ALBERT

Description: The ocean is responsible for up to a third of total global nitrous oxide (N2O) emissions, but uncertainties in emission rates of this potent greenhouse gas are high (〉100%). Here we use a marine biogeochemical model to assess six major uncertainties in estimates of N2O production, thereby providing guidance in how future studies may most effectively reduce uncertainties in current and future marine N2O emissions. Potential surface N2O production from nitrification causes the largest uncertainty in N2O emissions (estimated up to ~1.6 Tg N/yr, or 48% of modeled values), followed by the unknown oxygen concentration at which N2O production switches to N2O consumption (0.8 Tg N/yr, or 24% of modeled values). Other uncertainties are minor, cumulatively changing regional emissions by 〈15%. If production of N2O by surface nitrification could be ruled out in future studies, uncertainties in marine N2O emissions would be halved.

Description: Deep convective clouds (DCCs) are important to global climate, atmospheric chemistry, and precipitation. Dust, a dominant aerosol type over the tropical North Atlantic, has potentially large microphysical impacts on DCCs over this region. However, dust effects are difficult to identify, being confounded by covarying meteorology and other factors. Here, a method is developed to quantify DCC responses to dust and other aerosols at large spatial and temporal scales despite these uncertainties. Over 7 million tropical North Atlantic cloud, aerosol, and meteorological profiles from CloudSat satellite data and MERRA-2 reanalysis products are used to stratify cloud observations into meteorological regimes, objectively select a priori assumptions, and iteratively test uncertainty sensitivity. Dust is robustly associated with a 54% increase in DCC prevalence. However, marine aerosol proxy concentrations are 5 times more predictive of dust-associated increases in DCC prevalence than the dust itself, or any other aerosol or meteorological factor. Marine aerosols are also the most predictive factor for the even larger increases in DCC prevalence (61%–87%) associated with enhanced dimethyl sulfide and combustion and sulfate aerosols. Dust-associated increases in DCC prevalence are smaller at high dust concentrations than at low concentrations. These observations suggest that not only is dust a comparatively ineffective CCN source, but it may also act as a condensation/coagulation sink for chemical precursors to CCN, reducing total CCN availability over large spatial scales by inhibiting new particle formation from marine emissions. These observations represent the first time this process, previously predicted by models, has been supported and quantified by measurements.

Description: Anthropogenic nitrogen (N) emissions to the atmosphere have increased significantly the deposition of nitrate (NO3−) and ammonium (NH4+) to the surface waters of the open ocean, with potential impacts on marine productivity and the global carbon cycle. Global-scale understanding of the impacts of N deposition to the oceans is reliant on our ability to produce and validate models of nitrogen emission, atmospheric chemistry, transport and deposition. In this work,  ∼  2900 observations of aerosol NO3− and NH4+ concentrations, acquired from sampling aboard ships in the period 1995–2012, are used to assess the performance of modelled N concentration and deposition fields over the remote ocean. Three ocean regions (the eastern tropical North Atlantic, the northern Indian Ocean and northwest Pacific) were selected, in which the density and distribution of observational data were considered sufficient to provide effective comparison to model products. All of these study regions are affected by transport and deposition of mineral dust, which alters the deposition of N, due to uptake of nitrogen oxides (NOx) on mineral surfaces. Assessment of the impacts of atmospheric N deposition on the ocean requires atmospheric chemical transport models to report deposition fluxes; however, these fluxes cannot be measured over the ocean. Modelling studies such as the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP), which only report deposition flux, are therefore very difficult to validate for dry deposition. Here, the available observational data were averaged over a 5° × 5° grid and compared to ACCMIP dry deposition fluxes (ModDep) of oxidised N (NOy) and reduced N (NHx) and to the following parameters from the Tracer Model 4 of the Environmental Chemical Processes Laboratory (TM4): ModDep for NOy, NHx and particulate NO3− and NH4+, and surface-level particulate NO3− and NH4+ concentrations. As a model ensemble, ACCMIP can be expected to be more robust than TM4, while TM4 gives access to speciated parameters (NO3− and NH4+) that are more relevant to the observed parameters and which are not available in ACCMIP. Dry deposition fluxes (CalDep) were calculated from the observed concentrations using estimates of dry deposition velocities. Model–observation ratios (RA, n), weighted by grid-cell area and number of observations, were used to assess the performance of the models. Comparison in the three study regions suggests that TM4 overestimates NO3− concentrations (RA, n =  1.4–2.9) and underestimates NH4+ concentrations (RA, n =  0.5–0.7), with spatial distributions in the tropical Atlantic and northern Indian Ocean not being reproduced by the model. In the case of NH4+ in the Indian Ocean, this discrepancy was probably due to seasonal biases in the sampling. Similar patterns were observed in the various comparisons of CalDep to ModDep (RA, n =  0.6–2.6 for NO3−, 0.6–3.1 for NH4+). Values of RA, n for NHx CalDep–ModDep comparisons were approximately double the corresponding values for NH4+ CalDep–ModDep comparisons due to the significant fraction of gas-phase NH3 deposition incorporated in the TM4 and ACCMIP NHx model products. All of the comparisons suffered due to the scarcity of observational data and the large uncertainty in dry deposition velocities used to derive deposition fluxes from concentrations. These uncertainties have been a major limitation on estimates of the flux of material to the oceans for several decades. Recommendations are made for improvements in N deposition estimation through changes in observations, modelling and model–observation comparison procedures. Validation of modelled dry deposition requires effective comparisons to observable aerosol-phase species' concentrations, and this cannot be achieved if model products only report dry deposition flux over the ocean.

Description: Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol–cloud interactions. Here, we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify large-scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (∼10 W m−2) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain the majority of this signal. For example, combustion aerosols explain at most 40 % of the CF differences between the full dataset and the clean-condition subset, compared to between 57 % and 91 % of the differences that can be predicted by co-varying meteorology. After normalizing for meteorological regime, aerosol microphysical effects have small but significant impacts on CF, CP, and precipitation frequency on an Arctic-wide scale. These effects indicate that dominant aerosol–cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.

Description: Aerosol indirect effects have potentially large impacts on the Arctic Ocean surface energy budget, but model estimates of regional-scale aerosol indirect effects are highly uncertain and poorly validated by observations. Here we demonstrate a new way to quantitatively estimate aerosol indirect effects on a regional scale from remote sensing observations. In this study, we focus on nighttime, optically thin, predominantly liquid clouds. The method is based on differences in cloud physical and microphysical characteristics in carefully selected clean, average, and aerosol-impacted conditions. The cloud subset of focus covers just ∼ 5 % of cloudy Arctic Ocean regions, warming the Arctic Ocean surface by ∼ 1–1.4 W m−2 regionally during polar night. However, within this cloud subset, aerosol and cloud conditions can be determined with high confidence using CALIPSO and CloudSat data and model output. This cloud subset is generally susceptible to aerosols, with a polar nighttime estimated maximum regionally integrated indirect cooling effect of ∼ −0.11 W m−2 at the Arctic sea ice surface (∼ 8 % of the clean background cloud effect), excluding cloud fraction changes. Aerosol presence is related to reduced precipitation, cloud thickness, and radar reflectivity, and in some cases, an increased likelihood of cloud presence in the liquid phase. These observations are inconsistent with a glaciation indirect effect and are consistent with either a deactivation effect or less-efficient secondary ice formation related to smaller liquid cloud droplets. However, this cloud subset shows large differences in surface and meteorological forcing in shallow and higher-altitude clouds and between sea ice and open-ocean regions. For example, optically thin, predominantly liquid clouds are much more likely to overlay another cloud over the open ocean, which may reduce aerosol indirect effects on the surface. Also, shallow clouds over open ocean do not appear to respond to aerosols as strongly as clouds over stratified sea ice environments, indicating a larger influence of meteorological forcing over aerosol microphysics in these types of clouds over the rapidly changing Arctic Ocean.

Description: Aerosol indirect effects have uncertain, but potentially large, impacts on the Arctic energy budget. Here, we have reduced uncertainty in current-day Arctic net aerosol indirect effects on the surface by better constraining various physical and microphysical characteristics of optically thin, liquid-containing clouds in clean, average and aerosol-impacted conditions using a combination of CALIPSO and CloudSat data and model output. This work provides a foundation for how future observational studies can evaluate previous model estimates of the aerosol indirect effect. Clouds over sea ice and open ocean show large differences in surface and meteorological forcing, including a near doubling of multi-layer cloud presence over the open ocean compared to sea ice. The optically thin cloud subset is susceptible to aerosols, and over sea ice we estimate a regional scale maximum net indirect effect on these clouds during polar night equivalent to ~ 0.6–0.8 W m−2 at the surface. Aerosol presence is related to reduced precipitation, cloud thickness, and radar reflectivity, and may be associated with an increased likelihood of cloud presence in the liquid phase. The observations are consistent with a thermodynamic indirect effect hypothesis and are inconsistent with a glaciation indirect effect.

Description: Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol-cloud interactions. Here we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify regional-scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (~25Wm−2) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain much of this signal – for example, explaining up to 91% of the CF differences between the full dataset and the clean-condition subset. After normalizing for meteorological regime, aerosol microphysical effects have small but significant regional-scale impacts on CF, CP, and precipitation frequency. These effects indicate that dominant aerosol-cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.

Description: Nitrogen (N) emissions to the atmosphere have increased by a factor of 3–4 through anthropogenic activity since the Industrial Revolution. This has led to large increases in the deposition of nitrate (NO3−) and ammonium (NH4+) to the surface waters of the open ocean, with potential impacts on marine productivity and the global carbon cycle. Global-scale understanding of N deposition to the oceans is reliant on our ability to produce and validate models of nitrogen emission, atmospheric chemistry, transport and deposition. In this work, ~ 2900 observations of aerosol NO3− and NH4+ concentrations, acquired from sampling aboard ships in the period 1995–2012, are used to assess the performance of modelled N concentration and deposition fields over the remote ocean. Three ocean regions (the eastern tropical North Atlantic, the northern Indian Ocean and northwest Pacific) were selected in which the density and distribution of observational data were considered sufficient to provide effective comparison to model products. All of these study regions are affected by transport and deposition of mineral dust, which alters the deposition of N. Surface particulate NO3− and NH4+ concentrations simulated by the TM4-ECPL (TM4) model were compared to observed aerosol concentrations. Dry deposition fluxes of these species predicted by TM4 (ModDep) were compared with equivalent fluxes calculated from the observed concentrations (CalDep) using two commonly applied methods for the determination of CalDep. CalDep was also compared to total dry deposition fluxes of oxidised N (NOy) and reduced N (NHx) from TM4 and the ACCMIP multi-model mean product. Comparison in the three study regions suggests that TM4 over-estimates NO3− concentrations and under-estimates NH4+ concentrations, with spatial distributions in the tropical Atlantic and northern Indian Ocean not being reproduced by the model. In the case of NH4+ in the Indian Ocean, this discrepancy was probably due to seasonal biases in the sampling. Similar patterns were observed in the various comparisons of CalDep to ModDep and it was not possible to assess objectively the relative merits of the two methods for estimating CalDep. Comparisons of NH4+ CalDep to NHx ModDep were impaired by the significant fraction of gas-phase NH3 deposition incorporated in the TM4 and ACCMIP model products. All of the comparisons (of concentration and deposition) suffered due to the large uncertainty in dry deposition velocities used in the models and in the calculation of CalDep. These uncertainties have been a major limitation on estimates of the flux of material to the oceans for several decades.