Anu Dudhia

Abstract:

Abstract The remote sensing of volcanic ash plumes from space can provide a warning of an aviation hazard and knowledge on eruption processes and radiative effects. In this paper new algorithms are presented to provide volcanic plume properties from measurements by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the Advanced Along Track Scanning Radiometer (AATSR) and the Spinning Enhanced Visible and Infrared Imager (SEVIRI). A challenge of remote sensing is to provide near-real-time methods to identify, and so warn of, the presence of volcanic ash. To achieve this, a singular vector decomposition method has been developed for the MIPAS instrument on board the Environmental Satellite. This method was applied to observations of the ash clouds from the eruptions of Nabro and the Puyehue–Cordón Caulle in 2011 and led to a sensitive volcanic signal flag which was capable of tracking changes in the volcanic signal spectra as the plume evolved. A second challenge for remote sensing is to identify the ash plume height. This is a critical parameter for the initialization of algorithms that numerically model the evolution and transport of a volcanic plume. As MIPAS is a limb sounder, the identification of ash also provides an estimate of height provided the plume is above about 6 km. This is complemented by a new algorithm, Stereo Ash Plume Height Retrieval Algorithm, that identifies plume height using the parallax between images provided by Along Track Scanning Radiometer-type instruments. The algorithm was tested on an image taken at 14:01 GMT on 6 June 2011 of the Puyehue–Cordón Caulle eruption plume and gave a height of 11.9±1.4 km, which agreed with the value derived from the location of the plume shadow (12.7±1.8 km). This plume height was similar to the height observed by MIPAS (12 ± 1.5 km) at 02:56 GMT on 6 June. The quantitative use of satellite imagery and the full exploitation of high-resolution spectral measurements of ash depends upon knowing the optical properties of the observed ash. Laboratory measurements of ash from the 1993 eruption of Mt Aso, Japan have been used to determine the refractive indices from 1 to 20 µm. These preliminary measurements have spectral features similar to ash values that have been used to date, albeit with slightly different positions and strengths of the absorption bands. The refractive indices have been used to retrieve ash properties (plume height, optical depth and ash effective radius) from AATSR and SEVIRI instruments using two versions of Oxford-RAL Retrieval of Aerosol and Cloud (ORAC) algorithm. For AATSR a new ash cloud type was used in ORAC for the analysis of the plume from the 2011 Eyjafjallajökull eruption. For the first c . 500 km of the plume ORAC gave values for plume height of 2.5–6.5 km, optical depth 1–2.5 and effective radius 3–7 µm, which are in agreement with other observations. A weakness of the algorithm occurs when underlying cloud invalidates the assumption of a single cloud layer. This is rectified in a modified version of ORAC applied to SEVIRI measurements. In this case an extra model of a cloud underlying the ash plume was included in the range of applied models. In cases where the plume overlay cloud, this new model worked well, showing good agreement with correlative Cloud–Aerosol Lidar with Orthogonal Polarization observations.

Abstract:

High-resolution infrared sounders, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the current MetOp series of satellites, produce several orders of magnitude more data per location than previous instruments used in operational retrieval and data assimilation schemes. Using the full spectrum (8641 channels for IASI) is impractical and a common approach is to identify a subset of channels which, ideally, conveys the most information on the target parameters (e.g. atmospheric temperature and water vapour) but using a relatively small number of measurements. Representing the problem as a one-dimensional retrieval, optimal estimation provides an efficient framework for channel selection, and is the basis of several current schemes. However, while modelling the propagation of random (spectrally uncorrelated) errors into the retrieval, the standard algorithm does not allow for spectrally correlated errors, particularly arising from the radiative transfer modelling, which are often the limiting factor in retrieval accuracy. Such errors are either ignored or represented only approximately during the selection. This article describes a modification to the standard algorithm which allows spectrally correlated errors to be properly modelled, and quantified, within the channel selection process. Comparing the results with an established selection scheme shows that significant improvements can be obtained when retrieving temperature regarding water vapour as an error term, but are less dramatic when both are retrieved together. The concept of 'total' information available from an IASI spectrum is also re-assessed. © 2013 Royal Meteorological Society.

Abstract:

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is a mid-infrared emission spectrometer which is part of the core payload of the Envisat satellite, launched by ESA in March 2002. It provides unique observations of the atmospheric spectral radiances in the 4.15 - 14.6 μm spectral interval with innovative limb scanning capabilities for the three dimensional observation of the atmospheric composition and processes. The species, the processes and events that have been studied with this instrument in its 10 years of operation are briefly reviewed. © 2012 IEEE.