Quantifying Uncertainty of Past Pco2 Determined from Changes in C3 Plant Carbon Isotope Fractionation
Knowledge of the past concentrations of atmospheric CO2 level (pCO2) is critical to understanding climate sensitivity to changing pCO2. Towards this, a new proxy for pCO2 has been developed based on changes in carbon isotope fractionation (δ13C) in C3 land plants. The accuracy of this approach has b...
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ftmontclairstuni:oai:digitalcommons.montclair.edu:earth-environ-studies-facpubs-1494 2023-05-15T16:39:28+02:00 Quantifying Uncertainty of Past Pco2 Determined from Changes in C3 Plant Carbon Isotope Fractionation Cui, Ying Schubert, Brian A. 2016-01-01T08:00:00Z https://digitalcommons.montclair.edu/earth-environ-studies-facpubs/495 unknown Montclair State University Digital Commons https://digitalcommons.montclair.edu/earth-environ-studies-facpubs/495 Department of Earth and Environmental Studies Faculty Scholarship and Creative Works text 2016 ftmontclairstuni 2021-06-27T20:21:01Z Knowledge of the past concentrations of atmospheric CO2 level (pCO2) is critical to understanding climate sensitivity to changing pCO2. Towards this, a new proxy for pCO2 has been developed based on changes in carbon isotope fractionation (δ13C) in C3 land plants. The accuracy of this approach has been validated against ice-core pCO2 records, suggesting the potential to apply this proxy to other geological periods; however, no thorough uncertainty assessment of the proxy has been conducted. Here, we first analyze the uncertainty in the model-curve fit through the experimental data using a bootstrap approach. Then, errors of the five input parameters for the proxy are evaluated using sensitivity analysis; these include the carbon isotope composition of atmospheric CO2 (δ13CCO2) and that of the plant material (δ13Corg) for two time periods, a reference time (t=0) and the time period of interest (t), and the value of pCO2 at time t=0. We then propagated the errors on the reconstructed pCO2 using a Monte Carlo random sampling approach that combined the uncertainties of the curve fitting and the five inputs for a scenario in which the reference time was the Holocene with a target period for the reconstructed pCO2 during the Cenozoic. We find that the error in the reconstructed pCO2( t ) increases with increasing pCO2( t ), yet remains <122% (positive error) and <40% (negative error) for pCO2( t )<1000ppmv. The error assessment suggests that it can be used with confidence for much of the Cenozoic and perhaps the majority of the last 400 million years, which is characterized by pCO2 levels generally less than 1000 ppmv. Towards this, an application of this uncertainty analysis is presented for the Paleogene (52-63Ma) using published data. The resulting pCO2( t ) levels calculated using this method average 470 +288/-147ppmv (1σ, n=75), and overlap with previous pCO2( t ) estimates determined for this time period using stomata, liverwort, and paleosol proxies. The analysis presented here assumes that the paleoenvironment in which the plants grew is unknown and is determined to be the largest source of error in the reconstructed pCO2( t ) levels; errors in pCO2( t ) could be reduced provided independent determination of the paleoenvironmental conditions at the fossil site. Text ice core Montclair State University Digital Commons |
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Knowledge of the past concentrations of atmospheric CO2 level (pCO2) is critical to understanding climate sensitivity to changing pCO2. Towards this, a new proxy for pCO2 has been developed based on changes in carbon isotope fractionation (δ13C) in C3 land plants. The accuracy of this approach has been validated against ice-core pCO2 records, suggesting the potential to apply this proxy to other geological periods; however, no thorough uncertainty assessment of the proxy has been conducted. Here, we first analyze the uncertainty in the model-curve fit through the experimental data using a bootstrap approach. Then, errors of the five input parameters for the proxy are evaluated using sensitivity analysis; these include the carbon isotope composition of atmospheric CO2 (δ13CCO2) and that of the plant material (δ13Corg) for two time periods, a reference time (t=0) and the time period of interest (t), and the value of pCO2 at time t=0. We then propagated the errors on the reconstructed pCO2 using a Monte Carlo random sampling approach that combined the uncertainties of the curve fitting and the five inputs for a scenario in which the reference time was the Holocene with a target period for the reconstructed pCO2 during the Cenozoic. We find that the error in the reconstructed pCO2( t ) increases with increasing pCO2( t ), yet remains <122% (positive error) and <40% (negative error) for pCO2( t )<1000ppmv. The error assessment suggests that it can be used with confidence for much of the Cenozoic and perhaps the majority of the last 400 million years, which is characterized by pCO2 levels generally less than 1000 ppmv. Towards this, an application of this uncertainty analysis is presented for the Paleogene (52-63Ma) using published data. The resulting pCO2( t ) levels calculated using this method average 470 +288/-147ppmv (1σ, n=75), and overlap with previous pCO2( t ) estimates determined for this time period using stomata, liverwort, and paleosol proxies. The analysis presented here assumes that the paleoenvironment in which the plants grew is unknown and is determined to be the largest source of error in the reconstructed pCO2( t ) levels; errors in pCO2( t ) could be reduced provided independent determination of the paleoenvironmental conditions at the fossil site. |
format |
Text |
author |
Cui, Ying Schubert, Brian A. |
spellingShingle |
Cui, Ying Schubert, Brian A. Quantifying Uncertainty of Past Pco2 Determined from Changes in C3 Plant Carbon Isotope Fractionation |
author_facet |
Cui, Ying Schubert, Brian A. |
author_sort |
Cui, Ying |
title |
Quantifying Uncertainty of Past Pco2 Determined from Changes in C3 Plant Carbon Isotope Fractionation |
title_short |
Quantifying Uncertainty of Past Pco2 Determined from Changes in C3 Plant Carbon Isotope Fractionation |
title_full |
Quantifying Uncertainty of Past Pco2 Determined from Changes in C3 Plant Carbon Isotope Fractionation |
title_fullStr |
Quantifying Uncertainty of Past Pco2 Determined from Changes in C3 Plant Carbon Isotope Fractionation |
title_full_unstemmed |
Quantifying Uncertainty of Past Pco2 Determined from Changes in C3 Plant Carbon Isotope Fractionation |
title_sort |
quantifying uncertainty of past pco2 determined from changes in c3 plant carbon isotope fractionation |
publisher |
Montclair State University Digital Commons |
publishDate |
2016 |
url |
https://digitalcommons.montclair.edu/earth-environ-studies-facpubs/495 |
genre |
ice core |
genre_facet |
ice core |
op_source |
Department of Earth and Environmental Studies Faculty Scholarship and Creative Works |
op_relation |
https://digitalcommons.montclair.edu/earth-environ-studies-facpubs/495 |
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1766029824839647232 |