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| Titel |
Climatologies from satellite measurements: the impact of orbital sampling on the standard error of the mean |
| VerfasserIn |
M. Toohey, T. Clarmann |
| 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. 4 ; Nr. 6, no. 4 (2013-04-10), S.937-948 |
| Datensatznummer |
250017870
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| Publikation (Nr.) |
 copernicus.org/amt-6-937-2013.pdf |
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| Zusammenfassung |
| Climatologies of atmospheric observations are often produced by
binning measurements according to latitude and calculating zonal
means. The uncertainty in these climatological means is
characterised by the standard error of the mean (SEM). However, the
usual estimator of the SEM, i.e., the sample standard deviation
divided by the square root of the sample size, holds only for
uncorrelated randomly sampled measurements. Measurements of the
atmospheric state along a satellite orbit cannot always be
considered as independent because (a) the time-space interval
between two nearest observations is often smaller than the typical
scale of variations in the atmospheric state, and (b) the regular
time-space sampling pattern of a satellite instrument strongly
deviates from random sampling. We have developed a numerical experiment where
global chemical fields from a chemistry climate model are sampled
according to real sampling patterns of satellite-borne
instruments. As case studies, the model fields are sampled using sampling patterns of the Michelson
Interferometer for Passive Atmospheric Sounding (MIPAS) and
Atmospheric Chemistry Experiment Fourier-Transform Spectrometer
(ACE-FTS) satellite instruments. Through an iterative subsampling
technique, and by incorporating information on the random errors
of the MIPAS and ACE-FTS measurements, we produce empirical estimates of the
standard error of monthly mean zonal mean model O3 in
5° latitude bins. We find that generally the classic SEM
estimator is a conservative estimate of the SEM, i.e., the empirical
SEM is often less than or approximately equal to the classic estimate.
Exceptions occur only when natural variability is larger than
the random measurement error, and specifically in
instances where the zonal sampling distribution shows non-uniformity
with a similar zonal structure as variations in the sampled field,
leading to maximum sensitivity to arbitrary phase shifts between the
sample distribution and sampled field. The occurrence of such
instances is thus very sensitive to slight changes in the sampling
distribution, and to the variations in the measured field. This
study highlights the need for caution in the interpretation of the
oft-used classically computed SEM, and outlines a relatively simple
methodology that can be used to assess one component of the
uncertainty in monthly mean zonal mean climatologies produced from
measurements from satellite-borne instruments. |
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