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CMS: Daily GPP over CONUS from TROPOMI SIF, 2018-2021

Submitted by ORNL DAAC Staff on 2022-04-26
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Interannual variation in gross primary productivity (GPP) across conterminous United States. Map of annual mean GPP for 2018 (a) and 2019 (b). Map of the difference in annual mean GPP between 2019 and 2018 (c) wherein red indicates higher GPP in 2019 and blue indicates higher GPP in 2018. The inset in the bottom left corner shows a time series of the average GPP across CONUS for 2018 and 2019.
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Caption

Interannual variation in gross primary productivity (GPP) across conterminous United States. Map of annual mean GPP for 2018 (a) and 2019 (b). Map of the difference in annual mean GPP between 2019 and 2018 (c) wherein red indicates higher GPP in 2019 and blue indicates higher GPP in 2018. The inset in the bottom left corner shows a time series of the average GPP across CONUS for 2018 and 2019.

The ORNL DAAC recently released this dataset from the Carbon Monitoring Systems (CMS) project by Turner, A.J., et al., (2021):

CMS: Daily Gross Primary Productivity over CONUS from TROPOMI SIF, 2018-2021

This dataset includes estimates of gross primary production (GPP) for the conterminous U.S., for 2018-02-15 to 2021-10-15, based on measurements of solar-induced chlorophyll fluorescence from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5P satellite platform. GPP was estimated from rates of photosynthesis inferred from SIF using a linear model and ecosystem scaling factors from 102 AmeriFlux sites. Knowledge of the spatiotemporal patterns of GPP is necessary for understanding regional and global carbon budgets. Broad-scale estimates of GPP have typically relied upon carbon cycle models linking spatial patterns of vegetation with remotely sensed environmental data. SIF provides a means to directly estimate photosynthetic activity, and therefore, GPP. Recent deployments of satellite platforms that measure SIF provide near-real-time measurements and represent a breakthrough in measuring GPP on a global scale. Regular SIF measurements can detect spatially explicit ecosystem-level responses to climate events such as drought and flooding. 

The NASA CMS program is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System uses NASA satellite observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS data products are designed to inform near-term policy development and planning.

Additional data from Carbon Monitoring System (CMS) project and other relevant links can be found on the ORNL DAAC's CMS Project Page.

Citation: Turner, A.J., P. Koehler, T. Magney, C. Frankenberg, I. Fung, and R.C. Cohen. 2021. CMS: Daily Gross Primary Productivity over CONUS from TROPOMI SIF, 2018-2021. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1875

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