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| Titel |
High resolution modeling of CO2 over Europe: implications for representation errors of satellite retrievals |
| VerfasserIn |
D. Pillai, C. Gerbig, J. Marshall, R. Ahmadov, R. Kretschmer, T. Koch, U. Karstens |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 10, no. 1 ; Nr. 10, no. 1 (2010-01-07), S.83-94 |
| Datensatznummer |
250007893
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| Publikation (Nr.) |
 copernicus.org/acp-10-83-2010.pdf |
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| Zusammenfassung |
| Satellite retrievals for column CO2 with better spatial and temporal
sampling are expected to improve the current surface flux estimates of
CO2 via inverse techniques. However, the spatial scale mismatch between
remotely sensed CO2 and current generation inverse models can induce
representation errors, which can cause systematic biases in flux estimates.
This study is focused on estimating these representation errors associated
with utilization of satellite measurements in global models with a
horizontal resolution of about 1 degree or less. For this we used simulated
CO2 from the high resolution modeling framework WRF-VPRM, which links
CO2 fluxes from a diagnostic biosphere model to a weather forecasting
model at 10×10 km2 horizontal resolution. Sub-grid variability of
column averaged CO2, i.e. the variability not resolved by global
models, reached up to 1.2 ppm with a median value of 0.4 ppm. Statistical
analysis of the simulation results indicate that orography plays an
important role. Using sub-grid variability of orography and CO2 fluxes
as well as resolved mixing ratio of CO2, a linear model can be
formulated that could explain about 50% of the spatial patterns in the
systematic (bias or correlated error) component of representation error in
column and near-surface CO2 during day- and night-times. These findings
give hints for a parameterization of representation error which would allow
for the representation error to taken into account in inverse models or data
assimilation systems. |
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