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| Titel |
Spatial patterns in timing of the diurnal temperature cycle |
| VerfasserIn |
T. R. H. Holmes, W. T. Crow, C. Hain |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 17, no. 10 ; Nr. 17, no. 10 (2013-10-01), S.3695-3706 |
| Datensatznummer |
250085940
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| Publikation (Nr.) |
 copernicus.org/hess-17-3695-2013.pdf |
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| Zusammenfassung |
| This paper investigates the structural difference in timing of the diurnal temperature cycle (DTC)
over land resulting from choice of measuring device or model framework. It is shown that the
timing can be reliably estimated from temporally sparse observations acquired from a constellation
of low Earth-orbiting satellites given record lengths of at least three months. Based on a year of
data, the spatial patterns of mean DTC timing are compared between temperature estimates from microwave Ka-band,
geostationary thermal infrared (TIR), and numerical weather prediction model
output from the Global Modeling and Assimilation Office (GMAO). It is found that the spatial
patterns can be explained by vegetation effects, sensing depth differences and more speculatively
the orientation of orographic relief features. In absolute terms, the GMAO model puts the peak of the
DTC on average at 12:50 local solar time, 23 min before TIR with a peak temperature at 13:13
(both averaged over Africa and Europe). Since TIR is the shallowest observation of the land surface,
this small difference
represents a structural error that possibly affects the model's ability to assimilate observations
that are closely tied to the DTC. The equivalent average timing for Ka-band is 13:44, which is influenced
by the effect of increased sensing depth in desert areas. For non-desert areas, the Ka-band observations
lag the TIR observations by only 15 min, which is in agreement with their respective theoretical
sensing depth. The results of this comparison provide insights into the structural differences between
temperature measurements and models, and can be used as a first step to account for these differences
in a coherent way. |
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