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| Titel |
Global high-resolution simulations of CO2 and CH4 using a NIES transport model to produce a priori concentrations for use in satellite data retrievals |
| VerfasserIn |
T. Saeki, R. Saito, D. Belikov, S. Maksyutov |
| 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. 1 ; Nr. 6, no. 1 (2013-01-25), S.81-100 |
| Datensatznummer |
250017360
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| Publikation (Nr.) |
 copernicus.org/gmd-6-81-2013.pdf |
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| Zusammenfassung |
| The Greenhouse gases Observing SATellite (GOSAT) measures column-averaged
dry air mole fractions of carbon dioxide and methane (XCO2 and
XCH4, respectively). Since the launch of GOSAT, model-simulated
three-dimensional concentrations from a National Institute for Environmental
Studies offline tracer Transport Model (NIES TM) have been used as a priori
concentration data for operational near real-time retrievals of XCO2
and XCH4 from GOSAT short-wavelength infrared spectra at NIES. Although
the choice of a priori profile has only a minor effect on retrieved
XCO2 or XCH4, a realistic simulation with minimal deviation from
observed data is desirable. In this paper, we describe the newly developed
version of NIES TM that has been adapted to provide global and near
real-time concentrations of CO2 and CH4 using a high-resolution
meteorological dataset, the Grid Point Value (GPV) prepared by the Japan
Meteorological Agency. The spatial resolution of the NIES TM is set to
0.5° × 0.5° in the horizontal in order to
utilise GPV data, which have a resolution of 0.5° × 0.5°, 21 pressure levels and a time interval of 3 h. GPV
data are provided to the GOSAT processing system with a delay of several
hours, and the near real-time model simulation produces a priori
concentrations driven by diurnally varying meteorology. A priori
variance–covariance matrices of CO2 and CH4 are also derived from
the simulation outputs and observation-based reference data for each month
of the year at a resolution of 0.5° × 0.5° and
21 pressure levels. Model performance is assessed by comparing simulation
results with the GLOBALVIEW dataset and other observational data. The
overall root-mean-square differences between model predictions and
GLOBALVIEW analysis are estimated to be 1.45 ppm and 12.52 ppb for CO2
and CH4, respectively, and the seasonal correlation coefficients are
0.87 for CO2 and 0.53 for CH4. The model showed good performance
particularly at oceanic and free tropospheric sites. The high-resolution
model also performs well in reproducing both the observed synoptic
variations at some sites and stratospheric profiles over Japan. These
results give us confidence that the performance of our GPV-forced
high-resolution NIES TM is adequate for use in satellite retrievals. |
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