Atmospheric Chemistry and Physics Discussions
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10.5194/acpd-7-1067-2007
http://www.atmos-chem-phys-discuss.net/7/1067/2007/
http://www.atmos-chem-phys-discuss.net/7/1067/2007/acpd-7-1067-2007.html
http://www.atmos-chem-phys-discuss.net/7/1067/2007/acpd-7-1067-2007.pdf
1067
1117
2007-01-22
Effects of model chemistry and data biases on stratospheric ozone assimilation
L. Coy
coy@nrl.navy.mil
D. R. Allen
S. D. Eckermann
J. P. McCormack
I. Stajner
T. F. Hogan
E.O. Hulburt Center for Space Research, Naval Research Laboratory, Washington, DC, USA
Department of Physics and Astronomy, Dordt College, Sioux Center, IA, USA
Sciences Applications International Corporation, Beltsville, MD, USA and Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Naval Research Laboratory, Monterey, CA, USA
The innovations or observation minus forecast (O−F) residuals
produced by a data assimilation system provide a convenient metric
of evaluating global analyses. In this study, O–F statistics from the
Global Ozone Assimilation Testing System (GOATS) are used to examine
how ozone assimilation products and their associated O−F statistics
depend on input data biases and ozone photochemistry parameterizations (OPP).
All the GOATS results shown are based on a
6-h forecast and analysis cycle using observations from
SBUV/2 (Solar Backscatter UltraViolet instrument-2) during
September–October 2002. Results show that zonal
mean ozone analyses are more independent of observation
biases and drifts when using an OPP, while the mean ozone O−Fs are more
sensitive to observation drifts when using an OPP.
In addition, SD O−Fs (standard deviations) are reduced in the
upper stratosphere when using an OPP due to a reduction of forecast
model noise and to increased covariance between the
forecast model and the observations.
Experiments that changed the OPP reference state to match the observations
by using an "adaptive" OPP scheme
reduced the mean ozone O−Fs at the expense of zonal mean ozone
analyses being more susceptible to data biases and drifts.
Additional experiments showed that
the upper boundary of the ozone DAS can affect the
quality of the ozone analysis and therefore should be placed
well above (at least a scale height) the region of interest.
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