Retrieval of ash properties from IASI measurements

Abstract

Abstract. A new optimal estimation algorithm for the retrieval of volcanic ash properties has been developed for use with the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval method uses the wave number range 680-1200 cm −1 , which contains window channels, the CO 2 ν 2 band (used for the height retrieval), and the O 3 ν 3 band.Assuming a single infinitely (geometrically) thin ash plume and combining this with the output from the radiative transfer model RTTOV, the retrieval algorithm produces the most probable values for the ash optical depth (AOD), particle effective radius, plume top height, and effective radiating temperature. A comprehensive uncertainty budget is obtained for each pixel. Improvements to the algorithm through the use of different measurement error covariance matrices are explored, comparing the results from a sensitivity study of the retrieval process using covariance matrices trained on either clear-sky or cloudy scenes. The result showed that, due to the smaller variance contained within it, the clear-sky covariance matrix is preferable. However, if the retrieval fails to pass the quality control tests, the cloudy covariance matrix is implemented.The retrieval algorithm is applied to scenes from the Eyjafjallajökull eruption in 2010, and the retrieved parameters are compared to ancillary data sources. The ash optical depth gives a root mean square error (RMSE) difference of 0.46 when compared to retrievals from the MODerate-resolution Imaging Spectroradiometer (MODIS) instrument for all pixels and an improved RMSE of 0.2 for low optical depths (AOD < 0.1). Measurements from the Facility for Airborne Atmospheric Measurements (FAAM) and Deutsches Zentrum für Luft-und Raumfahrt e.V. (DLR) flight campaigns are used to verify the retrieved particle effective radius, with the retrieved distribution of sizes for the scene showing excellent consistency. Further, the plume top altitudes are compared to derived cloud-top altitudes from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument and show agreement with RMSE values of less than 1 km.

A New Parameterization of Volcanic Ash Complex Refractive Index Based on NBO/T and SiO2 Content

“…When using the outputs of our new parameterization, we observed good agreement with the measurement retrieval (A83) in terms of the shape and extent of the plumes in all three eruptions. Overall slightly higher mass loadings were observed with the calculated indices, and the change in cost function, the minimization parameter used by Ventress et al (2016), varied over different parts of the plume in each eruption (Figures 11a-11f).…”

“…The calculation was done by deriving coefficients from the linear regression parameterization at each wavelength to "reconstruct" a spectrum for n and k. This calculation is provided in section 5. These were then used to calculate optical parameters that allow the retrieval of ash mass loadings from the Infrared Atmospheric Sounding Interferometer (IASI) satellite data using the optimal estimation algorithm of Ventress et al (2016). IASI is a nadir-viewing Fourier Transform Spectrometer measuring in the infrared (3.62-15.5 μm).…”

Passive Earth Observations of Volcanic Clouds in the Atmosphere

“…Instruments with many channels, e.g., hyperspectral imagers are best suited to this approach as the size distribution requires many values of the effective radius to be properly determined and this necessarily means many measurements are required. This new method and the techniques already developed by [22,28,33,34,37,43] are being improved. Further details of these quantitative techniques can be found in the references and a summary of the status of quantitative remote sounding of volcanic ash can be found in [44].…”

Validation of ash optical depth and layer height retrieved from passive satellite sensors using EARLINET and airborne lidar data: the case of the Eyjafjallajökull eruption

“…Clear-sky radiances from RT-TOV are combined with an ash layer in a method described in detail by Thomas et al (2009a, b). The iterative scheme then provides probable values of AOD, effective radius and plume altitude (Ventress et al, 2016). The fast algorithm is used to flag IASI pixels (assuming an AOD threshold defined by the statistics of the scene) for the presence of volcanic ash, at which point the iterative retrieval is carried out on the pixel.…”