Anu Dudhia

Abstract:

The recent advent of very high spectral resolution measurements by the Fourier Transform Spectrometer (FTS) on board the Greenhouse gases Observing SATellite (GOSAT) platform has made possible the retrieval of sun-induced terrestrial chlorophyll fluorescence (F s) on a global scale. The basis for this retrieval is the modeling of the in-filling of solar Fraunhofer lines by fluorescence. This contribution to the field of space-based carbon cycle science presents an alternative method for the retrieval of F s from the Fraunhofer lines resolved by GOSAT-FTS measurements. The method is based on a linear forward model derived by a singular vector decomposition technique, which enables a fast and robust inversion of top-of-atmosphere radiance spectra. Retrievals are performed in two spectral micro-windows (~2-3nm width) containing several strong Fraunhofer lines. The statistical nature of this approach allows to avoid potential retrieval errors associated with the modeling of the instrument line shape or with a given extraterrestrial solar irradiance data set. The method has been tested on 22 consecutive months of global GOSAT-FTS measurements. The fundamental basis of this F s retrieval approach and the results from the analysis of the global F s data set produced with it are described in this work. Among other findings, the data analysis has shown (i) a very good comparison of F s intensity levels and spatial patterns with the state-of-the-art physically-based F s retrieval approach described in Frankenberg et al. (2011a), (ii) the overall good agreement between F s annual and seasonal patterns and other space-based vegetation parameters, (iii) the need for a biome-dependent scaling from F s to gross primary production, and (iv) the apparent existence of strong directional effects in the F s emission from forest canopies. These results reinforce the confidence in the feasibility of F s retrievals with GOSAT-FTS and open several points for future research in this emerging field. © 2012 Elsevier Inc.

Abstract:

A new optimal estimation algorithm for the retrieval of sulphur dioxide (SO2) has been developed for the Infrared Atmospheric Sounding Interferometer (IASI) using the channels between 1000-1200 and 1300-1410 cm -1. These regions include the two SO2 absorption bands centred at about 8.7 and 7.3 μm (the v1 and v3 bands respectively). The retrieval assumes a Gaussian SO2 profile and returns the SO2 column amount in Dobson units and the altitude of the plume in millibars (mb). Forward modelled spectra (against which the measurements are compared) are based on the Radiative Transfer for TOVS (RTTOV) code. In our implementation RTTOV uses atmospheric profiles from European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological data. The retrieval includes a comprehensive error budget for every pixel derived from an error covariance matrix that is based on the SO2-free climatology of the differences between the IASI and forward modelled spectra. The IASI forward model includes the ability to simulate a cloud or ash layer in the atmosphere. This feature is used to illustrate that: (1) the SO2 retrieval is not affected by underlying cloud but is affected if the SO2 is within or below a cloud layer; (2) it is possible to discern if ash (or other atmospheric constituents not considered in the error covariance matrix) affects the retrieval using quality control based on the fit of the measured spectrum by the forward modelled spectrum. In this work, the algorithm is applied to follow the behaviour of SO2 plumes from the Eyjafjallajökull eruption during April and May 2010. From 14 April to 4 May (during Phase I and II of the eruption) the total amount of SO2 present in the atmosphere, estimated by IASI measurements, is generally below 0.02 Tg. During the last part of the eruption (Phase III) the values are an order of magnitude higher, with a maximum of 0.18 Tg measured on the afternoon of 7 May. © 2012 Author(s).

Abstract:

Fast and reliable methods for the detection of atmospheric trace species are needed for near-real-time applications including volcanic hazard avoidance. One common approach using hyperspectral instruments is to measure the difference in brightness temperature between a small number of target sensitive and background channels to determine the presence of the target species. Although fast and robust, current brightness temperature difference methods do not fully exploit the spectral range and resolution of hyperspectral instruments, and the noise associated with the measurements remains high. In this paper, we describe a way to make full use of the spectral information from hyperspectral sounders allowing the presence of the target species to be determined with much better sensitivity in near-real-time if required. The technique is demonstrated using the MetOp Infrared Atmospheric Sounding Interferometer considering two case studies: (a) the detection of sulphur dioxide from the eruption of the Kasatochi volcano in Alaska in August 2008, and (b) the detection of ammonia emissions related to agriculture over Southern Asia in May 2008. The performance of this method is compared against that of existing brightness temperature difference methods. It is found that the sensitivity of the detection of these trace species is improved by up to an order of magnitude. © Author(s) 2011.