Global monitoring of terrestrial chlorophyll fluorescence from moderate spectral resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2

Abstract

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. In addition, fluorescence can contaminate photon path estimates from the O₂ A-band that has become an integral part of missions to accurately measure greenhouse gas concentrations. Global mapping of far-red (~ 755–770 nm) terrestrial vegetation solar-induced fluorescence from space has been accomplished using the high spectral resolution (ν/Δ ν > 35 000) interferometer on the Japanese Greenhouse gases Observing SATellite (GOSAT). These satellite retrievals of fluorescence rely solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data to disentangle the spectral signatures of three basic components in and surrounding the O₂ A-band: atmospheric absorption, surface reflectance, and fluorescence radiance. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate spectral resolution measurements with a relatively high signal-to-noise ratio within and outside the O₂ A-band can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with GOSAT. GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. It should be noted that both GOME-2 and GOSAT were designed to make atmospheric trace gas measurements and were not optimized for fluorescence measurements. Our approach can be applied to other existing and future space-based instruments that provide moderate spectral resolution observations in the near-infrared region

Prospects for chlorophyll fluorescence remote sensing from the Orbiting Carbon Observatory-2

“…The sun-synchronous orbit with 1:30 p.m. local overpass time will enable mid day SIF measurements similar to the GOSAT but with higher fidelity and much reduced standard error. The very narrow swath of OCO-2 won't allow for truly global retrievals as does GOME-2 (Joiner et al, 2013) but we found that this sampling bias will be small when averaged over regional (e.g. 1 × 1°) scales, thus only hampering local studies either not covered by the OCO-2 swaths or with gradients of interest not properly aligned with the flight track.…”

“…The first real retrievals were performed using high-resolution spectra of the oxygen A-band region from the Tanso Fourier Transform Spectrometer onboard of the Japanese GOSAT satellite (Hamazaki, Kaneko, Kuze, & Kondo, 2005;Kuze, Suto, Nakajima, & Hamazaki, 2009). Later, Joiner et al (2012) showed that even moderate spectral resolution can be used to infer SIF using either a very broad Fraunhofer line at 866 nm (using SCIAMACHY) or applying a larger spectral range from 715 to 780 nm using GOME-2 (Joiner et al, 2013). In general, there is a trade-off between spectral resolution and spatio-temporal sampling.…”

Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production

“…We developed a method to calculate a weighted ensemble of GPP from multiple models that best approximate spatial and temporal variations in SIF derived from GOME-2 instrument1424. To improve global estimates of GPP as compared with a straight average of an ensemble of models, we provided a weighted ensemble estimate using three data-driven models (VPM18, MTE25, and MOD1726) and eleven process-oriented models from the TRENDY-v4 project27 (CLM4.5, ISAM, JSBACH, JULES, LPJ, LPJ-GUESS, LPX, OCN, ORCHIDEE, VEGAS, and VISIT, see Materials and Methods).…”

Retrieval of aerosol parameters from the oxygen A band in the presence of chlorophyll fluorescence

“…If this is not the case, external information on fluorescence emission is needed to minimize its impact on aerosol retrieval. Note that if the objective of retrieval is to estimate fluorescence emissions, it is much more efficient to use filling-in of Fraunhofer lines outside atmospheric absorption bands, because complicated radiative transfer calculations are not needed (Frankenberg et al, 2011a;Joiner et al, 2011Joiner et al, , 2012bJoiner et al, , 2013Guanter et al, 2012).…”