Environmental Engineering Reference
In-Depth Information
present weather, thunderstorms, soil temperature
(at a range of depths) and terrestrial temperature.
The quality of the final data received by the
researcher or farmer can only be as good as the
quality of the sensors used. No post analysis of
the data can improve the accuracy or reliability
of the information obtained.
Many AWS manufacturers use sensors which
have poor accuracy, and whose calibration may
drift significantly over a short time. Some sen-
sors, particularly local made are also prone to
premature failure.
The manufacturer's sensor specifications
should be read very carefully as they can be
misleading in some situations and manufacturer's
claims can often not be replicated in the labora-
tory. For example, a manufacturer may quote the
response time for a humidity sensing element but
not the combined response time of the sensing
element, electronics and filter which can be orders
of magnitude longer; also, the manufacturer may
quote an accuracy for a device such as a pressure
sensor but give no indication as to confidence limits
of the specification. These omissions can make a
large difference as to the suitability of the device.
There are a number of fundamental character-
istics which make up the accuracy and precision
of a sensor.
•
Linearity
- the deviation of the sensor from
ideal straight line behaviour.
All of these factors go into defining the ac-
curacy and precision of a sensor. In the present
case monitoring climatic temperature changes at
high altitude regions in the Himalayas requires
that a significant amount of data is collected over
a long period and therefore a sensor is required
which has very little drift.
It is also necessary to ensure that AWS as a
device should be sturdy and robust to withstand
the vagaries of weather. As a general rule, these
devices are installed in harsh environments. For
the present study e.g the AWS was installed at
an altitude of about 13000 feet in the high hi-
malayas where weather conditions and terrain
was extremely harsh. This requires the sensors
to be well designed and constructed, have strong
waterproof cover for the electronics and be able
the withstand extremes of climate variability. It
is counterproductive to install a lightweight wind
vane that will break the first time a bird sits on it
or to use a sensing device which is designed for
laboratory use (e.g. many humidity probes) in
a dusty environment. Frequent replacement of
lightweight or unreliable instruments can end up
costing more than their more costly counterparts.
The swapping of sensors can also have a significant
effect on the quality of data, frequently introduc-
ing discontinuities into a data series.
Although AWS are a boon to gather data on
weather parameters we also need to ensure that
these communication technologies need to give
us the right kind of outputs through appropriate
formats.
In most situations the format used should be:
•
Resolution
- the smallest change the device
can detect (this is not the same as the ac-
curacy of the device).
•
Repeatability
- the ability of the sensor
to measure a parameter more than once
and produce the same result in identical
circumstances.
•
Response time
- normally defined as the
time the sensor takes to measure 63% of
the change.
•
Drift
- the stability of the sensor's calibra-
tion with time.
•
Hysteresis
- the ability of the sensor to pro-
duce the same measurement whether the
phenomenon is increasing or decreasing.
•
Flexible
- so new sensors can be added
without having to re-process all the sta-
tions records into the new format
•
Simple
- such that only simple program-
ming is required to decode the data
