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Diurnal cycles of fossil fuel CO 2 : Comparison of model results with observations at Heidelberg and Schauinsland Felix Vogel 1 including work of: I. Levin 1, U. Karstens 2, C. Rödenbeck 2, M. Krol 3, S. Houweling 3, P. Peylin 4, P. Bousquet 4, C. Aulagnier 4, C. Geels 5, A. Vermeulen 6 1 Institut für Umweltphysik, Universität Heidelberg 2 Max-Planck-Institute for Biogeochemistry, Jena 3 National Institute for Space Research Utrecht 4 Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette 5 National Environmental Research Institute Roskilde 6 Energy research Center of the Netherlands, Petten 5 th CarboEurope-IP Integrated Project Meeting, Poznań 2007
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Introduction Methods - Calculating FFCO 2 from observations - Statistics Comparison - Heidelberg - Schauinsland Summery & Outlook Outline
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Introduction Methods - Calculating FFCO 2 from observations - Statistics Comparison - Heidelberg - Schauinsland Summery & Outlook Outline
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Calculating FFCO 2 from observations weekly excess 14 C weekly excess CO 2 continuous excess CO calculated continuous excess FFCO 2 weekly excess ratio FFCO 2 /CO X = weekly excess CO weekly excess FFCO 2 [Levin et al. 2003 GRL Vol.30/23]
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Mean diurnal cycle - Heidelberg 2002 Central European Time Calculating FFCO 2 from observations
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Introduction Methods - Calculating FFCO 2 from observations - Statistics Comparison - Heidelberg - Schauinsland Summery & Outlook Outline
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Methods - Statistics Wrong phasing of the diurnal cycle significantly decreases the correlation coefficient ! Mean diurnal cycle - Heidelberg summer 2002
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R² < 0.2 R² = 0.63 R² = 1 Find maximal correlation coefficient Determine time shifts in model data Possibly validate diurnal cycle of the emission inventories No measure for variability! (Amplitude x 2) Methods - Statistics Time shift = 2h Time shift = 1hTime shift = 0h
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Methods - Statistics Why diurnal analysis and not pure comparison of the time series? Advantages: Less sensitive to pollution events Reduction of uncertainties Less computational effort Implicit assumptions: Similar emission statistics for each season Diurnal cycle is significant compared to the noise
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Motivation Methods - Calculating FFCO 2 from observations - Statistics Comparison - Heidelberg - Schauinsland Summery & Outlook Outline
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Results - Heidelberg Excess FFCO 2 diurnal cycle – Heidelberg Winter 2002 unshifted
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Results - Heidelberg Excess FFCO 2 diurnal cycle – Heidelberg Winter 2002 0.8 0.7 0.3 0.8 0.3 1.2 FFCO 2, corr = FFCO 2,mod x Rn mod Rn meas Amplitude shifted
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Results - Heidelberg Excess FFCO 2 diurnal cycle – Heidelberg Winter 2002 0.7 1.2 0.6 1.5 Amplitude shifted 0.8 0.7 0.3 0.8 0.3 1.2
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Results - Heidelberg Excess FFCO 2 diurnal cycle – Heidelberg Summer 2002 2.2 1.3 0.7 2.30.7 2.1 0.9 0.7 1.4 0.8 1.8 shifted Amplitude
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Results - Heidelberg Excess FFCO 2 diurnal cycle – Heidelberg summer 2002
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Introduction Methods - Calculating FFCO 2 from observations - Statistics Comparison - Heidelberg - Schauinsland Summery & Outlook Outline
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Results - Schauinsland Excess FFCO 2 diurnal cycle - Schauinsland Winter 2002 unshifted
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Results - Schauinsland Excess FFCO 2 diurnal cycle - Schauinsland Winter 2002 shifted
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Results - Schauinsland Excess FFCO 2 diurnal cycle - Schauinsland Winter 2002
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Motivation Methods - Calculating FFCO 2 from observations - Statistics Results - Schauinsland - Heidelberg Summery & Outlook Outline
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Differences between IER and EDGAR are not significant but IER seems to perform better in Heidelberg Large spread in models Ensemble analysis shows that the significant shifts in the diurnal cycle are not likely due to the inventories Winter better than summer - less variable boundary layer height in winter - vertical mixing in summer is still a problem Summery
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Analysis: - Extensive variability analysis - Running R² on continuous records Methods: - Studies on CO diurnal cycle - Include Δ 14 C bio - Further studies on the radon source - Measurements at more representative sites Outlook
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