Current Global Climate Models Research Articles

Locally narrow droplet size distributions are ubiquitous in stratocumulus clouds.

Marine stratocumulus clouds are the "global reflectors," sharply contrasting with the underlying dark ocean surface and exerting a net cooling on Earth's climate. The magnitude of this cooling remains uncertain in part owing to the averaged representation of microphysical processes, such as the droplet-to-drizzle transition in global climate models (GCMs). Current GCMs parameterize cloud droplet size distributions as broad, cloud-averaged gammas. Using digital holographic measurements of discrete stratocumulus cloud volumes, we found cloud droplet size distributions to be narrower at the centimeter scale, never resembling the cloud average. These local distributions tended to form pockets of similar-looking cloud regions, each characterized by a size distribution shape that is diluted to varying degrees. These observations open the way for new modeling representations of microphysical processes.

Local forcing mechanisms challenge parameterizations of ocean thermal forcing for Greenland tidewater glaciers

Abstract. Frontal ablation has caused 32 %–66 % of Greenland Ice Sheet mass loss since 1972, and despite its importance in driving terminus change, ocean thermal forcing remains crudely incorporated into large-scale ice sheet models. In Greenland, local fjord-scale processes modify the magnitude of thermal forcing at the ice–ocean boundary but are too small scale to be resolved in current global climate models. For example, simulations used in the Ice Sheet Intercomparison Project for CMIP6 (ISMIP6) to predict future ice sheet change rely on the extrapolation of regional ocean water properties into fjords to drive terminus ablation. However, the accuracy of this approach has not previously been tested due to the scarcity of observations in Greenland fjords, as well as the inability of fjord-scale models to realistically incorporate icebergs. By employing the recently developed IceBerg package within the Massachusetts Institute of Technology general circulation model (MITgcm), we here evaluate the ability of ocean thermal forcing parameterizations to predict thermal forcing at tidewater glacier termini. This is accomplished through sensitivity experiments using a set of idealized Greenland fjords, each forced with equivalent ocean boundary conditions but with varying tidal amplitudes, subglacial discharge, iceberg coverage, and bathymetry. Our results indicate that the bathymetric obstruction of external water is the primary control on near-glacier thermal forcing, followed by iceberg submarine melting. Despite identical ocean boundary conditions, we find that the simulated fjord processes can modify grounding line thermal forcing by as much as 3 °C, the magnitude of which is largely controlled by the relative depth of bathymetric sills to the Polar Water–Atlantic Water thermocline. However, using a common adjustment for fjord bathymetry we can still predict grounding line thermal forcing within 0.2 °C in our simulations. Finally, we introduce new parameterizations that additionally account for iceberg-driven cooling that can accurately predict interior fjord thermal forcing profiles both in iceberg-laden simulations and in observations from Kangiata Sullua (Ilulissat Icefjord).

Parameterized orographic gravity wave drag and dynamical effects in CMIP6 models

Orographic gravity waves (OGWs) are an important mechanism for coupling of the free atmosphere with the surface, mediating the momentum and energy transport and influencing the dynamics and circulation especially in the middle-atmosphere. Current global climate models are not able to resolve a large part of the OGW spectrum and hence, OGW effects have to be parameterized in the models. Typically, the only parameterized effect is the OGW induced drag. Despite producing the same quantity as an output and relying on similar assumptions (e.g. instantaneous vertical propagation), the individual OGW parameterization schemes differ in many aspects such as handling of the orography, the inclusion of non-linear effects near the surface and the tuning of the emergent free parameters. In this study, we have reviewed 7 different parameterizations, which are used in 9 different CMIP6 models. We report pronounced differences in the vertical distribution and magnitude of the parameterized OGW drag between the models and study to what extent the inter-model differences can be traced back to the difference in the type and tuning of the schemes. Finally, we demonstrate how the OGW drag differences project to the intermodel differences in the stratospheric dynamics. The study can pave the way for a more systematic research of the OGW parameterizations in the future, with an ultimate goal of lowering the amount of uncertainty of the future climate projections connected with the parameterized effects of unresolved orography.

Microbially mediated climate feedbacks from wetland ecosystems.

Wetlands are crucial nodes in the carbon cycle, emitting approximately 20% of global CH4 while also sequestering 20%-30% of all soil carbon. Both greenhouse gas fluxes and carbon storage are driven by microbial communities in wetland soils. However, these key players are often overlooked or overly simplified in current global climate models. Here, we first integrate microbial metabolisms with biological, chemical, and physical processes occurring at scales from individual microbial cells to ecosystems. This conceptual scale-bridging framework guides the development of feedback loops describing how wetland-specific climate impacts (i.e., sea level rise in estuarine wetlands, droughts and floods in inland wetlands) will affect future climate trajectories. These feedback loops highlight knowledge gaps that need to be addressed to develop predictive models of future climates capturing microbial contributions. We propose a roadmap connecting environmental scientific disciplines to address these knowledge gaps and improve the representation of microbial processes in climate models. Together, this paves the way to understand how microbially mediated climate feedbacks from wetlands will impact future climate change.

A new process-based and scale-aware desert dust emission scheme for global climate models – Part I: Description and evaluation against inverse modeling emissions

Abstract. Desert dust accounts for most of the atmosphere's aerosol burden by mass and produces numerous important impacts on the Earth system. However, current global climate models (GCMs) and land-surface models (LSMs) struggle to accurately represent key dust emission processes, in part because of inadequate representations of soil particle sizes that affect the dust emission threshold, surface roughness elements that absorb wind momentum, and boundary-layer characteristics that control wind fluctuations. Furthermore, because dust emission is driven by small-scale (∼ 1 km or smaller) processes, simulating the global cycle of desert dust in GCMs with coarse horizontal resolutions (∼ 100 km) presents a fundamental challenge. This representation problem is exacerbated by dust emission fluxes scaling nonlinearly with wind speed above a threshold wind speed that is sensitive to land-surface characteristics. Here, we address these fundamental problems underlying the simulation of dust emissions in GCMs and LSMs by developing improved descriptions of (1) the effect of soil texture on the dust emission threshold, (2) the effects of nonerodible roughness elements (both rocks and green vegetation) on the surface wind stress, and (3) the effects of boundary-layer turbulence on driving intermittent dust emissions. We then use the resulting revised dust emission parameterization to simulate global dust emissions in a standalone model forced by reanalysis meteorology and land-surface fields. We further propose (4) a simple methodology to rescale lower-resolution dust emission simulations to match the spatial variability of higher-resolution emission simulations in GCMs. The resulting dust emission simulation shows substantially improved agreement against regional dust emissions observationally constrained by inverse modeling. We thus find that our revised dust emission parameterization can substantially improve dust emission simulations in GCMs and LSMs.

Dynamic and thermodynamic processes related to precipitation diurnal cycle simulated by GRIST

Most state-of-the-art general circulation models cannot well simulate the diurnal cycle of precipitation, especially the nocturnal rainfall peak over land. This study assesses the diurnal cycle of precipitation simulated using the Global-to-Regional Integrated forecast SysTem (GRIST) in its numerical weather prediction (NWP) configuration at resolutions typical of current global climate models. In the refinement region, the variable-resolution model well distinguishes the distinct features of diurnal cycle. No apparent artificial features are observed in the transition zone of the variable-resolution mesh. The model also exhibits a similar diurnal cycle pattern to the observation in the coarse-resolution region. We further investigate the model behaviors of dynamics–physics interaction by analyzing hourly dynamical and thermodynamical diagnostics. Composite analysis based on rainfall peak time is applied to examine the model capability in distinguishing different precipitation processes of daytime and nighttime peaks. Over East Asia, the model well reproduces both the nocturnal-to-early-morning and the afternoon rainfall peaks. The model simulates the dominant contribution of large-scale upward moisture advection to the formation of stratiform-like rainfall peaks, and produces daytime surface-heating induced rainfall. Refinement of the resolution substantially increases the composited nighttime precipitation intensity but has little impact on the composite percentage. The model captures the realistic dynamical and thermodynamical conditions for the occurrence of nocturnal rainfall. These results demonstrate that the variable-resolution model is able to reproduce the diurnal cycle of climatological summer rainfall through realistic precipitation processes.

Evaluation and attribution of historical surface air temperature changes over China simulated by coupled and uncoupled models

The increase in the average surface air temperature anomaly (SATA) over China is higher than the global average. However, the accurate simulation and attribution of regional SATA evolution remain challenging for current global climate models. This study simulates historical SATA variations over China using the coupled (FGOALS-g3) and uncoupled (atmospheric component, GAMIL3) models and examines their possible causes. Results show that both models reproduce the historical SATA variation with higher correlation coefficients (0.735 and 0.782) than many global climate models (0.25–0.56), although they overestimate or underestimate the changes of SATA to some extent in different periods. The results show that the cooling trend during 1941–1970 is well simulated with the coupled model while poorly presented with the uncoupled model; the coupled simulations particularly produce stronger long-term trends than the uncoupled ones during 1870–2014 considering full interaction among the atmosphere, ocean, and sea ice. In contrast, the uncoupled simulations reproduce better decadal and multi-decadal SATA variations owing to the constraints of the observed sea surface temperature (SST), such as the Atlantic multidecadal oscillation, and sea ice cover. Using Detection and Attribution Model Intercomparison Project (DAMIP) experiments, we found that the warming in the early 20th century and the recent 50 years is mainly driven by natural forcings and greenhouse gases (GHGs), whereas the cooling during 1941–1970 is caused by natural factors and anthropogenic aerosols. The cooling effects of anthropogenic aerosols are mainly attributed from the indirect SST-mediated responses through the atmosphere-ocean interactions in the coupled model.

Climate impacts of parameterizing subgrid variation and partitioning of land surface heat fluxes to the atmosphere with the NCAR CESM1.2

Abstract. All current global climate models (GCMs) utilize only grid-averaged surface heat fluxes to drive the atmosphere, and thus their subgrid horizontal variations and partitioning are absent. This can result in many simulation biases. To address this shortcoming, a novel parameterization scheme considering the subgrid variations of the sensible and latent heat fluxes to the atmosphere and the associated partitioning is developed and implemented into the National Center for Atmospheric Research (NCAR) Climate Earth System Model 1.2 (CESM1.2). Compared to the default model, in addition to the improved boreal summer precipitation simulation over eastern China and the coastal areas of the Bay of Bengal, the long-standing overestimations of precipitation on the southern and eastern margins of the Tibetan Plateau (TP) in most GCMs are alleviated. The improved precipitation simulation on the southern margin of the TP is from suppressed large-scale precipitation, while that on the eastern edge of the TP is due to decreased convective precipitation. Moisture advection is blocked toward the southern edge of the TP, and the anomaly of anticyclonic moisture transport over northern China extends westward, suppressing local convection on the eastern edge of the TP. The altered large-scale circulation in the lower atmosphere resulting from anomalous heating and cooling in the planetary boundary layer is responsible for the change in moisture transport. The performance of other key variables (e.g., surface energy fluxes, clouds and 2 m temperature) is also evaluated thoroughly using the default CESM1.2, the new scheme and the scheme stochastically allocating the subgrid surface heat fluxes to the atmosphere (i.e., without subgrid partitioning included). This study highlights the importance of subgrid surface energy variations and partitioning to the atmosphere in simulating the hydrological and energy cycles in GCMs.

Impact of grid spacing, convective parameterization and cloud microphysics in ICON simulations of a warm conveyor belt

Abstract. Warm conveyor belts are important features of extratropical cyclones and are characterized by active diabatic processes. Previous studies reported that simulations of extratropical cyclones can be strongly impacted by the horizontal grid spacing. Here, we study to what extent and in which manner simulations of warm conveyor belts are impacted by the grid spacing. To this end, we investigate the warm conveyor belt (WCB) of the North Atlantic cyclone Vladiana that occurred around 23 September 2016 and was observed as part of the North Atlantic Waveguide and Downstream Impact Experiment. We analyze a total of 18 limited-area simulations with the ICOsahedral Nonhydrostatic (ICON) model run over the North Atlantic that cover grid spacings from 80 to 2.5 km, including those of current coarse-resolution global climate models with parameterized convection, as well as those of future storm-resolving climate models with explicit convection. The simulations also test the sensitivity with respect to the representation of convection and cloud microphysics. As the grid spacing is decreased, the number of WCB trajectories increases systematically, WCB trajectories ascend faster and higher, and a new class of anticyclonic trajectories emerges that is absent at 80 km. We also diagnose the impact of grid spacing on the ascent velocity and vorticity of WCB air parcels and the diabatic heating that these parcels experience. Ascent velocity increases at all pressure levels by a factor of 3 between the 80 and 2.5 km simulations, and vorticity increases by a factor of 2 in the lower and middle troposphere. We find a corresponding increase in diabatic heating as the grid spacing is decreased, arising mainly from cloud-associated phase changes in water. The treatment of convection has a much stronger impact than the treatment of cloud microphysics. When convection is resolved for grid spacings of 10, 5 and 2.5 km, the above changes to the WCB are amplified but become largely independent of the grid spacing. We find no clear connection across the different grid spacings between the strength of diabatic heating within the WCB and the deepening of cyclone Vladiana measured by its central pressure. An analysis of the pressure tendency equation shows that this is because diabatic heating plays a minor role in the deepening of Vladiana, which is dominated by temperature advection.

Improved Dust Representation and Impacts on Dust Transport and Radiative Effect in CAM5

AbstractDust transport and spatial distribution are poorly represented in current global climate models (GCMs) including the Community Atmosphere Model version 5 (CAM5). Particularly, models lack explicit representation of super‐coarse dust, which may have important implications for dust radiative forcing and impacts on biogeochemistry. A nine‐mode version of the modal aerosol model (MAM9) has been developed to address these issues. In this new aerosol scheme, four dust modes have been designed to treat dust particles of sizes up to 20 μm. The MAM9‐simulated results are compared with those from the default four‐mode version of MAM (MAM4) and also with the in situ surface measurements of dust concentration and deposition flux, satellite‐retrieved dust extinction profile, and in situ vertical measurements of dust concentrations from the NASA Atmosphere Tomography Mission (ATom). Overall, MAM9 improves the dust representation in remote regions while maintaining reasonably good results near the dust source regions. In addition, MAM9 reduces the fine dust burden and increases the coarse dust burden globally. The increased coarse dust burden has slightly increased the dust direct radiative effect by 0.01 W m−2 while it enhanced dust indirect radiative effect by 0.36 W m−2, globally.

Improved Trend-Aware Postprocessing of GCM Seasonal Precipitation Forecasts

Abstract Climate trends have been observed over the recent decades in many parts of the world, but current global climate models (GCMs) for seasonal climate forecasting often fail to capture these trends. As a result, model forecasts may be biased above or below the trendline. In our previous research, we developed a trend-aware forecast postprocessing method to overcome this problem. The method was demonstrated to be effective for embedding observed trends into seasonal temperature forecasts. In this study, we further develop the method for postprocessing GCM seasonal precipitation forecasts. We introduce new formulation and evaluation features to cater for special characteristics of precipitation amounts, such as having a zero lower bound and highly positive skewness. We apply the improved method to calibrate ECMWF SEAS5 forecasts of seasonal precipitation for Australia. Our evaluation shows that the calibrated forecasts reproduce observed trends over the hindcast period of 36 years. In some regions where observed trends are statistically significant, forecast skill is greatly improved by embedding trends into the forecasts. In most regions, the calibrated forecasts outperform the raw forecasts in terms of bias, skill, and reliability. Wider applications of the new trend-aware postprocessing method are expected to boost user confidence in seasonal precipitation forecasts.

The physiological acclimation and growth response of Populus trichocarpa to warming.

Plant metabolic acclimation to thermal stress remains underrepresented in current global climate models. Gaps exist in our understanding of how metabolic processes (i.e., photosynthesis, respiration) acclimate over time and how aboveground versus belowground acclimation differs. We measured the thermal acclimation of Populus trichocarpa, comparing aboveground versus belowground physiology over time. Ninety genetically identical ramets were propagated in mesocosms that separated root and microbial components. After establishment at 25°C for 6 weeks, 60 clones were warmed +4 or +8°C and monitored for 10 weeks, measuring photosynthesis (A), leaf respiration (R), soil respiration (Rs ), root plus soil respiration (Rs+r ), and root respiration (Rr ). We observed thermal acclimation in both A and R, with rates initially increasing, then declining as the thermal photosynthetic optimum (Topt ) and the temperature-sensitivity (Q10 ) of respiration adjusted to warmer conditions. Photosynthetic acclimation was constructive, based on an increase in both Topt and peak A. Belowground, Rs+r decreased linearly with warming, while Rs rates declined abruptly, then remained constant with additional warming. Plant biomass was greatest at +4°C, with 30% allocated belowground. Rates of mass-based Rr were similar among treatments; however, root nitrogen declined at +8°C leading to less mass nitrogen-based Rr in that treatment. The Q10 -temperature relationship of Rr was affected by warming, leading to differing values among treatments. Aboveground acclimation exceeded belowground acclimation, and plant nitrogen-use mediated the acclimatory response. Results suggest that moderate climate warming (+4°C) may lead to acclimation and increased plant biomass production but increases in production could be limited with severe warming (+8°C).

Understanding the Roles of Convective Trigger Functions in the Diurnal Cycle of Precipitation in the NCAR CAM5

AbstractThe wrong diurnal cycle of precipitation is a common weakness of current global climate models (GCMs). To improve the simulation of the diurnal cycle of precipitation and understand what physical processes control it, we test a convective trigger function described in Xie et al. with additional optimizations in the NCAR Community Atmosphere Model version 5 (CAM5). The revised trigger function consists of three modifications: 1) replacing the convective available potential energy (CAPE) trigger with a dynamic CAPE (dCAPE) trigger, 2) allowing convection to originate above the top of planetary boundary layer [i.e., the unrestricted air parcel launch level (ULL)], and 3) optimizing the entrainment rate and threshold value of the dynamic CAPE generation rate for convection onset based on observations. Results from 1° resolution simulations show that the revised trigger can alleviate the long-standing GCM problem of too early maximum precipitation during the day and missing the nocturnal precipitation peak that is observed in many regions, including the U.S. southern Great Plains (SGP). The revised trigger also improves the simulation of the propagation of precipitation systems downstream of the Rockies and the Amazon region. A further composite analysis over the SGP unravels the mechanisms through which the revised trigger affects convection. Additional sensitivity tests show that both the peak time and the amplitude of the diurnal cycle of precipitation are sensitive to the entrainment rate and dCAPE threshold values.

Vertical dependence of horizontal variation of cloud microphysics: observations from the ACE-ENA field campaign and implications for warm-rain simulation in climate models

Abstract. In the current global climate models (GCMs), the nonlinearity effect of subgrid cloud variations on the parameterization of warm-rain process, e.g., the autoconversion rate, is often treated by multiplying the resolved-scale warm-rain process rates by a so-called enhancement factor (EF). In this study, we investigate the subgrid-scale horizontal variations and covariation of cloud water content (qc) and cloud droplet number concentration (Nc) in marine boundary layer (MBL) clouds based on the in situ measurements from a recent field campaign and study the implications for the autoconversion rate EF in GCMs. Based on a few carefully selected cases from the field campaign, we found that in contrast to the enhancing effect of qc and Nc variations that tends to make EF > 1, the strong positive correlation between qc and Nc results in a suppressing effect that tends to make EF < 1. This effect is especially strong at cloud top, where the qc and Nc correlation can be as high as 0.95. We also found that the physically complete EF that accounts for the covariation of qc and Nc is significantly smaller than its counterpart that accounts only for the subgrid variation of qc, especially at cloud top. Although this study is based on limited cases, it suggests that the subgrid variations of Nc and its correlation with qc both need to be considered for an accurate simulation of the autoconversion process in GCMs.

Trees That Live Fast, Die Young, and Mess with Climate Models

The trade-off between tree longevity and life expectancy can mean future carbon uptakes are overestimated in current global climate models.

Significant Extremal Dependence of a Daily North Atlantic Oscillation Index (NAOI) and Weighted Regionalised Rainfall in a Small Island Using the Extremogram

Extremal dependence or independence may occur among the components of univariate or bivariate random vectors. Assessing which asymptotic regime occurs and also its extent are crucial tasks when such vectors are used as statistical models for risk assessment in the field of Climatology under climate change conditions. Motivated by the poor resolution of current global climate models in North Atlantic Small Islands, the extremal dependence between a North Atlantic Oscillation index (NAOI) and rainfall was considered at multi-year dominance of negative and positive NAOI, i.e., −NAOI and +NAOI dominance subperiods, respectively. The datasets used (from 1948–2017) were daily NAOI, and three daily weighted regionalised rainfall series computed based on factor analysis and the Voronoi polygons method from 40 rain gauges in the small island of Madeira (∼740 km2), Portugal. The extremogram technique was applied for measuring the extremal dependence within the NAOI univariate series. The cross-extremogram determined the dependence between the upper tail of the weighted regionalised rainfalls, and the upper and lower tails of daily NAOI. Throughout the 70-year period, the results suggest systematic evidence of statistical dependence over Madeira between exceptionally −NAOI records and extreme rainfalls, which is stronger in the −NAOI dominance subperiods. The extremal dependence for +NAOI records is only significant in recent years, however, with a still unclear +NAOI dominance.

Projections of future rainfall and temperature using statistical downscaling techniques in Tana Basin, Ethiopia

Global climate changes are becoming main threats to hydrological cycle, which thus influence environmental, social, and economic systems. Climate change studies using global climate models (GCMs) are mostly used for mitigation and adaptation strategies regarding the changing climate. The current GCMs’ data are, however, too coarse to use directly at the regional and local scales for climate change studies. Two widely used statistical downscaling methods, namely LARS-WG and SDSM models, were used to study the current and future climate change of Tana Basin, Ethiopia. Four GCMs (GFCM21, HadCM3, MPEH5, and NCCCS) for LARS-WG and two GCMs (HadCM3 and CanESM2) for SDSM with different emission scenarios were evaluated. Overall results indicated an acceptable response of the models to simulate and forecast climatic variables under HadCM3 and CanESM2 GCMs. Rainfall results downscaled by LARS-WG from the four GCMs indicated high intermodal variabilities and non-consistence; Increasing trend of rainfall showed on three of the GCMs while one GCM showed a decreasing trend in the range of − 9.6% to 45.2%. The four GCMs rainfall average ensemble value showed an increasing trend ranging from 3.9% to 18.8%, which is also consistent with HadCM3 projections ranging from 4.1% to 19.2%. However, the downscaled results from all four models showed increasing maximum and minimum temperature for all time periods. The mean annual maximum and minimum temperature change increased from 0.9 °C to 2.9 °C and 0.6 °C to 2.5 °C, respectively, while annual mean relative change of rainfall ranged from 9.9% to 44.7%. Both SDSM and LARS-WG methods were obtained good monthly rainfall data series than daily rainfall data series in the study area. However, both models with the selected GCMs (HadCM3 and CanESM2) performed reasonably well to simulate temperature than rainfall.

Vertical Dependence of Horizontal Variation of Cloud Microphysics: Observations from the ACE-ENA field campaign and implications for warm rain simulation in climate models

Z. Zhang acknowledges the financial support from the Atmospheric System Research (Grant DE607 SC0020057) funded by the Office of Biological and Environmental Research in the US DOE Office of Science. The computations in this study were performed at the UMBC High Performance Computing Facility (HPCF). The facility is supported by the U.S. National Science Foundation through the MRI program (Grants CNS-0821258 and CNS-1228778) and the SCREMS program (Grant DMS-0821311), with substantial support from UMBC. Co-author D. Mechem was supported by subcontract OFED0010- 01 from the University of Maryland Baltimore County and the U.S. Department of Energy’s Atmospheric Systems Research grant DE-SC0016522.

Reactive VOC Production from Photochemical and Heterogeneous Reactions Occurring at the Air-Ocean Interface.

The ocean surface serves as a source and sink for a diverse set of reactive trace gases in the atmosphere, including volatile organic compounds (VOCs), reactive halogens, and oxidized and reduced nitrogen compounds. The exchange of reactive trace gases between the atmosphere and ocean has been shown to alter atmospheric oxidant concentrations and drive particle nucleation and growth. Uncertainties in cloud radiative forcing and aerosol-cloud interactions are among the largest uncertainties in current global climate models. Climate models are particularly sensitive to cloud cover over the remote ocean due to large changes in albedo between the ocean surface and cloud tops. Oceanic emissions contribute to cloud condensation nuclei concentrations, either through the direct emission of particles during wave breaking or through the formation of secondary aerosol particles following the emission of reactive gas-phase compounds. Despite generally small and diffuse oceanic emission rates for reactive trace gases, it has been shown that oxidant and particle number concentrations are acutely sensitive to air-sea trace gas exchange rates and the chemical composition of emitted species. To date, field measurements of air-sea reactive gas exchange have focused primarily on the emission of gases of biological origin, such as dimethyl sulfide (DMS). While DMS emissions are relatively well constrained, the gas-phase oxidation that connects DMS to sulfate aerosol is less well understood. Recent laboratory measurements suggest that heterogeneous and photochemical reactions occurring at the air-sea interface can also lead to the production and emission of a wide array of reactive VOC. When laboratory-based measurements are used to derive global scale emissions, the calculated sea-to-air fluxes of reactive VOC generated from heterogeneous and photochemical processes are comparable or larger in magnitude to the sea-to-air flux of DMS. It is not yet clear how the mechanisms proposed in these laboratory experiments translate to atmospheric conditions. The proposed abiotic emissions are also a potential source of VOC in regions of low biological activity, which carries important implications for regional and global modeling.This Account reviews recent laboratory and field experiments of biotic and abiotic ocean VOC emissions, with a specific focus on exploring open questions related to proposed abiotic reactive VOC emissions and the impact of including a large, abiotic VOC emission source on atmospheric oxidants and aerosol particles. To date, abiotic emissions are not typically included in global chemical transport models. The proposed abiotic emissions mechanisms discussed here have the potential to drive significant changes to current understanding of chemistry in the marine atmosphere if present at the magnitudes suggested by laboratory studies. In order to validate their proposed significance, a coordinated set of laboratory, field, and modeling studies under ocean-relevant conditions are necessary.

The equatorial stratospheric semiannual oscillation and time‐mean winds in QBOi models

AbstractThe Quasi‐Biennial Oscillation initiative (QBOi) is a model intercomparison programme that specifically targets simulation of the QBO in current global climate models. Eleven of the models or model versions that participated in a QBOi intercomparison study have upper boundaries in or above the mesosphere and therefore simulate the region where the stratopause semiannual oscillation (SAO) is the dominant mode of variability of zonal winds in the tropical upper stratosphere. Comparisons of the SAO simulations in these models are presented here. These show that the model simulations of the amplitudes and phases of the SAO in zonal‐mean zonal wind near the stratopause agree well with the information derived from available observations. However, most of the models simulate time‐average zonal winds that are more westward than determined from observations, in some cases by several tens of m·s–1. Validation of wave activity in the models is hampered by the limited observations of tropical waves in the upper stratosphere but suggests a deficit of eastward forcing either by large‐scale waves, such as Kelvin waves, or by gravity waves.