Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userLow-level jets and the convergence of Mars data assimilation algorithms
90
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
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.
rate research
Read More
A Martian semiannual oscillation (SAO), similar to that in the Earths tropical stratosphere, is evident in the Mars Analysis Correction Data Assimilation reanalysis dataset (MACDA) version 1.0, not only in the tropics, but also extending to higher latitudes. Unlike on Earth, the Martian SAO is found not always to reverse its zonal wind direction, but only manifests itself as a deceleration of the dominant wind at certain pressure levels and latitudes. Singular System Analysis (SSA) is further applied on the zonal-mean zonal wind in different latitude bands to reveal the characteristics of SAO phenomena at different latitudes. The second pair of principal components (PCs) is usually dominated by a SAO signal, though the SAO signal can be strong enough to manifest itself also in the first pair of PCs. An analysis of terms in the Transformed Eulerian Mean equation (TEM) is applied in the tropics to further elucidate the forcing processes driving the tendency of the zonal-mean zonal wind. The zonal-mean meridional advection is found to correlate strongly with the observed oscillations of zonal-mean zonal wind, and supplies the majority of the westward (retrograde) forcing in the SAO cycle. The forcing due to various non-zonal waves supplies forcing to the zonal-mean zonal wind that is nearly the opposite of the forcing due to meridional advection above ~3 Pa altitude, but it also partly supports the SAO between 40 Pa and 3 Pa. Some distinctive features occurring during the period of the Mars year (MY) 25 global-scale dust storm (GDS) are also notable in our diagnostic results with substantially stronger values of eastward and westward momentum in the second half of MY 25 and stronger forcing due to vertical advection, transient waves and thermal tides.
Dust aerosol plays a fundamental role in the behavior and evolution of the Martian atmosphere. The first five Mars years of Mars Exploration Rover data provide an unprecedented record of the dust load at two sites. This record is useful for characterization of the atmosphere at the sites and as ground truth for orbital observations. Atmospheric extinction optical depths have been derived from solar images after calibration and correction for time-varying dust that has accumulated on the camera windows. The record includes local, regional, and globally extensive dust storms. Comparison with contemporaneous thermal infrared data suggests significant variation in the size of the dust aerosols, with a 1 {mu}m effective radius during northern summer and a 2 {mu}m effective radius at the onset of a dust lifting event. The solar longitude (LS) 20-136{deg} period is also characterized by the presence of cirriform clouds at the Opportunity site, especially near LS=50 and 115{deg}. In addition to water ice clouds, a water ice haze may also be present, and carbon dioxide clouds may be present early in the season. Variations in dust opacity are important to the energy balance of each site, and work with seasonal variations in insolation to control dust devil frequency at the Spirit site.
Data assimilation leads naturally to a Bayesian formulation in which the posterior probability distribution of the system state, given the observations, plays a central conceptual role. The aim of this paper is to use this Bayesian posterior probability distribution as a gold standard against which to evaluate various commonly used data assimilation algorithms. A key aspect of geophysical data assimilation is the high dimensionality and low predictability of the computational model. With this in mind, yet with the goal of allowing an explicit and accurate computation of the posterior distribution, we study the 2D Navier-Stokes equations in a periodic geometry. We compute the posterior probability distribution by state-of-the-art statistical sampling techniques. The commonly used algorithms that we evaluate against this accurate gold standard, as quantified by comparing the relative error in reproducing its moments, are 4DVAR and a variety of sequential filtering approximations based on 3DVAR and on extended and ensemble Kalman filters. The primary conclusions are that: (i) with appropriate parameter choices, approximate filters can perform well in reproducing the mean of the desired probability distribution; (ii) however they typically perform poorly when attempting to reproduce the covariance; (iii) this poor performance is compounded by the need to modify the covariance, in order to induce stability. Thus, whilst filters can be a useful tool in predicting mean behavior, they should be viewed with caution as predictors of uncertainty. These conclusions are intrinsic to the algorithms and will not change if the model complexity is increased, for example by employing a smaller viscosity, or by using a detailed NWP model.
We have produced a multiannual climatology of airborne dust from Martian year 24 to 31 using multiple datasets of retrieved or estimated column optical depths. The datasets are based on observations of the Martian atmosphere from April 1999 to July 2013 made by different orbiting instruments: the Thermal Emission Spectrometer (TES) aboard Mars Global Surveyor, the Thermal Emission Imaging System (THEMIS) aboard Mars Odyssey, and the Mars Climate Sounder (MCS) aboard Mars Reconnaissance Orbiter (MRO). The procedure we have adopted consists of gridding the available retrievals of column dust optical depth (CDOD) from TES and THEMIS nadir observations, as well as the estimates of this quantity from MCS limb observations. Our gridding method calculates averages and uncertainties on a regularly spaced, but possibly incomplete, spatio-temporal grid, using an iterative procedure weighted in space, time, and retrieval uncertainty. In order to evaluate strengths and weaknesses of the resulting gridded maps, we validate them with independent observations of CDOD. We have statistically analyzed the irregularly gridded maps to provide an overview of the dust climatology on Mars over eight years, specifically in relation to its interseasonal and interannual variability. Finally, we have produced multiannual, regular daily maps of CDOD by spatially interpolating the irregularly gridded maps using a kriging method. These synoptic maps are used as dust scenarios in the Mars Climate Database version 5, and are useful in many modelling applications in addition to forming a basis for instrument intercomparisons. The derived dust maps for the eight available Martian years are publicly available and distributed with open access.
In this paper we show that Sun-viewing images obtained by the Mars Science Laboratory (MSL) Navigation Cameras (Navcam) can be used for retrieving the dust optical depth and constrain the aerosol physical properties at Gale Crater by evaluating the sky brightness as a function of the scattering angle. We have used 65 Sun-pointing images covering a period of almost three Martian years, from MSL mission sol 21 to sol 1646 (MY 31 to 33). Radiometric calibration and geometric reduction were performed on MSL Navcam raw image data records to provide the observed sky radiance as a function of the scattering angle for the near-Sun region (scattering angle from 4{deg} to 30{deg}). These curves were fitted with a multiple scattering radiative transfer model for a plane-parallel Martian atmosphere model using the discrete ordinates method. Modelled sky brightness curves were generated as a function of two parameters: the aerosol particle size distribution effective radius and the dust column optical depth at the surface. A retrieval scheme was implemented for deriving the parameters that generated the best fitting curve under a least-square error criterion. The obtained results present a good agreement with previous work, showing the seasonal dependence of both dust column optical depth and the effectiveparticle radius.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
