Modelling marine emissions and atmospheric distributions of halocarbons and dimethyl sulfide: the influence of prescribed water concentration vs. prescribed emissions

Abstract

Marine-produced short-lived trace gases such as dibromomethane (CH2Br2), bromoform (CHBr3), methyliodide (CH3I) and dimethyl sulfide (DMS) significantly impact tropospheric and stratospheric chemistry. Describing their marine emissions in atmospheric chemistry models as accurately as possible is necessary to quantify their impact on ozone depletion and Earth's radiative budget. So far, marine emissions of trace gases have mainly been prescribed from emission climatologies, thus lacking the interaction between the actual state of the atmosphere and the ocean. Here we present simulations with the chemistry climate model EMAC (ECHAM5/MESSy Atmospheric Chemistry) with online calculation of emissions based on surface water concentrations, in contrast to directly prescribed emissions. Considering the actual state of the model atmosphere results in a concentration gradient consistent with model real-time conditions at the ocean surface and in the atmosphere, which determine the direction and magnitude of the computed flux. This method has a number of conceptual and practical benefits, as the modelled emission can respond consistently to changes in sea surface temperature, surface wind speed, sea ice cover and especially atmospheric mixing ratio. This online calculation could enhance, dampen or even invert the fluxes (i.e. deposition instead of emissions) of very short-lived substances (VSLS). We show that differences between prescribing emissions and prescribing concentrations (−28 % for CH2Br2 to +11 % for CHBr3) result mainly from consideration of the actual, time-varying state of the atmosphere. The absolute magnitude of the differences depends mainly on the surface ocean saturation of each particular gas. Comparison to observations from aircraft, ships and ground stations reveals that computing the air–sea flux interactively leads in most of the cases to more accurate atmospheric mixing ratios in the model compared to the computation from prescribed emissions. Calculating emissions online also enables effective testing of different air–sea transfer velocity (k) parameterizations, which was performed here for eight different parameterizations. The testing of these different k values is of special interest for DMS, as recently published parameterizations derived by direct flux measurements using eddy covariance measurements suggest decreasing k values at high wind speeds or a linear relationship with wind speed. Implementing these parameterizations reduces discrepancies in modelled DMS atmospheric mixing ratios and observations by a factor of 1.5 compared to parameterizations with a quadratic or cubic relationship to wind spee

Brominated VSLS and their influence on ozone under a changing climate

“…Bottom-up scenarios (e.g., Ziska et al, 2013) developed emission climatologies by extrapolating measurements in the surface ocean and marine boundary layer and calculate emissions accordingly. As shown by Lennartz et al (2015), the bottom-up fluxes based on the oceanic water concentrations of Ziska et al (2013) are in good agreement with available atmospheric VSLS observations. Recently, Ziska et al (2017) have investigated the future evolution of the ocean-atmosphere fluxes of VSLS through the 21st century based on Coupled Model Intercomparison Project (CMIP) 5 model output and fixed atmospheric VSLS concentrations.…”

“…The impact of various k w parameterizations on VSLS emission has been previously studied. The differences on the global level are < 15 % (see Table 4 in Lennartz et al, 2015, when comparing Nightingale et al, 2000, and Wanninkhof and McGillis, 1999. For wind speeds exceeding 10 ms −1 the Wanninkhof (1992) k w parameterization diverges slightly stronger towards higher transfer velocities compared to the Nightingale et al (2000) parameterization (cf.…”

“…We will assess the impact of changing physical factors (e.g., SST, SIC, and wind speed) on ocean-atmosphere gas exchange driven by the RCP6.0 scenario. Here we assume constant oceanic concentrations of VSLS over the course of the century (following Ziska et al, 2013;Lennartz et al, 2015). This specific assumption might not hold since the effects of climate change, e.g., increase of ocean temperature, acidification, change of salinity, and nutrient input, on marine organisms and thus the production of CH 2 Br 2 and CHBr 3 is not yet fully understood.…”

“…The simplified chemistry simulations use EMAC version 2.50 with sub- (Pozzer et al, 2006) (with the water-side transfer velocity parameterization k w = 0.222 u 2 + 0.333 u with respect to wind speed according to Nightingale et al, 2000), cloud, cloudopt, convect (with operational ECMWF convection scheme), cvtrans, ddep (Kerkweg et al, 2006a), ptrac (Jöckel et al, 2008), rad, scav (Tost et al, 2006), surface, and tnudge (Kerkweg et al, 2006b). The setup is as in Lennartz et al (2015); Hossaini et al (2016). Chemical reactions are not computed interactively, e.g., via the EMAC submodel mecca (Sander et al, 2011a).…”

Delivery of halogenated very short-lived substances from the west Indian Ocean to the stratosphere during the Asian summer monsoon

“…Additionally, the applied wind-speed-based parameterization for air-sea flux, which represents a reasonable mean of the published parameterizations, is uncertain by more than a factor of two (Lennartz et al, 2015). Both factors may lead to a systematic flux under-or overestimation in our study.…”