文件列表:

beerling2009co2\errorbar.m (3208, 2010-03-25)
beerling2009co2\errorbargrey.m (3210, 2010-03-25)
beerling2009co2\errorbarxy.m (1956, 2010-03-25)
beerling2009co2\figure_plotter_annot_080409.m (2832, 2010-03-25)
beerling2009co2\ginkgo_data.csv (1007, 2010-03-25)
beerling2009co2\ginkgo_foss_data_22.csv (605, 2010-03-25)
beerling2009co2\obs_inverter_annot_060409.m (3633, 2010-03-25)
beerling2009co2\simple_mono_smoother_annot_030409.m (4191, 2010-03-25)
beerling2009co2 (0, 2010-03-25)

MATLAB Code for CO2 Estimates from Leaf Stomatal Index ----------------------------------------------------------------------- World Data Center for Paleoclimatology, Boulder and NOAA Paleoclimatology Program ----------------------------------------------------------------------- NOTE: PLEASE CITE ORIGINAL REFERENCE WHEN USING THIS DATA!!!!! NAME OF DATA SET: MATLAB Code for CO2 Estimates from Leaf Stomatal Index LAST UPDATE: 1/2010 (Original receipt by WDC Paleo) CONTRIBUTORS: Beerling, D.J., A. Fox, and C.W. Anderson IGBP PAGES/WDCA CONTRIBUTION SERIES NUMBER: 2010-013 WDC PALEO CONTRIBUTION SERIES CITATION: Beerling, D.J., et al. 2010. MATLAB Code for CO2 Estimates from Leaf Stomatal Index. IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series # 2010-013. NOAA/NCDC Paleoclimatology Program, Boulder CO, USA. ORIGINAL REFERENCE: Beerling, D.J., A. Fox, and C.W. Anderson. 2009. Quantitative uncertainty analyses of ancient atmospheric CO2 estimates from fossil leaves. American Journal of Science, Vol. 309, pp. 775787, November 2009. doi:10.2475/09.2009.01 ABSTRACT: The relationship between atmospheric CO2 and ancient climate is of fundamental importance for gauging the climate sensitivity of the Earth system to a changing CO2 regime. One of the most widely adopted paleobiological CO2 proxies for reconstructing Earth's atmospheric CO2 history exploits the inverse relationship between leaf stomatal index, the fraction of leaf epidermal cells that are stomatal structures, and atmospheric CO2. However, fossil leaf-based CO2 reconstructions make a priori assumptions about the form of the empirical relationship between SI and CO2 required for transfer functions and have failed to correctly propagate error terms. These effects can translate into erroneous interpretations that undermine the value of the proxy. Here we report the development and application of a rigorous generalized statistical framework overcoming these limitations that generates probability density functions for each atmospheric CO2 estimate. The utility of our statistical tools is demonstrated by showing how they revise earlier atmospheric CO2 estimates from fossil cuticles of Ginkgo and Metasequoia trees during the early Eocene and middle Miocene warm periods upwards by +150 to 250 ppm to 450 to 700 ppm. The revised CO2 reconstructions therefore help to resolve the paradox of warm Paleogene and Neogene "greenhouse" climates co-existing with near present-day levels of CO2 and support the emerging view from independent paleoclimate studies for a high climate sensitivity of the Earth system. The statistical tools presented are sufficiently versatile to permit their use in other investigations of paleoCO2 estimates from fossil leaves. GEOGRAPHIC REGION: Global PERIOD OF RECORD: N/A FUNDING SOURCES: Leverhulme Trust award, Royal Society-Wolfson Research Merit Award (to DJB) DESCRIPTION: Instructions for using the MATLAB programs simple_mono_smoother, obs_inverter and figure_plotter: AMF 08 04 2009 These programs rely completely upon that which accompanies Ramsey and Silverman (2002) Applied Data Analysis: Methods and case studies, in particular Chapter 6. Their MATLAB code is available from ftp://ego.psych.mcgill.ca/pub/ramsay/FDAfuns/Matlab First download this and install using the installation instructions there. 1. It should then be relatively simple to first run the simple_mono_smoother program, edited to read in your input file, ginkgo_data.csv is included here as an example input file. Check the comments in this program and make alterations as required in your case. The output from this program is a MATLAB file (simple_out_g_030409.mat in this example) which contains the evaluation of the 2000 fitted functions. 2. Second, the obs_inverter program will then take the fossil leaf data (ginkgo_foss_data_22.csv is provided as example) and invert these SI values to give CO2. The output is another MATLAB file, CO2_SI_statistics_060409.mat in this example, which contains the statistics of the output PDFs and the data required to plot them. 3. Finally, the figure_plotter program uses both output .mat files to produce figures like those in the AJS paper. It also contains the code to calculate changes in global temperature (deltaT) on the basis of CO2. The figures are not formatted in anyway for publication, but they display the original data, the fitted curves, example PDFs and plots of CO2 and deltaT against age. For these figures to look their best, you also need the modified errorbar.m, errorbarxy.m and errobargrey.m files which are included.

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