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Abstract: Sun-induced chlorophyll fluorescence (Fs ) is an electromagnetic signal emitted in the 650–800nm spectral window by the chlorophyll-a of green leaves. Previous studies demonstrated the retrieval of Fs on a global scale using high spectral resolution measurements by the Fourier Transform Spectrometer (FTS) on board the greenhouse gases observing satellite (GOSAT). The retrieval of Fs from GOSAT-FTS data is based on the modeling of the in-filling of solar Fraunhofer lines by Fs . The first Fs retrieval methods for GOSAT-FTS measurements were based on physical formulations of the radiative transfer between the atmosphere, the surface and the instrument including the Fs emission. As an alternative, a statistical method was also successfully applied to GOSAT data. This method is based on a singular vector decomposition (SVD) technique producing a basis of spectral functions able to model the contribution of the reflected solar radiation to the top-of-atmosphere measurement in a linear way. The Fs signal is included in the forward model as an extra parameter adding to the reflected solar radiation. Here, we use field spectroscopy measurements to provide further experimental evidence on the retrieval of Fs with statistical approaches in both Fraunhofer lines and atmospheric oxygen and water vapor bands. The statistical retrieval method used with GOSAT-FTS data has been adapted to a set of ground-based spectro-radiometer measurements in the 717–780nm range. Retrieval results in the 745–759nm window, which contains only Fraunhofer lines, support the overall approach of estimating Fs from space measurements in that spectral window. Furthermore, the application of the method to broader fitting windows including both Fraunhofer lines and and (oxygen and water vapor) atmospheric bands atmospheric bands has been proven to be very effective to reduce the retrieval noise and has also shown a good comparison with reference O2A-based retrievals. This allows consideration of statistical methods as a powerful option for Fs retrieval from broad-band space-based measurements in the near-infrared. [Copyright &y& Elsevier]

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. [Copyright &y& Elsevier]