B52B-02
Validation and attribution of solar induced fluorescence (SIF) from OCO-2: first results
Friday, 18 December 2015: 10:35
2008 (Moscone West)
Manish Verma1, David Schimel1, Christian Frankenberg2, Darren Drewry1, Annmarie Eldering1, Michael R Gunson3, Bradley John Evans4, Jason Beringer5, Lindsay B Hutley6, Caitlin Moore7 and Ian Marang4, (1)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (2)NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (3)Jet Propulsion Laboratory, Pasadena, CA, United States, (4)Terrestrial Ecosystem Research Network Ecosystem Modelling and Scaling Infrastructure, Macquarie University 2109 and University of Sydney 2006, NSW, Australia, Sydney, Australia, (5)University of Western Australia, Crawley, WA, Australia, (6)Charles Darwin University, Casuarina, NT, Australia, (7)Monash University, Melbourne, Australia
Abstract:
Plant physiology exerts a key control on the exchange of carbon and water between terrestrial ecosystems and the atmosphere at different spatial and temporal scales. Therefore, accurate and reliable detection of variations in plant physiological functioning is critical for modeling and monitoring terrestrial carbon and water cycle. Using data from Greenhouse Gases Observing Satellite (GOSAT) and the Global Ozone Monitoring Mission (GOME), recent studies have shown that remotely sensed solar induced fluorescence (SIF) can provide reliable information of plant physiological functioning at a large spatial scale. SIF from GOSAT and GOME, however, have coarse spatial resolution, which restricts their application in understanding spatially heterogeneous variation in gross primary productivity. Launched in 2014, the Orbiting Carbon Observatory-2 (OCO-2) has enabled fine scale retrievals of SIF, a standard product from OCO-2. Because of the fine spatial resolution of OCO-2 SIF, it can be directly compared with eddy covariance measurement. Using field measurements, eddy covariance data, and several different complementary remotely sensed data such as land surface temperature, soil moisture, and vegetation indices we will validate and investigate spatiotemporal variations in SIF from OCO-2. Combined use of eddy covariance and meteorological measurements will help understand the relationship between SIF and photosynthesis. The focus will be on understanding the relationship between SIF and gross primary productivity at diurnal and seasonal time scale, and across different sites and ecosystems.
