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| Titel |
On the parallelization of atmospheric inversions of CO2 surface fluxes within a variational framework |
| VerfasserIn |
F. Chevallier |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 6, no. 3 ; Nr. 6, no. 3 (2013-06-07), S.783-790 |
| Datensatznummer |
250017822
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| Publikation (Nr.) |
 copernicus.org/gmd-6-783-2013.pdf |
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| Zusammenfassung |
| The variational formulation of Bayes' theorem allows inferring
CO2 sources and sinks from atmospheric concentrations at much
higher time–space resolution than the ensemble or
analytical approaches. However, it usually exhibits limited scalable
parallelism. This limitation hinders global atmospheric inversions
operated on decadal time scales and regional ones with kilometric
spatial scales because of the computational cost of the underlying
transport model that has to be run at each iteration of the
variational minimization. Here, we introduce a physical
parallelization (PP) of variational atmospheric inversions. In the
PP, the inversion still manages a single physically and statistically
consistent window, but the transport model is run in parallel
overlapping sub-segments in order to massively reduce the computation
wall-clock time of the inversion. For global inversions,
a simplification of transport modelling is described to connect the
output of all segments. We demonstrate the performance of the approach
on a global inversion for CO2 with a 32 yr inversion
window (1979–2010) with atmospheric measurements from 81 sites of the
NOAA global cooperative air sampling network. In this case, we show
that the duration of the inversion is reduced by a seven-fold factor
(from months to days), while still processing the three decades
consistently and with improved numerical stability. |
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