Related Experiment Video
Updated: Jun 2, 2026

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
Published on: October 21, 2016
Constraining predictions of the carbon cycle using data
P J Rayner1, E Koffi, M Scholze
1Bat. 701 Cea/Saclay, Orme des Merisiers, Gif sur Yvette 91191, France. prayner@unimelb.edu.au
Abstract:
We use a carbon-cycle data assimilation system to estimate the terrestrial biospheric CO(2) flux until 2090. The terrestrial sink increases rapidly and the increase is stronger in the presence of climate change. Using a linearized model, we calculate the uncertainty in the flux owing to uncertainty in model parameters. The uncertainty is large and is dominated by the impact of soil moisture on heterotrophic respiration. We show that this uncertainty can be greatly reduced by constraining the model parameters with two decades of atmospheric measurements.
More Related Videos
07:32Monitoring Pedogenic Inorganic Carbon Accumulation Due to Weathering of Amended Silicate Minerals in Agricultural Soils.
Published on: June 4, 2021
08:09Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management
Published on: September 12, 2017
Related Concept Videos
Global Climate Change
The Carbon Cycle
The Calvin Benson Cycle
Microbes and the Carbon Cycle
Microbes and Climate Change
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as: