Holmes, J. A.

Lewis, S. R.

Patel, M. R.

Lefèvere, F.

English

Open Research Online (The Open University)

Open Research OnlineThe Open University’s repository of research publicationsand other research outputsInvestigating the ozone cycle on Mars using GCMmodelling and data assimilationConference or Workshop ItemHow to cite:Holmes, J. A.; Lewis, S. R.; Patel, M. R. and Lefe`vere, F. (2014). Investigating the ozone cycle on Marsusing GCM modelling and data assimilation. In: Fifth International Workshop on the Mars Atmosphere: Modellingand Observations, 12-16 Jan 2014, Oxford, UK.For guidance on citations see FAQs.c© 2014 The AuthorsVersion: Accepted ManuscriptLink(s) to article on publisher’s website:http://www-mars.lmd.jussieu.fr/oxford2014/Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyrightowners. For more information on Open Research Online’s data policy on reuse of materials please consult the policiespage.oro.open.ac.ukINVESTIGATING  THE  OZONE  CYCLE  ON  MARS  USING  GCM MODELLING AND DATA ASSIMILATIONJ.  A.  Holmes, S.  R.  Lewis,  M.  R.  Patel ,  Department of  Physical  Sciences,  The Open University,  Milton  Keynes,  U.K.  (james.holmes@open.ac.uk),  F.  Lefèvre, LATMOS/IPSL,  Centre National  de  la  Recherche Scientifique, Paris, France.Introduction:  In this work we use atmospheric modelling and data  assimilation to  study the  annual ozone  cycle. There are a multitude of current issues which can be investigated including the chemical stability of the at-mosphere,  the  polar  vortices  and  habitability.  OH (part of the odd hydrogen family HOx and produced from the photolysis of water  vapour)  is  known to play a key role in the stability of the atmosphere and is also  a  major  catalytic destructor  of  ozone.  This chemical species has only recently been detected by Clancy et al. (2013) and for further studies a possible option is to use ozone as a tracer for OH.Ozone has also been found to be quasi-passive in the polar night (Lefèvre et al. 2004) due primarily to the lack of daylight hours and a negligible amount of HOx radicals present at this time of the year. The dy-namics associated with the northern polar vortex can therefore be traced using the ozone abundance. The UV flux reaching the ground, an important parameter for the habitability of Mars, is controlled by the atmo-spheric ozone. A more realistic ozone cycle reduces the  uncertainties  of  the  amount  of  UV  radiation reaching the surface of Mars. Further analysis of the ozone cycle can also provide a broader understanding of the Martian atmospheric chemistry.Providing a consistent temporal and spatial agree-ment between models and observations of ozone is also of great  benefit in furthering the understanding of important photochemical processes in the Martian atmosphere.  Seasonal variations,  that  are  governed primarily by the hygropause level at different times of the year (Clancy and Nair, 1996), have been known from the first  observations of ozone by Mariner 9. Ozone on Mars is primarily observed by the strong and wide absorption band centred at 255 nm detect-able by UV spectrometers  (Perrier et  al.,  2006).  It can also be retrieved at 9.7 μm where IR spectromet-ers can ascertain measurements (Fast et al., 2006) and indirectly in the 1.27 μm O2 (a1Δg) emission band (Al-tieri et al., 2009).To investigate the combined dynamical, physical and chemical processes  affecting ozone distribution requires ideally a three-dimensional model. Lefèvre et al. (2004)  were the first to  use a three-dimensional Martian global cirulation model (GCM) coupled to a photochemical module to increase knowledge of the properties of ozone in the Martian atmosphere. The agreement between the model and observations was later  improved by inclusion of  heterogeneous reac-tions (Lefèvre et al., 2008). Comparisons to spatially averaged  observations provide good  constraints  on the seasonal distribution. For an in-depth approach, identifying differences between models and observa-tions on a temporal and spatial scale can identify spe-cific regions  where  the  largest  discrepancies  exist. Higher resolution models with less parameterisations can consequently be used to study the identified area in more depth (Spiga and Forget, 2009), that would otherwise be computationally expensive.To make optimal use of information, observations and the model are combined by the process of data assimilation. The outcome of this process is a dynam-ical global reconstruction  of  the  observations.  The satellites currently orbiting Mars, combined with the future planned satellite missions, create  a great  op-portunity for the development of a data assimilation technique for ozone and more generally trace gases on Mars. Although data assimilation is now common-place on Earth,  it is a fairly new concept  for other planetary systems.Data  assimilation  is  fast  becoming  a  common technique for input of observations into a GCM to study a variety of topics (Lewis and Barker,  2005; Montabone et al., 2006; Greybush et al., 2012). Mars Express carries the Spectroscopy for  the Investiga-tion of the Characteristics of the Atmosphere of Mars (SPICAM)  instrument  from  which  total-column ozone can be retrieved. Ozone data has never before been assimilated for Mars, but the use of this tech-nique  is  widespread  for  Earth  (Kiesewetter  et  al., 2010 for example).The assimilation of total-column ozone can also be used to  inform instrument planning on upcoming missions such as the Trace Gas Orbiter (TGO) and provide  a  comprehensive  analysis,  constrained  by satellite observations, of the ozone cycle on Mars.Figure 1:  Retrievals of total-column ozone from the SPICAM instrument aboard Mars Express.SPICAM Observations:The  first  total-column  ozone  observations  we have  assimilated  into  our  model  are  from  the SPICAM  instrument  on  Mars  Express  (Figure  1). The gaps in data from LS = 70-90° and LS = 200-240° are due to a night side pericentre preventing observa-tions and other instruments aboard the spacecraft tak-ing priority respectively. Maximum values are  seen around  northern  hemisphere  spring  equinox,  after ozone has had time to build up due to the constant darkness over the north pole in winter. There is less observed total-column ozone in the tropical regions at the start of Mars year (MY) 28 than towards the beginning of MY 27, hinting at annual variations of atmospheric ozone. The majority of retrievals at the start of MY 28 occur earlier in the morning than the previous  year's  retrievals however,  so  these  differ-ences have to be analysed with caution.The  retrieval  of  total-column  ozone  from  the Hartley band of intense absorption (220-280 nm) is detailed in Perrier et al. (2006), with the outcome be-ing almost 28,000 high signal-to-noise ratio observa-tions for almost one and a half Martian years.. The ground resolution at pericentre is around 4 km2 with an average uncertainty in total-ozone of 10-15%. Ob-servational datasets for other  chemical species such as water vapour from TES have around 8,000 obser-vations a  day,  putting into  perspective the  relative sparseness  of  the  SPICAM  dataset.  Nevertheless, valuable information can be extracted from the data available.GCM Modelling:For modelling of the ozone cycle we use the UK version of the LMD GCM which is currently in use at the  Open University and the University of  Oxford. This GCM uses  the  physical parameterisations and photochemical module shared with the LMD GCM coupled to  a  UK-only spectral  dynamical core  and semi-lagrangian advection  scheme.  It  has  been  de-veloped  in  a  collaboration  of  the  Laboratoire  de Météorologie Dynamique, the Open University, the University of Oxford and the Instituto de Astrofisica de Andalucia.The dust distribution is prescribed horizontally us-ing an interpolation of numerous sets of observations from orbiters  and  landers  using  a  kriging  method (Montabone et al. 2013, in preparation) and vertically using the Conrath dust profile. The model was run at T31 resolution in the horizontal, corresponding to a resolution of 5° latitude by 5° longitude, with 32 ver-tical  sigma levels in the  range  0-105  km.  Vertical levels are much closer to one another near the surface and further apart in the upper atmosphere.The  photochemical  module  provides  multiple photolytic and chemical reactions with up-to-date re-action rates  between 16  advected  species including carbon dioxide, water vapour and ozone. Time-vary-ing dust amounts are also taken into account in the photolytic reactions. Tracers are advected using the semi-lagrangian advection  scheme (Newman et  al., 2002).Assimilation method:The assimilation is performed using the Analysis Correction scheme (Lorenc et al., 1991) converted to Martian conditions, and has been shown in the past to be a computationally inexpensive and robust method (Lewis et al., 2007). Using this methodology, obser-vations of short-lived (and long-lived) species can be supplemented by knowledge of the transport and at-mospheric chemistry from a GCM.Where observations exist, the model value is in-cremented towards the assimilated value, weighted by a horizontal correlation scale and time factor depend-ing on how close in space and time the model grid point and observation are. Since we are incrementing an integrated 2-D column value which is transported in 3 dimensions each timestep, the approach is to as-sume the vertical distribution predicted by the model and normalise this with the total-column ozone obser-vations. The ozone mass mixing ratio at each level is scaled equally using the ratio of the assimilated value to the model value. Currently, the model-observation error ratio has been defined to be unity, therefore an assumption has been made that the error in the model is also around 10-15% for the total-column ozone.Results:To  investigate  the  effect  of  total-column ozone assimilation on the seasonal cycle, we ran a 'control' model run with no assimilation and a second 'assimil-ation' run where the observations from SPICAM have been assimilated. Both runs start at LS = 330° in MY 26  with the  same initial distribution and  include a well-established water cycle. The evolution of ozone for the assimilation run is displayed in Figure 2. The figure displays the total-column ozone values at 12LT everywhere to  provide a fairly direct comparison to the SPICAM daytime observations in Figure 1. The general temporal and spatial distribution of ozone is familiar, with winter  polar maximums and the least abundance in the southern hemisphere around perihe-lion. Our model also agrees quantatively with the 3:1 ratio of total-ozone from just before aphelion to peri-helion in the equatorial region.Figure  2:  Assimilated  zonally averaged  ozone column for MY 27 and the start of MY 28.Deviations in total-column ozone from the control run are apparent primarily around the northern polar maximum build up and decrease (high latitudes from LS = 150-180° and  LS = 0-360° of MY 28).  These locations have been previously linked to possible het-erogeneous uptake of OH, which would decrease the abundance of OH in these regions and hence increase the  observed total-column ozone.  Both  the  control and  assimilation runs have included the  heterogen-eous parameterisation from Lefèvre et al. (2008). An increase in the uptake of OH is seen to decrease the positive bias in the identified regions with the greatest difference  in  total-column ozone,  however  a  sub-sequent negative bias in the second half of MY 27 is apparent. This suggests that a global increase of het-erogeneous uptake does not provide a better match to the observations but results in a greater abundance of total-column ozone residing to the end of the year.Water ice availability:Figure 3 displays the water  ice cloud opacity at 14LT which can be directly compared to TES retriev-als. The aphelion cloud belt and northern polar hood are clearly visible. The coefficient of heterogeneous uptake of OH is increased when the water ice surface is fresh (Cooper and Abbatt, 1996), which would be the case for the aphelion cloud belt where the resid-ence time of water ice clouds is fairly short. The ana-lysis in this region from the assimilation shows a good agreement between the model and observations. The northern polar hood conversely has a long residence time and so the low uptake coefficient seems more appropriate, but this is where we find the largest dis-crepancies between the control and assimilation run.This suggests that  heterogeneous uptake of odd hydrogen radicals on water ice clouds is not at least the primary cause of the mismatch between the model and observations.Figure 3: Model ice opacity at 14LT everywhere to compare with the TES observations.The extent  of  the  northern polar  hood  and the abundance of southern water ice clouds in late south-ern winter (LS = 180-220°) are much less when com-pared  to  the  distribution  in  Lefèvre  et  al.  (2008). These  regions are precisely where our model is find-ing it difficult to reconcile the SPICAM observations with the  modelled ozone,  suggesting the  water  ice cloud distribution to  be of extreme importance in a realistic ozone cycle.Trace gas assimilation:Assimilating observations of other trace gases in future will also be achievable, allowing for investiga-tions into interactions between chemical species and subsequently  improving  our  understanding  of  the Martian chemical environment. Chemical rate coeffi-cients imposed by reconciling observational datasets and theoretical models would add to our current es-timates which come primarily from laboratory experi-ments  only.  The  Nadir  and  Occultation  for  MArs Discovery (NOMAD) instrument on the TGO is set to measure water vapour and ozone abundance using the same instrument which would allow for a direct look at their apparent anti-correlation and deviations from this.The Mars Color Imager (MARCI, Clancy et al., 2011) on the Mars Reconnaissance Orbiter provides near-daily global mapping of ozone column concen-tration extending the currently available ozone data-set.  Alongside  Mars  Climate  Sounder  temperature and dust opacity observations, a fully comprehensive analysis of the ozone cycle should be possible.Summary:We have assimilated for the first time retrievals of ozone from SPICAM into a GCM to investigate the evolution of ozone on Mars. The water ice distribu-tion, especially during the onset of polar night at high latitudes, is an important factor in the initial build up of the polar maximum. Refined parameterisation of water ice cloud formation should also lead to an im-proved modelled ozone cycle.In the near future, assimilation of the MARCI and MCS observations will result in further constraints on the possible missing mechanisms contributing to  the sources and sinks of ozone in our GCM. This tech-nique could also be used for a number of trace gases which are likely to be observed by NOMAD on the TGO.Acknowledgements:The authors would like to  thank Todd Clancy. This work was supported by the UK Space Agency under the Aurora programme.References:Altieri, F.,  Zasova, L.,  D’Aversa, E.,  Bellucci, G.,  Carrozzo, F. G., Gondet, B., Bibring, J.-P. (2009) O2 1.27  μm  emission  maps  as  derived  from  OMEGA/MEx data, Icarus, 204, 499–511.Clancy, R.  T.,  Nair,  H.  (1996)  Annual (perihelion-aphelion) cycles in the photochemical behavior of the global Mars atmosphere,  J.  Geophys.  Res., 101, 12785–12790.Clancy, R.  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Investigating the ozone cycle on Mars using GCM modelling and data assimilation

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Investigating the ozone cycle on Mars using GCM modelling and data assimilation

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