High‐Resolution Global Contiguous SIF of OCO‐2

Abstract

The Orbiting Carbon Observatory‐2 (OCO‐2) collects solar‐induced chlorophyll fluorescence (SIF) at high spatial resolution along orbits ( trueSIF¯oco2_orbit), but its discontinuous spatial coverage precludes its full potential for understanding the mechanistic SIF‐photosynthesis relationship. This study developed a spatially contiguous global OCO‐2 SIF product at 0.05° and 16‐day resolutions ( trueSIF¯oco2_005) using machine learning constrained by physiological understandings. This was achieved by stratifying biomes and times for training and predictions, which accounts for varying plant physiological properties in space and time. trueSIF¯oco2_005 accurately preserved the spatiotemporal variations of trueSIF¯oco2_orbit across the globe. Validation of trueSIF¯oco2_005 with Chlorophyll Fluorescence Imaging Spectrometer airborne measurements revealed striking consistency (R2 = 0.72; regression slope = 0.96). Further, without time and biome stratification, (1) trueSIF¯oco2_005 of croplands, deciduous temperate, and needleleaf forests would be underestimated during the peak season, (2) trueSIF¯oco2_005 of needleleaf forests would be overestimated during autumn, and (3) the capability of trueSIF¯oco2_005 to detect drought would be diminished.

The Sensitivity of Satellite Solar‐Induced Chlorophyll Fluorescence to Meteorological Drought

“…With growing interests in satellite SIF, more satellite products at regional to global scale will become available such as TROPOMI SIF product with a global coverage . Future study can also take advantage of satellite SIF products extracted from satellite observation models such as high-resolution global contiguous Orbiting Carbon Observatory-2-based SIF product (Yu et al, 2018). In this study, we compared the original GOME-2 SIF product and downscaled high spatial resolution GOME-2 SIF product by Duveiller and Cescatti (2016); they showed a similar pattern when correlated to the meteorological drought indices ( Figures S7-S9).…”

Phenology Dynamics of Dryland Ecosystems Along the North Australian Tropical Transect Revealed by Satellite Solar‐Induced Chlorophyll Fluorescence

“…Achieving this will require higher spatial and temporal resolution SIF with less noise. Yu et al () reported that OCO2_005 tended to underpredict high values and overpredict low values of SIF although the mean value was well predicted for shrubland. This may have resulted from the lower magnitude of SIF and thus higher impact of SIF retrieval noise in shrublands.…”

“…We utilized both the native OCO‐2 SIF (Sun et al, ) and spatially contiguous SIF products ( OCO2_005 ) at 0.05° and 16‐day resolution gap‐filled from OCO‐2 by Yu et al (), available since September 2014. OCO‐2 SIF was retrieved at both 757 and 771 nm using solar Fraunhofer lines.…”

“…This study primarily relied on OCO2_005 , a global spatially contiguous daily‐average SIF product, for phenological characterization, because the existing native SIF retrievals have either spatial gaps (thus leading to lack of overlap with EC towers, e.g., OCO‐2) or low spatial resolution (thus challenging to be applied to examine the highly dynamic dryland systems that are commonly spatially heterogeneous, e.g., GOME‐2). OCO2_005 is generated by a machine learning method constrained by physiological understandings and could accurately preserve the spatiotemporal variability of the original OCO‐2 SIF across the globe (Yu et al, ). OCO2_005 has been validated with independent airborne measurements from Chlorophyll Fluorescence Imaging Spectrometer.…”

The Ability of Sun-Induced Chlorophyll Fluorescence From OCO-2 and MODIS-EVI to Monitor Spatial Variations of Soybean and Maize Yields in the Midwestern USA

“…Currently, one possible solution for estimating crop yield using SIF data is to downscale satellite SIF data. For example, several studies have proposed methods to produce spatially continuous high spatial resolution SIF datasets using OCO-2 SIF measurements [95][96][97]. It is worthy of investigating the applicability of such downscaled SIF in estimating crop yields.…”