[A-AS09] Stratosphere-troposphere Processes And their Role in Climate

[AAS09-07] Sensitivity to the Initial Condition for the Prediction of Stratospheric Ozone in the Southern Hemisphere during Spring

*Nakamura Haruna^1,2, Toshihiko Hirooka², Hideharu Akiyoshi³ (1.Fujitsu Japan Corporation, 2.Department of Earth and Planetary Sciences, Kyushu University, 3.National Institute for Environmental Studies)

Keywords:Ozone, Predictability, Data Assimilation

A reduction of the total ozone over the southern tip of South America lasting 3 weeks occurred in November 2009. In this event, the polar vortex was distorted to an elliptic shape due to enhanced planetary wave activity, bringing to migration of ozone depletion region associated with the Antarctic ozone hole towards the South American continent at the time of the vortex breakup. We attempt ensemble forecast experiments for the ozone reduction event, using the National Institute for Environmental Studies (NIES) chemical-climate model (NIES CCM) with 32 ensemble members whose initial data was produced by the ozone assimilated NIES CCM from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis data for the dynamical field, along with the Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) data for the ozone field. The forecast experiments are performed from the various initial dates in October-November 2009.
To quantify the model performance, we investigate the predictability of the geopotential height and total ozone fields, on the basis of the pattern correlation coefficient (PCC) and Root Mean Square Error (RMSE) between their forecast and reanalysis values.
We investigate the predictability dependence on three kinds of assimilated initial data for the forecast experiments, i.e., (1) dynamical data, (2) dynamical and total ozone data, and (3) dynamical, total ozone, and vertical ozone profile data. Results of the forecast experiments suggest the importance of the vertical ozone profile at the initial state for accurate prediction of ozone field.