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Published October 2003 | public
Journal Article

Analysis of Thermal Emission Spectrometer data using spectral EOF and tri-spectral methods

Abstract

We introduce two new techniques in analyzing martian spectrally resolved radiance data obtained by the Thermal Emission Spectrometer (TES): spectral empirical orthogonal function (EOF) analysis and the tri-spectral algorithm. Spectral EOF analysis allows us to obtain the variability of spectra and associated temporal and spatial patterns. The case study with TES 20° S–20° N data shows that the first principal component (PC1) dominates the total variance and is associated with surface or near-surface brightness temperature variations. The PC2 is associated with atmospheric variability, and a negative correlation between dust and ice absorptions can be clearly seen over many regions. The annual cycle is a major component of the PC1 temporal patterns. The fingerprint of the dust storm can be clearly seen in the PC2 temporal patterns in most areas except the highlands. Spectral EOF can be used for validation of the variability of martian GCMs. The tri-spectral algorithm is based on the differences between three bands (dust, ice and a weak CO_2 absorption band) to distinguish spectra sampled in different situations: water ice cloud, dust, and surface anisothermality. We use a line-by-line radiative transfer model coupled with multiple scattering to investigate the sensitivity of this algorithm to dust and ice optical depth as well as surface emissivity. The comparisons between results of this algorithm and the TES team's retrieved dust and ice opacity are consistent over all studied periods except during the peak of the dust storm. Our algorithm is complementary to the more sophisticated TES retrieval and can be used to screen large amounts of data to get an overview.

Additional Information

© 2003 Elsevier Inc. Received 12 February 2003; revised 20 May 2003. Available online 26 August 2003. We thank S. Byrne, M. Gerstell, A. Ingersoll, T. Martin, and M. Richardson for helpful discussions. We are greatly indebted to M. Richardson for his help in accessing TES data. One of the authors, Y.L. Yung, is indebted to T. Martin for pointing out the importance of anisothermality. We also thank two referees, including J.L. Bandfield for greatly improving the paper. This research was supported by NASA grant NAGS-10724 to the California Institute of Technology.

Additional details

Created:
August 22, 2023
Modified:
October 17, 2023