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Proceedings Paper

Information content analysis for a novel TES-based hyperspectral microwave atmospheric sounding instrument
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Paper Abstract

In context of numerical weather prediction (NWP), increased usage of satellites radiance observations from passive microwave sensors have brought significant improvements in the forecast skills. In the infrared spectral region, hyperspectral sounder instruments such as IASI have already benefitted the NWP assimilation systems, but they are useful only under clear sky conditions. Currently, microwave instruments are providing wealth of information on clouds, precipitation and surface etc., but only with limited number of channels. Furthermore, due to limited number of channels and with poor signal-to-noise ratio, existing passive microwave sensors have very poor resolution and accuracy.

We are currently developing a new microwave instrument concept, based on superconducting filterbank spectrometers, which will enable high spectral resolution observations of atmospheric temperature and humidity profiles across the microwave/sub-millimeter wavelength region with photon-noise-limited sensitivity. This study aims at investigating the information content on temperature and water-vapour that could be provided by such a hyperspectral microwave instrument under clear sky-conditions. Here, we present a new concept of Transition Edge Sensors (TESs)-based hyperspectral microwave instrument for atmospheric sounding applications. In this study, for assessing the impact of hyperspectral sampling in microwave spectral region in clear sky-conditions, we have estimated the information content as standard figure of merit called as degrees of freedom for signal (DFS). The DFS for a set of temperature and humidity sounding channels (50-60 GHz, 118GHz and 183 GHz) have been analyzed under the linear optimal estimation theory framework.

Paper Details

Date Published: 9 October 2018
PDF: 14 pages
Proc. SPIE 10786, Remote Sensing of Clouds and the Atmosphere XXIII, 1078608 (9 October 2018); doi: 10.1117/12.2500516
Show Author Affiliations
Prateek Kumar Dongre, Cardiff Univ. (United Kingdom)
Stephan Havemann, UK Met Office (United Kingdom)
Peter Hargrave , Cardiff Univ. (United Kingdom)
Angiola Orlando, Cardiff Univ. (United Kingdom)
Rashmikant Sudiwala, Cardiff Univ. (United Kingdom)
Stafford Withington, Univ. of Cambridge (United Kingdom)
Chris Thomas, Univ. of Cambridge (United Kingdom)
David Goldie, Univ. of Cambridge (United Kingdom)


Published in SPIE Proceedings Vol. 10786:
Remote Sensing of Clouds and the Atmosphere XXIII
Adolfo Comerón; Evgueni I. Kassianov; Klaus Schäfer; Richard H. Picard; Konradin Weber, Editor(s)

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