The Atmospheric Library is made up of an extensive set of integrated atmospheric data bases created by the Atmospheric Generator Model (AGM). The AGM, which is not part of the current MLSM, provides meteorological inputs from control fields, generated correlated fields, mesoscale fields to global meteorological fields. The AGM can create three types of atmospheric files: Global Atmospheric Data Set (GADS), Mesoscale Atmospheric Data Set (MADS)* and Pure/Spectral Atmospheric Data Set (PADS)*. The library screen includes options that allows the user to customize the effects of atmospheric turbulence, aerosol backscatter and aerosol attenuation  for the simulation. 

Atmosphere

A GADS is a FORTRAN 90 direct access file created by using a nature run's data in liaison with the AGM optical property models, and terrain data set. The Lidar Simulation Model (LSM) retrieves atmospheric profiles from a GADS as a function of latitude and longitude for each laser shot. 

During the course of this contract, SWA researched various Mars GCM models such as Mars Climate Database, NASA AMES Mars GCM and NASA  MARS-GRAM and attended a NASA workshop; Proper Use of M ars Atmospheric M odels. While it is planned that a future version of the MLSM will be able to simulate on many AMES and MCD databases for various time of the year and dust events, currently the MLSM is set up to only simulate on  a 1 day MCD database. 

The Mars Climate Database Surveyor for spring 2001 (Ls 0-30) from the Martian Global Circulation Model (Lewis et. al., 1999) was selected as the Nature Run first candidate due to the ease of obtaining the data set over the web. The horizontal resolution of the database is 5^ox5^o for every two hours and the temporal resolution is every 2 hours. 

Line of Sight Variance

Variance along the line of sight (pulse length) is not included in the MLSM version 1.0.

Subgrid Scale Variance  

The LSM has three options for estimating the wind variance on the sub-grid scale of the model. The first method uses pre-computed wind variance over the 3-dimensiona' grid volume for sub-grid scale uncertainties and then scales the variance to smaller (pulse) scales by the Von Karman relationship. This “reasonable” approach has been used for many years but has not been fully verified by real data. The second method represents the uncertainties by scaling them to 20 % of the mean model wind speed. Comparisons of the Earth model uncertainties with the NMC rawinsonde profiles suggest that the simulated variances using the 20 % rule are not unreasonable. Last, the user can choose no sub-grid scale variance option.  

Optical Properties

In the MLSM version 1.0, the user can customize the simulations optical properties via natural variability, vertical distribution,  concentration, particle size distribution  and elevated dust storms options

Last Updated: 02/07/2007