Geoscience Reference
In-Depth Information
Important points in this chapter
Precipitation gauges
: provide point observations by gathering precipitation
falling into a funnel of known area and storing it for later measurement
either manually or automatically, but preferred gauge designs and site rec-
ommendations vary between countries and most gauge data are systemati-
cally low by about 5-10% for rainfall, and by much greater than this (perhaps
~50%) for snowfall.
●
Gauge errors
: may include basic instrumental errors (e.g., evaporation loss)
but are mainly caused by wind blowing across the gauge top reducing the
catch
, although these can be reduced by improved (but rarely implemented)
gauge mounting (see text).
●
Gauge design
: most gauges are still operator read, but most historical
high
time resolution
precipitation data have been gathered using
siphon and chart
recorders, but recording systems which provide electronic output such as
when using a
tipping bucket
or a
strain gauge/load cell
are now preferred.
●
Areal representativeness of gauges
: gauge networks provide a poor (at best
5 × 10
−12
%) sample and are mainly biased toward wealthy, developed coun-
tries and population centers, but in new networks strategies that sample
likely systematic spatial influences (see text) can give improvements.
●
Snowfall measurement
: measurement of snowfall using gauges is problem-
atic because
catch
reduction due to wind is much greater and frozen precipi-
tation takes time to melt and might cover the gauge completely, so it is likely
preferable to measure snow depth and assume snow density or to measure it
as in
snow courses
, or to weigh the snow cover using
snow pads
/
pillows
.
●
Ground-based radar estimates
: provide real time estimates of area-average
precipitation over 10-20 km
2
pixels but they are inaccurate unless calibrated
by underlying gauges and as yet do not exist as long-term records.
●
Satellite precipitation estimates
: is an active area of hydrometeorological
research with activity in three general areas, i.e., (a) cloud mapping and char-
acterization; (b) passive measurement of cloud properties; and (c) space-
borne radar (see text for details), all of which involve developing empirical
relationships between remotely sensed variables and surface calibration data,
with some data products now using merged information from several
remotely sensed variables.
●
References
Firstweather (2010) Online at www.1stweather.com/global/radar/index.shtml.
Larson, L.W. & Peck, E.L. (1974) Accuracy of precipitation measurements for hydrological
modeling.
Water Resources Research
,
, 857-63.
NOAA (2010) Online at www.magazine.noaa.gov/stories/mag103.htm.
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