Thursday, 10 January 2013: 3:45 PM
Room 16B (Austin Convention Center)
Ross N. Hoffman
, NOAA/AOML, Miami, FL; and S. Greybush, D. Gombos, J. Eluszkiewicz, M. J. Hoffman, R. J. Wilson, K. Ide, and E. Kalnay
We have implemented an advanced Mars data assimilation system (DAS) based on the Local Ensemble Transform Kalman Filter (LETKF), including newly developed capabilities, and coupled it with the GFDL Mars general circulation model (GCM). Our DAS is designed to optimally combine available remote observations of the Martian atmosphere with our knowledge of the physics as embodied in the GCM. The DAS was tested first with simulated Thermal Emission Spectrometer (TES) observations. Real temperatures retrieved from the TES and Mars Climate Sounder (MCS), both available from Planetary Data System (PDS), have been also successfully assimilated. As a step towards interactive retrievals in which the ensemble mean and covariance of the atmospheric profiles are used as the prior in the retrieval process we are testing a new retrieval---DAS interface. For this interface we convert standard retrievals into "observations" with expected errors that should be zero mean, uncorrelated, and unit variance, and define a corresponding obs-function (or H-operator) that is a weighted sum of the temperatures on the radiative transfer model vertical grid. To reduce the number of observations, we make use of the EOFs used by the retrieval to represent the transformed observations.
Our approach follows some ideas from Rodgers' book, "Inverse Methods for Atmospheric Sounding: Theory and Practice". This allows us to properly account for the fact that a retrieved profile effectively smooths the true profile in the vertical and then mixes that with the prior profile. The weights are determined from various inputs and outputs of the retrieval process. The simplest set of these are just the prior and posteriori mean and covariance of the profile. No changes to the assimilation method are needed, except to interpolate to the radiative transfer model vertical grid and to calculate the weighted sum. The weights will be used in the vertical localization for data selection. We test this approach in our Mars data assimilation system using Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) radiances and retrievals based on the Optimal Spectral Sampling (OSS) forward model that we have tuned for TES.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner