This chapter overviews the precipitation measurement methods and quantifies its
uncertainty as a function of spatiotemporal scales and precipitation intensity in Section 13.2, with a case study on its scale-based uncertainty impact on and error propagation
into hydrological prediction in Section 13.2, followed by a conclusion in Section 13.4.
13.2 SPATIOTEMPORAL SCALING FOR PRECIPITATION
13.2.1 Overview of Precipitation Measurements
13.2.1.1 In Situ Precipitation Measurements Liquid precipitation is traditionally
measured by rain gauges, which is a point-based measurement but usually considered
as “ground truth.” The basic idea of the rain gauge is to collect rainfall into a
cylindrical container of a fixed diameter during storms. There are different types of
rain gauges: weighing gauges, tipping-bucket (TB) gauges, capacitance gauges,
optical gauges, disdrometers, and so on. Among all those types of rain gauges,
the TB gauge is commonly used by agencies such as the National Weather Service
(NWS) and United States Geological Survey (USGS) (Habib et al., 2001). Before the
era of radar and satellite precipitation missions, rain gauges were applied for
operational as well as calibration purposes [e.g., calibrate radar precipitation estimation algorithm (Anagnostou and Krajewski, 1998)].
Although rain gauges provide surface rainfall measurements at relatively high
accuracy compared to remote sensing precipitation estimations at a specific point, in
most cases, rain gauge instruments are so sparsely distributed that they are constrained
from accurately characterizing spatial and temporal variability (Villarini et al., 2008).
13.2.1.2 Remote Sensing Precipitation Measurements Unlike gauges that measure precipitation at point scales, recent developments of radar and satellite precipitation estimation techniques have provided much broader coverage beyond ground
in situ observations. Ground radar measures the electromagnetic backscatter power
return from raindrops, also expressed as the reflectivity factor Z (mm
6 /mm
3
). Usually
an empirical Z–R relationship (where R indicates the precipitation) is applied for
converting measured reflectivity to rainfall intensity estimation. Although ground
radar provides extended precipitation measurements over rain gauge stations, it is still
limited for remote areas, mountain regions, and vast oceanic surface. The recent
development of satellite-based precipitation retrieval techniques has provided
extended precipitation coverage beyond both in situ data and ground radar networks.
Spaceborne radar on the satellite platforms, together with passive radiometers and
infrared sensors, are combined to derive global precipitation information.
13.2.2 Spatiotemporal Scales of Precipitation
With the recent advances in remote sensing techniques, remotely sensed precipitation
can provide extended rainfall information at relatively high temporal and spatial
resolution. Current spatial resolution of ground radar can reach as high as around
250 m from the NWS WSR-88 radar network in the Continental United States while
254
SPATIOTEMPORAL SCALES OF REMOTE SENSING PRECIPITATION
uncertainty as a function of spatiotemporal scales and precipitation intensity in Section 13.2, with a case study on its scale-based uncertainty impact on and error propagation
into hydrological prediction in Section 13.2, followed by a conclusion in Section 13.4.
13.2 SPATIOTEMPORAL SCALING FOR PRECIPITATION
13.2.1 Overview of Precipitation Measurements
13.2.1.1 In Situ Precipitation Measurements Liquid precipitation is traditionally
measured by rain gauges, which is a point-based measurement but usually considered
as “ground truth.” The basic idea of the rain gauge is to collect rainfall into a
cylindrical container of a fixed diameter during storms. There are different types of
rain gauges: weighing gauges, tipping-bucket (TB) gauges, capacitance gauges,
optical gauges, disdrometers, and so on. Among all those types of rain gauges,
the TB gauge is commonly used by agencies such as the National Weather Service
(NWS) and United States Geological Survey (USGS) (Habib et al., 2001). Before the
era of radar and satellite precipitation missions, rain gauges were applied for
operational as well as calibration purposes [e.g., calibrate radar precipitation estimation algorithm (Anagnostou and Krajewski, 1998)].
Although rain gauges provide surface rainfall measurements at relatively high
accuracy compared to remote sensing precipitation estimations at a specific point, in
most cases, rain gauge instruments are so sparsely distributed that they are constrained
from accurately characterizing spatial and temporal variability (Villarini et al., 2008).
13.2.1.2 Remote Sensing Precipitation Measurements Unlike gauges that measure precipitation at point scales, recent developments of radar and satellite precipitation estimation techniques have provided much broader coverage beyond ground
in situ observations. Ground radar measures the electromagnetic backscatter power
return from raindrops, also expressed as the reflectivity factor Z (mm
6 /mm
3
). Usually
an empirical Z–R relationship (where R indicates the precipitation) is applied for
converting measured reflectivity to rainfall intensity estimation. Although ground
radar provides extended precipitation measurements over rain gauge stations, it is still
limited for remote areas, mountain regions, and vast oceanic surface. The recent
development of satellite-based precipitation retrieval techniques has provided
extended precipitation coverage beyond both in situ data and ground radar networks.
Spaceborne radar on the satellite platforms, together with passive radiometers and
infrared sensors, are combined to derive global precipitation information.
13.2.2 Spatiotemporal Scales of Precipitation
With the recent advances in remote sensing techniques, remotely sensed precipitation
can provide extended rainfall information at relatively high temporal and spatial
resolution. Current spatial resolution of ground radar can reach as high as around
250 m from the NWS WSR-88 radar network in the Continental United States while
254
SPATIOTEMPORAL SCALES OF REMOTE SENSING PRECIPITATION