Estimation of Arctic ozone loss in winter 2004/05 based on assimilation of EOS MLS and SBUV/2 observations

Abstract

ABSTRACT:In this paper we present a new technique for the estimation of ozone loss in the stratospheric polar vortex based on the assimilation of Earth Observing System Microwave Limb Sounder (EOS MLS) and Solar Backscatter Ultraviolet radiometer (SBUV/2) ozone observations in the Met Office data assimilation system. We focus on the northern winter of 2004/05, which was exceptionally cold in the Arctic stratosphere, with associated large ozone depletion due to heterogeneous chemistry. Our ozone loss estimate, which was calculated for the 1 February to 10 March 2005 period, peaks at 450 K (approximately 17-18 km), and is 0.6 ppmv at that isentropic level (our loss estimate for the vortex core only was somewhat higher (1.0 ppmv) and indicates uncertainties related to mixing at the vortex edge). This value is similar to or smaller than results from other studies, which estimate ozone loss in this period to be in the 0.6-1.2 ppmv range. When combined with results from other studies that estimate ozone loss occurring outside our assimilation period, we obtain an estimate of 0.8-1.2 ppmv for ozone loss from early January to early March 2005. We find a second maximum in ozone loss for the 1 February-10 March period near 650 K (approximately 25 km) of around 0.4 ppmv. This is a lower figure than found in other studies, but ozone loss is actually much stronger at this level outside the vortex in a low-ozone pocket in the Aleutian anticyclone, likely due to the NOx catalytic cycle. Our results show that the ozone data assimilation method we have used to estimate ozone loss is very promising, and can lead to potentially more accurate ozone-loss estimates than other methods.

A Match-based approach to the estimation of polar stratospheric ozone loss using Aura Microwave Limb Sounder observations

“…The stricter 10 % sPV variability criterion (grey line) also increases our estimated loss, though to a much lesser degree. Estimates of peak ozone loss that winter from all the studies shown here range from around 1.0 ppmv (our study, as well as Rösevall et al, 2008 andOrsolini, 2008), to as high as 2.2 ppmv (Jin et al, 2006;von Hobe et al, 2006). This wide range reflects the challenges associated with quantifying chemical ozone loss in a manner that properly accounts for transport processes.…”

“…3f) on constant potential temperature surfaces gives peak loss of slightly larger than 1 ppmv at 450 K. In addition, there are indications of a secondary peak of ∼ 0.8 ppmv loss between 550 and 600 K. Previous studies of the 2004/05 winter have shown that ozone loss at these altitudes largely resulted from nitrogen-based catalytic cycles, although the studies report different magnitudes and vertical distributions for the overall loss. Grooß and Müller (2007) find as much as 1.6 ppmv loss at 600 K, while find ∼ 1.2 ppmv loss at the same altitude, and Jackson and Orsolini (2008) report only ∼ 0.4 ppmv loss. Section 4 discusses in more detail how our results compare with estimates from previous studies.…”

“…This method was first developed by Manney et al (1995b, a) to quantify ozone loss during the 1992/93 Arctic winter, using a trajectory-based passive ozone estimate, and has been subsequently applied in similar form to other seasons (e.g., Manney et al, 1996aManney et al, , b, 1997Manney et al, , 2003Schoeberl et al, 2002). Where a full chemistry transport model is employed (e.g., Deniel et al, 1998;Goutail et al, 1999;Singleton et al, , 2007; L. Grooß and Müller, 2007;Rösevall et al, 2008;Jackson and Orsolini, 2008;Kuttippurath et al, , 2012Feng et al, 2011;Brakebusch et al, 2013), ozone loss can be estimated by comparing the modeled passive ozone to both the ozone simulated by the same model and to observed ozone, with comparisons between the latter two fields typically used to quantify the overall accuracy of the model calculations (both from the dynamical and chemical perspective). The passive subtraction approach can be taken a stage further by considering a "pseudo passive" ozone tracer , subject to both dynamical and gas-phase chemistry influences, but not the losses due to chlorine activated through heterogeneous processes.…”

“…Rather, the diversity seems to be driven by individual choices made by the investigators, such as the time period over which the loss was estimated and the choice of vortex edge criterion. For the passive subtraction studies employing a full chemistry transport model, important factors include the choice of whether it is the observed or model simulated ozone from which the modeled passive ozone is subtracted, and/or any methods used to correct for biases in the model ozone fields (e.g., as discussed in Jackson and Orsolini, 2008). Figure 6 shows integrated losses for each of the Arctic and Antarctic winters observed by MLS through March 2013.…”

The use of SMILES data to study ozone loss in the Arctic winter 2009/2010 and comparison with Odin/SMR data using assimilation techniques

“…In this paper, we employ the data assimilation technique developed for other Arctic winters by Rösevall et al (2007aRösevall et al ( , b, 2008 to investigate the ozone depletion in the 2009/2010 winter using SMILES ozone data. Other similar studies have used various models and assimilation methods (El Amraoui et al, 2008;Jackson and Orsolini, 2008;Søvde et al, 2011). One advantage of data assimilation is that it allows us to optimally use all measurements and is useful for interpolating or extrapolating the ozone distributions when and where no measurements are available.…”