Effects of model chemistry and data biases on stratospheric ozone assimilation

Abstract

Abstract. 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.

Forecasts and assimilation experiments of the Antarctic ozone hole 2008

“…The applied observation errors for MIPAS were of similar size (5%) as the values used for MLS in this study. Coy et al (2007) showed improved analyses in the upper stratosphere when using a linear chemical scheme instead of no chemical scheme when assimilating only SBUV-2 observations.…”

“…(2007) compare different ozone assimilation systems based on linear chemistry schemes. Coy et al (2007) investigate the influence of observation and model biases for the assimilation by a model system with and without a linear chemical scheme. As pointed out in a review by Lahoz et al (2007), using data assimilation systems based on CTMs (e.g.…”

High-altitude data assimilation system experiments for the northern summer mesosphere season of 2007

“…It uses lookup tables of diurnally averaged photochemical coefficients derived from a full chemistry model based on linearizing scaled odd-oxygen production and loss rates about equilibrium states. These equilibrium states are specified in the model using zonalmean observational climatologies that are chosen carefully here to match characteristics of the assimilated ozone observations so as to avoid model-data bias (Geer et al, 2007;Coy et al, 2007). The scheme does not at present parameterize either diurnal ozone photochemistry at altitudes above $0:3 hPa or tropospheric ozone chemistry, relaxing ozone in both altitude regions to a reference state based on a mean photochemical relaxation rate.…”

Data assimilation of stratospheric constituents: a review

“…However, these results also show that observational gaps can seriously degrade the ozone analyses. Arguably, in the upper stratosphere (fast chemical time-scales), a better solution than omitting chemistry would be to bias correct the Cariolle scheme (see, e.g., Coy et al, 2007).…”