Low level jets and the convergence of Mars data assimilation algorithms
Data assimilation is an increasingly popular technique in Mars atmospheric science, but its effect on the mean states of the underlying atmosphere models has not been thoroughly examined. The robustness of results to the choice of model and assimilation algorithm also warrants further study. We investigate these issues using two Mars general circulation models (MGCMs) with particular emphasis on zonal wind and temperature fields. When temperature retrievals from the Mars Global Surveyor Thermal Emission Spectrometer (TES) are assimilated into the U.K. Laboratoire de Meteorologie Dynamique (UK LMD) MGCM to create the Mars Analysis Correction Data Assimilation (MACDA) reanalysis, low level zonal jets in the winter northern hemisphere shift equatorward and weaken relative to a free running control simulation from the same MGCM. The Ensemble Mars Atmosphere Reanalysis System (EMARS) reanalysis, which is also based on TES temperature retrievals, also shows jet weakening (but less if any shifting) relative to a control simulation performed with the underlying Geophysical Fluid Dynamics Laboratory (GFDL) MGCM. Examining higher levels of the atmosphere, monthly mean three dimensional temperature and zonal wind fields are in generally better agreement between the two reanalyses than between the two control simulations. In conjunction with information about the MGCMs' physical parametrizations, intercomparisons between the various reanalyses and control simulations suggest that overall the EMARS control run is plausibly less biased (relative to the true state of the Martian atmosphere) than the MACDA control run. Implications for future observational studies are discussed. Plain Language Summary An increasingly popular way to study Martian weather and climate is to combine atmospheric temperature observations with a computer model (specifically, a general circulation model) The process of combining model and observations is referred to as "data assimilation" and the resulting merged data set is referred to as a "reanalysis" Several Mars reanalyses have been produced. One advantage of reanalyses is that they include meteorological variables (such as wind) that are not directly observed however, it is not clear how accurately data assimilation algorithms compute these unobserved variables. Our study investigates this issue using two Mars reanalyses and two model simulations that do not assimilate temperature data. We focus on slowly varying atmospheric phenomena (timescales from 10 Mars days to a season) Assimilating temperature data into two different general circulation models changes the strength and/or spatial pattern of east west winds at low altitudes. Furthermore, monthly mean three dimensional temperature and east west wind fields agree better between reanalyses than between non assimilating model simulations. This suggests that the data assimilation process is basically successful. One non assimilating model simulation has less realistic representations of atmospheric physical processes than the other we argue that this plausibly gives it larger biases relative to the true state of the atmosphere.