Environmental effects on aerosol–cloud interaction in non-precipitating marine boundary layer (MBL) clouds over the eastern North Atlantic

Over the eastern North Atlantic (ENA) ocean, a total of 20 non-precipitating single-layer marine boundary layer (MBL) stratus and stratocumulus cloud cases are selected to investigate the impacts of the environmental variables on the aerosol–cloud interaction (ACIr) using the ground-based measurements from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the ENA site during 2016–2018. The ACIr represents the relative change in cloud droplet effective radius re with respect to the relative change in cloud condensation nuclei (CCN) number concentration at 0.2 % supersaturation (NCCN,0.2 %) in the stratified water vapor environment. The ACIr values vary from −0.01 to 0.22 with increasing sub-cloud boundary layer precipitable water vapor (PWVBL) conditions, indicating that re is more sensitive to the CCN loading under sufficient water vapor supply, owing to the combined effect of enhanced condensational growth and coalescence processes associated with higher Nc and PWVBL. The principal component analysis shows that the most pronounced pattern during the selected cases is the co-variations in the MBL conditions characterized by the vertical component of turbulence kinetic energy (TKEw), the decoupling index (Di), and PWVBL. The environmental effects on ACIr emerge after the data are stratified into different TKEw regimes. The ACIr values, under both lower and higher PWVBL conditions, more than double from the low-TKEw to high-TKEw regime. This can be explained by the fact that stronger boundary layer turbulence maintains a well-mixed MBL, strengthening the connection between cloud microphysical properties and the below-cloud CCN and moisture sources. With sufficient water vapor and low CCN loading, the active coalescence process broadens the cloud droplet size spectra and consequently results in an enlargement of re. The enhanced activation of CCN and the cloud droplet condensational growth induced by the higher below-cloud CCN loading can effectively decrease re, which jointly presents as the increased ACIr. This study examines the importance of environmental effects on the ACIr assessments and provides observational constraints to future model evaluations of aerosol–cloud interactions.

Analysis of the MODIS above-cloud aerosol retrieval algorithm using MCARS

The Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS) presently produces synthetic radiance data from Goddard Earth Observing System version 5 (GEOS-5) model output as if the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of atmospheric column inclusive of clouds, aerosols, and a variety of gases and land–ocean surface at a specific location. In this paper we use MCARS to study the MODIS Above-Cloud AEROsol retrieval algorithm (MOD06ACAERO). MOD06ACAERO is presently a regional research algorithm able to retrieve aerosol optical thickness over clouds, in particular absorbing biomass-burning aerosols overlying marine boundary layer clouds in the southeastern Atlantic Ocean. The algorithm's ability to provide aerosol information in cloudy conditions makes it a valuable source of information for modeling and climate studies in an area where current clear-sky-only operational MODIS aerosol retrievals effectively have a data gap between the months of June and October. We use MCARS for a verification and closure study of the MOD06ACAERO algorithm. The purpose of this study is to develop a set of constraints a model developer might use during assimilation of MOD06ACAERO data. Our simulations indicate that the MOD06ACAERO algorithm performs well for marine boundary layer clouds in the SE Atlantic provided some specific screening rules are observed. For the present study, a combination of five simulated MODIS data granules were used for a dataset of 13.5 million samples with known input conditions. When pixel retrieval uncertainty was less than 30 %, optical thickness of the underlying cloud layer was greater than 4, and scattering angle range within the cloud bow was excluded, MOD06ACAERO retrievals agreed with the underlying ground truth (GEOS-5 cloud and aerosol profiles used to generate the synthetic radiances) with a slope of 0.913, offset of 0.06, and RMSE=0.107. When only near-nadir pixels were considered (view zenith angle within ±20∘) the agreement with source data further improved (0.977, 0.051, and 0.096 respectively). Algorithm closure was examined using a single case out of the five used for verification. For closure, the MOD06ACAERO code was modified to use GEOS-5 temperature and moisture profiles as an ancillary. Agreement of MOD06ACAERO retrievals with source data for the closure study had a slope of 0.996 with an offset of −0.007 and RMSE of 0.097 at a pixel uncertainty level of less than 40 %, illustrating the benefits of high-quality ancillary atmospheric data for such retrievals.

Arctic fog chemistry induces the unexpected growth of Aitken mode particles to CCN-active particles

<p>New particle formation (NPF) and early growth are efficient processes producing high concentrations of cloud condensation nuclei (CCNs) precursors in the Arctic marine boundary layer (AMBL). However, due to short lifetime and lack of condensable vapors, newly formed particles do often not grow beyond 50 nm and cause low CCN particle concentrations in the AMBL. Thus, even the smallest amount of Aitken mode particle growth is capable to significantly increase the CCN budget. However, the growth mechanism of Aitken-mode particles from NPF into CCN range in the Arctic is still rather unclear and was therefore investigated during the cruise campaign PASCAL in 2017.</p> <p>During PASCAL, aerosol particles measurements were performed and an unexpected rapid growth of Aitken mode particles was observed right after fog episodes. Combined field data analyses and detailed multiphase chemistry box model simulations with the CAPRAM mechanism were performed to study the underlying processes. Resulting, a new mechanism is proposed explaining how particles with d < 50 nm are able to grow into CCN size range in the Arctic without requiring high water vapor supersaturation (SS). The investigations demonstrated that the rapid post-fog particle growth of Aitken mode is related to chemical processes within the Arctic fog. The redistribution of semi-volatile acidic (e.g., methanesulfonic acid) and basic (e.g., ammonia) compounds from processed CCN-active particles to smaller CCN-inactive particles can cause a rapid particle growth of Aitken mode particles after fog evaporation enabling them to grow towards CCN size. Comparisons of the model results with Berner impactor measurements supports the proposed growth mechanism.</p> <p>Overall, this study provided new insights on how the increasing frequency of NPF and fog-related particle processing can increase in the number of CCNs and cloud droplets leading to an increased albedo of Arctic clouds and thus affect the radiative balance in the Arctic. Since fogs will occur more frequently in the Arctic as a result of climate change, this growth mechanism and a deeper knowledge on its feedbacks can be essential to understand Arctic warming.</p>

Is the ocean surface a source of nitrous acid (HONO) in the marine boundary layer?

Nitrous acid, HONO, is a key net photolytic precursor to OH radicals in the atmospheric boundary layer. As OH is the dominant atmospheric oxidant, driving the removal of many primary pollutants and the formation of secondary species, a quantitative understanding of HONO sources is important to predict atmospheric oxidising capacity. While a number of HONO formation mechanisms have been identified, recent work has ascribed significant importance to the dark, ocean-surface-mediated conversion of NO2 to HONO in the coastal marine boundary layer. In order to evaluate the role of this mechanism, here we analyse measurements of HONO and related species obtained at two contrasting coastal locations – Cabo Verde (Atlantic Ocean, denoted Cape Verde herein), representative of the clean remote tropical marine boundary layer, and Weybourne (United Kingdom), representative of semi-polluted northern European coastal waters. As expected, higher average concentrations of HONO (70 ppt) were observed in marine air for the more anthropogenically influenced Weybourne location compared to Cape Verde (HONO < 5 ppt). At both sites, the approximately constant HONO/NO2 ratio at night pointed to a low importance for the dark, ocean-surface-mediated conversion of NO2 into HONO, whereas the midday maximum in the HONO/NO2 ratios indicated significant contributions from photo-enhanced HONO formation mechanisms (or other sources). We obtained an upper limit to the rate coefficient of dark, ocean-surface HONO-to-NO2 conversion of CHONO = 0.0011 ppb h−1 from the Cape Verde observations; this is a factor of 5 lower than the slowest rate reported previously. These results point to significant geographical variation in the predominant HONO formation mechanisms in marine environments and indicate that caution is required when extrapolating the importance of such mechanisms from individual study locations to assess regional and/or global impacts on oxidising capacity. As a significant fraction of atmospheric processing occurs in the marine boundary layer, particularly in the tropics, better constraint of the possible ocean surface source of HONO is important for a quantitative understanding of chemical processing of primary trace gases in the global atmospheric boundary layer and associated impacts upon air pollution and climate.

Global to local impacts on atmospheric CO2 from the COVID-19 lockdown, biosphere and weather variabilities

The world-wide lockdown in response to the COVID-19 pandemic in year 2020 led to economic slowdown and large reduction in fossil fuel CO2 emissions, but it is unclear how much it would slow the increasing trend of atmospheric CO2 concentration, the main driver of climate change, and whether this impact can be observed in light of large biosphere and weather variabilities. We used a state-of-the-art atmospheric transport model to simulate CO2, driven by a new daily fossil fuel emissions dataset and hourly biospheric fluxes from a carbon cycle model forced with observed climate variability. Our results show 0.21 ppm decrease in atmospheric column CO2 anomaly in the Northern Hemisphere latitude band 0-45°N (NH45) in March 2020, and an average of 0.14 ppm for the period of February-April 2020, the largest in the last 10 years. A similar decrease was observed by the carbon satellite GOSAT. Using model sensitivity experiments, we further found that COVID and weather variability are the major contributors of this CO2 drawdown, and the biosphere gave a small positive anomaly. Measurements at marine boundary layer stations such as Hawaii exhibits 1-2 ppm anomalies, mostly due to weather and the biosphere. At city scale, on-road CO2 enhancement measured in Beijing shows reduction of 20-30 ppm, consistent with drastically reduced traffic during COVID lockdown. A stepwise drop of 20 ppm at the city-wide lockdown was observed in the city of Chengdu. The ability of our current carbon monitoring systems in detecting the small and short-lasting COVID signal on the background of fossil fuel CO2 accumulated over the last two centuries is encouraging. The COVID-19 pandemic is an unintended experiment. Its impact suggests that to keep atmospheric CO2 at a climate-safe level will require sustained effort of similar magnitude and improved accuracy and expanded spatiotemporal coverage of our monitoring systems.