A Coupled Atmosphere-Chemistry Data Assimilation: Impact of Ozone Observation on Structure of a Tropical Cyclone

Abstract

Ozone (O$_3$) generally shows lower concentration inside the eyewall and higher concentration around the eye in tropical cyclones (TCs). In this study, we identify the impact of O$_3$ observations on TC structure through a coupled atmosphere-chemistry data assimilation (DA) system. We applied the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and an ensemble-based DA algorithm—the maximum likelihood ensemble filter (MLEF ) to a case TC over East Asia, Typhoon Nabi (2005). The ensemble forecast with 32 ensembles shows larger background state uncertainty over the TC . The assimilation of O$_3$ observations, with a 6 h assimilation window, impacts both O$_3$ itself and wind field in the vicinity of TC . Several measures for verification, including the cost function, root mean square (RMS) error with respect to observations and degrees of freedom for signal (DFS), indicate improvement of the analysis fields through the O$_3$ DA. The cost function and RMS error have decreased by 17 and 9 %, respectively. The DFS shows large reduction in uncertainty, indicating a strong positive impact of observations in the TC area.