light on the differences between the radar and 
gauge measurements. The first one occurred the 16th 
of May 2008 and may be considered characteristic of 
precipitation events during the warm period in The 
Netherlands (see Figure 2a)). The second one oc-
curred the 11th of November and can be considered an 
example of cold period precipitation (see Figure 2b)). 
Due to the presence of other instruments that can be 
used as an indicator of the data quality, rain gauge 
number 6 have been used for the comparison. Fur-
thermore, since it is placed relatively close to the ra-
dar, the radar data over rain gauge 6 is less prone to 
suffer from phenomena like attenuation or misalign-
ment and therefore differences between the actual 
values can be attributed mainly to the weather condi-
tions or the nature of precipitation.. 
As it is shown in Table II, the total precipitation over 
the 24 h period retrieved by the radar is in very good 
agreement with that measured by the rain gauges 
during the 16th of May. On the contrary, the precipita-
tion is greatly underestimated during the 11th of No-
vember. 
Table II. Total rainfall over the 24h period in mm for 
each case study measured by different sensors.  
 Total Rainfall over 24 h [mm] 
 16-5-2008 11-11-2008 
Radar over RG 6 12.2 6.9 
RG 6 12.5 20.1 
KNMI gauge 11.0 18.8 
PWS 5.3 N.A. 
 
S11 - P04  -2
 
a) 16th of May 
 
b) 11th of November 
Figure 2. Rain gauge 6-radar data comparison graph 
for the two case study precipitation events 
4.1 Case study 1: 16th of May 2008 
Plan Position Indicator (PPI) graphs of reflectivity ob-
tained by the IDRA radar show a quite uniform precipi-
tation pattern with relatively low precipitation over the 
whole area covered by the radar until 4:00 UTC, when 
a squall line appears in the image. The squall line 
moves from south to north in approximately 2 hours. 
This relatively low velocity is in correspondence with a 
situation of calm atmosphere. This squall line is what 
causes the first peak in the precipitation pattern exhibit 
by rain gauge 6. From 6:00 UTC to 8:30 UTC strong 
precipitation is present all over the area measured by 
the system, which causes the second peak in the pre-
cipitation pattern. After 8:30 UTC only scattered low 
intensity rain is observed. A selection of some relevant 
PPIs is presented in Figure 3. The complete data sets 
are available on demand. 
During the 16th of May the temperature was mild, with 
little variation during the whole day. During the rain 
event the temperature measured on top of the Ca-
bauw tower (200 m) oscillated from a maximum of 
14°C to a minimum of 10°C. The temperature meas-
ured at the surface was just one degree higher. Ra-
diosonde measurements in De Bilt show that the 0°C 
altitude was above 2500 m and few temperature varia-
tions were observed from midnight to midday The wind 
velocity measured both on top of the tower and at the 
surface is low and there is little variation between the 
two, suggesting a quite stable atmosphere. 
The analysis of the 35 GHz KNMI cloud radar data for 
the period when it was precipitating shows a very dis-
tinguishable melting layer situated around 2500 m in 
accordance to the radiosonde data. Also the two peri-
ods of stronger precipitation as shown from IDRA and 
rain gauge measurements between 5:00 and 6:00 
UTC and from 7:00 to 8:30 UTC are clearly observable 
in the measurements. 
 
 a) 3:00 UTC  b) 5:00 UTC 
 
c) 7:00 UTC  d) 8:00 UTC 
Figure 3. PPIs of reflectivity obtained during the pre-
cipitation event on May 16th. 
4.2 Case study 2: 11th of November 2008 
The analysis of the reflectivity PPIs obtained during 
the 11th of November shows a much more dynamic 
situation than that in the 16th of May, with little correla-
tion between one image and the next. Overall though, 
it follows the trend measured by rain gauge number 6 
with intensive precipitation from midnight until 6:00 
UTC and a squall line crossing the image around mid-
day. A selection of the PPIs can be seen in Figure 4. 
 
 a) 1:30 UTC  b) 3:30 UTC 
 
 c) 5:30 UTC  d) 14:00 UTC 
Figure 4. PPIs of reflectivity obtained during the pre-
cipitation event on November 11th. 
The situation the 11th of November 2008 is very differ-
ent from that of the 16th of May. The temperature 
measured on the tower is much lower than that of the 
16th of May, oscillating between 10.5°C and 7°C. Also 
the radiosonde temperature shows a dramatic de-
crease of the 0°C altitude from midnight to midday that 
day, going from close to 2500 m to 1500 m. The ra-
diosonde measurements suggest a situation of turbu-
lent atmosphere which is confirmed by the measure-
S11 - P04  -3
ments of wind velocity and direction on the tower. This 
measurements show a much windier day than the 16th 
of May. Also, the differences between the measured 
velocities on top and on the bottom of the tower are 
much wider. The wind speed increases constantly 
from midnight until noon and then remains approxi-
mately the same for the rest of the day. 
The data from the 35 GHz cloud radar and the 
ceilometer show two very distinguishable precipitation 
periods, one from midnight until 6:00 UTC and another 
between 12:00 and 14:00 UTC. It is noticeable that 
during the first precipitation period the melting layer 
altitude decreases steadily from 2.2 km to 1.2 km. This 
is in accordance to the measurements from the ra-
diosonde. Also, the melting layer is not as well defined 
as during the 16th of May. In fact there seems to be a 
gradual transition of reflectivity until 1 km altitude. 
In conclusion, the two case studies are representative 
of two different precipitation regimes. In the first case 
there is a stable atmospheric situation which leads to 
little variations in drop size distribution during the 
event and a good correlation between the situation at 
200 m (the measuring altitude of the radar) and that on 
the ground. Consequently the precipitation intensity 
retrieved from radar data is in good agreement with 
that obtained from rain gauge measurements. In the 
second case the atmosphere is very turbulent and this 
leads to significant variations in the drop size distribu-
tion in a very short period of time. Disdrometer data 
from that period, shown in Figure 5, corroborates this 
hypothesis. 
 
Figure 5. Rainfall rate as a function of reflectivity ob-
tained from disdrometer data from the 11th of Novem-
ber. The large variance of the measurements shows 
that the drop size distribution was varying in time. 
5. CONCLUSION 
A preliminary study of the feasibility of obtaining accu-
rate quantitative precipitation estimation from IDRA 
data has been performed, leading to encouraging re-
sults.  
The analysis shows a good agreement between the 
precipitation pattern retrieved from radar data and that 
obtained from rain gauge measurements. Of particular 
interest is the fact that radar can provide the precipita-
tion pattern of light rain and drizzle, which cannot be 
measured properly by tipping bucket rain gauges due 
to the lack of resolution of the bucket. This shows the 
great potential of this kind of radars in the study of 
such phenomena. 
From an operational perspective it is also relevant to 
notice that another advantage that radar data offers 
respect to high density rain gauge networks is the 
large area covered and the simplicity in the mainte-
nance and the easiness with which malfunctions of the 
system are detected. In the long term, this can reduce 
greatly the cost of such measurements.  In this study 
this has proved not to be a minor issue.  
However, it has also been shown the great variability 
of correlation of the absolute value of precipitation 
obtained from radar data respect to rain gauge data. It 
is speculated that such variability is caused mainly due 
to rapid changes in the drop size distribution of precipi-
tation occurring mostly during periods of instability of 
the atmosphere and, to a lesser extend, by differences 
in the composition of the precipitation measured at 
200 m altitude by the radar system and that on the 
ground. 
Issues like propagation attenuation, which at such high 
frequencies can already be relevant at moderate pre-
cipitation intensities, have not been addressed by this 
study and they may improve such correlation, particu-
larly for areas at the furthest range of the radar.  
The reduced number of precipitation events where 
both rain gauge and radar data were available has 
prevented a more thorough statistical study of precipi-
tation. Such study is required in order to obtain Z-R 
relations adapted to the general characteristics of the 
precipitation in the area and its seasonal variations.  
Having assessed the need for intensive maintenance 
of the high density rain gauges, a thorough check was 
performed and a maintenance schedule was estab-
lished. Therefore it is expected that a similar analysis 
based on data from 2009 will lead to more accurate 
relations between radar data and actual precipitation 
intensity. 
ACKNOWLEDGEMENTS 
The authors would like to thank KNMI (The Dutch Me-
teorological Institute) and the CESAR (Cabauw Ex-
perimental Site for Atmospheric Research) Consortium 
for the data provided. Dr. Hidde Leijnse provided the 
present weather sensor and the disdrometer data. 
REFERENCES 
[1] J. Figueras i Ventura, H.W.J. Russchenberg, 
2009: Towards a better understanding of the impact of 
anthropogenic aerosols in the hydrological cycle: 
IDRA, IRCTR Drizzle Radar, Physics and Chemistry of 
the Earth, 34:1-2. 
[2] C. Z. van de Beek, H. Leijnse, J. N. M. Stricker, R. 
Uijlenhoet, H. W. J. Russchenberg, 2009: Perform-
ance of high resolution X-band radar for rainfall meas-
urement in The Netherlands, Hydrology and Earth 
System Sciences, (Submitted).  
   
 
S11 - P04  -4


Performance of high resolution X-band radar for rainfall measurement

Towards a better understanding of the impact of anthropogenic aerosols

Preliminary Study on the Feasibility of Performing Quantitative Precipitation Estimation Using X-band Radar

Name not available

NARCIS 

Preliminary Study on the Feasibility of Performing Quantitative Precipitation Estimation Using X-band Radar

Abstract

Similar works

Full text

Available Versions

Wageningen Yield

Name not available

NARCIS