Towards a Harmonized Long‐Term Spaceborne Record of Far‐Red Solar‐Induced Fluorescence

Abstract

Far-red solar-induced chlorophyll fluorescence (SIF) has been retrieved from multiple satellites with nearly continuous global coverage since 1996. Multiple official and research-grade retrievals provide a means for cross validation across sensors and algorithms, but produces substantial variation across products due to differences in instrument characteristics and retrieval algorithm. The lack of a consistent, calibrated SIF data set hampers scientific interpretation of planetary photosynthesis. NASA's Orbiting Carbon Observatory 2 (OCO-2) offers small sampling footprints, high data acquisition, and repeating spatially resolved targets at bioclimatically diverse locations, providing a unique benchmark for spaceborne sensors traceable to ground data. We leverage overlap between the longer running Global Ozone Monitoring Instrument version 2 (GOME-2) SIF time series, and more recent state-of-the-art OCO-2 and TROPOspheric Monitoring Instrument (TROPOMI) data, in a first attempt to reconcile inconsistencies in the long-term record. After screening and correcting for key instrument differences (time of day, wavelength, Sun-sensor geometry, cloud effects, footprint area), we find that Global Ozone Monitoring Instrument version 2 and TROPOspheric Monitoring Instrument perform exceedingly well in capturing spatial, seasonal, and interannual variability across OCO-2 targets. However, Global Ozone Monitoring Instrument version 2 retrieval methods differ by up to a factor of 2 in signal-to-noise and magnitude. Magnitude differences are largely attributed to retrieval window choice, with wider windows producing higher magnitudes. The assumed SIF spectral shape has negligible effect. Substantial research is needed to understand remaining sensitivities to atmospheric absorption and reflectance. We conclude that OCO-2 and TROPOspheric Monitoring Instrument have opened up the possibility to produce a multidecadal SIF record with well-characterized uncertainty and error quantification for overlapping instruments, enabling back-calibration of previous instruments and production of a consistent, research-grade, harmonized time series.

Differences Between OCO‐2 and GOME‐2 SIF Products From a Model‐Data Fusion Perspective

“…The mean bias between GOME‐2‐GF and GOME‐2‐N28/OCO‐2(@740 nm) is 0.18/0.2 W·m −2 ·sr −1 ·μm −1 (averaged value over all PFTs considered and for year 2015) when it is only of 0.04 between GOME‐2‐N28 and OCO‐2(@740 nm). On another hand, the three SIF products show relatively consistent seasonal variations across PFTs (also found by Parazoo et al, ). Likely, the differences in annual mean value and seasonal amplitude originate from multiple sources.…”

“…Apart for BoC3GRA that exhibits lower biases (below 0.1 W·m −2 ·sr −1 ·μm −1 ), the biases for the other PFTs are also significant, varying between 0.1 and 0.2 W·m −2 ·sr −1 ·μm −1 . Given that the two GOME-2 products are derived from the same instrument, we expected them to be rather similar, although this disagreement has already been pointed out Parazoo et al, 2019). The mean ratio between GOME-2-GF and GOME-2-N28 varies typically between 1.5 and 2 depending on the PFT.…”

“…For instance, a scaling factor of about 1.5 is expected between SIF products estimated at 757 nm (GOSAT and OCO-2) and those estimated at 740 nm (GOME-2, SCIAMACHY ) (Joiner et al, 2013;Köhler, Frankenberg, et al, 2018), which is related to the spectral variation of fluorescence emission intensity. Nevertheless, as highlighted by Köhler et al (2015) and recently by Parazoo et al (2019), significant differences in absolute SIF values may arise for products derived from the same set of raw observations (GOME-2) due to the use of different retrieval algorithms.…”

Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing

“…However, since our time series was relatively short and since we did not explicitly account for land use or land cover change, we suggest that the causes and consequences of these shifts in phenoregion area merit further research. Combining long-term NDVI and VOD datasets with a multisensor SIF synthesis [59] or with reconstructed SIF based on other optical sensors [60] could extend the length of the temporal record and allow longer-term change detection [61]. productivity, high-latitude systems, and phenoregion 11 (+153,000 km 2 yr −1 ), which mostly occurred in the subtropics.…”

Improved SIFTER v2 algorithm for long-term GOME-2A satellite retrievals of fluorescence with a correction for instrument degradation

“…This long data record provides good prospects to generate a climate 20 data record of SIF (e.g. Parazoo et al, 2019). The spectral resolution of the GOME-2 instrument (~0.5 nm) allows a technique that matches the observed reflectances close to the wavelength of the far-red fluorescence peak to a model that consists of contributions from surface reflectance, atmospheric transmittance, and fluorescence, where the latter fills in the Fraunhofer lines present in the incoming sunlight.…”