NSF MMIA Isotopes

Sources and Sinks of Anthropogenic CO2: Integrated Assessment Using Biogeochemical Modeling and Inversion of Atmospheric Tracer Transport 

NSF MMIA 1999-2001

A crucial issue in predicting and developing appropriate responses to global environmental change is the need for reliable assessment of future atmospheric concentrations of CO2 and other greenhouse gases. Research to quantify the present, and to predict the future carbon budget, will necessarily involve multiple components of the Earth system, including the atmosphere, the oceans, the terrestrial biosphere, and anthropogenic emissions. A joint research program between the University of California at Santa Barbara (UCSB) and Princeton University will be developed to calculate the sources and sinks of atmospheric CO2 (including anthropogenic emissions) by inversion of atmospheric observations using atmospheric chemical tracer transport models. Unlike previous studies, this inverse modeling will constrain the CO2 budget using the isotopic composition of atmospheric CO2, and will incorporate the seasonal as well as the spatial variability of the natural carbon cycle.

The objective of this study is to provide a quantitative assessment of the current CO2 budget of the atmosphere. This objective will be accomplished by inversion of atmospheric tracer transport of CO2 as constrained by simultaneous observations of the seasonal and spatial variability of the

atmospheric concentration of CO2, δ13C, and δ18O. The inversion calculation will require basis functions for fluxes of each isotopic species of CO2 at the earth’s surface, which will be developed from terrestrial and marine isotope biogeochemistry models developed under this project. The surface flux basis functions will include a temporal component with sufficient resolution in time to include the redistribution of the isotopic tracers by nonlinear covariance between the fluxes and atmospheric transport (rectification). This will involve resolved seasonal cycles for marine basis functions and resolved diurnal cycles for terrestrial basis functions.

Specific tasks that will be undertaken in support of the major objective will include:

  1. The development of a next-generation model of terrestrial biogeochemistry to predict theisotopic composition of CO2 fluxes, including fractionation during photosynthetic carbon assimilation, the isotopic composition of various carbon pools of varying ages at multiple depths in the soil, and the isotopic composition of water in the terrestrial hydrologic cycle. This model will be derived from the Simple Biosphere Model (SiB2) at UCSB.
  2. Development of a model of global air-sea exchange of 13CO2 and CO18O at seasonal as well as annual time scales. This will be done in the context of the Ocean Biogeochemistry Model at Princeton University, by combining remotely sensed seasonal ocean color data with existing physical, chemical, and biological ocean models.
  3. Coupling of the above-mentioned terrestrial and marine flux models to three atmospheric circulation and chemical tracer transport models, to investigate the influence of surface isotope exchanges on the spatial and temporal variability of atmospheric CO2 and its isotopes.
  4. Inverse calculation of sources and sinks of atmospheric CO2 using the results of the three atmospheric models coupled to the terrestrial and marine isotope BGC models, as constrained by atmospheric observations. The results from these inversions will also be used to suggest improvements to the component models.

The proposed research directly addresses both priorities of the MMIA initiative:

  1. The inversion method integrates atmospheric, terrestrial, and marine processes withanthropogenic emissions, providing a direct calculation of the current carbon budget and enhancing our ability to monitor compliance with emissions agreements or international treaties; and
  2. The development and enhancement of the component models of terrestrial and marine biogeochemistry, climate, atmospheric chemical tracer transport, and transport inversion will significantly improve our understanding of the relevant processes that control the rate of increase of atmospheric CO2. The application of observational constraints through the inversion calculation during the development of the biogeochemical component models will enhance the applicability of these models for integrated assessments.

This proposal is to be considered as a linked effort with another proposal by PI/PD Jorge L. Sarmiento and Co-PI Songmiao Fan at Princeton University.