Technical Note: Ozonesonde climatology between 1995 and 2011: description, evaluation and applications - Tilmes, S.; Lamarque, J.-F.; Emmons, L. K.; Conley, A.; Schultz, M. G.; Saunois, M.; Thouret, V.; Thompson, A. M.; Oltmans, S. J.; Johnson, B.; Tarasick, D. (Atmospheric chemistry and physics, 2012)
An ozone climatology based on ozonesonde measurements taken over the last 17 yr has been constructed for model evaluation and comparisons to other observations. Vertical ozone profiles for 42 stations around the globe have been compiled for the period 1995–2011, in pressure and tropopause-referenced altitudes. For each profile, the mean, standard deviation, median, the half-width are provided, as well as information about interannual variability. Regional aggregates are formed in combining stations with similar ozone characteristics. The Hellinger distance is introduced as a new diagnostic to identify stations that describe similar shapes of ozone probability distribution functions (PDFs). In this way, 12 regions were selected covering at least 2 stations and the variability among those stations is discussed. Significant variability with longitude of ozone distributions in the troposphere and lower stratosphere in the northern mid- and high latitudes is found. The representativeness of regional aggregates is discussed for high northern latitudes, Western Europe, Eastern US, and Japan, using independent observations from surface stations and MOZAIC aircraft data. Good agreement exists between ozonesondes and aircraft observations in the mid-troposphere and between ozonesondes and surface observations for Western Europe. For Eastern US and high northern latitudes, surface ozone values from ozonesondes are biased 10 ppb high compared to independent measurements. An application of the climatology is presented using the NCAR CAM-Chem model. The climatology allows evaluation of the model performance regarding ozone averages, seasonality, interannual variability, and the shape of ozone distributions. The new assessment of the key features of ozone distributions gives deeper insights into the performance of models.