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| Titel |
The impact of orbital sampling, monthly averaging and vertical resolution on climate chemistry model evaluation with satellite observations |
| VerfasserIn |
A. M. Aghedo, K. W. Bowman, D. T. Shindell  , G. Faluvegi |
| 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 ; 11, no. 13 ; Nr. 11, no. 13 (2011-07-08), S.6493-6514 |
| Datensatznummer |
250009899
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| Publikation (Nr.) |
 copernicus.org/acp-11-6493-2011.pdf |
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| Zusammenfassung |
Ensemble climate model simulations used for the Intergovernmental Panel on
Climate Change (IPCC) assessments have become important tools for exploring
the response of the Earth System to changes in anthropogenic and natural
forcings. The systematic evaluation of these models through global satellite
observations is a critical step in assessing the uncertainty of climate
change projections. This paper presents the technical steps required for
using nadir sun-synchronous infrared satellite observations for multi-model
evaluation and the uncertainties associated with each step. This is motivated
by need to use satellite observations to evaluate climate models. We
quantified the implications of the effect of satellite orbit and spatial
coverage, the effect of variations in vertical sensitivity as quantified by
the observation operator and the impact of averaging the operators for use
with monthly-mean model output. We calculated these biases in ozone, carbon
monoxide, atmospheric temperature and water vapour by using the output from
two global chemistry climate models (ECHAM5-MOZ and GISS-PUCCINI) and the
observations from the Tropospheric Emission Spectrometer (TES) instrument on
board the NASA-Aura satellite from January 2005 to December 2008.
The results show that sampling and monthly averaging of the observation
operators produce zonal-mean biases of less than ±3 % for ozone and
carbon monoxide throughout the entire troposphere in both models. Water
vapour sampling zonal-mean biases were also within the insignificant range of
±3 % (that is ±0.14 g kg−1) in both models. Sampling led to a
temperature zonal-mean bias of ±0.3 K over the tropical and mid-latitudes
in both models, and up to −1.4 K over the boundary layer in the higher
latitudes. Using the monthly average of temperature and water vapour
operators lead to large biases over the boundary layer in the
southern-hemispheric higher latitudes and in the upper troposphere,
respectively. Up to 8 % bias was calculated in the upper troposphere water
vapour due to monthly-mean operators, which may impact the detection of water
vapour feedback in response to global warming. Our results reveal the
importance of using the averaging kernel and the a priori profiles to account
for the limited vertical resolution and clouds of a nadir observation during
model application. Neglecting the observation operators resulted in large
biases, which are more than 60 % for ozone, ±30 % for carbon monoxide,
and range between −1.5 K and 5 K for atmospheric temperature, and between
−60 % and 100 % for water vapour. |
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