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| Titel |
The SPRINTARS version 3.80/4D-Var data assimilation system: development and inversion experiments based on the observing system simulation experiment framework |
| VerfasserIn |
K. Yumimoto, T. Takemura |
| 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. 6 ; Nr. 6, no. 6 (2013-11-19), S.2005-2022 |
| Datensatznummer |
250085018
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| Publikation (Nr.) |
 copernicus.org/gmd-6-2005-2013.pdf |
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| Zusammenfassung |
We present an aerosol data assimilation system based on a global aerosol
climate model (SPRINTARS – Spectral Radiation-Transport Model for Aerosol Species) and a four-dimensional variational data
assimilation method (4D-Var). Its main purposes are to optimize emission
estimates, improve composites, and obtain the best estimate of the radiative
effects of aerosols in conjunction with observations. To reduce the huge
computational cost caused by the iterative integrations in the models, we
developed an offline model and a corresponding adjoint model, which are
driven by pre-calculated meteorological, land, and soil data. The offline
and adjoint model shortened the computational time of the inner loop by more
than 30%.
By comparing the results with a 1 yr simulation from the original online
model, the consistency of the offline model was verified, with correlation
coefficient R > 0.97 and absolute value of normalized mean bias
NMB < 7% for the natural aerosol emissions and aerosol optical
thickness (AOT) of individual aerosol species. Deviations between the
offline and original online models are mainly associated with the time
interpolation of the input meteorological variables in the offline model;
the smaller variability and difference in the wind velocity near the surface
and relative humidity cause negative and positive biases in the wind-blown
aerosol emissions and AOTs of hygroscopic aerosols, respectively.
The feasibility and capability of the developed system for aerosol inverse
modelling was demonstrated in several inversion experiments based on the
observing system simulation experiment framework. In the experiments, we
used the simulated observation data sets of fine- and coarse-mode AOTs from
sun-synchronous polar orbits to investigate the impact of the observational
frequency (number of satellites) and coverage (land and ocean), and assigned
aerosol emissions to control parameters. Observations over land have a
notably positive impact on the performance of inverse modelling as compared
with observations over ocean, implying that reliable observational
information over land is important for inverse modelling of land-born
aerosols. The experimental results also indicate that information that
provides differentiations between aerosol species is crucial to inverse
modelling over regions where various aerosol species coexist (e.g.
industrialized regions and areas downwind of them). |
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