Copy the page URI to the clipboard
Read, P. L.; Valeanu, A.; Ruan, Tao; Montabone, L.; Lewis, S. R. and Young, R. M. B.
(2022).
URL: http://www-mars.lmd.jussieu.fr/paris2022/abstracts...
Abstract
The dust cycle is a key component of the Martian climate, and is extremely important for understanding the interannual, seasonal and synoptic evolution of the Martian environment. (e.g., Kahre et al., 2017; Newman et al., 2002a, and references therein). Intensive measurements of atmospheric temperature and dust extending over more than eleven Mars years (MY) now exist with unprecedented spatial coverage, thanks to various orbital spacecraft. Such observations have already helped to improve our understanding of Mars' weather and climate. However, the incomplete coverage of these measurements across the planet constrains our ability to study the general circulation in full detail, particularly those aspects related to dust opacity.
On the other hand, numerical models provide four-dimensional simulated data with moderate to high temporal and spatial resolution and complete coverage in space and time, but often fail to reproduce the dust cycle's full range of variability. Even the most sophisticated free-running GCMs still struggle to capture realistic interannual variability associated with dust lifting and transport.
To aid in this task, data assimilation has become an optimal approach to provide a solution that is consistent with both observations and modeled physical constraints. Data assimilation corrects model-predicted variables toward observations such that the resulting solution can represent the full observed variability of the climate. Such an assimilated record is often termed a “reanalysis” by analogy with the practice in Earth weather and climate forecasting.
Several publicly available reanalyses of observations of the Martian atmosphere have been produced in recent years, based mainly on remote sounding measurements of atmospheric temperature, dust and ice opacity and chemical constituents from various orbital platforms (e.g. Montabone et al. 2014; Greybush et al. 2019; Holmes et al. 2020). However, almost all of these have so far mainly used measurements of column dust opacity without information on the vertical distribution of dust. Such products provide much useful information on how dust evolves during the Martian year, but may misrepresent some important features, such as elevated layers of dust (Heavens et al. 2011), and give no information on the vertical extent of dust loading in the atmosphere.
In the present work, we have extended the Analysis Correction assimilation scheme (Lorenc et al. 1991), as used for the MACDA and OPENMARS reanalyses, to make use of both column-integrated (CIDO) and layer-integrated dust opacity (LIDO), such as obtained from Mars Climate Sounder limb observations. Here we outline the new assimilation scheme and present some results (a) that validate the reanalysis with independent observations and (b) that demonstrate significant improvements in the representation of the 3D distribution of dust opacity in the Martian atmosphere, even when this distribution differs markedly from the long term climatology.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)
