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The design, installation and operation of a fully computerized, automatic
weather station for high quality meteorological measurements
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Fresenius Environmental Bulletin
THE DESIGN, INSTALLATION AND OPERATION OF A FULLY
COMPUTERIZED, AUTOMATIC WEATHER STATION FOR HIGH
QUALITY METEOROLOGICAL MEASUREMENTS
Haralambos S. Bagiorgas1*, Margarita N. Assimakopoulos2, Argiro Patentalaki1,
Nikolaos Konofaos3, Demetrios P. Matthopoulos1 and Giouli Mihalakakou1
1
University of Ioannina, Department of Environmental and Natural Resources Management, 2 G. Sepheri Str., 30100 Agrinio, Greece.
2
University of Athens, Department of Physics, Division of Applied Physics,
Laboratory of Meteorology, University Campus, Build. Phys V, 15784 Athens, Greece.
3
University of Patras, Computer Engineering and Informatics Department, 26500 Rio Patras, Greece.
SUMMARY
The design, installation and operation of an Automatic
Weather Station (AWS) are described and analysed in the
present paper. This station of high endurance is easy to be
installed and capable for long-time operation without significant problems. The metadata of the station which are
the characteristics of the instruments, electronic logic control and datalogging systems are described in detail, according to the Guides of the World Meteorological Organization (WMO). Moreover, a computer controlled environment is designed and implemented, with capabilities of
data acquisition and control with flexible and high performing software and hardware capabilities. The AWS can easily
communicate, so directly as remotely, with some modifications and both possibilities are examined in detail. Finally, an evaluation procedure is presented and analyzed,
while the obtained results are used for testing the system.
The evaluation depicted the unique and well established
characteristics of the system and proved its potential application to meteorological data collection and calculation.
KEYWORDS:
Automatic weather station, real-time communication data link, control software, direct communication, remote station.
INTRODUCTION
Real-time meteorological and environmental observations can be provided by Automatic Weather Stations
(AWS), gathering data from a network through various
communication channels. The design, installation and operation of well-functional AWS is a challenging task be-
cause the data obtained from the device should be both accurate and compatible with the World Meteorological Organization (WMO) standards. Moreover, the station’s maintenance is a hard process, time consuming and of high cost.
In general, AWS contains sensor-based equipment. Its
sensors contain a conventional cup anemometer, wind vane,
miniature temperature screen with wet and dry bulb platinum resistance thermometers, solarimeter, net radiometer
and tipping bucket raingauge. Many researchers have dealt
with this matter and a great improvement has been achieved
in accomplishing the technical characteristics of the meteorological instruments [1-10] as well as in the communication part of the AWS and the data acquisition and processing [11-13]. Βesides, so far, significant new developments
and operational experiences together with new observation
technology have been presented. Today, as AWS are completely automated, AWS may record weather conditions almost everywhere on the globe, even under extremely hard
conditions [14-16], hence, AWS networks of completely
automated weather stations have been adopted [17-20].
There are many advantages of using AWS’s systems
instead of customary stations, but the main are: monitoring
of data in sparse areas where human observations are not
practical, continuously flux of data at frequent intervals and
for any observation time, increase of coverage, elimination
of the subjectivity in observations, cost reduction [10] etc.
Of course, there are many difficulties in AWS’s operation,
as the disagreement between the professional meteorological observer and the automated observations [21-23], especially in the type and the intensity of precipitation [24,25],
the inabilities in guaranteeing the renewal of the spare parts,
a wear of the material, the lack of flexibility, an aging system of transmission of the data, etc. [10] but these problems decrease day by day.
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Our AWS has been established in Western Greece, in
the center of the prefecture of Aitoloakarnania, in the city
of Agrinio, an urban area of about 100,000 habitants, which
is characterized by a rather complicated topography. In
Western Greece the climate has the basic features of Greek
climate (a typical Mediterranean climate): mild and rainy
winters, relatively warm and dry summers and, generally,
extended periods of sunshine throughout most of the year
[26]. Moreover, due to the influence of topography (great
mountain chains along the central part and other mountainous bodies) on the air masses coming from the moisture
sources of the central Mediterranean Sea, Western Greece
has a more wet climate comparatively to the dry climate of
Attiki (Athens’ greater area) and East Greece in general, including sometimes some harsh phenomena (storms, floods,
etc.) [27]. Despite of the particular climatological characteristics of Agrinio area (such as Western Greece), there was
sparse meteorological data coverage, which led to the imperative need for an AWS that could monitor continuously
- and on regularly selected time steps - basic meteorological parameters in order to provide a weather identification
and determination as similar to a human observer as possible, ultimately replacing the observer.
The descriptions in this paper AWS should be used for
energy, environmental, agricultural and meteorological applications, such as the estimation of the wind and solar
energy potential of the area, the investigation of urban heat
island effect (in Agrinio region, which is recently highly
developed and urbanized), the calculation of the area’s
potential in ground cooling applications, etc.
The wind energy potential in Western Greece was
evaluated from measurements of wind speed and direction
at four weather stations. Weibull parameters estimated by
three different methods were used to estimate wind power
potential in this area [28]. Additionally, analysis of the “unit
energy cost”, being the specific cost per kilowatt-hour obtained for several wind turbines, at different hub heights,
has been carried out for every station [29].
An aluminium nocturnal radiator, painted with appropriate white paint, was established on the roof of the Department of Environmental and Natural Resources Management in Agrinio, in Western Greece [30]. A both simple and accurate model for the prediction of the radiator
heat exchange performance was presented. The model, using
as input data some meteorological parameters from our
AWS measurements, calculated with appropriate algorithms
the outlet temperature of the radiator.
The station ought to serve in educational purposes as
well, without compromising the systems integrity. Moreover, it ought to communicate easily, either directly for
short distances, as remote for long, with the necessary
modifications. The system needs to be economically viable
and maintainable on a long-term basis and the data collected
should be accurate and physically accepted while extra care
should be taken in eliminating any possible reasons for obtaining poor quality data.
The present paper has as main objective to emerge information and guidance on the design, installation and operation of an, easy to install and maintain, fully computerized, automatic weather station for high quality meteorological measurements in an urban area. It also demonstrates
the “flexibility” and propriety of this station both for near, as
well as for remote applications, with some appropriate modifications each time. Moreover, this paper presents a procedure for the validation of the station, so in case of direct
communication as in case of the remote station too, which
had been achieved by comparison of the AWS’s data with
these of a thermograph, barograph and other conventional
recording devices of the Greek Meteorological Agency’s
(EMY) station in Agrinio. This comparison verified both
accuracy and reliability of the AWS. Finally, the present
paper depicts the general difficulties that erase in the establishment of an urban meteorological station, concerning the
selection of the station’s position and the settlement of the
sensors, for the station to be well representative for urban
sites and in accordance to the WMO guidelines at the same
time.
AWS FOR DIRECT COMMUNICATION
Description of the equipment,
communications link and power supply
Equipment: In planning a new AWS, the selection of
equipment depends on the nature of the regular data that
are to be measured and on the site location. Consideration
should also be given to whether the versatility of the system might be enhanced by future addition of further sensors. The range of sensors offered and similar equipment
is wide and the selection of a well established set guarantees trouble-free performance in the future.
The various instruments making up the station involve
a datalogger, a temperature and humidity probe, a windsonic 2D anemometer, a tipping bucket raingauge, a barometric pressure sensor, a pyranometer, a soil temperature
probe, a soil moisture probe, a pyrgeometer and a sunshine
duration meter. Table 1 summarizes the instruments and
their specifications and characteristics, while technical details, specifications, operation ranges and other special information for the instruments can be found in data sheets
available1 [31].
Communications Link: AWSs report observations by a
variety of formats, including telephone lines, radio modems, mobile phone networks and satellite networks. The
communications between the AWS and the data collection
agency should be: reliable, inexpensive (satellite telephone
can be expensive) and in accordance to standard protocols.
There are several ways to communicate with the datalogger in order to retrieve data. The most commonly rec1
http://www.campbellsci.co.uk/ (Campbell Scientific, 2004),
http://www.munro-group.co.uk, www.druckinc.com, www.kippzonen.com
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© by PSP Volume 16 – No 8. 2007
Fresenius Environmental Bulletin
TABLE 1 - WMO recommendations.
Instrument
Description
CR10X Measurement
and Control System
[i,ii]
Datalogger
MP101A-T7-WAW
temperature and
humidity probe [i]
Air temperature Air moisture
Windsonic 2D
Anemometer (Gill
Instruments) [iii]
Wind speed and
direction
ARG100 Tipping
Bucket Raingauge
Rainfall
Druck RPT410F [iv]
Barometric pressure
CM3 pyranometer
[v]
Short wave (solar)
radiation
PT100/3 (1/3 DIN
PRT) Probe)
Soil temperature
CS616 Water Content
Rreflectometer [i]
Soil moisture
CG3 pyrgeometer [v]
Long wave (Infrared)
earth radiation
CSD1 Sunshine
duration meter [v]
Sunshine duration
General description - Characteristics
Maximum rate of program execution: 64 times per second
Maximum rate of single input measured: 750 samples per second
Data and programs storing: non-volatile Flash memory or battery-backed SRAM
Standard memory storing: 62,000 data points
Ports: 25-pin female; configured as DCE, 9-pin CS I/O Port male; connects to datalogger via SC12 cable
Processor: Hitachi 6303
Data storage: 128 Kb SRAM standard (approximately 60,000 data values - Additional 2 Mb Flash as an option
Voltage: 9.6 to 16 Vdc
Typical current drain:1.3 mA quiescent, 13 mA during processing, and 46 mA during analog measurement
Batteries: DM12-9 (12V9Ah DiaMec) directly connected.
Humidity Sensor: ROTRONIC HYGROMER C94
Temperature Sensor: Pt100RTD
Humidity Measuring Range: 0...100%RH
Temperature Measuring Range (operating): -40 to 60oC
Temperature Limits (storage): -50 to 70oC
Humidity Accuracy at 20oC: ±1,0%RH (factory)
Temperature Accuracy at 20oC: ±0,2oC
Humidity Sensor Stability: better than 1%RH over a year
Response Time (without filter): 10 seconds (%RH and temperature)
Measurement Units: m/s in SDI-12 mode; knots, mph, kph, ft/min also available in other communication modes
Wind Speed
Range: 0 to 60ms-1 (130mph) for maximum accuracy; gust survival 100ms-1 (220mph)
Accuracy: ±2%
Resolution: 0.01ms-1
Wind Direction
Range: 0 to 360° – no dead band
Accuracy: ±3°
Resolution: 1°
Environmental
Operating Temperature: -35° to +70°C
Operating Humidity: <5% to 100%
Power Requirement: 9-30V DC at 40mA (typical)
Funnel Diameter: 254mm
Overall Height: 340mm
Output: Contact closure at tip
Weight: 1.0 kg
Operating Pressure Ranges: 600 to 1100 mbar absolute, Overpressure: 1.4 bar absolute
Frequency Output: TTL square wave from 600 to 1100Hz
Voltage Output: 0 to 2.5V (4-wire) or 0 to 5V (4-wire)
Accuracy (standard): ±0.5 mbar at 20oC, ±1 mbar from -10 to 50 oC, ±2 mbar from -20 to 60 oC, ±2.5 mbar from -40 to 60 oC
Long Term Stability: Better than 100 ppm/year
Operating Temperature Range: -40 oC to 60 oC
Response time (95 %): 18 s
Non stability (change/year): ± 1 %
Temperature dependence of sensitivity: ± 6 % (-10 to +40 °C)
Sensitivity (µV/W/m2): 10 to 35
Level accuracy: 1°
Operating temperature: -40 to +80 °C
Spectral range (50 % points): 305 - 2800 nm
Typical signal output for atmospheric applications: 0 - 50 mV
Maximum irradiance : 2000 W/m2
Expected daily accuracy: ± 10 %
Element: 1/3 DIN (to BS1904, IEC751, DIN43760)
Typical PRT Element Error: <±0.15°C at -100°C, <±0.1°C at 0°C, <±0.31°C at +200°C
(excluding datalogger and bridge resistor accuracy)
Maximum temp. of standard probe: +80°C
Accuracy: ±2.5% VWC using standard calibration iwith bulk electrical conductivity, < 0.5 deciSiemen m-1 (dSm-1) and bulk
density, <1.55g cm-3 in measurement range 0% VWC to 50% VWC
Precision (reproducibility): 0.05% VWC
Resolution: Probe-to-probe variability ±0.5% VWC in typical saturated soil
Output: ±0.7 volt square wave with frequency dependent on water content
Typical Power Requirements: 65mA at 12V DC during measurement - 45µA quiescent
Measurement Time: with Instruction 138: 0.50ms - With Instruction 27: 50ms
Power Supply Voltage: 5V DC minimum, 18V DC maximum
Enable Voltage: 4V DC minimum, 18V DC maximum
Sensitivity (nominal): 10 µV/W/m²
Spectral Range: 4.5 µm to 42 µm (50 % points)
Window Heating Offset (under direct solar irradiance): 25 W/m² max. (with 1000 W/m²normal incidence solar radiation)
Operating Temperature: -40 ºC to +80 ºC
Response time (63 %): <8 seconds
Thermopile Output Range: -250 to +250 W/m²
Temperature Dependence of Sensitivity: less than ±5 % (-10 ºC to +40 ºC)
Field of View: 150 º
Operating temperature: -30 °C to +70 °C
Heating level 1: dew removal
Heating level 2: ice and snow removal above -15 °C (wind speed<1 m/s)
Output: 0 VDC or 1 VDC ±0.1 V
Power requirement: without heating: 12 ±3 VDC, <10 mA, with heating level 1: 12 ±3 VDC, 1 W (nominal), with heating level
2: 12 ±3 VDC, 10 W (nominal)
[i] Campbell Scientific (2004) http://www.campbellsci.co.uk/
[ii] http://www.munro-group.co.uk
[iii] Stock C 2002 Ultrasonic Wind Sensor – A new approach from Gill Instruments Royal Met Society Newsletter No 19 15-17
[iv] www.druckinc.com
[v] www.kippzonen.com
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© by PSP Volume 16 – No 8. 2007
Fresenius Environmental Bulletin
ommended method is to use a direct link to a computer,
either a laptop on site, or to a desktop PC at any convenient location using an appropriate interface package. It is
more convenient to have our measurements transmitted to,
and stored in a computer either for immediate viewing or
for later retrieval and manipulation. As a further option,
communication can be carried out by using a remote communications package with a modem to transmit data, either
via the public telephone network or by one of the cellular
networks. In that occasion we must select another appropriate interface. However a long connection is more vulnerable to lightning damage, so we need to consider extra
lightning protection measures. For distances over 15 metres
we use RAD-SRM Short Range Modems in the communications link.
Since the computer-station distance is less than 15 metres, the simplest communication method is to use an appropriate interface package; hence we use the SC32A optoisolated interface, permanently mounted inside the enclosure together with the datalogger. The SC32A interfaces a
RS232 peripheral, commonly a computer or a printer, to the
serial I/O port of the Campbell Scientific datalogger. The
SC32A provides optical isolation between the datalogger
and the computer’s electrical system, protecting against
ground loops, normal static discharge and noise. The SC12
cable connects the datalogger to the 9-pin port of the SC32A.
Connection to the serial port of a PC is made with an
RS232 cable such as the Campbell Scientific SC25AT.
Figure 1 shows a photograph of the datalogger, SC32A
interface, battery and barometric pressure sensor into the
enclosure and the relevant connections.
a transformer and a charger. This offers a great stability to
power voltage and protects the station from abrupt network
voltage changes; as the station is not directly connected to
the electricity network. Moreover, the battery offers a stable energy supplying for a short-time period. The battery
voltage is monitored through a datalogger channel. The
battery is a lead acid battery, non spillable sealed and rechargeable and it is connected to a charging regulator.
As said, Figure 1 pictures clearly the battery and its
connection to the power supply system.
Software
A powerful and simple software, which is used to support direct communications (not remote) between CR10X
datalogger and the PC is the Campbell Scientific’s PC200W
ver3.0 software2. This software, which is compatible, so
with many contemporary dataloggers (including the CR800),
as many retired dataloggers (e.g., CR10, 21X, CR23X) can
support programming of the datalogger, data collection and
storing in comma separated files on the PC’s hard disk,
setting of the datalogger’s clock, access to a terminal emulation mode and display of real-time measurements.
For better data processing and display, we use a new,
more powerful software, called Analyzer ver4.5 (Scientific
Enterprises Ltd, 45 Agion Saranta Str., Moschato, Athens),
which has all the PC200W’s capabilities, but also supports
direct or remote communications between the datalogger
and the PC, as well as data display in a website, statistical analysis and graphics presentation.
The overall scheme of the communication setup diagram with the weather station data flux is displayed in the
diagram appearing in Figure 2.
System’s requirements; installation and maintenance
There are basic requirements that are essential for proper
sitting, operation and validation of the weather station. These
requirements are depicted clearly in the Guide to Meteorological Instruments and Methods of Observation [32], and
can be presented comprehensively at the following categories:
Observation requirements: WMO recommendations define the standards that basic meteorological instruments
have to satisfy. These standards are pictured in Table 2. By
the description and general characteristics of the instruments, given in Table 1, it is clear that these instruments
are appropriate for use in our AWS.
FIGURE 1 - A photograph of the datalogger, SC32A interface,
battery and barometric pressure sensor into the enclosure and
the relevant connections for direct communication.
Power supply: Power supply is also an essential fact at
the whole installation. Most stations mainly operate at 120
or 240 V AC supply. In our station, as any 9-16 Vdc source
can power the CR10X; we use a 12V9Ah battery connected
in parallel to the datalogger and the 240 V AC network
only supports and recharges battery with 13.5 Vdc, through
Sitting criteria for sensors: The AWS in Agrinio can
monitor the following meteorological parameters continuously and on regularly selected time steps:
1) air temperature (oC) 2) relative humidity (%) 3) wind
speed (m/s) 4) wind direction (o - deg clockwise from N)
5) rainfall (mm) 6) barometric pressure (mbar) 7) solar radiation (W/m2) 8) soil temperature (oC) 9) soil moisture (%)
10) IR (earth) radiation (W/m2) 11) sunshine duration (min).
2
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© by PSP Volume 16 – No 8. 2007
Fresenius Environmental Bulletin
Digital inputs
ARG100 Raingauge
PT100/3 (1/3 DIN PRT Probe)
CS12 cable
Analog inputs
CG3 pyrgeometer
Barometric pressure (Druck PRT410F)
25 to 9 pin
RS232 cable
(15 m max)
Personal Computer
CS616 Reflectometer
SC32ACommunication Interface
CR10X Data Logger
CSD1 Sunshine duration meter
CM3 pyranometer
Windsonic 2D Gill Anemometer
MP101A-T7-WAW
FIGURE 2 - The communication setup diagram for direct communication with the overall scheme of the weather station data flux.
TABLE 2 - Instruments and their specifications.
Variable
Air temperature
Relative humidity
Unit
°C
%
Range
-60 to +60°C
0 to 100 %
Wind speed
m/s
0 to 75 m/s
Wind direction
Rainfall
°
mm
Atmospheric pressure
hPa
0 to 360°
100 hPa
(within the range from
920 to 1080 hPa)
WMO recomendations
Accuracy requirements
± 0.1°C
±5%
± 0.5m/s for ≤ 5m/s
± 10% for > 5m/s
± 5%
3%
± 0.1hPa
According to WMO recommendations [32,33] some
sensors don’t demand special requirements for their sitting and can be mounted on the mast, while others, due to
the special criteria for the selection of their location, they
have specific sitting “treatment”. The sensors that belong
to the first category are the wind sensor, the barometric
pressure sensor, the pyranometer and the sunshine duration meter. The second category of sensors includes the
temperature and humidity sensor, the precipitation gauge,
the soil thermometers and hygrometers and the pyrgeometer.
The “classic” sitting criteria of WMO [32] suggest that
the wind sensor should be mounted at 10 m height above
Reported resolution
0.1°C
1%
Averaging time
1 minute
0.5
2 minutes
o
10
0.1 mm
2 minutes
0.1hPa
1 minute
ground of open terrain. Open terrain is defined as an area
where the distance between anemometer and any obstruction is at least 10 times the height of the obstruction. Using this rule, we should place the station 100 m away from
the 10 m high building of the University to ensure proper
wind flow at the site. This was the main difficulty we had
to face in our AWS in Agrinio, due to the limited open area
of the University campus.
Many urban weather stations have been placed over
short grass in open locations (parks, playing fields), with
standards similar to the stations in open rural areas. This
results in the fact that urban stations are actually monitoring modified rural-type conditions, not representative urban
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© by PSP Volume 16 – No 8. 2007
Fresenius Environmental Bulletin
ones and show no urban effect on temperature [33,34]. So,
the WMO standards have to be modified for urban sites
and urban stations must be centred in sites representative
of the location [33]. For our urban AWS, the better choice
is the roof of the 10 m height building of the Department
of Environmental and Natural Resources Management
(University of Ioannina). Rooftop weather stations have
been installed almost everywhere3,4,5,6,7, allowing constant
monitoring and archiving of local weather conditions. The
usual practice for such weather stations is that most sensors are mounted on the mast. However, it is better for many
sensors to be placed separately, on such a position that satisfies the more the WMO recommendations [33].
The wind sensor must be placed on a mast, high enough
above the roof structure, in order to avoid potentially turbulent air below. In order to find the best position for the mast
and the height of the wind sensor, many tests had to be
done on comparing the wind sensor’s values with these
from a certified portable anemometer such as Kestrel 1000
Pocket Wind Meter (certified by the USA’s National Institute of Standards and Testing - NIST), placed on a park
near the University building, according to the WMO recommendations. The wind characteristics in the park have
not been influenced from the “rural” standards of that area
(as it could happen in temperature or humidity and such
reasons led us to the selection of the roof, as mentioned
before). The values from this portable anemometer were
transformed to the wind sensor’s height equivalents by the
use of the power law equation [35]:
v sens  z sens
=
v port  z port




1/ 7
where vsens and vport are the wind speeds at heights
zsens and zport of the wind sensor on the mast and the portable anemometer, respectively. Wind speed and direction
measurements taken from the wind sensor at several locations and heights on the roof, were compared with the portable anemometer’s measurements transformed to the wind
sensor’s height equivalents each time. At low heights on
the roof (2, 3, 4 m), the wind sensor presented significantly
lower wind speed measurements (more than 10%) from the
portable anemometer’s transformed ones. Moreover, when
the mast with the wind sensor was placed on the edge of
the roof, there was a great divergence in sensitivity, having the biggest problem, especially, when wind flows from
the opposite side of the roof. After a long time with several tests, it was found that if the wind sensor is mounted
on a mast at 5 m or higher and the mast is placed at the
centre of the roof area, there is a significant similarity with
3
University of Otago (New Zeeland)
(http://www.physics.otago.ac.nz/eman/weather_station/index.html)
4
College of Engineering University of Iowa
(http://www.iihr.uiowa.edu/facilities/weather/index.html)
5
Case Western Reserve University (Cleveland Ohio)
(http://studentaffairs.case.edu/living/resources/weather/)
6
Weather Center of Central Connecticut State University
(http://www.ccsu.edu/weather/)
7
Cambridge University Computer Laboratory
(http://www.cl.cam.ac.uk/research/dtg/attarchive/weather/)
the portable anemometer equivalents (differences are less
than 1.5 % for every direction). Consequently, the 5 m height
is a satisfying choice for the wind sensor height. Therefore, as the building is 10 m height, the wind sensor is
placed at 15 m height above the ground level and transformations to the standard 10 m height [32] should be done
with the use of the power law equation [35].
For the pressure sensor (which is also mounted on the
mast) the difference between sensor elevation and field
elevation should be less than 30 m [32]. In our AWS this
condition is valid, as the roof of the building is about 10 m.
Besides, there is no vicinity of buildings where pressure
‘pumping’ due to gusts is probable, and also interior-exterior pressure differences do not exist as the sensor is not
located into a room. The barometric pressure sensor is kept
in a weatherproof enclosure which is mounted on the mast.
As the observed temperature and humidity should be
representative of the free air conditions surrounding the
station, at a height between 1.25 m and 2.00 m above the
ground level, this sensor is placed on an iron rod extension
placed at a corner of the building, at 2.00 m height and is
connected to the datalogger with a wire. WMO recommendations [32,33] emphasize mainly the height of the sensor
(1.25-2.00 m) and also the fact that the sensor must be
housed in a ventilated radiation shield to protect the sensor
from thermal radiation. Several tests had been made involving the comparison between the measurements taken by the
temperature sensor placed on an iron rod at the four corners
of the building at the height of 2 m and the temperature
measurements of a simple mercury thermometer placed at
the same height into a radiation shield, at an open area nearby. The diversions of the measurements at the four corners
and those of the mercury thermometer were less than 1%.
Yet, the orientation of the area where the sensor is placed
may also be relevant because the systematic sun-shade
patterns could influence the measurements. As continuous
monitoring is planned, a south oriented area is favoured
because there is less phase distortion [33].
For the precipitation gauge, the roof area beside the
mast is suitable, as objects should not be closer to the gauge
than a distance twice their height and sites on a slope should
be avoided [32].
According to WMO recommendations for urban meteorological stations [33], the main difficulty in measuring
outgoing radiation terms accurately is the exposure of the
down-facing pyrgeometer to view a representative area of
the underlying urban surface. CG3 pyrgeometer, although
the window is flat, has a 150 degrees field of view, which
practically means that the instrument “sees” a circular radiative source area of diameter more than seven times the sensor height (tan75o = 3.732). For “classic” weather stations,
a sensor height of 2 m is appropriate over a short grass surface (circular radiative source area of diameter more than
12 m). For urban sites, the radiative source area should
ideally be a representative sample of the main surfaces contributing to the flux. Clearly a much greater height is nec-
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© by PSP Volume 16 – No 8. 2007
Fresenius Environmental Bulletin
essary over an urban area in order to sample an area that
contains a sufficient population of surface facets to be representative. Considering the case of a radiometer at 10 m
(mounted on the rod extension at the most “representative” corner of the roof, beyond the roof’s edge, “looking”
towards the ground), the 90% source area has a diameter
of 60 m at ground level. This might seem sufficient to “see”
several buildings and roads.
The soil thermometers are placed into the soil at the
grass surrounding place next to the building, connected to
the datalogger.
The roof of the building is also an appropriate site for
radiation sensors, due to shade avoidance.
The exact position of all sensors is illustrated in the
schematic sketches of Figure 3.
The selected sitting is an ideal choice, because it offers the following advantages:
1) There are no obstacles nearby and no shade.
2) Testing of the station and maintenance (examination and
cleaning of the sensors etc.) can be done easily, since
there is direct access to the station.
3) There is direct access to AC power supply, which is
more trust-worthy than independent supplies (solar panels etc.), so peripherals consuming a significant amount
of power may be supplied in a continuous manner.
The station is secured to interventions from irrelevant
persons or animals, due to building security. The disadvantage of the concrete roof existence and the reflection of
solar radiation, which could influence the temperature and
FIGURE 3 - Schematic sketches of the building with the exact position of all sensors: a) over view; b) side view.
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humidity sensor primarily, have been restricted as this sensor is placed on an iron rod extension at a corner of the
building. The influence of the “harsh” thermal properties
of the concrete roof to the other sensors is negligible, as
the only instrument that could be affected, the pyrgeometer, is “hanging” beyond the roof’s edge, not facing any of
the roof area.
The wind sensor, the pyranometer and the sunshine
duration meter are mounted on a mast at the height of 5 m,
supported on wire ropes and no instrumentation towers or
portable tripods are required. The mast is less weighty,
cheaper and easier to install. It is not concreted on the roof,
but it is fixed with guy ropes, so it can be easily moved
from site to site even by one person and can be set up on
uneven ground. Moreover, the mast is of stainless-steel,
galvanized, with anti-lightning protection.
Since the mounted instruments are exposed to hazards,
we keep some instruments that do not demand directly open
air for their operation, as the datalogger, the interface, the
battery and the barometric pressure sensor, in a weatherproof enclosure which must be mounted on the mast and
is big enough to encapsulate them. The used enclosure has a
UV-stabilized rectangular protection box, and is made of
white, fibreglass-reinforced polyester. Sun protection is
achieved with a stainless-steel sunbonnet. There are also gas
tubes for rugged electrostatic discharge protection. Moreover, it is ventilated through a small tube that leads air to
the barometric sensor
In Figure 4 a photograph of the system with all instruments mounted can be seen.
As mentioned before, the station has being set-up in
Agrinio, Greece, at a longitude: E021o24'56.7", a latitude
of: N38o36'45.8" and an altitude of 82 m from the sea surface. Operation of this station and systematic observations
began on 26 November 2004. The collected meterological
data cover both research and educational needs. The station
is connected to the internet both for educational purposes
as well as to establish a direct real time connection.
Maintenance: The station has been made up by systems
that are simple to program and easy to operate, by personnel at no special experience. The station should have
the ability to be networked, if required.
A weather station, like any other piece of equipment,
requires regular maintenance in order to achieve a good and
validated performance. Some of the more important routine
maintenance chores can and should be performed by local
maintenance personnel since they can access the station
on a regular basis, while special work should be performed
by a trained technician8.
Validation of data
Accuracy checks, calibration and problems’ confronting: All instruments have been calibrated prior to installation by the manufacturers and could be installed without
any additional calibration. However, further calibration [36]
was performed and checks were made according to the requirements of the sitting location.
Regular field checks and calibrations of the used instruments are essential for guaranteeing the high quality and
homogeneity of the observations. These actions and their
results, as information about instrument validation, inspection and repair information, instrument inventory and station comparison experiments compose the station’s metadata and are archived along with the data [37].
All instruments of our AWS are equipped with calibration certification, but factory calibration should be performed
at least every two years in a calibration laboratory. Till
then, it is really essential to check the accuracy of our AWS
by field checks with suitable travelling reference instruments regularly. As professional reference instruments of
known high accuracy are too expensive, this check could
be done by comparing the station’s data with that from other
reference station in the locality, if the two stations have
similar microclimates. The reference station is a manned
professional station settled by the Greek Meteorological
Agency (EMY) in Agrinio airport (IATA code: AGQ,
ICAO code: LGAG), equipped with thermometer, barometer, hygrometer and raigauge, three kilometers away from
the University, at a similar distance from the lake as our
AWS and at rather similar terrain. As the reference station
has been settled in an airport, it is characterized by accurate measurements; especially in barometric pressure. Analytically:
Field checks for the temperature sensor have been done
by comparing our values with these from a simple mercury
thermometer with the bulb at exactly the same point in space
as the AWS probe. For wind speed and direction measurements, checks have also been done easily by comparing the
AWS’s values with the readings from the Kestrel portable
anemometer, placed near the wind sensor for a short period.
FIGURE 4
A photograph of the station with all instruments mounted.
8
The University of Arizona: Sitting and Maintenance of Weather Stations
http://ag.arizona.edu/pubs/water/az1260.pdf
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During the period of the station’s operation, our AWS
was characterized by remarkable reliability and endurance
to external difficult situations (power supply failure, harsh
weather conditions, long period without data gathering etc.).
Only once the PC200W software seemed to be “blocked”
and real-time monitoring was impossible. This problem was
a superficial instant failure of data presentation, as after reloading the starting program to the datalogger, it performed
well, without any loss of the previous data. This problem
showed that even after possible errors and failures when
data display procedure has been stopped, there is the ability
of data recovery.
Comparison: Since there are too many errors (random,
systematic, large, micrometeorological) we ought to verify
the validity and the quality of the station’s data. The primary
purpose of quality control is missing data detection and
error detection in order to ensure the highest possible standard of accuracy and the optimum use of these data. Prior to
their use in computation of the parameter values, two types
of control were made [3,38]:
Quality control of raw data, drawn from the data archives, comprised of a) a plausible value check, where we
verified that the values are within the acceptable range
limits and b) a time consistency check on a plausible rate
of change, where we verified that there are no unrealistic
leaps in values.
tion, as there is an airport, have been regularly checked from
the authority for their accuracy and sensitivity, at frequent
intervals.
The aim of these comparisons is mainly to check if
the AWS’s data follow the same temporal fluctuations in
their values as the EMY’s data, in order to strengthen the
validation of our station. The similarity in data of both stations could not achieve a hundred percent, as differences in
characteristics of the stations could cause slight differentiations in measurements.
On a monthly basis, Figures 5, 6, 7, 8 and 9 show the
temporal variations of the monthly mean measured values
of air temperature, air relative humidity, monthly rainfall
values, rainy days per month and monthly mean barometric pressure respectively, for a 19-months period, from the
1st of December 2004 to the 31th of August 2006 for AWS
(UNIV) and the Greek Meteorological Agency’s station
(EMY) in Agrinio.
As shown, there is a good agreement between the values from the two stations for air temperature (correlation
coefficient λ=0.998886) as both stations present the same
Air temperature
30
Air temperature ( o C)
© by PSP Volume 16 – No 8. 2007
Quality control of processed data, drawn from the
monitoring of instantaneous ones, consisted of a) a plausible value check and b) a time consistency check on a plausible rate of change.
In both types, missing and erroneous values are distinguished by appropriate algorithmic routines running in a
PC. Installation and set-up followed the standard suggestions, presented in the instrument and micrologger manuals. Suggested daily, weekly, and longer term checks, maintenance and set instrument replacements were scheduled
while maintenance logs for each station were kept.
20
UNIV
15
EMY
10
5
0
0
5
10
15
20
25
Month
FIGURE 5 - Temporal variations of the monthly mean measured
values of air temperature for a 19-months period, from the 1st of
December 2004 to the 31th of August 2006 for AWS (UNIV) and the
Greek Meteorological Agency’s station (EMY) in Agrinio (AWS in
direct communication).
All instruments have been calibrated prior to installation by the manufacturers and could be installed without
any additional calibration. However, further calibration [36]
was performed and checks were made according to the
requirements of the sitting location.
Relative humidity
RH (%)
The safest way to assess the quality of data from our
AWS is to compare them with that from the established
station of EMY at Agrinio airport. More attention has to
be paid to the exposure of the reference station’s sensors
and to the accuracy and validation of that station.
In the EMY’s station, the thermometer is protected by
a natural aspiration radiation shield, (as in the University’s AWS), the barometer and hygrometer are placed
into a wooden shield and the raigauge is exposed directly to
the open air, according to WMO recommendations. Consequently, the meteorological instruments in both stations
have similar exposure. The instruments in the EMY’s sta-
25
90
80
70
60
50
40
30
20
10
0
EMY
UNIV
0
5
10
15
20
25
Month
FIGURE 6 - Temporal variations of the monthly mean measured
values of relative humidity for a 19-months period, from the 1st of
December 2004 to the 31th of August 2006 for AWS (UNIV) and the
Greek Meteorological Agency’s station (EMY) in Agrinio (AWS in
direct communication).
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tions (λ=0.974325), monthly rainfall totals (λ=0.984431)
and rainy days per month (λ=0.982505). For monthly mean
barometric pressure (λ=0.994632), the values from AWS
are systematically lower than those from the EMY’s station
by a stable quantity each month, as AWS is settled in upper
altitude.
Rainfall values
350
Rainfall (mm)
300
250
200
EMY
150
UNIV
100
50
0
0
5
10
15
20
25
Month
FIGURE 7 - Temporal variations of the measured values of monthly
rainfall totals for a 19-months period, from the 1st of December 2004
to the 31th of August 2006 for AWS (UNIV) and the Greek Meteorological Agency’s station (EMY) in Agrinio (AWS in direct communication).
18
16
14
12
10
8
6
4
2
0
EMY
Air temperature
UNIV
20
18
0
5
10
15
20
25
Tair (o C)
Rainy days
Rainy days
On a daily basis, Figures 10 and 11 present the fluctuations of air temperature and barometric pressure measurements for our AWS (UNIV) and the EMY’s station in
the Agrinio airport during 72 hours (from 00.00 at the 1st
of December 2004 to 24.00 at the 3rd of December 2004).
There is also a strong agreement between these values (coefficient correlations are: λ=0.996242 for air temperature
measurements and λ=0.997138 for barometric pressure
measurements respectively). AWS’s air temperature measurements also present slightly higher values than those from
the EMY’s station, due to the heat island effect. Moreover,
EMY’s station barometric pressure measurements have
systematically higher values than those from AWS, due to
the different altitude. By that time, intradiurnal differences
are been checked out regularly.
Month
FIGURE 8 - Temporal variations of the number of rainy days per
month for a 19-months period, from the 1st of December 2004 to the
31th of August 2006 for AWS (UNIV) and the Greek Meteorological
Agency’s station (EMY) in Agrinio (AWS in direct communication).
16
UNIV
14
EMY
12
10
0
20
40
60
80
Hour
FIGURE 10 - Temporal variations of the measured values of air
temperature for a 72-hours period, from the 1st of December 2004 to
the 3rd of December 2004 for our AWS (UNIV) in direct communication and the Greek Meteorological Agency’s station (EMY) in Agrinio.
Barometric pressure
1025
Patm (mbar)
1020
1015
EMY
1010
Barometric pressure
UNIV
1005
1024
1000
1022
995
5
10
15
20
25
Patm (mbar)
0
Month
FIGURE 9 - Temporal variations of monthly mean values of measured barometric pressure for a 19-months period, from the 1st of
December 2004 to the 31th of August 2006 for AWS (UNIV) and the
Greek Meteorological Agency’s station (EMY) in Agrinio (AWS in
direct communication).
fluctuations month by month, but the values from our AWS
are slightly greater than these from EMY’s station, due to
the heat island effect. There is also a good agreement between the values of air relative humidity from both sta-
1020
UNIV
1018
EMY
1016
1014
1012
0
20
40
60
80
Hour
FIGURE 11 - Temporal variations of the measured values of barometric pressure for a 72-hours period, from the 1st of December 2004
to the 3rd of December 2004 for our AWS (UNIV) in direct communication and the Greek Meteorological Agency’s station (EMY) in
Agrinio.
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Of course, weather conditions can change over relatively short distances, but as the region between the two
stations is relatively flat, the weather conditions are similar. Small systematic differentiations between two stations’
measurements, mainly concern the air temperature measurements (due to the heat island effect) and measurements
of barometric pressure (due to the different altitude) and
in no occasion measurements of solar radiation, sunshine
duration or even relative humidity, the differentiations of
which are by chance and negligible. For wind measurements, the use of the portable anemometer can justify the
accuracy and validity of the measurements at the AWS.
dataloggers and a PC. This 32-bit software supports all
contemporary dataloggers (including the CR1000), all datalogger operating systems (e.g., mixed-array, table data,
PAKBUS), and many retired dataloggers (e.g., CR500,
CR10, 21X).
REMOTE AWS
Our AWS could also be installed in remote areas. In
that occasion, three basic modifications should be performed: change in communications link, in power supply
and in software.
Description of the equipment,
communications link and power supply
The equipment (sensors, battery, mast, guy ropes, enclosure) remains unaltered. Instead of a SC32A opto-isolated interface, a SC932A is used to interface a CSI datalogger to any modem that is configured with an RS-232 DCE
(Data Communications Equipment) serial port. The used
modem is a M2M Wavecom, with an advanced open software platform: Open AT, with a fixed dialing number, SIM
Toolkit Class 2, SIM, locked network and service provider,
real time clock, alarm management and software upgrade
through Xmodem protocol. This modem, which carries a
dual band antenna, can also support remote station control
and other wireless services: GSM/GPRS data, SMS and
voice via a simple serial connection.
Figure 12 shows the datalogger, the interface, the modem and the antenna for remote communications, while in
Figure 13 the overall scheme of the communication setup
diagram with the weather station data flux can be seen.
When there is no city power supply, the same remote
AWS could be used, without any modification, except of
the addition of renewable energy sources, such as a photovoltaic solar panel [39], a wind-powered generator or a hybrid of solar panel and wind-powered generator, charging
the 12V9Ah rechargeable battery.
Software
PC200W Campbell’s software supports only direct communications. For telemetry and scheduled data collection the
company provides LoggerNet support software9, which lets
us manage an existing LoggerNet datalogger network from
a remote location. This software is based on the client/ server network architecture, facilitates programming, communications, and data retrieval between Campbell Scientific
9
http://www.campbellsci.com/loggernet3x
FIGURE 12 - A photograph of the datalogger, SC932A interface,
M2M Wavecom’s modem and dual band antenna into the enclosure and the relevant connections for remote communication.
LoggerNet is a company’s basic software that supports
mainly communication and data collection and less data
displaying or analysis. For better data presentation through
the internet network and extra advantages and capabilities,
the Analyzer ver4.5, that has been also used for direct communication, is a more powerful software.
System’s requirements; installation and maintenance
System’s requirements and installation: As in direct communication, system’s requirements for remote communication are in accordance to WMO recommendations [32].
Installation was performed on a remote site of the roof area,
where the distance from the PC is about 150 meters, so a
direct communication could not be established (as the distance is greater than 15 meters). The conditions of this AWS
are similar to any other remote site having city power supply.
Maintenance: The required maintenance chores are generally more “painful” than these for the short distance
AWS, for the instruments’ check requires now longer removal. A camera connected to a network could possibly
help in monitoring the instruments’ good state and operation and in the safety and protection of the instruments at
the same time.
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Digital inputs
ARG100 Raingauge
Barometric pressure (Druck PRT410F)
Analog inputs
CG3 pyrgeometer
25 to 9 pin
RS232 cable
Dual band antenna
PT100/3 (1/3 DIN PRT Probe)
CS12 I/O 9-pin
cable
M2M Wavecom modem
CR10X Data Logger
CS616 Reflectometer
SC932A Communication Interface
CSD1 Sunshine duration meter
CM3 pyranometer
Windsonic 2D Gill Anemometer
MP101A-T7-WAW
FIGURE 13 - The communication setup diagram for remote communication with the overall scheme of the weather station data flux.
Validation of data – comparison test and results
Comparison of Tair
As in case of the AWS with direct communication,
validation of data could be done by comparing the station’s
data with that from the reference station in the airport.
40
35
As mentioned in the case of the AWS with direct communication, the accuracy and validity of the measurements
at the remote AWS could have been done additionally by
field checks (with a simple mercury thermometer for the
temperature sensor checking and with the Kestrel portable
anemometer for wind speed and direction sensor). For barometric pressure sensor and sunshine duration meter, the
comparison with the airport’s measurements gives a strong
validation to the measurements of the AWS and field checks
are unnecessary.
Tair (o C)
Figure 14 presents the fluctuations of air temperature
measurements for our remote AWS (UNIV) and the
EMY’s station in Agrinio airport during 72 hours (from
00.00 at the 6th of September 2006 to 24.00 at the 8th of
September 2006). There is also a strong agreement between
these values (coefficient correlation λ=0.999013). A slight
differentiation (higher values of UNIV’ station) is due to
the heat island effect.
30
EMY
25
UNIV
20
15
0
20
40
60
80
Hour
FIGURE 14 - Temporal variations of the measured values of air
temperature for a 72-hours period, from the 6th of September 2006 to
the 8th of September 2006 for our AWS (UNIV) in remote communication and the Greek Meteorological Agency’s station (EMY) in Agrinio.
AWS remote capabilities and enhancement
As a modern and up-to date version of the station, its
operation can be monitored via a webpage which may display the status of the AWS network in real-time using suitable software. This reduces manual labour and at the same
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time enhances data quality. A filter can be installed as a
quality assurance, cutting erroneous data and alerting maintenance staff to action via automatic email. The advantage
of this automatic alerting feature is that it enables early detection and fault diagnosis, enhancing data availability [38].
This AWS can be enhanced with network cameras, visible and infrared in order to provide real-time weather photographs to the University website via broadband network
or GPRS [38,40]. They could assist forecasters in monitoring more closely changes in weather conditions as well as
the development of strong convective weather [38]. Moreover, this could assist in solving problems on disagreements
between human and automated observations i.e. when there
is a big difficulty in determine the rainfall. The desired
0.05 mm h–1 sensitivity, chosen on a recent recommendation for detection of precipitation, was almost impossible
to determine from any rain gauge data [24,25]. So, network
cameras, turned at the sky, could help, for instance, in slight
drizzle, which could never be detected.
Further work involves the improvement of the station’s
capabilities, the addition of extra instruments such as a net
radiation detector and more soil thermometers. While the
station is currently connected to the Internet, an extensive
network performance is a further requirement, including
services of voice/data information through communication
lines. This procedure is currently on, including a local wireless net with cameras and relevant internet facilities.
ACKNOWLEDGEMENTS
Mr. Bagiorgas gratefully acknowledges the Greek State
Scholarships Foundation for the attainment of educational
leave and financial support, grant number: 1534/2004.
Our AWS can also be enhanced with a broadband UV
sensor for measuring ultraviolet radiation to alert people
about the need to adopt protective measures when exposed
to the sun [38]. The last could be very useful in rural areas,
where people deal with agriculture activities, without taking any protection, for many hours under the sun.
CONCLUSIONS AND FURTHER WORK
The design, installation and operation of an effective
AWS are described in this paper. This station is easy to be
installed and capable of operating throughout the year without significant problems, while maintenance of all the instruments of the station is quite simple. Moreover, the station can easily communicate by various ways (direct or remote – with some modifications) and has been tested for its
performance in order to verify that it can perform according to the specifications set by the users. The station is
found accurate as regards its data in both conditions (short
distance or remote site) and it is easily connected to the
Internet.
Except of the direct meteorological applications of the
AWS as monitoring of the meteorological parameters,
analysis of the microclimatological regime with long term
meteorological data acquisition, weather prediction, archiving of the meteorological extremes (such as heatwaves and
floods) etc., the described AWS could serve in many energy and environmental applications, where meteorological
data are needed.
The data obtained from our AWS agree with the climatological characteristics of Agrinio area: hot and dry summer with long sunshine duration, and mild winter with high
rainfall. Comparing to other inland locations of the prefecture of Aitoloakarnania, Agrinio has rather poor wind potential (the area is surrounded by mountains) and higher values
of relative humidity (there are two lakes nearby).
960
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© by PSP Volume 16 – No 8. 2007
Fresenius Environmental Bulletin
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Received: October 11, 2006
Revised: December 27, 2006; February 07, 2007
Accepted: April 10, 2007
CORRESPONDING AUTHOR
Haralambos S. Bagiorgas
University of Ioannina
Department of Environmental and
Natural Resources Management
2 G. Sepheri Str.
30100 Agrinio
GREECE
Phone: +302641074111
Fax: +302641074102
E-mail: chbagior@cc.uoi.gr
FEB/ Vol 16/ No 8/ 2007 – pages 948 - 962
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