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| Titel |
Quantifying uncertainty in climatological fields from GPS radio occultation: an empirical-analytical error model |
| VerfasserIn |
B. Scherllin-Pirscher, G. Kirchengast, A. K. Steiner, Y.-H. Kuo, U. Foelsche |
| 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 ; 4, no. 9 ; Nr. 4, no. 9 (2011-09-29), S.2019-2034 |
| Datensatznummer |
250002105
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| Publikation (Nr.) |
 copernicus.org/amt-4-2019-2011.pdf |
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| Zusammenfassung |
| Due to the measurement principle of the radio occultation (RO) technique, RO
data are highly suitable for climate studies. RO profiles can be used to
build climatological fields of different atmospheric parameters like bending
angle, refractivity, density, pressure, geopotential height, and temperature.
RO climatologies are affected by random (statistical) errors, sampling
errors, and systematic errors, yielding a total climatological error. Based
on empirical error estimates, we provide a simple analytical error model for
these error components, which accounts for vertical, latitudinal, and
seasonal variations. The vertical structure of each error component is
modeled constant around the tropopause region. Above this region the error
increases exponentially, below the increase follows an inverse height
power-law. The statistical error strongly depends on the number of
measurements. It is found to be the smallest error component for monthly mean
10° zonal mean climatologies with more than 600 measurements per bin.
Due to smallest atmospheric variability, the sampling error is found to be
smallest at low latitudes equatorwards of 40°. Beyond 40°, this
error increases roughly linearly, with a stronger increase in hemispheric
winter than in hemispheric summer. The sampling error model accounts for this
hemispheric asymmetry. However, we recommend to subtract the sampling error
when using RO climatologies for climate research since the residual sampling
error remaining after such subtraction is estimated to be only about 30%
of the original one or less. The systematic error accounts for potential
residual biases in the measurements as well as in the retrieval process and
generally dominates the total climatological error. Overall the total error
in monthly means is estimated to be smaller than 0.07% in refractivity and
0.15 K in temperature at low to mid latitudes, increasing towards higher
latitudes. This study focuses on dry atmospheric parameters as retrieved from
RO measurements so for context we also quantitatively explain the difference
between dry and physical atmospheric parameters, which can be significant at
altitudes below about 6 km (high latitudes) to 10 km (low latitudes). |
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