|WOOD, J - University Of Missouri
|GRIFFIS, TIMOTHY - University Of Minnesota
|FRANKENBURG, CHRISTIAN - California Institute Of Technology
|VERMA, MANISH - California Institute Of Technology
|YUEN, KAREN - California Institute Of Technology
Submitted to: Geophysical Research Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/12/2017
Publication Date: 1/16/2017
Citation: Wood, J.D., Griffis, T.J., Baker, J.M., Frankenburg, C., Verma, M., Yuen, K. 2017. Multiscale analyses of solar-induced florescence and gross primary production. Geophysical Research Letters. 44(1):533-541. doi:10.1002/2016GL070775.
Interpretive Summary: A critical uncertainty with respect to global climate change is its impact on photosynthetic production, commonly known as gross primary productivity (GPP). To this point, the primary method for measuring GPP uses ground-based flux towers. They can produce accurate estimates of GPP for an individual field, but they are so sparsely located that it is difficult to extrapolate from them to obtain regional and continental-scale estimates. A newly developed instrument that is mounted on the OCO-2 satellite measures sun-induced fluorescence (SIF) continuously as it orbits the earth, with relatively fine spatial resolution, on the order of a few square kilometers. Theory indicates that SIF should be strongly related to GPP. We tested this by comparing SIF retrievals from the satellite as it repeatedly passed over the US corn belt to ground-based observations of GPP from flux towers. The results showed a strong linear relationship that persisted across instantaneous to monthly time scales. These results will be useful in providing robust estimates of regional and continental-scale GPP and its interannual variability.
Technical Abstract: Remotely sensed solar induced fluorescence (SIF) has shown great promise for probing spatiotemporal variations in terrestrial gross primary production (GPP), the largest component flux of the global carbon cycle. However, scale mismatches between SIF and ground-based GPP have posed challenges towards fully exploiting these data. We used novel SIF observations from NASA’s Orbiting Carbon Observatory (OCO-2) satellite to elucidate GPP-SIF relationships across space and time in the US Corn Belt. Strong linear scaling functions (R2 = 0.79) that were consistent across instantaneous to monthly time scales were obtained for corn ecosystems, and for a heterogeneous landscape based on tall tower observations. Although the slope of the corn function was ~56% higher than for the landscape, SIF was similar for corn (C4) and soybean (C3). Taken together, there is strong observational evidence showing robust linear GPP-SIF scaling that is sensitive to plant physiology but insensitive to the spatial or temporal scale.