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Calibrating Ground-Based Radars against TRMM and GPM
by
Louf, Valentin
, Manton, Michael J.
, Warren, Robert A.
, Protat, Alain
, Kane, Thomas A.
, Ramsay, Hamish A.
, Siems, Steven T.
in
Atmosphere
/ Atmospheric precipitations
/ Calibration
/ Errors
/ Global precipitation
/ Precipitation
/ Radar
/ Radar data
/ Radar systems
/ Rain
/ Rainfall
/ Rainfall measurement
/ Reflectance
/ Regions
/ Satellite observation
/ Satellites
/ Superhigh frequencies
/ Tropical climate
/ Tropical rainfall
/ Tropical Rainfall Measuring Mission (TRMM)
2018
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Calibrating Ground-Based Radars against TRMM and GPM
by
Louf, Valentin
, Manton, Michael J.
, Warren, Robert A.
, Protat, Alain
, Kane, Thomas A.
, Ramsay, Hamish A.
, Siems, Steven T.
in
Atmosphere
/ Atmospheric precipitations
/ Calibration
/ Errors
/ Global precipitation
/ Precipitation
/ Radar
/ Radar data
/ Radar systems
/ Rain
/ Rainfall
/ Rainfall measurement
/ Reflectance
/ Regions
/ Satellite observation
/ Satellites
/ Superhigh frequencies
/ Tropical climate
/ Tropical rainfall
/ Tropical Rainfall Measuring Mission (TRMM)
2018
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Do you wish to request the book?
Calibrating Ground-Based Radars against TRMM and GPM
by
Louf, Valentin
, Manton, Michael J.
, Warren, Robert A.
, Protat, Alain
, Kane, Thomas A.
, Ramsay, Hamish A.
, Siems, Steven T.
in
Atmosphere
/ Atmospheric precipitations
/ Calibration
/ Errors
/ Global precipitation
/ Precipitation
/ Radar
/ Radar data
/ Radar systems
/ Rain
/ Rainfall
/ Rainfall measurement
/ Reflectance
/ Regions
/ Satellite observation
/ Satellites
/ Superhigh frequencies
/ Tropical climate
/ Tropical rainfall
/ Tropical Rainfall Measuring Mission (TRMM)
2018
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Journal Article
Calibrating Ground-Based Radars against TRMM and GPM
2018
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Overview
Calibration error represents a significant source of uncertainty in quantitative applications of ground-based radar (GR) reflectivity data. Correcting it requires knowledge of the true reflectivity at well-defined locations and times during a volume scan. Previous work has demonstrated that observations from certain spaceborne radar (SR) platforms may be suitable for this purpose. Specifically, the Ku-band precipitation radars on board the Tropical Rainfall Measuring Mission (TRMM) satellite and its successor, the Global Precipitation Measurement (GPM) mission Core Observatory satellite together provide nearly two decades of well-calibrated reflectivity measurements over low-latitude regions (±35°). However, when comparing SR and GR reflectivities, great care must be taken to account for differences in instrument sensitivity and frequency, and to ensure that the observations are spatially and temporally coincident. Here, a volume-matching method, developed as part of the ground validation network for GPM, is adapted and used to quantify historical calibration errors for three S-band radars in the vicinity of Sydney, Australia. Volume-matched GR–SR sample pairs are identified over a 7-yr period and carefully filtered to isolate reflectivity differences associated with GR calibration error. These are then used in combination with radar engineering work records to derive a piecewise-constant time series of calibration error for each site. The efficacy of this approach is verified through comparisons between GR reflectivities in regions of overlapping coverage, with improved agreement when the estimated errors are removed.
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