HR: 09:30h
AN: A21G-07 INVITED     [Abstracts]
TI: Midlatitude ozone trends deduced from data: Uncertainties and lessons learned from a 3D CTM
AU: * Stolarski, R S
EM: stolar@polska.gsfc.nasa.gov
AF: NASA Goddard Space Flight Center, Mail Code 613.3, Greenbelt, MD 20771 United States
AU: Douglass, A R
EM: Anne.R.Douglass@nasa.gov
AF: NASA Goddard Space Flight Center, Mail Code 613.3, Greenbelt, MD 20771 United States
AU: Frith, S
EM: smh@code916.gsfc.nasa.gov
AF: SSAI, 10210 Greenbelt Road, Lanham-Seabrook, MD 20706 United States
AB: We present an updated global merged ozone data set using TOMS and SBUV data. We emphasize the uncertainties in this data record as they apply to derivation of trends or recovery. We then compare this data record with its uncertainties to simulations using our 3D chemical transport model driven by GCM winds. We find that our model predicts larger trends due to chlorine/bromine than those we deduce from the data. This is especially true in the tropics where the data show little trend. Our model simulation has interannual variability in ozone due to the variability of the transport by the GCM winds. We will use the results from the simulation to demonstrate difficulties in the application of time-series analysis for the deduction of trends in data. Short data sets can contain apparent trends due solely to the "normal" fluctuations in the data. We show that about 25 years are sufficient to reduce these "accidental" trends due to statistics of short time series to insignificance. Our present total ozone data set is now more than 25 years in length. Transient "accidental" trends should now be small enough that the main source of any dynamical component to trend should be only from forced trends in the circulation due to greenhouse gas increases or to the ozone change itself.
DE: 0340 Middle atmosphere: composition and chemistry
DE: 0341 Middle atmosphere: constituent transport and chemistry (3334)
SC: Atmospheric Sciences [A]
MN: Fall Meeting 2005