| In this paper, we introduce a statistical method for examining and adjusting
chemical-transport models. We illustrate the findings with total column ozone
predictions, based on the University of Illinois at Urbana-Champaign 2-D
(UIUC 2-D) chemical-transport model of the global atmosphere.
We propose a general diagnostic procedure for the model outputs in
total ozone over the latitudes ranging from 60°
South to 60° North to see
if the model captures some typical patterns in the data.
The method proceeds in two steps to avoid possible
collinearity issues. First, we regress the measurements given by a
cohesive data set from the SBUV(/2) satellite system on the model
outputs with an autoregressive noise component.
Second, we regress the residuals of this first regression on
the solar flux, the annual cycle, the Antarctic or Arctic Oscillation,
and the Quasi Biennial Oscillation. If the
coefficients from this second regression are statistically
significant, then they mean that the model did not simulate properly
the pattern associated with these factors.
Systematic anomalies of the model are identified using data from 1979
to 1995, and statistically corrected afterwards. The 1996–2003 validation sample
confirms that the combined approach yields better predictions than the
direct UIUC 2-D outputs. |