The ocean is estimated to contribute up to ~20% of global fluxes of atmospheric nitrous oxide (N2O), an important greenhouse gas and ozone depletion agent. Marine oxygen minimum zones contribute disproportionately to this flux. To further understand the partition of nitrification and denitrification and their environmental controls on marine N2O fluxes, we report new relationships between oxygen concentration and rates of N2O production from nitrification and denitrification directly measured with 15N tracers in the Eastern Tropical Pacific. Highest N2O production rates occurred near the oxic‐anoxic interface, where there is strong potential for N2O efflux to the atmosphere. The dominant N2O source in oxygen minimum zones was nitrate reduction, the rates of which were 1 to 2 orders of magnitude higher than those of ammonium oxidation. The presence of oxygen significantly inhibited the production of N2O from both nitrification and denitrification. These experimental data provide new constraints to a multicomponent global ocean biogeochemical model, which yielded annual oceanic N2O efflux of 1.7–4.4 Tg‐N (median 2.8 Tg‐N, 1 Tg = 1012 g), with denitrification contributing 20% to the oceanic flux. Thus, denitrification should be viewed as a net N2O production pathway in the marine environment.

The contribution of ocean dimethyl sulfide (DMS) emissions to changes in cloud microphysical properties is quantified seasonally and globally for present day climate conditions using an aerosol-chemistry-climate general circulation model, ECHAM5-HAMMOZ, coupled to a cloud microphysics scheme. We evaluate DMS aerosol-cloud-climate linkages over the southern oceans where anthropogenic influence is minimal. The changes in the number of activated particles, cloud droplet number concentration (CDNC), cloud droplet effective radius, cloud cover and the radiative forcing are examined by analyzing two simulations: a baseline simulation with ocean DMS emissions derived from a prescribed climatology and one in which the ocean DMS emissions are switched off. Our simulations show that the model realistically simulates the seasonality in the number of activated particles and CDNC, peaking during Southern Hemisphere (SH) summer coincident with increased phytoplankton blooms and gradually declining with a minimum in SH winter. In comparison to a simulation with no DMS, the CDNC level over the southern oceans is 128% larger in the baseline simulation averaged over the austral summer months. Our results also show an increased number of smaller sized cloud droplets during this period. We estimate a maximum decrease of up to 15–18% in the droplet radius and a mean increase in cloud cover by around 2.5% over the southern oceans during SH summer in the simulation with ocean DMS compared to when the DMS emissions are switched off. The global annual mean top of the atmosphere DMS aerosol all sky radiative forcing is −2.03 W/m2, whereas, over the southern oceans during SH summer, the mean DMS aerosol radiative forcing reaches −9.32 W/m2

The use of global three-dimensional (3-D) models with satellite observations of CO₂ in inverse modeling studies is an area of growing importance for understanding Earth's carbon cycle. Here we use the GEOS-Chem model (version 8-02-01) CO₂ simulation with multiple modifications in order to assess their impact on CO₂ forward simulations. Modifications include CO2 surface emissions from shipping (~0.19 Pg C/yr), 3-D spatially-distributed emissions from aviation (~0.16 Pg C/yr), and 3-D chemical production of CO₂ (~1.05 Pg C/yr). Although CO₂ chemical production from the oxidation of CO, CH₄ and other carbon gases is recognized as an important contribution to global CO₂, it is typically accounted for by conversion from its precursors at the surface rather than in the free troposphere. We base our model 3-D spatial distribution of CO₂ chemical production on monthly-averaged loss rates of CO (a key precursor and intermediate in the oxidation of organic carbon) and apply an associated surface correction for inventories that have counted emissions of carbon precursor as CO₂. We also explore the benefit of assimilating satellite observations of CO into GEOS-Chem to obtain an observation-based estimate of the CO₂ chemical source. The CO assimilation corrects for an underestimate of atmospheric CO abundances in the model, resulting in increases of as much as 24% in the chemical source during May–June 2006, and increasing the global annual estimate of CO₂ chemical production from 1.05 to 1.18 Pg C. Comparisons of model CO₂ with measurements are carried out in order to investigate the spatial and temporal distributions that result when these new sources are added. Inclusion of CO₂ emissions from shipping and aviation are shown to increase the global CO₂ latitudinal gradient by just over 0.10 ppm (~3%), while the inclusion of CO₂ chemical production (and the surface correction) is shown to decrease the latitudinal gradient by about 0.40 ppm (~10%) with a complex spatial structure generally resulting in decreased CO2 over land and increased CO₂ over the oceans. Since these CO₂ emissions are omitted or misrepresented in most inverse modeling work to date, their implementation in forward simulations should lead to improved inverse modeling estimates of terrestrial biospheric fluxes

Abstract. Inverse modeling of CO 2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO 2 -CO inversion. CO is measured from space with high precision, is strongly correlated with CO 2 , and is more sensitive than CO 2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO 2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO 2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48-vs. 24-h GEOS-5 CTM forecasts of CO 2 and CO columns for the same forecast time). We find strong error correlations (r 2 >0.5) between CO 2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to Correspondence to: H. Wang (hwang@cfa.harvard.edu) variability in the averaging kernels) but preserves the largescale correlation structure. We present a simple inverse modeling application to demonstrate that CO 2 -CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO 2 -CO inversion vs. a CO 2 -only inversion.

Abstract. Understanding carbon dioxide (CO 2 ) biospheric processes is of great importance because the terrestrial exchange drives the seasonal and interannual variability of CO 2 in the atmosphere. Atmospheric inversions based on CO 2 concentration measurements alone can only determine net biosphere fluxes, but not differentiate between photosynthesis (uptake) and respiration (production). Carbonyl sulfide (OCS) could provide an important additional constraint: it is also taken up by plants during photosynthesis but not emitted during respiration, and therefore is a potential means to differentiate between these processes. Solar absorption Fourier Transform InfraRed (FTIR) spectrometry allows for the retrievals of the atmospheric concentrations of both CO 2 and OCS from measured solar absorption spectra. Here, we investigate co-located and quasi-simultaneous FTIR measurements of OCS and CO 2 performed at five selected sites located in the Northern Hemisphere. These measurements are compared to simulations of OCS and CO 2 using a chemical transport model (GEOS-Chem). The coupled biospheric fluxes of OCS and CO 2 from the simple biosphere model (SiB) are used in the study. The CO 2 simulation with SiB fluxes agrees with the measurements well, while the OCS simulation reproduced a weaker drawdown than FTIR measurements at selected sites, and a smaller latitudinal gradient in the Northern Hemisphere during growing season when comparing with HIPPO (HIAPER Pole-to-Pole Observations) data spanning both hemispheres. An offset in the timing of the seasonal cycle minimum between SiB simulation and measurements is also seen. Using OCS as a photosynthesis proxy can help to understand how the biospheric processes are reproduced in models and to further understand the carbon cycle in the real world.