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Titel |
Characterization of video disdrometer uncertainties and impacts on estimates of snowfall rate and radar reflectivity |
VerfasserIn |
N. B. Wood, T. S. L'Ecuyer, F. L. Bliven, G. L. Stephens |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1867-1381
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Digitales Dokument |
URL |
Erschienen |
In: Atmospheric Measurement Techniques ; 6, no. 12 ; Nr. 6, no. 12 (2013-12-20), S.3635-3648 |
Datensatznummer |
250085141
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Publikation (Nr.) |
copernicus.org/amt-6-3635-2013.pdf |
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Zusammenfassung |
Estimates of snow microphysical properties obtained by analyzing
collections of individual particles are often limited to short timescales
and coarse time resolution. Retrievals using disdrometer
observations coincident with bulk measurements such as radar
reflectivity and snowfall amounts may overcome these limitations;
however, retrieval techniques using such observations require
uncertainty estimates not only for the bulk measurements themselves,
but also for the simulated measurements modeled from the disdrometer
observations. Disdrometer uncertainties arise due to sampling and
analytic errors and to the discrete, potentially truncated form of the
reported size distributions. Imaging disdrometers such as the
Snowflake Video Imager and 2-D Video Disdrometer provide remarkably
detailed representations of snow particles, but view limited
projections of their three-dimensional shapes. Particle sizes
determined by such instruments underestimate the true dimensions of
the particles in a way that depends, in the mean, on particle shape,
also contributing to uncertainties. An uncertainty model that accounts
for these uncertainties is developed and used to establish their
contributions to simulated radar reflectivity and snowfall rate.
Viewing geometry effects are characterized by a parameter, ϕ,
that relates disdrometer-observed particle size to the true maximum
dimension of the particle. Values and uncertainties for ϕ are
estimated using idealized ellipsoidal snow particles. The model is
applied to observations from seven snow events from the Canadian
CloudSat/CALIPSO Validation Project (C3VP), a mid-latitude cold-season
cloud and precipitation field experiment. Typical total uncertainties
are 4 dB for reflectivity and 40–60% for snowfall rate, are
highly correlated, and are substantial compared to expected
uncertainties for radar and precipitation gauge observations. The
dominant sources of errors are viewing geometry effects and the
discrete, truncated form of the size distributions. While modeled
Ze–S relationships are strongly affected by assumptions about snow
particle mass properties, such relationships are only modestly
sensitive to ϕ owing to partially compensating effects on both
the reflectivity and snowfall rate. |
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