Assessment of the interannual variability and influence of the QBO and upwelling on tracer–tracer distributions of N₂O and O₃ in the tropical lower stratosphere

Abstract

Abstract. A modified form of tracer–tracer correlations of N2O and O3 has been used as a tool for the evaluation of atmospheric photochemical models. Applying this method, monthly averages of N2O and O3 are derived for both hemispheres by partitioning the data into altitude (or potential temperature) bins and then averaging over a fixed interval of N2O. In a previous study, the method has been successfully applied to the evaluation of two chemical transport models (CTMs) and one chemistry–climate model (CCM) using a 1 yr climatology derived from the Odin Sub-Millimetre Radiometer (Odin/SMR). However, the applicability of a 1 yr climatology of monthly averages of N2O and O3 has been questioned due to the inability of some CCMs to simulate a specific year for the evaluation of CCMs. In this study, satellite measurements from Odin/SMR, the Aura Microwave Limb Sounder (Aura/MLS), the Michelson Interferometer for Passive Atmospheric Sounding on ENVISAT (ENVISAT/MIPAS), and the Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA-1 and CRISTA-2) as well as model simulations from the Whole Atmosphere Community Climate Model (WACCM) are considered. By using seven to eight years of satellite measurements derived between 2003 and 2010 from Odin/SMR, Aura/MLS, ENVISAT/MIPAS and six years of model simulations from WACCM, the interannual variability of lower stratospheric monthly averages of N2O and O3 is assessed. It is shown that the interannual variability of the monthly averages of N2O and O3 is low, and thus can be easily distinguished from model deficiencies. Furthermore, it is investigated why large differences are found between Odin/SMR observations and model simulations from the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA) and the atmospheric general circulation model ECHAM5/Messy1 for the Northern and Southern Hemisphere tropics (0° to 30° N and 0° to −30° S, respectively). The differences between model simulations and observations are most likely caused by an underestimation of the quasi-biennial oscillation and tropical upwelling by the models as well as due to biases and/or instrument noise from the satellite instruments. A realistic consideration of the QBO in the model reduces the differences between model simulation and observations significantly. Finally, an intercomparison between Odin/SMR, Aura/MLS, ENVISAT/MIPAS and WACCM was performed. The comparison shows that these data sets are generally in good agreement, although some known biases of the data sets are clearly visible in the monthly averages. Nevertheless, the differences caused by the uncertainties of the satellite data sets are sufficiently small and can be clearly distinguished from model deficiencies. Thus, the method applied in this study is not only a valuable tool for model evaluation, but also for satellite data intercomparisons.

Evaluation of CESM1 (WACCM) free-running and specified dynamics atmospheric composition simulations using global multispecies satellite data records

“…3 WACCM (CESM1) description and simulations WACCM (CESM1) is a chemistry-climate model of the Earth's atmosphere, from the surface to the lower thermosphere (Garcia et al, , 2017Kinnison et al, 2007;Marsh et al, 2013). WACCM is a superset of the Community Atmosphere Model, version 4 (CAM4), and includes all of the physical parameterizations of CAM4 (Neale et al, 2013) and a finite volume dynamical core (Lin, 2004) for the tracer advection.…”

“…Both WACCM versions used here contain an identical representation of tropospheric and stratospheric chemistry (Kinnison et al, 2007;Tilmes et al, 2016). The species included in this mechanism are contained within the O x , NO x , HO x , ClO x , and BrO x chemical families, along with CH 4 and its degradation products.…”

Driving of the SAO by gravity waves as observed from satellite

“…Both QBO and SAO have an effect on the tracer transport in the stratosphere (e.g., Huang et al, 2008;Punge et al, 2009;Khosrawi et al, 2013;Shu et al, 2013). Further, the QBO has an effect on the stability of the polar vortex (e.g., Holton and Tan, 1980), and there are indications that both QBO and SAO have an influence on the timing of sudden stratospheric warmings (e.g., Pascoe et al, 2006).…”

Tropical troposphere to stratosphere transport of carbon monoxide and long-lived trace species in the Chemical Lagrangian Model of the Stratosphere (CLaMS)

“…Therefore, the seasonal variation in the mixing ratio of species like water vapour, CO, and HCN in the lower tropical stratosphere provides information on the rate of tropical upwelling in this region, a quantity which is important, but relatively poorly constrained in meteorological analyses (e.g., Ploeger et al, 2011;Diallo et al, 2012;Wright and Fueglistaler, 2013;Randel and Jensen, 2013). Robust anomaly patterns in the tropical stratosphere have also been reported for CCl 3 F (CFC-11), CCl 2 F 2 , N 2 O, and CH 4 based on satellite measurements (Randel et al, 1998;Schoeberl et al, 2008;Kellmann et al, 2012;Khosrawi et al, 2013). CCl 3 F, CCl 2 F 2 , N 2 O, and CH 4 are trace gases with purely tropospheric sources and with very long stratospheric lifetimes, ranging between about 50 years and more than 100 years (e.g., Volk et al, 1997;Brown et al, 2013;Minschwaner et al, 2013;Ko et al, 2013;Hoffmann et al, 2014).…”

“…Nonetheless, in the lower tropical stratosphere, where mixing ratios of these trace gases are only moderately reduced compared to tropospheric values, a weak tape recorder signal for N 2 O and CH 4 is detectable because of annual variations in the vertical velocity (Schoeberl et al, 2008). Further, variability in tropical upwelling induced by the QBO (Baldwin et al, 2001;Ribera et al, 2004;Punge et al, 2009;Flury et al, 2013), acting on the stronger vertical trace gas gradient in the tropical stratosphere at altitudes above ≈ 500 K, induces more pronounced anomaly patterns in long-lived trace species like CCl 3 F, N 2 O, and CH 4 (Randel et al, 1998;Schoeberl et al, 2008;Kellmann et al, 2012;Khosrawi et al, 2013).…”