Based on @CaseyBeck's hint, I've done some further reading.
Examples of fluorescence data can be accessed here: https://disc.gsfc.nasa.gov/datasets/OCO2_L2_Lite_SIF_V8r/summary?keywords=OCO-2%20fluorescence
From The Orbiting Carbon Observatory-2 early science investigations of regional carbon dioxide fluxes Science 13 Oct 2017 Vol. 358, Issue 6360, eaam5745 DOI: 10.1126/science.aam5745:
Measuring plant fluorescence from space with OCO-2
Measurements of solar-induced chlorophyll fluorescence (SIF) from satellites offer insight into terrestrial gross primary productivity (GPP), the gross uptake of CO2 through photosynthesis (38). The SIF signal, a small amount of light emitted during photosynthesis, is detected in remote sensing measurements of radiance within solar Fraunhofer lines. Retrieval methods were developed in recent years with the Japanese Greenhouse Gases Observing Satellite (GOSAT) Thermal and Near-Infrared Sensor for Carbon Observation–Fourier Transform Spectrometer (TANSO-FTS), Global Ozone Monitoring Experiment-2 (GOME-2) onboard MetOp-A, and OCO-2 measurements, and its potential for quantifying GPP is being assessed (38–42). Although the SIF signal is quite small—enhancements are typically less than 2% of the reflected sunlight (43)—the high signal-to-noise spectra from OCO-2 enable precise SIF measurements at high spatial resolution (37). Typically, the random component of the retrieval error varies between 0.3 and 0.5 Wm−2 μm−1 sr−1 (15 to 25% of typical peak values of SIF) in the 757-nm fitting window (44), but the errors are substantially reduced by a factor of Embedded Image if single retrievals (from individual soundings) are binned to gridded maps (n is the number of soundings per grid cell) at certain temporal averaging domains. In a companion paper in this issue, Sun et al. (37) describe OCO-2 SIF characteristics in detail and illustrate mechanistic connections between SIF and GPP. They show that when OCO-2 data are compared with GPP from flux tower measurements, well matched in spatial scale, they have correlation coefficients ranging from 0.89 to 0.99, with similar slopes for three different biomes. Earlier studies that used sparse data sets that had to be interpolated over time indicated biome-specific linear relationships.
Fig. 3 The OCO-2 SIF retrieval at 757 nm on 1° by 1° grid for the spring (i.e., the mean of April-May-June for 2015 and 2016).
Reference 44 from the Science paper is Prospects for chlorophyll fluorescence remote sensing from the Orbiting Carbon Observatory-2 Remote Sensing of Environment v. 147, 5 May 2014, pp 1-12 doi.org/10.1016/j.rse.2014.02.007
- The OCO-2 satellite
The OCO-2 instrument is a 3-channel grating spectrometer scheduled to launch into a sun-synchronous orbit (as part of the A-train) in mid 2014. At 3 Hz readout rate, it will record high resolution spectra of the O2 A-band (0.757–0.775 μm, FWHM = 0.042 nm), a weak CO2 band (1.594–1.627 μm, FWHM = 0.076 nm), and a strong CO2 band (2.043–2.087 μm, FWHM = 0.097 nm) with 8 independent along-slit focal plane array readouts, from here on denoted as footprints. The nominal spatial resolution per footprint is 1.3 × 2.25 km2 with all 8 individual footprints covering a 10.3 km full swath width. Fig. 1 shows a real O2-A band example spectrum of the OCO-2 instrument. Similar to the GOSAT, Fraunhofer lines at 758.8 and 770.1 nm can be used for the fluorescence retrieval.
Fig. 1. Exemplary OCO-2 spectrum to be used for chlorophyll fluorescence retrievals. Data were taken during a thermal vacuum test at JPL on April 20, 2012 looking into the sun using a diffuser plate. The primary SIF retrieval fit windows are indicated by transparent green rectangles.
The windows focus careful analysis in the narrow spectral slice near those relatively isolated absorption lines.
Fig. 5 shows the leading singular vectors as determined from the OCO-2 Thermal VACuum (TVAC) dataset under a large range of viewing angles. The first singular vector typically represents the main spectral shape and a simple multiplicative factor of this singular vector explains most of the signal variance. In the ideal case, the following singular vectors represent derivatives of the observed radiance with respect to changes in key physical quantities such as Doppler shift, oxygen column amount or viewing geometry. As apparent in Fig. 5, the short wavelength window, which only encompasses the Fraunhofer lines (devoid of oxygen absorption lines) exhibits singular vectors (SV2 and SV3) mostly representing a spectral shift due to the Doppler shifts. Spectral shifts have a non-linear impact on the observed radiance and the singular vectors most likely represent a linear approximation of this effect using two terms. The 770 nm window includes two stronger oxygen features at 769.8 and 769.9 nm and the varying optical depths during TVAC (due to varying solar zenith angles) are represented in the second singular vector while the third covers most of the spectral shift effect. The advantage of the SVD approach is that these derivatives are directly computed from the measurements themselves without the need for computationally expensive forward model simulations of the true physics of the process. The non-linear effect of the spectral shift is linearized with the SVD, enabling a simple linear least squares approach for the retrieval. In addition, subtle uncharacterized instrumental features are taken into account at the same time.
Fig. 5. First three leading singular vectors (SV) of the OCO-2 TVAC test dataset for the two chlorophyll fluorescence retrievals windows covering the Fraunhofer lines at 758.6 and 758.8 nm (left panel) and 770.1 nm (right panel). The explained variance of each singular value is provided within the respective panels. Only 3 out of the 8 OCO-2 footprints are shown for clarity.
