Potential for the use of reconstructed IASI radiances in the detection of atmospheric trace gases

Atkinson, Nigel; Hilton, F.; Illingworth, Sam; Eyre, J. R.; Hultberg, Tim

doi:10.5194/amt-3-991-2010

Cited by 17 publications

(15 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Making a principal component analysis (PCA) (Jolliffe, 2002) of an ensemble of spectra is a way of reducing the dimensionality by extracting the principal components of spectral variation and disregarding those that carry no information (Huang and Antonelli, 2001;Antonelli et al, 2004;Klüser et al, 2011). This allows to remove instrumental noise as was illustrated in Atkinson et al (2010) with a better detection of NH 3 by the application of a BTD filter on reconstructed spectra. PCA can also be applied in a different way for the detection of trace gases or aerosols.…”

Section: Methods Based On Singular Value Decomposition and Principal mentioning

confidence: 99%

“…Principal components should be calculated from a large number of random training spectra to accommodate for all observed variability. However, as discussed in Atkinson et al (2010), very rare events (volcanic eruptions, large fires) will typically be reconstructed poorly as their weight is too low for their spectral features to be represented in the principal components. This opens up the possibility of using principal components as a detection tool by explicitly avoiding the presence of the target species in the spectra of the training set.…”

Section: Methods Based On Singular Value Decomposition and Principal mentioning

confidence: 99%

See 1 more Smart Citation

A unified approach to infrared aerosol remote sensing and type specification

et al. 2013

View full text Add to dashboard Cite

Atmospheric aerosols impact air quality and global climate. Space based measurements are the best way to observe their spatial and temporal distributions, and can also be used to gain better understanding of their chemical, physical and optical properties. Aerosol composition is the key parameter affecting the refractive index, which determines how much radiation is scattered and absorbed. Composition of aerosols is unfortunately not measured by state of the art satellite remote sounders. Here we use high resolution infrared measurements for aerosol type differentiation, exploiting, in that part of spectrum, the dependency of their refractive index on wavelength. We review existing detection methods and present a unified detection method based on linear discrimination analysis. We demonstrate this method on measurements of the Infrared Atmospheric Sounding Interferometer (IASI) and five different aerosol types, namely volcanic ash, windblown sand, sulfuric acid droplets, ammonium sulfate and smoke particles. We compare these with traditional MODIS AOD measurements. The detection of the last three types is unprecedented in the infrared in nadir mode, but is very promising, especially for sulfuric acid droplets which are detected in the lower troposphere and up to 6 months after injection in the upper troposphere/lower stratosphere

show abstract

Section: Methods Based On Singular Value Decomposition and Principal mentioning

confidence: 99%

Section: Methods Based On Singular Value Decomposition and Principal mentioning

confidence: 99%

A unified approach to infrared aerosol remote sensing and type specification

et al. 2013

View full text Add to dashboard Cite

show abstract

“…In addition to the main trace gases, IASI can detect emission sources of short-lived species. These species usually have very weak spectral signatures, and so currently simple radiance indexing methods based on brightness temperature differences are applied to produce global distribution maps Razavi et al 2011;Walker et al 2011), with possible extension to the use of noise-filtered radiances (Atkinson et al 2010). …”

Section: Ozone (O 3 )mentioning

confidence: 99%

Hyperspectral Earth Observation from IASI: Five Years of Accomplishments

Hilton

Armante

August

et al. 2012

Bulletin of the American Meteorological Society

411

313

View full text Add to dashboard Cite

The Infrared Atmospheric Sounding Interferometer (IASI) forms the main infrared sounding component of the European Organisation for the Exploitation of Meteorological Satellites's (EUMETSAT's) Meteorological Operation (MetOp)-A satellite (Klaes et al. 2007), which was launched in October 2006. This article presents the results of the first 4 yr of the operational IASI mission. The performance of the instrument is shown to be exceptional in terms of calibration and stability. The quality of the data has allowed the rapid use of the observations in operational numerical weather prediction (NWP) and the development of new products for atmospheric chemistry and climate studies, some of which were unexpected before launch. The assimilation of IASI observations in NWP models provides a significant forecast impact; in most cases the impact has been shown to be at least as large as for any previous instrument. In atmospheric chemistry, global distributions of gases, such as ozone and carbon monoxide, can be produced in near–real time, and short-lived species, such as ammonia or methanol, can be mapped, allowing the identification of new sources. The data have also shown the ability to track the location and chemistry of gaseous plumes and particles associated with volcanic eruptions and fires, providing valuable data for air quality monitoring and aircraft safety. IASI also contributes to the establishment of robust long-term data records of several essential climate variables. The suite of products being developed from IASI continues to expand as the data are investigated, and further impacts are expected from increased use of the data in NWP and climate studies in the coming years. The instrument has set a high standard for future operational hyperspectral infrared sounders and has demonstrated that such instruments have a vital role in the global observing system.

show abstract

“…The inversion solution in PCA space is therefore constrained to lie in the space defined by the retained eigenvectors and that can potentially mask climate trends. PCA over the whole spectrum (for transmission purpose for instance) tends to filter out (or disseminate in multiple non‐reliable higher‐order PCs) small signals due to minor gas constituents. This can be solved by building a dedicated dataset (Atkinson et al , ). A particularly important problem is referred to as the ‘mixing problem’, i.e. multiple physical components are mixed in the first PCs (in order to maximize the explained variance) and only fragmented residual components are left in the higher‐order PCs (Aires et al , ).…”

Section: Compression Methodsmentioning

confidence: 99%

Dimension reduction of satellite observations for remote sensing. Part 1: A comparison of compression, channel selection and bottleneck channel approaches

Aires

Pellet²,

Prigent

et al. 2016

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

With the increasing volume of satellite observations, dimension reduction techniques are more and more important for storage or transmission. Furthermore, they are essential for inversion schemes that, in practice, cannot handle the huge amount of information provided by modern instruments for near‐real‐time inversion. In this article, we compare the theoretical advantages and limitations of the two general strategies: compression (i.e. feature extraction) and channel selection (i.e. feature selection). The statistical ‘input variable selection’ framework is adopted to revisit the basis of these remote‐sensing techniques. The flexibility of these methods to specific applications is demonstrated. Special emphasis is put on the optimization of observation dimension reduction for the simultaneous retrieval of several variables (e.g. temperature and humidity). In addition to considering the signal‐to‐noise ratio for the variable to retrieve, we propose to account for contamination by other unknown variables. We also introduce a new approach named ‘bottleneck channels’ (BC), which combines compression and channel selection techniques and can therefore benefit from the advantages of both strategies. Various configurations of the BC approach can be considered: strict, linearly or nonlinearly projected, each with advantages and drawbacks. In the companion article, experiments will be conducted on microwave data to illustrate the practical advantages of each approach. BC are able to compress and suppress noise in a similar way to principal component analysis (PCA) and they can be interpreted as channels, as in channel selection.

show abstract

Potential for the use of reconstructed IASI radiances in the detection of atmospheric trace gases

Cited by 17 publications

References 23 publications

A unified approach to infrared aerosol remote sensing and type specification

A unified approach to infrared aerosol remote sensing and type specification

Hyperspectral Earth Observation from IASI: Five Years of Accomplishments

Dimension reduction of satellite observations for remote sensing. Part 1: A comparison of compression, channel selection and bottleneck channel approaches

Contact Info

Product

Resources

About