Collecting and Measuring
Precipitation Using a Rain
Gauge
Anthony Joseph Marro
4/15/2010
Abstract
The measuring of the amount of precipitation over an area has been important to society since
ancient times where the amount of taxes for a land was determined by the rainfall on that area. In
today’s age the amount of rainfall over an area is used to study the possible trends of the atmosphere.
In this experiment I constructed a rain gauge using materials that can all be bought in a shopping store,
and used the gauge to measure the amount of rain that fell in State College, PA. The rain gauge was
placed on the roof of the Walker building on the Pennsylvania State University campus, along with a
commercial gauge. The amount of precipitation that fell was recorded for 2 weeks using both of the
gauges along with the amount that was recorded by the National Weather Service in State College,
which was 6 miles from the site of the home-made gauge. The results of the experiment presented
evidence that home-made rain gauges suffer from a systematic error when compared to the National
Weather Service because of the spatial heterogeneity of the storms that produced the rain. Errors when
comparing the home-made rain gauge to that of the National Weather Service readings, ranged from
2.87% to 220%, while comparing the commercial rain gauge to that of the National Weather Service the
errors range from 8.96% to 350%. A systematic instrumental error was present in all of the
measurements which had an average of 8.68. The importance of this entire experiment is to prove that
a better method is needed to measure the amount of rainfall in an area, as although our readings had an
acceptable error on some days, one of the days the error between the home-made gauge and the NWS
site was unacceptable and not caused by systematic reasons. The spatial heterogeneity of storms was
the cause of this error and proof that a better method of measure the amount of precipitation that falls
in an area is needed to cover a larger area.
Introduction
The observation of rain fall dates back to 400 B.C. where the people of ancient India would
measure rain fall on fields and predict growth and adjust taxes on growing land accordingly. In modern
times we use precipitation amounts as a means of observing the condition of the atmosphere, aiding
mostly with the long term observations of an area to better predict and observe trends. In this day and
age we use rain gauges to properly measure the amount of precipitation that falls using a rain gauge. A
rain gauge can be made using only a container and a funnel or can be easily bought in the store for a
reasonable price.
Although one might think that all rain gauges are fine tuned perfectly to measure the amount of
precipitation, there is a small amount of systematic error associated with any rain gauge. Storms are not
uniform by any stretch of the imagination, it could be raining heavily in an area, and only 5 miles away it
could be sunny at the very same time. Because of this the amount of precipitation measured varies
greatly with distance. A rain gauge can only really properly report the amount of precipitation for the
immediate area around the rain gauge. Along with only being able to read the amount of precipitation
over a small area, unless the rain gauge is electronic there will almost always be an error with the
reading of the amount of precipitation that has fallen.
The goal of this lab is to create a rain gauge that will produce the most accurate measure of
precipitation amount. The accuracy and error of the rain gauge along with a commercial gauge will then
be analyzed to better understand the inevitable errors that come along with measure precipitation
amounts with any rain gauge. The gauges will be compared to the precipitation amounts measure by a
professional site that is in the State College area. The hypotheses that this lab will tests are as follows.
1. The observed accuracy and precision of daily precipitation measurements using a home-made
rain gauge is lower (that is, the errors are larger) than or similar to the level of accuracy and
precision suggested by error propagation calculations.
2. Spatial heterogeneity of rainfall causes systematic and random differences in daily precipitation
measurements that can be detected despite the observed instrumental systematic and random
errors.
Procedure
The first thing that had to be done was the acquiring of the necessary tools to make the rain
gauge. To do this, I went to the local Home Depot and bought a 10 inch by 10 inch piece of plywood and
some duct tape and Gorilla Wood Glue. I then went to Wal-Mart and bought a hardened plastic water
bottle and a car funnel. At home I attached the funnel to the water bottle and glued it down with the
gorilla glue. After which I glued the funnel to the water bottle and then glued the water bottle with the
funnel attached to it down to the piece of plywood. After the rain gauge was assembled it was set up on
the roof of the Walker building on the campus of The Pennsylvania State University. Along with the
home-made rain gauge a commercial rain gauge was also set up on the roof of the walker building,
hanging from a ledge about three feet above the home-made rain gauge. The observations started on
March 20th, 2010 and were taken every day around 1400, with some exceptions due to class and
organizational obligations. Every day the amount of precipitation that fell was recorded using both the
home-made and the commercial rain gauge. After recording the amount of precipitation that fell since
the last observation, the precipitation was transferred to a separate water bottle to keep for a future lab
that dealt with the acidity of State College’s rainwater. During the experiment, after a dry windy day
and after discovering that my rain gauge has been blown over due to the high winds I duct taped the
rain gauge and funnel securely to the plywood sheet and the water bottle respectively. The observations
continued for two weeks until April 2nd, 2010 upon which time the experimental phase ended.
Results
Figure 1 collects all of our observations made using our home made rain gauge, the commercial
rain gauge, and the National Weather service observed value. Included in the table are the percent
errors comparing the home-made gauge to the commercial gauge, the commercial gauge to the
observed NWS values, and the home-made gauge against the NWS values. Also included are the
estimated random and systematic errors of each observation made using the home-made gauge, finally
the date and time are included along with the precipitation type and condition of the weather at the
time of observation.
Date and
Time of
Observati
on
Type of
Precipitati
on
HomeMade
Gauge
Precipitati
on Value
(cm)
Commerci
al Rain
Gauge
Precipitati
on Value
(cm)
NWS
Precipitati
on Value
(cm)
%Error
of homemade
gauge
against
commerc
ial
%
Differenc
e
between
commerc
ial gauge
and NWS
%
Error
of
Homemade
against
NWS
Estimat
ed
rando
m
error
in
homemade
gauge
Estimate
d
systemat
ic error
in homemade
gauge
Meteorologi
cal
observation
3/20
1300
3/21
1300
3/22
1300
3/23
1000
3/24
1730
3/25
1530
3/26
1500
3/27
1400
3/28
1400
3/29
1400
3/30
1400
3/31
1400
4/1
1400
4/2
1400
N/A
0
0
0
N/A
N/A
N/A
N/A
N/A
Clear
N/A
0
0
0
N/A
N/A
N/A
N/A
N/A
Clear
Rain
Trace
Trace
0
N/A
N/A
N/A
N/A
N/A
Rain
Rain
.271
.254
.279
74.0%
8.96%
0.06
0.31
Overcast
Rain
Trace
Trace
0
N/A
N/A
2.87
%
N/A
N/A
N/A
Sunny
N/A
0
0
0
N/A
N/A
N/A
N/A
N/A
Overcast
Rain
.814
1.14
.254
16.7%
350%
220%
0.06
0.88
Sunny
N/A
0
0
0
N/A
N/A
N/A
N/A
N/A
Cloudy
Rain
Trace
Trace
0
N/A
N/A
N/A
N/A
N/A
Rain
1.46
2.29
1.24
4.36%
84.4%
0.06
1.55
Rain
Trace
Trace
0
N/A
N/A
17.7
%
N/A
Overcast
/Drizzle
Cloudy
N/A
N/A
Overcast
N/A
0
0
0
N/A
N/A
N/A
N/A
N/A
Sunny
N/A
0
0
0
N/A
N/A
N/A
N/A
N/A
Sunny
N/A
0
0
0
N/A
N/A
N/A
N/A
N/A
Sunny
Fig. 1
Figure two details the error analyses of the experiment.
Theoreti
cal
estimate
of
instrume
ntal
random
error
(cm)
.061
Average
theoretic
al
estimate
of
instrume
ntal
random
error
10.7
Theoreti
Average Observed
cal
theoretic instrume
estimate
al
ntal
of
estimate systemati
instrume
of
c error in
ntal
instrume
daily
systemati
ntal
precipita
c error
systemati
tion
(cm)
c error
depth
.166
8.68
23.9
Observed
instrume
ntal
random
error in
daily
precipita
tion
depth
15.3
Observed
spatial
systemati
c
differenc
e in daily
precipita
tion
depth
148
Observed
spatial
random
differenc
e in daily
precipita
tion
depth
179
.061
.061
.055
.039
Fig. 2
The following calculations were used in the analysis of this experiment.
pi
HM
 h1 
r2 2
h2.
r12

1
pr,iT
M  2  2
f
 f  
 x 2j 

j1 x j 





PrT 
1 N pr,i
100

N i1 piCOM
T

ps,iT  pi HM (max)  pi HM (best)

PsT 

1 N ps,i
100

N i1 piCOM
T

HM
COM
1 N pi  pi
P  
N i1
piCOM
O
s
100

1
2

  2
N  p HM  p COM
i
i
 1

O
O

Pr  
100  Ps  

COM
pi

N 1 i1 

 






COM
WS
 pi
1 N pi
P  
WS
N i1
pi
100

1
2

  2
N  p COM  p W S
1
i
i


 P  
100  P 

WS

pi

N 1 i1 

 





Figure 3 depicts the amount of precipitation that fell from March 20th through April 2nd.
3
2.5
2
1.5
Home-Made
1
Commercial
NWS
0.5
2-Apr
1-Apr
31-Mar
30-Mar
29-Mar
28-Mar
27-Mar
26-Mar
25-Mar
24-Mar
23-Mar
22-Mar
21-Mar
0
20-Mar
Measured precipitation (cm)
Precipitation amounts from March
20th to April 2nd
Fig. 3
Figure 4 shows the location of the rain gauge with respect to nearby obstructions. The scale is
located on the bottom right of the figure.
Fig. 4
Figure 5 shows the location of the rain gauges with respect to each other.
Fig. 5
Discussion
Our rain gauge was more accurate than that of the commercial rain gauge when compared to
the National Weather Service observations. Although the gauge was by no means completely accurate,
with errors ranging from 2.87% to 220%, it was still more accurate than that of the commercial gauge
which had errors ranging from 8.96% to 350%. The plastic gauge was good at collecting the precipitation
as the mouth was wide and collected the precipitation well, but the measurement of it was obviously off.
The major sources of error in both the gauges were the variation in observational times which affected
the 24 hour period concept, along with that was the placement of the rain gauge. We placed the rain
gauge on the roof of the Walker Building on the Pennsylvania State University, which has on top of it a
communications tower and its own weather station, all making a 10 foot wall only about 8 feet to the
west of our gauges. This wall created a source of error by creating swirling winds and the possibility of
eddies on the roof, which would affect the accuracy of the readings of the rain gauge. The last error is
the fact that the National Weather Service observations are taken 6 miles from the site of our rain gauge.
These errors specifically affected our results by making them less accurate and therefore creating more
error when our results were compared to the standard and accurate measurements of the National
Weather Service.
From this experience the elements that are essential to design of a rain gauge is robustness the
ability to collect enough precipitation so it can be measured. The robustness is essential because the
gauge will go through strong weather conditions such as gusting winds and depending on the season
you are observing the possibility of flying debris. To ensure the robustness of the gauge make sure the
gauge is made of sturdy material and weighted down securely to a strong heavy base. The other aspect
of the rain gauge is the ability to collect enough rain to be able to measure the amount that fell. This can
be achieved by placing a big enough funnel on the rain gauge to make sure rain is collected. The only
drawback of this is that sometimes having a big funnel can increase your possibility for error.
The home-made rain gauge was not accurate compared to the reading of the National Weather
Service. The difference in the observations of the National Weather Service and our home-made rain
gauge are due to both systematic errors in the design of the rain gauge, and the spatial variability of
precipitation. This is evident because the rain gauge was not a cylindrical build and therefore required
an equation which although converted the volume of water into a height amount, it also can create
error through the calculation. Also the fact that we had to look at the volume which was only at
increments of 50 mL so errors in interpretation could have occurred. The spatial variability of the
precipitation is a key factor because the State College area is a very mountain heavy area, which can
cause dispersion of storms where it could be raining at a site, but as little as 2 miles away it could not be
raining.
The location of the rain gauge affects its accuracy in collecting precipitation because if you place
it near an obstructing object you will not get accurate results. For example, our rain gauge was placed on
top of a roof with a 3 foot high wall only 7 feet to the east, and a 10 foot high wall 8 feet to west.
Without a doubt these obstructions caused errors in our observations because on at least one occasion
during the experiment, there was a blowing rain. And because of the wall, the blowing rain would not be
able to be properly measured due to the wall blocking the rain. The aspect of good placement of a rain
gauge is in a remote area away from anything that might disturb it, be they natural or human. The most
ideal place for an official rain gauge would be in an empty field that is not near anything that might
disturb it, and to keep both animals and humans away, a small fence placed around it would make it
even more accurate.
This experiment had two different hypotheses; the first hypothesis stated that home-made rain
gauges are not accurate; this can be supported through this experiment because of the amount of error
that is present when comparing the readings of the home-made rain gauge to that of the National
Weather Service. The inaccuracy could be traced back to the fact that we had to measure the volume of
the amount of precipitation that fell which could have caused a major source of error due to the inability
to get a very precise volume reading. Also, the use of a funnel creates an instrumental error that leads
to random and systematic errors throughout the entire experiment. Another reason why the hypothesis
is supported is because the placement of a home-made rain gauge can be obstructed by nearby
buildings and structures, while official rain gauges are strategically places to make sure that they get the
most accurate readouts.
The second hypothesis stated that the spatial heterogeneity of rainfall causes random and
systematic differences in daily precipitation measurements that can be detected despite the
observational systematic and random errors. Evidence towards this hypothesis is supported through the
fact that on multiple occasions it was observed that we had a trace amount of precipitation that fell at
our gauge site, while at the NWS site no rain fell at all. Also the fact that there was an error of 350% on
March 26th from the home-made rain gauge site compared to that of the NWS site shows that there was
obviously a difference in the amount of rain that fell on both areas. The large error was not just confined
to our experiment but also seen in people doing the exact same experiment all received a massive error
on the 26th of March.
Conclusion
After completing this experiment it is evident that in order to properly measure the amount of
precipitation in an area it is not sufficient to have only one rain gauge in the area. Due to the effects of
the spatial heterogeneity of storm systems, the amount of rain that falls at the site of a rain gauge could
be completely different from that of the amount that falls in a town that is no more than 3 miles away.
Due to this spatial heterogeneity a better method is needed to measure the amount of rainfall in an
area. An idea that I think would work to properly measure the amount of precipitation in an area would
be to have ordinary citizens take weather observations so that there could more of an abundance of
observations over an area. That way there would be a more dense area of observations taking place,
thus eliminating the error caused by the spatial heterogeneity of a storm. The National Weather Service
utilizes citizens through their cooperative observer program, where normal citizens with a passion for
weather can report daily observations to the National Weather Service. The NWS then uses the
observations and reports the better detailed observation map to the rest of the country. An expansion
on this program or the implementation of automatic rain gauges on top of commercial buildings in cities
would help gather better regional data for the amount of precipitation that has fallen in that area.