Cloud Drop Number Concentration Research Articles

Secondary droplet activation during condensational growth in convective clouds and its detection from satellites

By acting as cloud condensation nuclei (CCN), aerosol particles play a key role in the climate system. The CCN can be activated into cloud droplets at the cloud base (i.e., primary activation), or above it (i.e., secondary activation). This study shows the conditions required for secondary activation during the condensational growth phase in convective clouds. It also proposes a methodology for detecting this secondary activation from satellites. Using a spectral bin adiabatic parcel model, we simulate the vertical profile of cloud microphysical properties and demonstrate how different aerosol size distributions and updraft velocities greatly affect the secondary activation initiation and the cloud properties. The secondary activation slows down the cloud drop effective radius (re) growth rate with increasing height, and decreasing temperature (T), due to the relatively larger population of smaller droplets in the cloud parcel. Therefore, the vertical profile of re growth with height is slower than the adiabatic rate when the secondary activation occurs.The proposed physical principle was verified by satellite-retrieved T-re profiles and adiabatic cloud drop number concentrations (Nd) over the Amazon region. The results obtained from this study can be utilized to identify the secondary droplet activation during the condensational growth phase, which can lead to an overestimation of the retrieved Nd as well as suppression of warm rain. This improves our knowledge and observational capabilities of the role of aerosol particles in the microphysics, dynamics, and precipitation behavior of convective clouds. Plain text summarySmall particles serve as sites for cloud droplets' condensation at the cloud base (primary droplet activation) or above it (secondary activation). Once a droplet is activated at the cloud base, the surrounding water vapor condenses on it and the droplet grows - this is called condensational growth. The cloud droplet number concentrations (Nd) can be obtained by the satellite-retrieved vertical growth rate of droplet size in the condensational growth phase. However, new small droplets formed during this phase (i.e., secondary activation), might cause an overestimate in the retrieved Nd. This study presents the physical principle of secondary activation during condensational growth. Using a model, we simulate the condensational growth of aerosol particles, which act as cloud condensation nuclei (CCN), for different particle size distributions and thermodynamic conditions (i.e., vertical velocities). Our simulations show that secondary activation slows the cloud droplet growth rate with height due to the larger competition for the available water vapor promoted by the new drops. Comparisons between satellite-retrieved Nd of convective clouds and in-situ measurements show that the satellite retrievals overestimate Nd when the secondary activation of droplets is neglected. Our findings improve the understanding of aerosols' role in the condensational growth of droplets in convective clouds.

Quantifying the dependence of drop spectrum width on cloud drop number concentration for cloud remote sensing

Abstract. In situ measurements of liquid cloud and precipitation drop size distributions from aircraft-mounted probes are used to examine the relationship of the width of drop size distributions to cloud drop number. The width of the size distribution is quantified in terms of the parameter k=(rv/re)3, where rv is the volume mean radius and re is the effective radius of the distributions. We find that on small spatial scales (∼100 m), k is positively correlated with cloud drop number. This correlation is robust across a variety of campaigns using different probe technology. A new parameterization of k versus cloud drop number is developed. This new parameterization of k is used in an algorithm to derive cloud drop number in liquid phase clouds using satellite measurements of cloud optical depth and effective radius from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor on Aqua. This algorithm is compared to the standard approach to derive drop number concentration that assumes a fixed value for k. The general tendency of the parameterization is to narrow the distribution of derived number concentration. The new parameterization generally increases the derived number concentration over ocean, where N is low, and decreases it over land, where N is high. Regional biases are as large as 20 % with the magnitude of the bias closely tracking the regional mean number concentration. Interestingly, biases are smallest in regions of frequent stratocumulus cloud cover, which are a regime of significant interest for study of the aerosol indirect effect on clouds.

Frontiers in Satellite‐Based Estimates of Cloud‐Mediated Aerosol Forcing

AbstractAtmospheric aerosols affect the Earth's climate in many ways, including acting as the seeds on which cloud droplets form. Since a large fraction of these particles is anthropogenic, the clouds' microphysical and radiative characteristics are influenced by human activity on a global scale leading to important climatic effects. The respective change in the energy budget at the top of the atmosphere is defined as the effective radiative forcing due to aerosol‐cloud interaction (ERFaci). It is estimated that the ERFaci offsets presently nearly 1/4 of the greenhouse‐induced warming, but the uncertainty is within a factor of two. A common method to calculate the ERFaci is by the multiplication of the susceptibility of the cloud radiative effect to changes in aerosols by the anthropogenic change of the aerosol concentration. This has to be done by integrating it over all cloud regimes. Here we review the various methods of the ERFaci estimation. Global measurements require satellites' global coverage. The challenge of quantifying aerosol amounts in cloudy atmospheres are met with the rapid development of novel methodologies reviewed here. The aerosol characteristics can be retrieved from space based on their optical properties, including polarization. The concentrations of the aerosols that serve as cloud drop condensation nuclei can be also estimated from their impact on the satellite‐retrieved cloud drop number concentrations. These observations are critical for reducing the uncertainty in the ERFaci calculated from global climate models (GCMs), but further development is required to allow GCMs to properly simulate and benefit these novel observables.

Tracing the Rain Formation Pathways in Numerical Simulations of Deep Convection

AbstractQuantifying the microphysical process contributions to surface precipitation in numerical simulations can be challenging. This is due to the fact that many microphysical processes contribute to the formation and depletion of rain drops and there is almost always a spatial/temporal mismatch between where/when rain is formed and where/when it strikes the surface. In this work, we develop a tracing method that tracks the sources and sinks of raindrop mass and number as they are advected by the Weather Research and Forecasting model. Applying the method to an idealized squall line confirms that convective precipitation is dominated by warm rain processes (autoconversion and accretion) while stratiform precipitation is dominated by the melting of rimed and unrimed ice crystals. Sensitivity experiments in which the prescribed cloud drop number concentration is increased confirm the conventional wisdom that weakened autoconversion increases the fraction of raindrops originating from cold rain processes. The method also reveals that when applied to deep convection the Khairoutdinov and Kogan autoconversion scheme produces an excessive number of raindrops which are subsequently clipped in P3 microphysics to keep the rain size distribution within prescribed limits. This problem can mostly be mitigated by increasing the assumed radius for raindrops created by autoconversion.

Numerical Simulations of Cloud Number Concentration and Ice Nuclei Influence on Cloud Processes and Seeding Effects

Aerosols, through cloud condensation nuclei (CCN) or ice nuclei (IN), affect cloud microphysics. With increasing concentrations of aerosols, it is important to consider the impact of IN along with CCN on clouds and precipitation in numerical simulations; further, aerosols may also affect the weather-modification seeding effect. On the basis of the observation of natural IN concentration and cloud-drop number concentrations, numerical sensitivity experiments for a snowfall case were designed to study the effects of parameters of IN and cloud number concentrations at the cloud base to consider the CCN effects on clouds and precipitation as well as weather-modification seeding effects. Generally, with smaller cloud-drop number concentration, the mass contents were much lower. With more ice nuclei, more ice crystals were able to nucleate, and additional snow particles were generated through ice crystals. Cloud-drop number concentrations heavily affected the location and amount of snowfall. During the 1e9 test, 2.4 mm was the highest reduction in the amount of snowfall; additionally, the amount of snowfall from the combined impacts of increased IN and cloud-drop number decreased in wide areas, and its maximum precipitation reduction exceeded 2.7 mm as well as up to 15% of the daily amount of snowfall. More IN reduced the artificial seeding effect, lowered the increase in snowfall in the center of the seeding, and lowered the reduction of snowfall in the reduction center of the seeding. With more IN, the seeding effect was able to shift approximately 0.6% from the 3.9% seeding effect of the control simulation.

A Lagrangian analysis of pockets of open cells over the southeastern Pacific

Abstract. Pockets of open cells (POCs) have been shown to develop within closed-cell stratocumulus (StCu), and a large body of evidence suggests that the development of POCs result from changes in small-scale processes internal to the boundary layer rather than large-scale forcings. Precipitation is widely viewed as a key process important to POC development and maintenance. In this study, GOES-16 satellite observations are used in conjunction with MERRA-2 winds to track and compare the microphysical and environmental evolution of two populations of closed-cell StCu selected by visual inspection over the southeastern Pacific Ocean: one group that transitions to POCs and another comparison group (CLOSED) that does not. The high spatiotemporal resolution of the new GOES-16 data allows for a detailed examination of the temporal evolution of POCs in this region. We find that POCs tend to develop near the coast, last tens of hours, are larger than 104 km2, and often (88 % of cases) do not re-close before they exit the StCu deck. Most POCs are observed to form at night and tend to exit the StCu during the day when the StCu is contracting in area. Relative to the CLOSED trajectories, POCs have systematically larger effective radii, lower cloud drop number concentrations, a comparable conditional in-cloud liquid water path, and a higher frequency of more intense precipitation. Meanwhile, no systematic environmental differences other than boundary layer height are observed between POC and CLOSED trajectories. Interestingly, there are no differences in reanalysis aerosol optical depth between both sets of trajectories, which may lead one to the interpretation that differences in aerosol concentrations are not influencing POC development or resulting in a large number that re-close. However, this largely depends on the reanalysis treatment of aerosol–cloud interactions, and the product used in this study has no explicit handling of these important processes. These results support the consensus view regarding the importance of precipitation on the formation and maintenance of POCs and demonstrate the utility of modern geostationary remote sensing data in evaluating the POC life cycle.

Biomass Burning Over the United States East Coast and Western North Atlantic Ocean: Implications for Clouds and Air Quality.

Biomass burning (BB) aerosol events were characterized over the U.S. East Coast and Bermuda over the western North Atlantic Ocean (WNAO) between 2005 and 2018 using a combination of ground-based observations, satellite data, and model outputs. Days with BB influence in an atmospheric column (BB days) were identified using criteria biased toward larger fire events based on anomalously high AERONET aerosol optical depth (AOD) and MERRA-2 black carbon (BC) column density. BB days are present year-round with more in June-August (JJA) over the northern part of the East Coast, in contrast to more frequent events in March-May (MAM) over the southeast U.S. and Bermuda. BB source regions in MAM are southern Mexico and by the Yucatan, Central America, and the southeast U.S. JJA source regions are western parts of North America. Less than half of the BB days coincide with anomalously high PM2.5 levels in the surface layer, according to data from 14 IMPROVE sites over the East Coast. Profiles of aerosol extinction suggest that BB particles can be found in the boundary layer and into the upper troposphere with the potential to interact with clouds. Higher cloud drop number concentration and lower drop effective radius are observed during BB days. In addition, lower liquid water path is found during these days, especially when BB particles are present in the boundary layer. While patterns are suggestive of cloud-BB aerosol interactions over the East Coast and the WNAO, additional studies are needed for confirmation.

Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors.

Cloud drop number concentrations (Nd) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing Nd on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-Nd days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-Nd days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing Nd to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to Nd for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol–Nd relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of Nd.

Quantification of the Radiative Effect of Aerosol–Cloud Interactions in Shallow Continental Cumulus Clouds

Abstract The indirect radiative effect of aerosol variability on shallow cumulus clouds is realized in nature with considerable concurrent meteorological variability. Large-eddy simulations constrained by observations at a continental site in Oklahoma are performed to represent the variability of different meteorological states on days with different aerosol conditions. The total radiative effect of this natural covariation between aerosol and other meteorological drivers of total cloud amount and albedo is quantified. The changes to these bulk quantities are used to understand the response of the cloud radiative effect to aerosol–cloud interactions (ACI) in the context of concurrent processes, as opposed to attempting to untangle the effect of individual processes on a case-by-case basis. Mutual information (MI) analysis suggests that meteorological variability masks the strength of the relationship between cloud drop number concentration and the cloud radiative effect. This is shown to be mostly due to variation in solar zenith angle and cloud field horizontal heterogeneity masking the relationship between cloud drop number and cloud albedo. By combining MI and more traditional differential analyses, a framework to identify important modes of covariation between aerosol, clouds, and meteorological conditions is developed. This shows that accounting for solar zenith angle variation and implementing an albedo bias correction increases the detectability of the radiative effects of ACI in simulations of shallow cumulus.

A Two-Moment Bulk Parameterization of the Drop Collection Growth in Warm Clouds

Abstract To improve the modeling of warm rain initiation, a two-moment bulk parameterization of the drop collection growth in warm clouds is developed by two steps: (i) its prototype is first derived based on the analytic solution of the stochastic collection equation (SCE) with the Golovin kernel, and (ii) the prototype is then revamped empirically to fit the numerical solution of SCE with the real hydrodynamic collection kernel, reaching the final version of the parameterization. Since the final version represents the self-collection of cloud drops explicitly, it replicates warm rain initiation well even when liquid water content (cloud-drop number concentration) is very low (high). It also replicates the autoconversion threshold and time delay of rain initiation via a small autoconversion rate.

On the Covariability of Cloud and Rain Water as a Function of Length Scale

AbstractMicrophysics parameterizations in large-scale models often account for subgrid variability in the calculation of process rates by integrating over assumed subgrid distributions of the input variables. The variances and covariances that define distribution width may be specified or diagnosed. The correlation ρ of cloud and rain mass mixing ratio/liquid water content (LWC) is a key input for accurate prediction of the accretion rate and a constant value is typically assumed. In this study, high-frequency aircraft measurements with a spatial resolution of ≈22 cm are used to evaluate the scaling behavior of cloud and rain LWC (qc and qr, respectively) and to demonstrate how and why covariability varies with length scale ℓ. It is shown that power spectral densities of both qc and qr exhibit scale invariance across a wide range of scales (2.04–142 m for qc; 33–1.45 × 104 m for qr). Because the cloud–rain cospectrum is also scale invariant, ρ is therefore expected to vary with ℓ. Direct calculation of ρ shows that it generally increases with ℓ, but there is significant variability in the ρ–ℓ relationship that primarily depends on cloud drop number concentration N and cloud cellular organization, suggesting that ρ may also vary with cloud regime. A parameterization of ρ as a function of ℓ and N is developed from aircraft observations and implications for diagnosis of ρ from limited-area model output are also discussed.

Aerosol influences on low-level clouds in the West African monsoon

Abstract. Low-level clouds (LLCs) cover a wide area of southern West Africa (SWA) during the summer monsoon months and have an important cooling effect on the regional climate. Previous studies of these clouds have focused on modelling and remote sensing via satellite. We present the first comprehensive set of in situ measurements of cloud microphysics from the region, taken during June–July 2016, as part of the DACCIWA (Dynamics–aerosol–chemistry–cloud interactions in West Africa) campaign. This novel dataset allows us to assess spatial, diurnal, and day-to-day variation in the properties of these clouds over the region. LLCs developed overnight and mean cloud cover peaked a few hundred kilometres inland around 10:00 local solar time (LST), before clouds began to dissipate and convection intensified in the afternoon. Regional variation in LLC cover was largely orographic, and no lasting impacts in cloud cover related to pollution plumes were observed downwind of major population centres. The boundary layer cloud drop number concentration (CDNC) was locally variable inland, ranging from 200 to 840 cm−3 (10th and 90th percentiles at standard temperature and pressure), but showed no systematic regional variations. Enhancements were seen in pollution plumes from the coastal cities but were not statistically significant across the region. A significant fraction of accumulation mode aerosols, and therefore cloud condensation nuclei, were from ubiquitous biomass burning smoke transported from the Southern Hemisphere. To assess the relative importance of local and transported aerosol on the cloud field, we isolated the local contribution to the aerosol population by comparing inland and offshore size and composition measurements. A parcel model sensitivity analysis showed that doubling or halving local emissions only changed the calculated cloud drop number concentration by 13 %–22 %, as the high background meant local emissions were a small fraction of total aerosol. As the population of SWA grows, local emissions are expected to rise. Biomass burning smoke transported from the Southern Hemisphere is likely to dampen any effect of these increased local emissions on cloud–aerosol interactions. An integrative analysis between local pollution and Central African biomass burning emissions must be considered when predicting anthropogenic impacts on the regional cloud field during the West African summer monsoon.

Efficient Determination of Cloud Drop Number Concentration Near the Cloud Base With Parameterization Based on Fundamental Theory and Parcel Model Simulations

AbstractAn effective parameterization scheme for determining the maximum cloud drop number concentration near the cloud base under given updraft speeds was developed based on a theoretical analysis of the supersaturation development equation with key factors determined from a binned microphysical parcel model. This scheme is mathematically quite straightforward and can be applied to condensation nuclei of any composition and size spectrum. The accuracy of this method is comparable with the most advanced schemes currently available, but it features considerably higher computational efficiency. Sources of error or uncertainty in our scheme are discussed in details.

Comparison of Observed and Simulated Drop Size Distributions from Large-Eddy Simulations with Bin Microphysics

Abstract Two case studies of marine stratocumulus (one nocturnal and drizzling, the other daytime and nonprecipitating) are simulated by the UCLA large-eddy simulation model with bin microphysics for comparison with aircraft in situ observations. A high-bin-resolution variant of the microphysics is implemented for closer comparison with cloud drop size distribution (DSD) observations and a turbulent collision–coalescence kernel to evaluate the role of turbulence on drizzle formation. Simulations agree well with observational constraints, reproducing observed thermodynamic profiles (i.e., liquid water potential temperature and total moisture mixing ratio) as well as liquid water path. Cloud drop number concentration and liquid water content profiles also agree well insofar as the thermodynamic profiles match observations, but there are significant differences in DSD shape among simulations that cause discrepancies in higher-order moments such as sedimentation flux, especially as a function of bin resolution. Counterintuitively, high-bin-resolution simulations produce broader DSDs than standard resolution for both cases. Examination of several metrics of DSD width and percentile drop sizes shows that various discrepancies of model output with respect to the observations can be attributed to specific microphysical processes: condensation spuriously creates DSDs that are too wide as measured by standard deviation, which leads to collisional production of too many large drops. The turbulent kernel has the greatest impact on the low-bin-resolution simulation of the drizzling case, which exhibits greater surface precipitation accumulation and broader DSDs than the control (quiescent kernel) simulations. Turbulence effects on precipitation formation cannot be definitively evaluated using bin microphysics until the artificial condensation broadening issue has been addressed.

Under What Conditions Can We Trust Retrieved Cloud Drop Concentrations in Broken Marine Stratocumulus?

AbstractIn this study, we show how to obtain more reliable satellite‐retrieved cloud drop number concentrations (Nd) from Moderate Resolution Imaging Spectroradiometer (MODIS) standard cloud products. Nd is important as a fundamental cloud property that determines cloud albedo, precipitation‐forming processes, cloud longevity, and fractional cover, all of which determine cloud radiative effects. Nd is determined by cloud base aerosols and updrafts. Satellite retrievals of Nd for marine stratocumulus clouds are performed based on the assumption of a nearly adiabatic cloud column. The retrievals, however, are fraught with problems that cause large biases (e.g., the retrieved Nd for partially filled cloudy pixels are less than one third of the retrieved Nd for the convective cores) and limit the usefulness of Nd, especially in broken cloud fields. The Nd of the brightest 10% of cloudy pixels are selected because the brightest clouds are the convective cores that most closely follow adiabatic parcels, a key assumption of our retrieval. It is shown that this criterion is representative of pixels that are also fully surrounded by cloudy pixels (Nd agreement within 5%).

Relationships between giant sea salt particles and clouds inferred from aircraft physicochemical data

AbstractThis study uses airborne data from multiple field campaigns off the California coast to determine the extent to which a size distribution parameter and a cloud water chemical measurement can capture the effect of giant cloud condensation nuclei (GCCN), specifically sea salt, on marine stratocumulus cloud properties. The two GCCN proxy variables, near‐surface particle number concentration for diameters >5 µm and cloud water chloride concentration, are significantly correlated (95% confidence) with each other, and both exhibit expected relationships with other parameters (e.g., surface wind) that typically coincide with sea salt emissions. Factors influencing the relationship between these two GCCN proxy measurements include precipitation rate (R) and the standard deviation of the subcloud vertical velocity owing likely to scavenging effects and improved mixing/transport of sea salt to cloud base, respectively. When comparing 12 pairs of high and low chloride cloud cases (at fixed liquid water path and cloud drop number concentration), the average drop spectra for high chloride cases exhibit enhanced drop number at diameters exceeding 20 µm, especially above 30 µm. In addition, high chloride cases coincide with enhanced mean columnar R and negative values of precipitation susceptibility. The difference in drop effective radius between high and low chloride conditions decreases with height in cloud, suggesting that some GCCN‐produced raindrops precipitate before reaching cloud tops. The sign of cloud responses (i.e., R) to perturbations in giant sea salt particle concentration, as evaluated from Modern Era Retrospective Analysis for Research and Applications version 2 reanalysis data, is consistent with the aircraft data.

Aerosol measurements during COPE: composition, size, and sources of CCN and INPs at the interface between marine and terrestrial influences

Abstract. Heavy rainfall from convective clouds can lead to devastating flash flooding, and observations of aerosols and clouds are required to improve cloud parameterisations used in precipitation forecasts. We present measurements of boundary layer aerosol concentration, size, and composition from a series of research flights performed over the southwest peninsula of the UK during the COnvective Precipitation Experiment (COPE) of summer 2013. We place emphasis on periods of southwesterly winds, which locally are most conducive to convective cloud formation, when marine air from the Atlantic reached the peninsula. Accumulation-mode aerosol mass loadings were typically 2–3 µg m−3 (corrected to standard cubic metres at 1013.25 hPa and 273.15 K), the majority of which was sulfuric acid over the sea, or ammonium sulfate inland, as terrestrial ammonia sources neutralised the aerosol. The cloud condensation nuclei (CCN) concentrations in these conditions were  ∼  150–280 cm−3 at 0.1 % and 400–500 cm−3 at 0.9 % supersaturation (SST), which are in good agreement with previous Atlantic measurements, and the cloud drop concentrations at cloud base ranged from 100 to 500 cm−3. The concentration of CCN at 0.1 % SST was well correlated with non-sea-salt sulfate, meaning marine sulfate formation was likely the main source of CCN. Marine organic aerosol (OA) had a similar mass spectrum to previous measurements of sea spray OA and was poorly correlated with CCN. In one case study that was significantly different to the rest, polluted anthropogenic emissions from the southern and central UK advected to the peninsula, with significant enhancements of OA, ammonium nitrate and sulfate, and black carbon. The CCN concentrations here were around 6 times higher than in the clean cases, and the cloud drop number concentrations were 3–4 times higher. Sources of ice-nucleating particles (INPs) were assessed by comparing different parameterisations used to predict INP concentrations, using measured aerosol concentrations as input. The parameterisations based on total aerosol produced INP concentrations that agreed within an order of magnitude with measured first ice concentrations at cloud temperatures as low as −12 °C. Composition-specific parameterisations for mineral dust, fluorescent particles, and sea spray OA were 3–4 orders of magnitude lower than the measured first ice concentrations, meaning a source of INPs was present that was not characterised by our measurements and/or one or more of the composition-specific parameterisations greatly underestimated INPs in this environment.

Simulated 2050 aviation radiative forcing from contrails and aerosols

Abstract. The radiative forcing from aviation-induced cloudiness is investigated by using the Community Atmosphere Model Version 5 (CAM5) in the present (2006) and the future (through 2050). Global flight distance is projected to increase by a factor of 4 between 2006 and 2050. However, simulated contrail cirrus radiative forcing in 2050 can reach 87 mW m−2, an increase by a factor of 7 from 2006, and thus does not scale linearly with fuel emission mass. This is due to non-uniform regional increase in air traffic and different sensitivities for contrail radiative forcing in different regions. CAM5 simulations indicate that negative radiative forcing induced by the indirect effect of aviation sulfate aerosols on liquid clouds in 2050 can be as large as −160 mW m−2, an increase by a factor of 4 from 2006. As a result, the net 2050 radiative forcing of contrail cirrus and aviation aerosols may have a cooling effect on the planet. Aviation sulfate aerosols emitted at cruise altitude can be transported down to the lower troposphere, increasing the aerosol concentration, thus increasing the cloud drop number concentration and persistence of low-level clouds. Aviation black carbon aerosols produce a negligible net forcing globally in 2006 and 2050 in this model study. Uncertainties in the methodology and the modeling are significant and discussed in detail. Nevertheless, the projected percentage increase in contrail radiative forcing is important for future aviation impacts. In addition, the role of aviation aerosols in the cloud nucleation processes can greatly influence on the simulated radiative forcing from aircraft-induced cloudiness and even change its sign. Future research to confirm these results is necessary.

How sensitive are aerosol‐precipitation interactions to the warm rain representation?

AbstractIt is widely acknowledged that aerosol‐cloud interactions are a major uncertainty in climate and numerical weather prediction. One of the sources of uncertainty is the sensitivity of the cloud microphysics parameterization to changes in aerosol, in particular the response of precipitation. In this work, we conduct an idealized, dynamically consistent, intercomparison of warm rain microphysics schemes to understand this source of uncertainty. The aims of this investigation are: (i) investigate how sensitive precipitation susceptibility (S0) is to cloud microphysics representation and (ii) use S0 to determine the minimum complexity of microphysics required to produce a consistent precipitation response to changes in cloud drop number concentration (Nd). The main results from this work are: (i) over a large range of liquid water path and Nd, all the bulk schemes, but particularly the single moment schemes, artificially produce rain too rapidly. Relative to a reference bin microphysics scheme, this leads to a low in‐cloud S0 and impacts the evolution of S0 over time. (ii) Rain evaporation causes surface S0 from all schemes to be larger than the cloud base S0. The magnitude of the change in S0 with altitude is dependent on the scheme and the representation of the rain drop size distribution. Overall, we show that single‐moment schemes produce the largest range in the sensitivity of precipitation to changes in Nd. Modifying rain production parameterization alone does not reduce this spread. Instead, increasing the complexity of the rain representation to double‐moment significantly improves this behavior and the overall consistency between schemes.

Global observations of aerosol-cloud-precipitation-climate interactions

Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects of meteorology from those of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing. Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol-cloud-precipitation-climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing.