Cloud Condensation Nuclei Concentrations Research Articles

A new method for calculating number concentrations of cloud condensation nuclei based on measurements of a three-wavelength humidified nephelometer system

Abstract. The number concentration of cloud condensation nuclei (CCN) plays a fundamental role in cloud physics. Instrumentations of direct measurements of CCN number concentration (NCCN) based on chamber technology are complex and costly; thus a simple way for measuring NCCN is needed. In this study, a new method for NCCN calculation based on measurements of a three-wavelength humidified nephelometer system is proposed. A three-wavelength humidified nephelometer system can measure the aerosol light-scattering coefficient (σsp) at three wavelengths and the light-scattering enhancement factor (fRH). The Ångström exponent (Å) inferred from σsp at three wavelengths provides information on mean predominate aerosol size, and hygroscopicity parameter (κ) can be calculated from the combination of fRH and Å. Given this, a lookup table that includes σsp, κ and Å is established to predict NCCN. Due to the precondition for the application, this new method is not suitable for externally mixed particles, large particles (e.g., dust and sea salt) or fresh aerosol particles. This method is validated with direct measurements of NCCN using a CCN counter on the North China Plain. Results show that relative deviations between calculated NCCN and measured NCCN are within 30 % and confirm the robustness of this method. This method enables simplerNCCN measurements because the humidified nephelometer system is easily operated and stable. Compared with the method using a CCN counter, another advantage of this newly proposed method is that it can obtain NCCN at lower supersaturations in the ambient atmosphere.

Biomass burning CCN enhance the dynamics of a mesoscale convective system over the La Plata Basin: a numerical approach

Abstract. High aerosol loadings are discharged into the atmosphere every year by biomass burning in the Amazon and central Brazil during the dry season (July–December). These particles, suspended in the atmosphere, can be carried via a low-level jet toward the La Plata Basin, one of the largest hydrographic basins in the world. Once they reach this region, the aerosols can affect mesoscale convective systems (MCSs), whose frequency is higher during the spring and summer over the basin. The present study is one of the first that seeks to understand the microphysical effects of biomass burning aerosols from the Amazon Basin on mesoscale convective systems over the La Plata Basin. We performed numerical simulations initialized with idealized cloud condensation nuclei (CCN) profiles for an MCS case observed over the La Plata Basin on 21 September 2010. The experiments reveal an important link between CCN number concentration and MCS dynamics, where stronger downdrafts were observed under higher amounts of aerosols, generating more updraft cells in response. Moreover, the simulations show higher amounts of precipitation as the CCN concentration increases. Despite the model's uncertainties and limitations, these results represent an important step toward the understanding of possible impacts on the Amazon biomass burning aerosols over neighboring regions such as the La Plata Basin.

Influence of Common Assumptions Regarding Aerosol Composition and Mixing State on Predicted CCN Concentration

A 4-year record of aerosol size and hygroscopic growth factor distributions measured at the Department of Energy’s Southern Great Plains (SGP) site in Oklahoma, U.S. were used to estimate supersaturation (S)-dependent cloud condensation nuclei concentrations (NCCN). Baseline or reference NCCN(S) spectra were estimated using κ-Köhler Theory without any averaging of the measured distributions by creating matrices of size- and hygroscopicity-dependent number concentration (N) and then integrating for S > critical supersaturation (Sc) calculated for the same size and hygroscopicity pairs. Those estimates were first compared with directly measured NCCN at the same site. Subsequently, NCCN was calculated using the same dataset but with an array of simplified treatments in which the aerosol was assumed to be either an internal or an external mixture and the hygroscopicity either assumed or based on averages derived from the growth factor distributions. The CCN spectra calculated using the simplified treatments were compared with those calculated using the baseline approach to evaluate the error introduced with commonly used approximations.

Helicopter-borne observations of the continental background aerosol in combination with remote sensing and ground-based measurements

Abstract. This paper examines the representativeness of ground-based in situ measurements for the planetary boundary layer (PBL) and conducts a closure study between airborne in situ and ground-based lidar measurements up to an altitude of 2300 m. The related measurements were carried out in a field campaign within the framework of the High-Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in September 2013 in a rural background area of central Europe.The helicopter-borne probe ACTOS (Airborne Cloud and Turbulence Observation System) provided measurements of the aerosol particle number size distribution (PNSD), the aerosol particle number concentration (PNC), the number concentration of cloud condensation nuclei (CCN-NC), and meteorological atmospheric parameters (e.g., temperature and relative humidity). These measurements were supported by the ground-based 3+2 wavelength polarization lidar system PollyXT, which provided profiles of the particle backscatter coefficient (σbsc) for three wavelengths (355, 532, and 1064 nm). Particle extinction coefficient (σext) profiles were obtained by using a fixed backscatter-to-extinction ratio (also lidar ratio, LR). A new approach was used to determine profiles of CCN-NC for continental aerosol. The results of this new approach were consistent with the airborne in situ measurements within the uncertainties.In terms of representativeness, the PNSD measurements on the ground showed a good agreement with the measurements provided with ACTOS for lower altitudes. The ground-based measurements of PNC and CCN-NC are representative of the PBL when the PBL is well mixed. Locally isolated new particle formation events on the ground or at the top of the PBL led to vertical variability in the cases presented here and ground-based measurements are not entirely representative of the PBL. Based on Mie theory (Mie, 1908), optical aerosol properties under ambient conditions for different altitudes were determined using the airborne in situ measurements and were compared with the lidar measurements. The investigation of the optical properties shows that on average the airborne-based particle light backscatter coefficient is 50.1 % smaller for 1064 nm, 27.4 % smaller for 532 nm, and 29.5 % smaller for 355 nm than the measurements of the lidar system. These results are quite promising, since in situ measurement-based Mie calculations of the particle light backscattering are scarce and the modeling is quite challenging. In contrast, for the particle light extinction coefficient we found a good agreement. The airborne-based particle light extinction coefficient was just 8.2 % larger for 532 nm and 3 % smaller for 355 nm, for an assumed LR of 55 sr. The particle light extinction coefficient for 1064 nm was derived with a LR of 30 sr. For this wavelength, the airborne-based particle light extinction coefficient is 5.2 % smaller than the lidar measurements. For the first time, the lidar ratio of 30 sr for 1064 nm was determined on the basis of in situ measurements and the LR of 55 sr for 355 and 532 nm wavelength was reproduced for European continental aerosol on the basis of this comparison. Lidar observations and the in situ based aerosol optical properties agree within the uncertainties. However, our observations indicate that a determination of the PNSD for a large size range is important for a reliable modeling of aerosol particle backscattering.

Cloud condensation nuclei over the Bay of Bengal during the Indian summer monsoon

The first measurements of cloud condensation nuclei (CCN) at five supersaturations were carried out onboard the research vessel “Sagar Kanya” (cruise SK-296) from the south to the head-bay of the Bay of Bengal as part of the Continental Tropical Convergence Zone (CTCZ) Project during the Indian summer monsoon of 2012. In this paper, we assess the diurnal variation in CCN distributions at supersaturations from 0.2% to 1% (in steps of 0.2%) and the power-law fit at supersaturation of 1%. The diurnal pattern shows peaks in CCN concentration (NCCN) at supersaturations from 0.2% to 1% between 0600 and 0700 LST (local standard time, UTC+0530), with relatively low concentrations between 1200 and 1400 LST, followed by a peak at around 1800 LST. The power-law fit for the CCN distribution at different supersaturation levels relates the empirical exponent (k) of supersaturation (%) and the NCCN at a supersaturation of 1%. The NCCN at a supersaturation of 0.4% is observed to vary from 702 cm−3 to 1289 cm−3, with a mean of 961±161 cm−3 (95% confidence interval), representing the CCN activity of marine air masses. Whereas, the mean NCCN of 1628±193 cm−3 at a supersaturation of 1% is higher than anticipated for the marine background. When the number of CCN spectra is 1293, the value of k is 0.57±0.03 (99% confidence interval) and its probability distribution shows cumulative counts significant at k ≈ 0.55±0.25. The results are found to be better at representing the features of the marine environment (103 cm−3 and k ≈ 0.5) and useful for validating CCN closure studies for Indian sea regions.

Aerosol microphysical and radiative effects on continental cloud ensembles

Aerosol–cloud–radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity (typically less than 2%) to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.

Machine Learning to Predict the Global Distribution of Aerosol Mixing State Metrics

Atmospheric aerosols are evolving mixtures of chemical species. In global climate models (GCMs), this “aerosol mixing state” is represented in a highly simplified manner. This can introduce errors in the estimates of climate-relevant aerosol properties, such as the concentration of cloud condensation nuclei. The goal for this study is to determine a global spatial distribution of aerosol mixing state with respect to hygroscopicity, as quantified by the mixing state metric χ . In this way, areas can be identified where the external or internal mixture assumption is more appropriate. We used the output of a large ensemble of particle-resolved box model simulations in conjunction with machine learning techniques to train a model of the mixing state metric χ . This lower-order model for χ uses as inputs only variables known to GCMs, enabling us to create a global map of χ based on GCM data. We found that χ varied between 20% and nearly 100%, and we quantified how this depended on particle diameter, location, and time of the year. This framework demonstrates how machine learning can be applied to bridge the gap between detailed process modeling and a large-scale climate model.

High Sensitivity of Arctic Liquid Clouds to Long‐Range Anthropogenic Aerosol Transport

AbstractThe rate of warming in the Arctic depends upon the response of low‐level microphysical and radiative cloud properties to aerosols advected from distant anthropogenic and biomass‐burning sources. Cloud droplet cross‐section density increases with higher concentrations of cloud condensation nuclei, leading to an increase of cloud droplet absorption and scattering radiative cross sections. The challenge of assessing the magnitude of the effect has been decoupling the aerosol impacts on clouds from how clouds change solely due to natural meteorological variability. Here we address this issue with large, multi‐year satellite, meteorological, and tracer transport model data sets to show that the response of low‐level clouds in the Arctic to anthropogenic aerosols lies close to a theoretical maximum and is between 2 and 8 times higher than has been observed elsewhere. However, a previously described response of arctic clouds to biomass‐burning plumes appears to be overstated because the interactions are rare and modification of cloud radiative properties appears better explained by coincident changes in temperature, humidity, and atmospheric stability.

The seasonal characteristics of cloud condensation nuclei (CCN) in the arctic lower troposphere

Cloud Condensation Nuclei (CCN) concentration and aerosol size distributions in the Arctic were collected during the period 2007–2013 at the Zeppelin observatory (78.91° N, 11.89° E, 474 masl). Annual median CCN concentration at a supersaturation (SS) of 0.4% show the ranges of 45 ∼ 81 cm−3. The monthly median CCN number density varied between 17 cm−3 in October 2007 and 198 cm−3 in March, 2008. The CCN spectra parameters C (83 cm−3) and k (0.23) were derived. In addition, calculated annual median value of hygroscopicity parameter is 0.46 at SS of 0.4%. Particle number concentration of accumulation mode from aerosol size distribution measurements are well correlated with CCN concentration. The CCN to CN>10 nm (particle number concentration larger than 10nm in diameter) ratio shows a maximum during March and minimum during July. The springtime high CCN concentration is attributed to high load of accumulation mode aerosol transported from the mid-latitudes, known as Arctic Haze. CCN concentration remains high also during Arctic summer due to the source of new CCN through particle formation followed by consecutive aerosol growth. Lowest aerosol as well as CCN number densities were observed during Arctic autumn and early winter when aerosol formation in the Arctic and long-range transport into the Arctic are not effective.

Seasonal variations in physical characteristics of aerosol particles at the King Sejong Station, Antarctic Peninsula

Abstract. Seasonal variability in the physical characteristics of aerosol particles sampled from the King Sejong Station in the Antarctic Peninsula was investigated over the period between March 2009 and February 2015. Clear seasonal cycles for the total particle concentration (CN) were observed. The mean monthly concentration of particles larger than 2.5 nm (CN2.5) was highest during the austral summer, with an average value of 1080.39 ± 595.05 cm−3, and lowest during the austral winter, with a mean value of 197.26 ± 71.71 cm−3. The seasonal patterns in the concentrations of cloud condensation nuclei (CCN) and CN coincide, with both concentrations being at a minimum in winter and maximum in summer. The measured CCN spectra were approximated by fitting a power-law function relating the number of CCN for a given supersaturation (SS) to each SS value, with fitting coefficients C and kT. The values for C varied from 6.35 to 837.24 cm−3, with a mean of 171.48 ± 62.00 cm−3. The values for kT ranged from 0.07 to 2.19, with a mean of 0.41 ± 0.10. In particular, the kT values during the austral summer were higher than those during the winter, indicating that aerosol particles are more sensitive to SS changes during summer. Furthermore, the annual mean hygroscopicity parameter, κ, was estimated as 0.15 ± 0.05, for a SS of 0.4 %. The effects of the origin and pathway travelled by the air mass on the physical characteristics of the aerosol particles were also determined. The modal diameter of aerosol particles originating in the South Pacific Ocean showed a seasonal variation varying from 0.023 µm in winter to 0.034 µm in summer for the Aitken mode, and from 0.086 µm in winter to 0.109 µm in summer for the accumulation mode.

Exploring CCN droplet suppression with a higher sensitivity optical particle counter

ABSTRACTThe continuous flow thermal gradient cloud condensation nuclei counter (CCNc) is the instrument currently widely used in exploring the interactions of aerosol with water vapor in the supersaturated regime. In this study we use a CCNc with an optical particle counter (OPC) modified to twice the sensitivity of the default OPC on the standard CCNc built by DMT, Inc. The standard OPC and the modified OPC-β are used to explore the droplet growth of inorganic and organic salts and the effects of cloud condensation nuclei concentrations on the final droplet sizes. We also couple the higher sensitivity OPC-β with the continuous flow streamwise thermal gradient CCNc (CFSTGC) model to estimate the mass accommodation coefficient, α. For inorganic and organic aerosol, a mass accommodation coefficient, α >> 0.2 will yield modeled droplet diameters consistent with experimental and ambient observations. However, using higher sensitivity CCN data, the final droplet diameters of CCN appear independent of aerosol h...

Cloud Condensation Nuclei activity in the tropical marine regions during Indian southwest monsoon

This paper presents the first onboard measurements of cloud condensation nuclei (CCN) distributions at super-saturations (ss) less than 0.5% (0.2% and 0.4%) and more than 0.5% (0.6% and 0.8%) as a function of prevailing winds during July and August over south to southeastern head-Bay region of Bay of Bengal (BoB). During monsoon season of 2012, the cross equatorial flow (CEF) along the belt 50°N–50°S was towards north and prevailing winds were stronger than normal by 2.6ms−1 and 5.14ms−1 respectively. Also, 2 and 5 low-pressure systems were formed during July and August 2012 respectively. Due to the strength of CEF, winds and low-pressure systems, mean value of wind speeds (U) observed onboard the ship during August was found to be stronger than that for July by 28%. As a result, mean values of CCN concentrations in August when winds were above 10ms−1 were higher in magnitude by 9.5%, 15.6%, 13.4%, 12.13% and 11.9% for supersaturations of 0.2%, 0.4%, 0.6%, 0.8% and 1.0% respectively compared to corresponding means of CCN concentration during July when winds were below 10ms−1. Wind-driven (U above 10ms−1) CCN activity is found to be of high CCN concentrations at ss more than 0.5% despite active monsoonal cloud-aerosol interaction in the tropical marine environment. Relationships between CCN concentration and U when winds were above 10ms−1 are found to be log10CCN = 0.057U + 2.4 and log10CCN = 0.047U + 2.6 at ss of 0.6% (R = 0.43) and 0.8% (R = 0.4) respectively, slopes of which appear to be reasonable climatic regulators for wind-induced CCN activity over south to southeastern head-Bay region of BoB.

Aerosol–Cloud Interaction in Deep Convective Clouds over the Indian Peninsula Using Spectral (Bin) Microphysics

Abstract The Weather Research and Forecasting (WRF) Model coupled with a spectral bin microphysics (SBM) scheme is used to investigate aerosol effects on cloud microphysics and precipitation over the Indian peninsular region. The main emphasis of the study is in comparing simulated cloud microphysical structure with in situ aircraft observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX). Aerosol–cloud interaction over the rain-shadow region is investigated with observed and simulated size distribution spectra of cloud droplets and ice particles in monsoon clouds. It is shown that size distributions as well as other microphysical characteristics obtained from simulations such as liquid water content, cloud droplet effective radius, cloud droplet number concentration, and thermodynamic parameters are in good agreement with the observations. It is seen that in clouds with high cloud condensation nuclei (CCN) concentrations, snow and graupel size distribution spectra were broader compared to clouds with low concentrations of CCN, mainly because of enhanced riming in the presence of a large number of droplets with a diameter of 10–30 μm. The Hallett–Mossop ice multiplication process is illustrated to have an impact on snow and graupel mass. The changes in CCN concentrations have a strong effect on cloud properties over the domain, amounts of cloud water, and the glaciation of the clouds, but the effects on surface precipitation are small when averaged over a large area. Overall enhancement of cold-phase cloud processes in the high-CCN case contributed to slight enhancement (5%) in domain-averaged surface precipitation.

Causes and importance of new particle formation in the present‐day and preindustrial atmospheres

AbstractNew particle formation has been estimated to produce around half of cloud‐forming particles in the present‐day atmosphere, via gas‐to‐particle conversion. Here we assess the importance of new particle formation (NPF) for both the present‐day and the preindustrial atmospheres. We use a global aerosol model with parametrizations of NPF from previously published CLOUD chamber experiments involving sulfuric acid, ammonia, organic molecules, and ions. We find that NPF produces around 67% of cloud condensation nuclei at 0.2% supersaturation (CCN0.2%) at the level of low clouds in the preindustrial atmosphere (estimated uncertainty range 45–84%) and 54% in the present day (estimated uncertainty range 38–66%). Concerning causes, we find that the importance of biogenic volatile organic compounds (BVOCs) in NPF and CCN formation is greater than previously thought. Removing BVOCs and hence all secondary organic aerosol from our model reduces low‐cloud‐level CCN concentrations at 0.2% supersaturation by 26% in the present‐day atmosphere and 41% in the preindustrial. Around three quarters of this reduction is due to the tiny fraction of the oxidation products of BVOCs that have sufficiently low volatility to be involved in NPF and early growth. Furthermore, we estimate that 40% of preindustrial CCN0.2% are formed via ion‐induced NPF, compared with 27% in the present day, although we caution that the ion‐induced fraction of NPF involving BVOCs is poorly measured at present. Our model suggests that the effect of changes in cosmic ray intensity on CCN is small and unlikely to be comparable to the effect of large variations in natural primary aerosol emissions.

Top-down and bottom-up aerosol–cloud closure: towards understanding sources of uncertainty in deriving cloud shortwave radiative flux

Abstract. Top-down and bottom-up aerosol–cloud shortwave radiative flux closures were conducted at the Mace Head Atmospheric Research Station in Galway, Ireland, in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) European collaborative project, with the goal of understanding key processes affecting aerosol–cloud shortwave radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based unmanned aerial vehicles (UAVs)1 and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1-D microphysical aerosol–cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction or a five-hole probe for 3-D wind vectors. UAV cloud measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 and 60 W m−2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNCs) were within 30 % of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m−2 after accounting for cloud-top entrainment and up to 50 W m−2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m−2, even high (> 30 W m−2) after accounting for cloud-top entrainment. This work demonstrates the need to take in situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux. 1The regulatory term for UAV is remotely piloted aircraft (RPA).

The role of initial cloud condensation nuclei concentration in hail using the WRF NSSL 2-moment microphysics scheme

The effects of the initial cloud condensation nuclei (CCN) concentrations (100–3000 mg−1) on hail properties were investigated in an idealized non-severe hail storm experiment using theWeather Research and Forecasting (WRF) model, with the National Severe Storms Laboratory 2-moment microphysics scheme. The initial CCN concentration (CCNC) had obvious non-monotonic effects on the mixing ratio, number concentrations, and radius of hail, both in clouds and at the surface, with a CCNC threshold between 300 and 500 mg−1. An increasing CCNC is conducive (suppressive) to the amount of surface hail precipitation below (above) the CCNC threshold. The non-monotonic effects were due to both the thermodynamics and microphysics. Below the CCNC threshold, the mixing ratios of cloud droplets and ice crystals increased dramatically with the increasing CCNC, resulting in more latent heat released from condensation and frozen between 4 and 8 km and intensified updraft volume. The extent of the riming process, which is the primary process for hail production, increased dramatically. Above the CCNC threshold, the mixing ratio of cloud droplets and ice crystals increased continuously, but the maximum updraft volume was weakened because of reduced frozen latent heating at low level. The smaller ice crystals reduced the formation of hail and smaller clouds, with decreased rain water reducing riming efficiency so that graupel and hail also decreased with increasing CCNC, which is unfavorable for hail growth.

Development of a global aerosol model using a two‐dimensional sectional method: 2. Evaluation and sensitivity simulations

AbstractGlobal aerosol simulations are conducted by using the Community Atmosphere Model version 5 with the Aerosol Two‐dimensional bin module for foRmation and Aging Simulation version 2 (CAM5‐chem/ATRAS2) which was developed in part 1. The model uses a two‐dimensional (2‐D) section representation with 12 size bins from 1 nm to 10 μm and 8 black carbon (BC) mixing state bins, and it can calculate detailed aerosol processes and their interactions with radiation and clouds. The simulations have similar or better agreement with aerosol observations (e.g., aerosol optical depth, absorption aerosol optical depth (AAOD), aerosol number concentrations, mass concentrations of each species) compared with the simulations using the Modal Aerosol Model with three modes. Sensitivity simulations show that global mean AAOD is reduced by 15% by resolving BC mixing state as a result of two competing effects (optical and lifetime effects). AAOD is reduced by 10–50% at low and midlatitudes in the 2‐D sectional simulation because BC absorption enhancement by coating species is reduced by resolving pure BC, thinly coated BC, and BC‐free particles in the model (optical effect). In contrast, AAOD is enhanced by 5–30% at high‐latitudes because BC concentrations are enhanced by 40–200% over the regions by resolving less CCN active particles (lifetime effect). The simulations also suggest a model which resolves more than 3 BC categories (including BC‐free particles) is desirable to calculate the optical and lifetime effects accurately. The complexity of aerosol representation is shown to be especially important for simulations of BC and CCN concentrations and AAOD.

A global lightning parameterization based on statistical relationships among environmental factors, aerosols, and convective clouds in the TRMM climatology

AbstractThe objective of this study is to determine the relative contributions of normalized convective available potential energy (NCAPE), cloud condensation nuclei (CCN) concentrations, warm cloud depth (WCD), vertical wind shear (SHEAR), and environmental relative humidity (RH) to the variability of lightning and radar reflectivity within convective features (CFs) observed by the Tropical Rainfall Measuring Mission (TRMM) satellite. Our approach incorporates multidimensional binned representations of observations of CFs and modeled thermodynamics, kinematics, and CCN as inputs to develop approximations for total lightning density (TLD) and the average height of 30 dBZ radar reflectivity (AVGHT30). The results suggest that TLD and AVGHT30 increase with increasing NCAPE, increasing CCN, decreasing WCD, increasing SHEAR, and decreasing RH. Multiple‐linear approximations for lightning and radar quantities using the aforementioned predictors account for significant portions of the variance in the binned data set (R2 ≈ 0.69–0.81). The standardized weights attributed to CCN, NCAPE, and WCD are largest, the standardized weight of RH varies relative to other predictors, while the standardized weight for SHEAR is comparatively small. We investigate these statistical relationships for collections of CFs within various geographic areas and compare the aerosol (CCN) and thermodynamic (NCAPE and WCD) contributions to variations in the CF population in a partial sensitivity analysis based on multiple‐linear regression approximations computed herein. A global lightning parameterization is developed; the average difference between predicted and observed TLD decreases from +21.6 to +11.6% when using a hybrid approach to combine separate approximations over continents and oceans, thus highlighting the need for regionally targeted investigations in the future.

Prediction of size-resolved number concentration of cloud condensation nuclei and long-term measurements of their activation characteristics

Atmospheric aerosol particles acting as cloud condensation nuclei (CCN) are key elements in the hydrological cycle and climate. To improve our understanding of the activation characteristics of CCN and to obtain accurate predictions of their concentrations, a long-term field campaign was carried out in the Yangtze River Delta, China. The results indicated that the CCN were easier to activate in this relatively polluted rural station than in clean (e.g., the Amazon region) or dusty (e.g., Kanpur-spring) locations, but were harder to activate than in more polluted urban areas (e.g., Beijing). An improved method, using two additional parameters—the maximum activation fraction and the degree of heterogeneity, is proposed to predict the accurate, size-resolved concentration of CCN. The value ranges and prediction uncertainties of these parameters were evaluated. The CCN predicted using this improved method with size-resolved chemical compositions under an assumption that all particles were internally mixed showed the best agreement with the long-term field measurements.

A comparison of two chemistry and aerosol schemes on the regional scale and the resulting impact on radiative properties and liquid- and ice-phase aerosol–cloud interactions

Abstract. The complexity of atmospheric aerosol causes large uncertainties in its parameterization in atmospheric models. In a process-based comparison of two aerosol and chemistry schemes within the regional atmospheric modeling framework COSMO-ART (Consortium for Small-Scale Modelling, Aersosol and Reactive Trace gases extension), we identify key sensitivities of aerosol parameterizations. We consider the aerosol module MADE (Modal Aerosol Dynamics model for Europe) in combination with full gas-phase chemistry and the aerosol module M7 in combination with a constant-oxidant-field-based sulfur cycle. For a Saharan dust outbreak reaching Europe, modeled aerosol populations are more sensitive to structural differences between the schemes, in particular the consideration of aqueous-phase sulfate production, the selection of aerosol species and modes, and modal composition, than to parametric choices like modal standard deviation and the parameterization of aerosol dynamics. The same observation applies to aerosol optical depth (AOD) and the concentrations of cloud condensation nuclei (CCN). Differences in the concentrations of ice-nucleating particles (INPs) are masked by uncertainties between two ice-nucleation parameterizations and their coupling to the aerosol scheme. Differences in cloud droplet and ice crystal number concentrations are buffered by cloud microphysics as we show in a susceptibility analysis.