Detecting Dust Storms and Water Ice Clouds Onboard THEMIS

Details Detecting Dust Storms and Water Ice Clouds Onboard THEMIS Detecting Dust Storms and Water Ice Clouds Onboard THEMIS

May 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agusmin43a..05w&link_type=abstract

American Geophysical Union, Fall Meeting 2007, abstract #IN43A-05

Other

5405 Atmospheres (0343, 1060), 5464 Remote Sensing, 0305 Aerosols And Particles (0345, 4801, 4906)

Scientific paper

We are developing and testing the first data analysis algorithms to be used onboard a spacecraft in Mars orbit. In particular, these algorithms will be uploaded to the Mars Odyssey spacecraft, where they will analyze data collected by the Thermal Emission Imaging System (THEMIS) instrument. In order of increasing sophistication, they can detect thermal anomalies (which could be indicators of geothermal activity), track the movements of the seasonal polar caps, detect dust storms, and detect water ice clouds in the atmosphere. The benefit of estimating atmospheric constituents in an onboard setting is that we can then detect features or events of interest and use them to prioritize data for transmission back to Earth. Rather than collecting only a pre-specified list of target images, THEMIS can use a more continuous operating mode and only return images that successfully capture events of interest, such as the onset of a dust storm or particularly dense water ice clouds. We will present recent results obtained by our dust and water ice cloud detection algorithms when applied to raw data that was collected by THEMIS. To estimate the dust and water ice content of the atmosphere, we trained a support vector machine (SVM) to perform regression based on previous analyses of a combination of fully calibrated TES and THEMIS data by Smith et al. (JGR 108, 2003). We find that both algorithms are, on average, able to estimate optical depth to within the same level of the uncertainty associated with the values computed by Smith et al. We conclude that these algorithms are performing at a level suitable for use onboard THEMIS. We will also report on the status of onboard infusion of these methods.

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