Campbell Scientific PWS100 Present Weather Sensor - Manual (Page 96)

Section 8. Functional Description
8.6.3 Precipitation Accumulation
Precipitation accumulation is calculated in millimeters over a specified time
period by summing the volume of all precipitation particles falling through the
defined volume. As mentioned above, as with most other similar optical
detectors, the PWS100 will be subjected to increased error and bias in windy
conditions.
Accumulations of snow are based on the water content of those particles. The
snow water content is a user definable parameter in the instrument, see Section
7.4.5. The accumulation given will be the water equivalent depth and not the
snow depth which requires further knowledge of packing structures, wind
effects, ground temperature, ground type and a myriad of other parameters
related to snow depth. The ratio of water accumulation to snow depth will be
lower than the snow water content figure and is typically in the order of 0.1
(i.e., the snow pack is 10 times deeper than the water accumulation of the
melted snow pack). Local conditions will dictate the values to use and since
these will be different for every location it is not possible to give accurate snow
depth figures with the PWS100. Thus only accurate snow water content values
for the particles falling through the detection volume are given.
8.6.4 Present Weather
Present weather covers precipitation type analysis and visibility in the PWS100
algorithms. The PWS has separate routines for these two functions along with
various housekeeping tasks to ensure that the output is as accurate as possible.
8.6.4.1 Precipitation Types
The precipitation types identified are drizzle, freezing drizzle, rain, freezing
rain, snow grains, snow flakes, ice pellets, hail and graupel. A mixture of these
types and intensity of these types gives an array of outputs that have been
assigned codes by the WMO. These are defined as the WMO SYNOP codes
(4680, W
a
W
a
). See Appendix A for the code table. Each particle is assigned a
type from analysis of particle size, velocity, signal structure and inclusion of
any other weather parameters from auxiliary instruments connected to the
PWS100. The CS215-PWS provides three additional parameters, temperature,
relative humidity and wetbulb temperature. Fuzzy logic is used to define
particle type from these values as this provides the best estimate of a particle
type, allowing for grey boundaries in terms of size and velocity measurements
for example, which may help to determine particle types during windy
conditions. Standard logic can be flawed when incorporating a number of
different parameters from the signal and auxiliary instruments as the
boundaries have to be effectively black and white allowing for no margin of
error, this is highlighted by the use of temperature matrices on certain
instruments which have fixed boundaries between snow and rain. With such
non-fuzzy logic instruments all particles above a set temperature are classified
as rain, drizzle or unknown and below that temperature have to be snow or
unknown (the unknown classification sometimes being used if other sensor
values are contradictory to the temperature measurement – for example a
wetness grid on the instrument remains dry). The PWS100 clearly does not
have such limitations and can cope with a wider variation in meteorological
parameters within its classification routines.
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