Atmospheric Sounding using IASI

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Title: Atmospheric Sounding using IASI
Authors: Ventress, Lucy Jane
Committee Members: Dudhia, Anu; Eyre, John
Summary: The Infrared Atmospheric Sounding Interferometer (IASI) provides atmospheric observations with high spectral resolution and its data have been shown to have a significant positive impact on global Numerical Weather Prediction (NWP) and trace gas retrievals. A fundamental component of the retrieval of atmospheric composition is the radiative transfer model used to simulate the observations. An accurate representation of the expected emission spectrum measured by the satellite is essential given that differences in the reproduced atmospheric spectra propagate through a retrieval procedure and produce an altered estimate of the atmospheric state. The importance of the assumptions within the forward model are discussed and it is established that in the simulation of spectra from satellite-borne instruments the choice of the model parameters can have a large impact upon the resulting output. These assumptions are explored in the context of the Reference Forward Model (RFM), which is further configured to optimise its output for simulating the IASI spectrum in the troposphere. In order to ascertain the consistency of different radiative transfer models, comparisons are carried out between the RFM and the Radiative Transfer model for TOVS (RTTOV) in order to quantify any discrepancies in the reproduction of IASI measurements. Good agreement is shown across the majority of the spectrum, with exceptions caused by CO2 line mixing effects and the H2O continuum. Alongside model comparisons, the RFM is validated against real IASI measurements. Being a Fourier Transform Spectrometer, there are a large number of channels available from the IASI instrument, which leads to a very large quantity of data. However, this can lead to problems within retrievals and data assimilation. Choosing an optimal subset of the channels is an established method to reduce the amount of data; maintaining the information contained within it whilst eliminating spectral regions with large uncertainties. The method currently used at the UK Met Office to select their spectral channels is re-assessed and a modified method is presented that improves upon the modelling of spectrally correlated errors.
URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669887
Database: OpenDissertations
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An: ddu.oai.ethos.bl.uk.669887
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PubType: Dissertation/ Thesis
PubTypeId: dissertation
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IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Atmospheric Sounding using IASI
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Ventress%2C+Lucy+Jane%22">Ventress, Lucy Jane</searchLink>
– Name: Author
  Label: Committee Members
  Group: Au
  Data: <searchLink fieldCode="CO" term="%22Dudhia%2C+Anu%22">Dudhia, Anu</searchLink>; <searchLink fieldCode="CO" term="%22Eyre%2C+John%22">Eyre, John</searchLink>
– Name: Abstract
  Label: Summary
  Group: Ab
  Data: The Infrared Atmospheric Sounding Interferometer (IASI) provides atmospheric observations with high spectral resolution and its data have been shown to have a significant positive impact on global Numerical Weather Prediction (NWP) and trace gas retrievals. A fundamental component of the retrieval of atmospheric composition is the radiative transfer model used to simulate the observations. An accurate representation of the expected emission spectrum measured by the satellite is essential given that differences in the reproduced atmospheric spectra propagate through a retrieval procedure and produce an altered estimate of the atmospheric state. The importance of the assumptions within the forward model are discussed and it is established that in the simulation of spectra from satellite-borne instruments the choice of the model parameters can have a large impact upon the resulting output. These assumptions are explored in the context of the Reference Forward Model (RFM), which is further configured to optimise its output for simulating the IASI spectrum in the troposphere. In order to ascertain the consistency of different radiative transfer models, comparisons are carried out between the RFM and the Radiative Transfer model for TOVS (RTTOV) in order to quantify any discrepancies in the reproduction of IASI measurements. Good agreement is shown across the majority of the spectrum, with exceptions caused by CO2 line mixing effects and the H2O continuum. Alongside model comparisons, the RFM is validated against real IASI measurements. Being a Fourier Transform Spectrometer, there are a large number of channels available from the IASI instrument, which leads to a very large quantity of data. However, this can lead to problems within retrievals and data assimilation. Choosing an optimal subset of the channels is an established method to reduce the amount of data; maintaining the information contained within it whilst eliminating spectral regions with large uncertainties. The method currently used at the UK Met Office to select their spectral channels is re-assessed and a modified method is presented that improves upon the modelling of spectrally correlated errors.
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  Data: <link linkTarget="URL" linkTerm="https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669887" linkWindow="_blank">https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669887</link>
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: 551.5
        Type: general
      – SubjectFull: Atmospheric, Oceanic, and Planetary physics ; Physics ; atmospheric physics ; remote sensing ; radiative transfer models ; retrievals ; channel selection
        Type: general
    Titles:
      – TitleFull: Atmospheric Sounding using IASI
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Ventress, Lucy Jane
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2013
ResultId 1