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A Comprehensive Global Three-Dimensional Model of Δ18o in Atmospheric CO 2: 2

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A Comprehensive Global Three-Dimensional Model of Δ18o in Atmospheric CO 2: 2 A comprehensive global three-dimensional model of δ18O in atmospheric CO_2: 2. Mapping the atmospheric signal Matthias Cuntz, Philippe Ciais, Georg Hoffmann, Colin E. Allison, Roger J. Francey, Wolfgang Knorr, Pieter P. Tans, James W. C. White, Ingeborg Levin To cite this version: Matthias Cuntz, Philippe Ciais, Georg Hoffmann, Colin E. Allison, Roger J. Francey, et al.. A compre- hensive global three-dimensional model of δ18O in atmospheric CO_2: 2. Mapping the atmospheric signal. Journal of Geophysical Research, American Geophysical Union, 2003, 108 (D17), pp.4528. 10.1029/2002JD003154. hal-02681705 HAL Id: hal-02681705 https://hal.inrae.fr/hal-02681705 Submitted on 18 Jul 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Copyright JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. D17, 4528, doi:10.1029/2002JD003154, 2003 A comprehensive global three-dimensional model of D18O in atmospheric CO2: 2. Mapping the atmospheric signal Matthias Cuntz,1,2 Philippe Ciais,1 Georg Hoffmann,1 Colin E. Allison,3 Roger J. Francey,3 Wolfgang Knorr,4 Pieter P. Tans,5 James W. C. White,6 and Ingeborg Levin2 Received 7 November 2002; revised 1 March 2003; accepted 1 May 2003; published 4 September 2003. 18 [1] We have modeled the distribution of d O in atmospheric CO2 with a new comprehensive global three-dimensional model. We have focused in this study on the seasonal cycle and the meridional gradient in the atmosphere. The model has been 18 compared with a data set of d O-CO2, which merges measurements made by different laboratories, with allowance for recently elucidated calibration biases. The model 18 compares well with the seasonal cycle of CO2, but advances the measured d O-CO2 seasonal cycle by two months. The calculated seasonal amplitude is typically 2/3 of the measured value, but the sensitivity to uncertainties in the input parameter set is such that a range of amplitudes over a factor of 3 is accommodated. Unlike the case for the amplitude, the sensitivity analyses demonstrate that the modeled phase of the seasonal cycle and the north-south gradient are practically unaffected by uncertainty in the parameter set. The north-south gradient comes, on the one hand, from the disequilibrium 18 of the d O-CO2 isofluxes at every grid point and, on the other hand, from rectification 18 gradients, a covariance of the varying d O-CO2 source with the atmospheric transport. The model exhibits a very strong rectification gradient that can lead to a misinterpretation of the measurements compared to the model. We therefore restrict comparison to the latitudinal means of only ocean grid cells with measurements from stations sampling the marine boundary layer. Assimilation and respiration are the determining factors of the 18 seasonal cycle and the north-south gradient of d O-CO2. In a number of sensitivity studies we have explored the range of possible processes affecting the simulated seasonal cycle and hemispheric gradient. None of these processes contributed significantly to improve the model-observation mismatch. The contribution of assimilation and respiration to the total signal does change significantly in the sensitivity studies, but, because of feedback processes, they change in such a way that the overall response of the model is 18 only marginally altered. In particular, prescribing d O-H2O soil values to monthly means of rain does not significantly change the modeled signal, either in the seasonal cycle or in the meridional gradient. This highlights the need to accurately model assimilation and 18 respiration in order to understand d O in atmospheric CO2. INDEX TERMS: 1615 Global Change: Biogeochemical processes (4805); 0315 Atmospheric Composition and Structure: Biosphere/ atmosphere interactions; 3210 Mathematical Geophysics: Modeling; 0322 Atmospheric Composition and Structure: Constituent sources and sinks; 1610 Global Change: Atmosphere (0315, 0325); KEYWORDS: isotope 18 model, OinCO2, isotope feedback mechanism, rectifier effect, global model Citation: Cuntz, M., P. Ciais, G. Hoffmann, C. E. Allison, R. J. Francey, W. Knorr, P. P. Tans, J. W. C. White, and I. Levin, A 18 comprehensive global three-dimensional model of d O in atmospheric CO2: 2. Mapping the atmospheric signal, J. Geophys. Res., 108(D17), 4528, doi:10.1029/2002JD003154, 2003. 1 Laboratoire des Sciences du Climat et de l’Environnement, Unite´ 3Division of Atmospheric Research, Commonwealth Scientific and Mixte de CNRS/CEA, Gif-sur-Yvette, France. Industrial Research Organisation, Melbourne, Victoria, Australia. 2 Institut fu¨r Umweltphysik, Universita¨t Heidelberg, Heidelberg, 4Max-Planck-Institut fu¨r Biogeochemie, Jena, Germany. Germany. 5Climate Monitoring and Diagnostic Laboratory, NOAA, Boulder, Colorado, USA. Copyright 2003 by the American Geophysical Union. 6Institute of Arctic and Alpine Research and Department of Geological 0148-0227/03/2002JD003154 Sciences, University of Colorado, Boulder, Colorado, USA. ACH 2 - 1 18 ACH 2 - 2 CUNTZ ET AL.: MODEL OF d O-CO2,2 1. Introduction new aircraft sites in Eurasia [Levin et al., 2002] plus one discrete sampling record at Schauinsland, Germany (SCH) [2] The emission of human induced CO , mostly in the 2 [Schmidt et al., 2001]. A characteristic of MBL stations is northern hemisphere, causes the atmospheric CO mixing 2 that discrete and (quasi-)continuous measurements are very ratio to increase with time and imprints a strong north-south close in the monthly or annual mean. Non-MBL stations gradient on the CO mixing ratio. Regionally, Anthropo- 2 show quite large deviations between means of continuous genic emissions of CO are typically of the same order of 2 and discrete samples even if one applies filter methods to magnitude as natural net CO fluxes of the biosphere. This 2 catch continental air representing large regions. Figure 1 is different for the d18O isotopic composition of atmospheric shows the distribution of 59 stations that we used here for the CO . The fluxes for the isotopic CO signal are called 2 2 comparison because we have d18O-CO data at these stations isofluxes and are a convolution of CO fluxes and the 2 2 as well. Figure 2 presents seasonal cycles at 45 measurement difference between the isotopic ratio of these fluxes and sites (out of 59 stations in Figure 1) for which we have the atmospheric isotope ratio. The latter difference is the sufficient data to calculate seasonal cycles of d18O-CO apparent discrimination and the isoflux is the CO flux 2 2 (continuous measurements are open and discrete measure- multiplied by the apparent discrimination. This means that ments are closed symbols; the lines are model results and are for the isotopic composition of atmospheric CO ,the 2 explained in the result section). We take the model values at importance of each CO flux can be attenuated or amplified 2 the latitude, longitude and altitude of the stations as plain by the apparent discrimination. Peylin [1999] showed that monthly means. We do not sample the model at different the global d18O-CO isoflux of anthropogenic emissions can 2 times to emulate special sampling strategies at individual be smaller by more than an order of magnitude in certain stations but we shift sometimes the sampled latitude and/or regions, compared to the global net (or total) d18O-CO 2 longitude by one or two grid cells in order to take into isoflux of the biosphere. It is hence mainly the biosphere account different sampling and filtering methods applied to which defines the spatial distribution of d18O-CO . (The 2 the measurements [cf. Ramonet and Monfray, 1996]. One gradient reflects in part the underlying gradient of the number after the station abbreviation represents the number isotopic value of the soil water which is communicated, of model grid cells or vertical layers by which we shifted the with modification, to the atmosphere only in the presence of model. For example MHD1 means that we took one grid cell fluxes with the terrestrial biosphere.) Because of the small further to the west than the actual Mace Head coordinate to seasonal variance of fossil fuel emissions, the seasonal cycle sample our model. The 4 aircraft sites have the designation of d18O-CO is also mostly determined by the biospheric 2 ‘030’ that is the GLOBALVIEW-CO affix for aircraft CO gross fluxes, i.e., assimilation and respiration, which in 2 2 measurements made at 3000 m height, e.g., SYK030 for contrast to fossil fuel combustion show big seasonal varia- aircraft measurements over Syktyvkar, Russia in 3000 m tions. To understand the atmospheric signal of d18O-CO ,it 2 a.s.l. One can see the difference between MBL and non- is therefore essential to understand the biospheric CO 2 MBL stations at, e.g., the two stations Point Barrow (BRW), fluxes and their associated apparent discriminations. On MBL, and Schauinsland (SCH), non-MBL, where continu- the other hand, one can learn about the biospheric CO 2 ous and discrete sampling procedures are installed. Whereas fluxes by examining the atmospheric d18O-CO signal. 2 Point Barrow shows almost no difference between continu- [3] We have developed a comprehensive global three- ous and discrete sampling, Schauinsland shows a peak-to- dimensional (3-D) model of d18OinatmosphericCO, 2 peak amplitude in the discrete record 1/3 of that in the which is described in detail in a companion paper [Cuntz continuous record. The continuous record at Schauinsland is et al., 2003] (hereinafter referred to as part 1).
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