Effects of model chemistry and data biases on stratospheric ozone assimilation

[摘要] The innovations or observation minus forecast (O–F) residualsproduced by a data assimilation systemprovide a convenient metricof evaluating global analyses. In this study, O–F statistics from theGlobal Ozone Assimilation Testing System (GOATS) are used to examinehow ozone assimilation products and their associated O–F statisticsdepend on input data biases and ozone photochemistry parameterizations (OPP).All the GOATS results shown are based on a6-h forecast and analysis cycle using observations fromSBUV/2 (Solar Backscatter UltraViolet instrument-2) duringSeptember–October 2002.Results show that zonalmean ozone analyses are more independent of observationbiases and drifts when using an OPP, while the mean ozone O–Fs are moresensitive to observation drifts when using an OPP.In addition, SD O–Fs (standard deviations) are reduced in theupper stratosphere when using an OPP due to a reduction of forecastmodel noise and to increased covariance between theforecast model and the observations.Experiments that changed the OPP reference state to match the observationsby using an "adaptive" OPP schemereduced the mean ozone O–Fs at the expense of zonal mean ozoneanalyses being more susceptible to data biases and drifts.Additional experiments showed thatthe upper boundary of the ozone DAS can affect thequality of the ozone analysis and therefore should be placedwell above (at least a scale height) the region of interest.

[学科分类] 大气科学