Cloud Droplet Number Concentration Research Articles

Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part II: Aerosol–Meteorology–Cloud Interaction

Abstract Aerosol effects on micro/macrophysical properties of marine stratocumulus clouds over the western North Atlantic Ocean (WNAO) are investigated using in situ measurements and large-eddy simulations (LES) for two cold-air outbreak (CAO) cases (28 February and 1 March 2020) during the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). The LES is able to reproduce the vertical profiles of liquid water content (LWC), effective radius reff and cloud droplet number concentration Nc from fast cloud droplet probe (FCDP) in situ measurements for both cases. Furthermore, we show that aerosols affect cloud properties (Nc, reff, and LWC) via the prescribed bulk hygroscopicity of aerosols () and aerosol size distribution characteristics. Nc, reff, and liquid water path (LWP) are positively correlated to and aerosol number concentration (Na) while cloud fractional cover (CFC) is insensitive to and aerosol size distributions for the two cases. The realistic changes to aerosol size distribution (number concentration, width, and the geometrical diameter) with the same meteorology state allow us to investigate aerosol effects on cloud properties without meteorological feedback. We also use the LES results to evaluate cloud properties from two reanalysis products, ERA5 and MERRA-2. Compared to LES, the ERA5 is able to capture the time evolution of LWP and total cloud coverage within the study domain during both CAO cases while MERRA-2 underestimates them.

Implementation of a double moment cloud microphysics scheme in the UK met office regional numerical weather prediction model

AbstractCloud microphysics parametrizations control the transfer of water between phases and hydrometeor species in numerical weather prediction and climate models. As a fundamental component of weather modelling systems cloud microphysics can determine the intensity and timing of precipitation, the extent and longevity of cloud cover and its impact on radiative balance, and directly influence near surface weather metrics such as temperature and wind. In this paper we introduce and demonstrate the performance of a double moment cloud microphysical scheme (CASIM: Cloud AeroSol Interacting Microphysics) in both midlatitude and tropical settings using the same model configuration. Comparisons are made against a control configuration using the current operational single moment cloud microphysics, and CASIM configurations that use fixed in‐cloud droplet number or compute cloud droplet number concentration from the aerosol environment. We demonstrate that configuring CASIM as a single moment scheme results in precipitation rate histograms that match the operational single moment microphysics. In the midlatitude setting, results indicate that CASIM performs as well as the single moment microphysics configuration, but improves certain aspects of the surface precipitation field such as greater extent of light (1 mm hr) rain around frontal precipitation features. In the tropical setting, CASIM outperforms the single moment cloud microphysics as evident from improved comparison with radar derived precipitation rates.

Influence of air mass origin on microphysical properties of low-level clouds in a subarctic environment

Abstract. In this work, an analysis was performed to investigate how different long-range transport air masses can affect the microphysical properties of low-level clouds in a clean subarctic environment. The cloud measurements included in situ and remote sensing ground-based techniques and were conducted during eight Pallas Cloud Experiments (PaCEs) held in the autumn between 2004 and 2019. Each PaCE was carried out at the Pallas Atmosphere-Ecosystem Supersite, located in the Finnish subarctic region. Two cloud spectrometer ground setups were installed on the roof of the station to measure cloud microphysical properties: the cloud, aerosol and precipitation spectrometer (CAPS) and the forward-scattering spectrometer probe (FSSP). Air mass histories were analyzed using the Lagrangian FLEXible PARTicle dispersion model (FLEXPART) in order to investigate the differences between five distinct source regions (“Arctic”, “Eastern”, “Southern”, “Western” and “Local”). We observed clear differences in the cloud microphysical properties for the air mass source regions. Arctic air masses were characterized by low liquid water content (LWC), low cloud droplet number concentration (Nc) and comparatively large median volume and effective droplet diameter. The Western region (marine North Atlantic) differed from the Arctic by both higher Nc and LWC. The Eastern region (continental Eurasia) only had a little higher LWC than the Arctic but substantially higher Nc and a smaller droplet diameter. The Southern region (continental Europe) had high Nc and LWC and a very similar droplet diameter to the Eastern region. Finally, the relationship between Nc and droplet size (i.e., the Twomey effect) was characterized for the different source regions, indicating that all region clouds were sensitive to increases in Nc.

Assessing the Aerosols, Clouds and Their Relationship Over the Northern Bay of Bengal Using a Global Climate Model

AbstractComprehensive evaluation of aerosol‐cloud interactions (ACI) simulated by climate models using observations is crucial for advancing model development. Here, we use Moderate Resolution Imaging Spectroradiometer (MODIS) data to evaluate aerosol and cloud properties obtained from Community Atmosphere Model 5 (CAM5) over northern Bay of Bengal during winter season. We conduct simulations for default model setup as well as for prescribed, and nudged meteorology using Goddard Earth Observing System (GEOS5) reanalysis dataset in order to study the impact of meteorological parameters on simulated ACI. CAM5 captures the spatial variability of cloud optical depth (τc), cloud droplet number concentration (Nc), and liquid water path (LWP), although the values are overestimated in the model. Default model strongly simulates observed negative cloud effective radius (re)‐Nc susceptibility but fails to reproduce the observed positive LWP‐Nc susceptibility possibly due to evaporative cooling of the large number of smaller droplets. Compared to default and prescribed meteorology simulations, nudging specific humidity (Q) at 6‐hr relaxation time scale leads to a positive LWP‐Nc susceptibility, and an overall improved simulation of aerosol indirect effects. Increasing the relaxation time scale beyond 6‐hr degrade the simulation of indirect effects suggesting high sensitivity of indirect effects to Q and serious deficiencies in Q simulated by the model. Improvement in simulation of aerosol and cloud characteristics are also noted when winds (UV) are nudged but it worsens some of the simulated ACI sensitivities due to increased transport of absorbing aerosols over the study region and a dominant semi‐direct effect in the model.

The Radiative and Cloud Responses to Sea Salt Aerosol Engineering in GFDL Models

AbstractMarine cloud brightening is a proposal to counteract global warming by increasing sea salt aerosol emissions. In theory, this increases the cloud droplet number concentration of subtropical marine stratocumulus decks, increasing cloud brightness and longevity. However, this theoretical progression remains uncertain in coupled climate models, especially the response of liquid water path and cloud fraction to aerosol seeding. We use the GFDL CM4 climate model to simulate marine cloud brightening following the published G4sea‐salt protocol, in which sea salt aerosol emissions are uniformly increased over 30 S–30 N in addition to standard forcings from a SSP2‐4.5 future warming scenario. The perturbed radiative and cloud responses are temporally stable though spatially heterogeneous, and direct scattering by the added sea salt predominates over changes to cloud reflectance. In fact, feedbacks in the coupled simulation lead to a net warming, rather than cooling, response by clouds.

Emission Reductions Significantly Reduce the Hemispheric Contrast in Cloud Droplet Number Concentration in Recent Two Decades

AbstractAnthropogenic activities have drastically impacted the climate system since the Industrial Revolution. However, to what extent anthropogenic emissions influence the cloud droplet number concentration (Nd), the critical parameter for understanding aerosol‐cloud interactions, is poorly known on the hemispheric scale due to the considerable retrieval uncertainty. We employed multiple widely used Nd retrieval sampling methods to evaluate the long‐term trend in Nd contrast (ΔNd(NH‐SH)) between the Northern Hemisphere (NH) and Southern Hemisphere (SH). Here we show that the ΔNd(NH‐SH) was halved from 2003 to 2020 using different sampling methods and channels, even though the range of magnitudes of ΔNd(NH‐SH) from different retrieval sampling methods is large. Such dramatic changes in ΔNd(NH‐SH) are dominated by the significantly decreased Nd over the NH (∼20%) due to emission reductions compared to the relatively stable and pristine nature of the SH. Aerosol optical depth (AOD) and aerosol index (AI) correlate poorly with Nd based on long‐term trends, even though they replicate the contrast trends. This poor correlation is partly contributed by stratospheric smoke from wildfires in Australia that had little influence on Nd in the SH. The northwest Atlantic shows the largest contribution, ∼38%, to the Nd trend, whereas the northwest Pacific dominates the change in AOD and AI, contributing more than 60% to AOD and ∼50% to the AI trend in the NH. Our results imply that emission reductions significantly reduced ΔNd(NH‐SH) and provide strong observational evidence that anthropogenic activities have extensively altered liquid clouds in the NH in the last two decades.

Impact of the Microphysics in HARMONIE-AROME on Fog

This study concerns the impact of microphysics on the HARMONIE-AROME NWP model. In particular, the representation of cloud droplets in the single-moment bulk microphysics scheme is examined in relation to fog forecasting. We focus on the shape parameters of the cloud droplet size distribution and recent changes to the representation of the cloud droplet number concentration (CDNC). Two configurations of CDNC are considered: a profile that varies with height and a constant one. These aspects are examined together since few studies have considered their combined impact during fog situations. We present a set of six experiments performed for two non-idealised three-dimensional case studies over the Iberian Peninsula and the North Sea. One case displays both low clouds and fog, and the other shows a persistent fog field above sea. The experiments highlight the importance of the considered parameters that affect droplet sedimentation, which plays a key role in modelled fog. We show that none of the considered configurations can simultaneously represent all aspects of both cases. Hence, continued efforts are needed to introduce relationships between the governing parameters and the relevant atmospheric conditions.

When Do Subpollen Particles Become Relevant for Ice Nucleation Processes in Clouds?

AbstractWhen exposed to sufficiently humid environments, pollen grains burst and release large quantities of small subpollen particles (SPPs) which carry ice nucleating macromolecules. In this study, for the first time we develop a physically based parameterization describing the bursting process of pollen by applying a turgor pressure parameterization and quantify the impact SPPs have on overall ice nucleation in clouds. SPPs are generated from simulated birch pollen emissions over Europe for a 10‐day case study in spring. We found SPP concentrations to surpass pollen grain concentrations by 4–6 orders of magnitude leading to an abundance of biological ice nuclei from SPPs in the range of 103−104 m−3. However, it is found that these concentrations lead to only small changes in hydrometeor number densities and precipitation. Addressing the question when SPPs become relevant for ice nucleation in clouds, we conducted a sensitivity investigation. We find that amplifying ice nucleation efficiency of biological particles by factors greater 100 increases the ice particle numbers by up to 25% (T ≈ 268 K). Strong reductions show in cloud droplet number concentration and water vapor at these temperatures while water vapor is increasing at 600 m. Overall, we found a net reduction of water in the atmosphere as liquid and particularly water vapor density is reduced, while frozen water mass density increases above 257 K. Findings indicate an alteration of mixed‐phase cloud composition and increased precipitation (up to 6.2%) when SPPs are considered as highly efficient biological ice nuclei.

Physical evaluation of hygroscopic cloud seeding in convective clouds using in situ observations and numerical simulations during CAIPEEX

The hygroscopic cloud seeding is conducted over the rain shadow region of the Indian peninsula with an airborne field experiment and radar observations. Physical evaluation of hygroscopic seeding is illustrated with in situ microphysical observations and numerical simulations in convective clouds. Large raindrops were formed near the tops of the cloud, as documented by aircraft observations and model simulations with spectral bin microphysics scheme. Scattering particle number concentration and refractory black carbon in the cloud residue were found up to 4 km in the seeded cloud. The cloud residue measurements of scattering particles and the cloud droplet number concentration showed good agreement in the cloud cores and that has reduced drastically in the cloud edges. Numerical simulations with bin microphysics using observed (background and flare) particle spectra were conducted. Fairly good agreement is noted for the cloud drop size distributions from in situ measurements and numerical simulation. The clouds developed downwind of the seeded area showed further organized convection and longevity and relative enhancement of rainfall as illustrated by the radar observations and the numerical simulations compared to unseeded clouds. The investigation has also brought out the nonlocal impact of the seeded plumes and the new challenges in documenting extra area effects of seeding in the monsoon environment.

Towards reliable retrievals of cloud droplet number for non-precipitating planetary boundary layer clouds and their susceptibility to aerosol

Remote sensing has been a key resource for developing extensive and detailed datasets for studying and constraining aerosol-cloud-climate interactions. However, aerosol-cloud collocation challenges, algorithm limitations, as well as difficulties in unraveling dynamic from aerosol-related effects on cloud microphysics, have long challenged precise retrievals of cloud droplet number concentrations. By combining a series of remote sensing techniques and in situ measurements at ground level, we developed a semi-automated approach that can address several retrieval issues for a robust estimation of cloud droplet number for non-precipitating Planetary Boundary Layer (PBL) clouds. The approach is based on satellite retrievals of the PBL cloud droplet number (Ndsat) using the geostationary meteorological satellite data of the Optimal Cloud Analysis (OCA) product, which is obtained by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The parameters of the retrieval are optimized through closure with droplet number obtained from a combination of ground-based remote sensing data and in situ observations at ground level. More specifically, the remote sensing data are used to retrieve cloud-scale vertical velocity, and the in situ aerosol measurements at ground level were used constrain as input to a state-of-the-art droplet activation parameterization to predict the respective Cloud Condensation Nuclei (CCN) spectra, cloud maximum supersaturation and droplet number concentration (Nd), accounting for the effects of vertical velocity distribution and lateral entrainment. Closure studies between collocated Nd and Ndsat are then used to evaluate exising droplet spectral width parameters used for the retrieval of droplet number, and determine the optimal values for retrieval. This methodology, used to study aerosol-cloud interactions for non-precipitating clouds formed over the Athens Metropolitan Area (AMA), Greece from March to May 2020, shows that droplet closure can be achieved to within 30%, comparable to the level of closure obtained in many in situ studies. Given this, the ease of applying this approach with satellite data obtained from SEVIRI with high temporal (15 min) and spatial resolution (3.6 km × 4.6 km), opens the possibility of continuous and reliable Ndsat, giving rise to high value datasets for aerosol-cloud-climate interaction studies.

On the Trend in Below-Cloud Solar Irradiance in The Netherlands versus That in Aerosol Sulfate Concentration

The below-cloud irradiance in The Netherlands increased by over 10 Wm−2 in the past half century. It was hypothesized that this could be due to a decrease in the aerosol serving as cloud condensation nuclei, on which the cloud droplets form, in the following way. With unchanged macrophysics, clouds with a lower number of droplets are less reflective, in other words, they transmit more solar radiation. This hypothesis cannot be substantiated with data because of a generic absence of long-term information on cloud droplet number concentrations (CDNCs) worldwide. To assess the historic trend in CDNC, we used the Boucher and Lohmann (B&L) empirical relationship between CDNC and the mass concentration of the water-attracting hygroscopic aerosol components. The B&L parameterization was tested and validated with observations from the CHIEF cloud chamber, in which the formation of marine stratocumulus, the most frequent cloud type in The Netherlands, is simulated. This study will focus on summer periods because the irradiance governs the yearly average at this latitude. The summer trend of sulfate, the most dominant hygroscopic component of observed aerosol mass concentration, was analyzed with EBAS data from 1972 onwards. The average summer CDNCs were then calculated via the B&L parameterization, showing an upper limit of 380 cm−3 in the 1970s and decreasing to around 200 cm−3 in the 2010s. The associated increase in transmission for thin marine stratocumulus without overlying clouds would be, at most, 3.5 W m−2. Unobstructed stratocumuli occur only part of the time, and the change in irradiance based on the reduction in cloud droplet number is certainly small in comparison to the empirically derived trend of 10 W m−2.

Aerosol effects on clouds are concealed by natural cloud heterogeneity and satellite retrieval errors

One major source of uncertainty in the cloud-mediated aerosol forcing arises from the magnitude of the cloud liquid water path (LWP) adjustment to aerosol-cloud interactions, which is poorly constrained by observations. Many of the recent satellite-based studies have observed a decreasing LWP as a function of cloud droplet number concentration (CDNC) as the dominating behavior. Estimating the LWP response to the CDNC changes is a complex task since various confounding factors need to be isolated. However, an important aspect has not been sufficiently considered: the propagation of natural spatial variability and errors in satellite retrievals of cloud optical depth and cloud effective radius to estimates of CDNC and LWP. Here we use satellite and simulated measurements to demonstrate that, because of this propagation, even a positive LWP adjustment is likely to be misinterpreted as negative. This biasing effect therefore leads to an underestimate of the aerosol-cloud-climate cooling and must be properly considered in future studies.

Aerosol–cloud interaction in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on mesoscale numerical weather prediction under haze pollution conditions in Jing–Jin–Ji in China

Abstract. The representation of aerosol–cloud interaction (ACI) and its impacts in the current climate or weather model remains a challenge, especially for severely polluted regions with high aerosol concentration, which is even more important and worthy of study. Here, ACI is first implemented in the atmospheric chemistry model GRAPES_Meso5.1/CUACE by allowing for real-time aerosol activation in the Thompson cloud microphysics scheme. Two experiments are conducted focusing on a haze pollution case with coexisting high aerosol and stratus cloud over the Jing–Jin–Ji region in China to investigate the impact of ACI on the mesoscale numerical weather prediction (NWP). Study results show that ACI increases cloud droplet number concentration, water mixing ratio, liquid water path (CLWP), and optical thickness (COT), as a result improving the underestimated CLWP and COT (reducing the mean bias by 21 % and 37 %, respectively) over a certain subarea by the model without ACI. A cooling in temperature in the daytime below 950 hPa occurs due to ACI, which can reduce the mean bias of 2 m temperature in the daytime by up to 14 % (∼ 0.6 ∘C) in the subarea with the greatest change in CLWP and COT. The 24 h cumulative precipitation in this subarea corresponding to moderate-rainfall events increases, which can reduce the mean bias by 18 %, depending on the enhanced melting of the snow by more cloud droplets. In other areas or periods with a slight change in CLWP and COT, the impact of ACI on NWP is not significant, suggesting the inhomogeneity of ACI. This study demonstrates the critical role of ACI in the current NWP model over the severely polluted region and the complexity of the ACI effect.

Effects of aerosols on the forecasting of Mei-yu frontal storms over the Yangtze–Huai River valley

The evolutions of Mei-yu frontal storms during the Mei-yu season in 2018 were simulated in the Weather Research and Forecasting with Chemistry (WRF/Chem) model to investigate the effects of aerosols on the prediction of clouds and precipitation. Two groups of daily launched forecast experiments were conducted with a duration of 17 days, by turning the chemistry–aerosol module on (WRF/Chem) and off (WRF), and additional cloud droplet number concentration (Nd) experiments were perturbed in WRF. Comparison between the two groups of experiments suggested that activating the chemistry–aerosol module improved the forecast skill for precipitation exceeding 5 mm/h during the Mei-yu season, while had no positive forecast skill on precipitation exceeding 0.1 mm/h in terms of both traditional and neighborhood spatial verifications. In contrast to the uniform Nd distribution adopted in WRF, the inhomogeneous Nd distribution in WRF/Chem agreed better with in-situ aircraft observations collected during the field campaign. As Nd increases in WRF experiments, the warm clouds decreased and deep convective clouds significantly increased with more convective updraft mass flux and net heat budget. Scavenging in Mei-yu frontal storms generally reduced the median Nd in the WRF/Chem experiment. The fewer and larger cloud particles in WRF/Chem promoted the conversion of cloud to rain and the accretion of cloud by rain, thereby leading to invigoration of warm clouds and precipitation efficiency, which explains the improved forecast skill for precipitation exceeding 5 mm/h. Enhanced warm-rain processes caused fewer cloud particles for further ascent and ultimately resulted in suppression of deep convective clouds. The preliminary findings in this study highlights the potential significance of incorporating chemistry–aerosol schemes in the operational forecasting of Mei-yu rainfall.

Chemistry-driven changes strongly influence climate forcing from vegetation emissions

Biogenic volatile organic compounds (BVOCs) affect climate via changes to aerosols, aerosol-cloud interactions (ACI), ozone and methane. BVOCs exhibit dependence on climate (causing a feedback) and land use but there remains uncertainty in their net climatic impact. One factor is the description of BVOC chemistry. Here, using the earth-system model UKESM1, we quantify chemistry’s influence by comparing the response to doubling BVOC emissions in the pre-industrial with standard and state-of-science chemistry. The net forcing (feedback) is positive: ozone and methane increases and ACI changes outweigh enhanced aerosol scattering. Contrary to prior studies, the ACI response is driven by cloud droplet number concentration (CDNC) reductions from suppression of gas-phase SO2 oxidation. With state-of-science chemistry the feedback is 43% smaller as lower oxidant depletion yields smaller methane increases and CDNC decreases. This illustrates chemistry’s significant influence on BVOC’s climatic impact and the more complex pathways by which BVOCs influence climate than currently recognised.

Cloud Phase Simulation at High Latitudes in EAMv2: Evaluation Using CALIPSO Observations and Comparison With EAMv1

AbstractThis study performs a comprehensive evaluation of the simulated cloud phase in the U.S. Department of Energy, Energy Exascale Earth System Model, atmosphere model version 2 (EAMv2), and version 1 (EAMv1). Enabled by the CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation) simulator, EAMv2 and EAMv1 predicted cloud phase is compared against the GCM‐Oriented CALIPSO Cloud Product (CALIPSO‐GOCCP) at high latitudes where mixed‐phase clouds are prevalent. Our results indicate that the underestimation of cloud ice in simulated high‐latitude mixed‐phase clouds in EAMv1 has been significantly reduced in EAMv2. The increased ice clouds in the Arctic mainly result from the modification on the WBF (Wegner‐Bergeron‐Findeisen) process in EAMv2. The impact of the modified WBF process is moderately compensated by the low limit of cloud droplet number concentration in cloud microphysics and the new dCAPE_ULL trigger used in deep convection in EAMv2. Moreover, it is found that the new trigger largely contributes to the better cloud phase simulation over the Norwegian Sea and Barents Sea in the Arctic and the Southern Ocean where large errors are found in EAMv1. However, errors in simulated cloud phase in EAMv1, such as the overestimation of supercooled liquid clouds near the surface in both hemispheres and the underestimation of ice clouds over Antarctica, persist in EAMv2. This study highlights the impact of deep convection parameterizations, which has received little attention, on high‐latitude mixed‐phase clouds, and the importance of continuous improvement of cloud microphysics in climate models for accurately representing mixed‐phase clouds.

The Shortwave Radiative Flux Response to an Injection of Sea Salt Aerosols in the Gulf of Mexico

AbstractMarine cloud brightening (MCB) has been proposed as a potential means of geoengineering the climate, temporarily providing cooling to offset some of the effects of climate change. Marine sky brightening (MSB), involving the direct scattering of sunlight from sea salt injection into the marine boundary layer, has been proposed as an additional geoengineering method that could work in areas that are not regularly cloudy. Here, we use a regional atmospheric model to simulate MCB and MSB over the Gulf of Mexico and nearby land, a highly populated and economically important region that is not characterized by persistent marine stratocumulus cloud cover. Injection of sea salt in the Aitken mode from a region in the central Gulf of Mexico equivalent to 10.8 Tg yr−1 produces an upwards 8.4 W m−2 radiative flux change across the region at the top of the atmosphere, largely due to cloud property changes. Comparatively, a similar mass injection in the accumulation mode produces a 3.1 W m−2 radiative flux change driven primarily by direct scattering. Injection of even larger particles produces a much smaller radiative flux change. Shortwave flux changes due to clouds are largely driven by an increase in cloud droplet number concentration and an increase in cloud liquid water path (each contributing about 45% to the flux change), with a much lower contribution from cloud fraction changes (10%).

Aerosol characteristics and polarimetric signatures for a deep convective storm over the northwestern part of Europe – modeling and observations

Abstract. The Terrestrial Systems Modeling Platform (TSMP) was extended with a chemical transport model and polarimetric radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. The model was used at kilometer-scale (convection-permitting) resolution to simulate a deep convective storm event over Germany which produced large hail, high precipitation, and severe damaging winds. The ensemble model simulation was, in general, able to capture the storm structure, its evolution, and the spatial pattern of accumulated precipitation. However, the model was found to underestimate regions of high accumulated precipitation (> 35 mm) and convective area fraction in the early period of the storm. While the model tends to simulate too high reflectivity in the downdraft region of the storm above the melting layer (mostly contributed by graupel), the model also simulates very weak polarimetric signatures in this region, when compared to the radar observations. The above findings remained almost unchanged when using a narrower cloud drop size distribution (CDSD) acknowledging the missing feedback between aerosol physical and chemical properties and CDSD shape parameters. The kilometer-scale simulation showed that the strong updraft in the convective core produces aerosol-tower-like features, increasing the aerosol number concentrations and hence increasing the cloud droplet number concentration and reducing the mean cloud drop size. This could also be a source of discrepancy between the simulated polarimetric features like differential reflectivity (ZDR) and specific differential-phase (KDP) columns along the vicinity of the convective core compared to the X-band radar observations. However, the use of narrow CDSD did improve the simulation of ZDR columns. Besides, the evaluation of simulated trace gases and aerosols was encouraging; however, a low bias was observed for aerosol optical depth (AOD), which could be partly linked to an underestimation of dust mass in the forcing data associated with a Saharan dust event. This study illustrates the importance and the additional complexity associated with the inclusion of chemistry transport model when studying aerosol–cloud–precipitation interactions. But, along with polarimetric radar data for model evaluation, it allows us to identify and better constrain the traditional two-moment bulk cloud microphysical schemes used in the numerical weather prediction models for weather and climate.

Simulating Aerosol Lifecycle Impacts on the Subtropical Stratocumulus‐to‐Cumulus Transition Using Large‐Eddy Simulations

AbstractObserved stratocumulus to cumulus transitions (SCTs) and their sensitivity to aerosols are studied using a large‐eddy simulation (LES) model that simulates the aerosol lifecycle, including aerosol sources and sinks. To initialize, force, and evaluate the LES, we used a combination of reanalysis, satellite, and aircraft data from the 2015 Cloud System Evolution in the Trades field campaign over the Northeast Pacific. The simulations follow two Lagrangian trajectories from initially overcast stratocumulus (Sc) to the tropical shallow cumulus region near Hawaii. The first trajectory is characterized by an initially clean, well‐mixed Sc‐topped marine boundary layer (MBL), then continuous MBL deepening and precipitation onset followed by a clear SCT and a consistent reduction of aerosols that ultimately leads to an ultra‐clean layer in the upper MBL. The second trajectory is characterized by an initially polluted and decoupled MBL, weak precipitation, and a late SCT. Overall, the LES simulates the observed general MBL features. Sensitivity studies with different aerosol initial and boundary conditions reveal aerosol‐induced changes in the transition, and albedo changes are decomposed into the Twomey effect and adjustments of cloud liquid water path and cloud fraction. Impacts on precipitation play a key role in the sensitivity to aerosols: for the first case, runs with enhanced aerosols exhibit distinct changes in microphysics and macrophysics such as enhanced cloud droplet number concentration, reduced precipitation, and delayed SCT. Cloud adjustments are dominant in this case. For the second case, enhancing aerosols does not affect cloud macrophysical properties significantly, and the Twomey effect dominates.

An improved representation of aerosol mixing state for air quality–weather interactions

Abstract. We implement a detailed representation of aerosol mixing state in the Global Environmental Multiscale – Modelling Air quality and CHemistry (GEM-MACH) air quality and weather forecast model. Our mixing-state representation includes three categories: one for more hygroscopic aerosol, one for less hygroscopic aerosol with a high black carbon (BC) mass fraction, and one for less hygroscopic aerosol with a low BC mass fraction. The more detailed representation allows us to better resolve two different aspects of aerosol mixing state: differences in hygroscopicity due to aerosol composition and the amount of absorption enhancement of BC due to non-absorbing coatings. Notably, this three-category representation allows us to account for BC thickly coated with primary organic matter, which enhances the absorption of the BC but has a low hygroscopicity. We compare the results of the three-category representation (1L2B, (one hydrophilic, two hydrophobic)) with a simulation that uses two categories, split by hygroscopicity (HYGRO), and a simulation using the original size-resolved internally mixed assumption (SRIM). We perform a case study that is focused on North America during July 2016, when there were intense wildfires over northwestern North America. We find that the more detailed representation of the aerosol hygroscopicity in both 1L2B and HYGRO decreases wet deposition, which increases aerosol concentrations, particularly of less hygroscopic species. The concentration of PM2.5 increases by 23 % on average. We show that these increased aerosol concentrations increase cloud droplet number concentrations and cloud reflectivity in the model, decreasing surface temperatures. Using two categories based on hygroscopicity yields only a modest benefit in resolving the coating thickness on black carbon, however. The 1L2B representation resolves BC with thinner coatings than the HYGRO simulation, resulting in absorption aerosol optical depths that are 3 % less on average, with greater differences over strong anthropogenic source regions. We did not find strong subsequent effects of this decreased absorption on meteorology.