Cloud Droplet Effective Radius Research Articles

Opposite effects of aerosols and meteorological parameters on warm clouds in two contrasting regions over eastern China

Abstract. The sensitivity (S) of cloud parameters to the influence of different aerosol and meteorological parameters has in most previous aerosol–cloud interaction (aci) studies been addressed using traditional statistical methods. In the current study, relationships between cloud droplet effective radius (CER) and aerosol optical depth (AOD, used as a proxy for cloud condensation nuclei, CCN), i.e., the sensitivity (S) of CER to AOD, are investigated with different constraints of AOD and cloud liquid water path (LWP). In addition to traditional statistical methods, the geographical detector method (GDM) is applied in this study to quantify the relative importance of the effects of aerosol and meteorological parameters, as well as their interaction, on S. Moderate Resolution Imaging Spectroradiometer (MODIS) C6 L3 data and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-5 reanalysis data, for the period from 2008 to 2022, were used to investigate aci over eastern China. Two contrasting areas were selected: the heavily polluted Yangtze River Delta (YRD) and a relatively clean area over the East China Sea (ECS). Linear regression analysis shows that CER decreases with the increase in AOD (negative S) in the moderately polluted atmosphere (0.1<AOD<0.3) over the ECS, whereas, in contrast, CER increases with increasing AOD (positive S) in the polluted atmosphere (AOD>0.3) over the YRD. Evaluation of S as function of the LWP shows that in the moderately polluted atmosphere over the ECS, S is negative in the LWP interval [40 g m−2, 200 g m−2], and the sensitivity of CER to AOD is substantially stronger as LWP is larger. In contrast, in the polluted atmosphere over the YRD, S is positive in the LWP interval [0 g m−2, 120 g m−2] and does not change notably as function of LWP in this interval. The study further shows that over the ECS, the CER is larger for higher low tropospheric stability (LTS) and relative humidity (RH) but lower for higher pressure vertical velocity (PVV). Over the YRD, there is no significant influence of LTS on the relationship between CER and AOD. The GDM has been used as an independent method to analyze the sensitivity of cloud parameters to AOD and meteorological parameters (RH, LTS and PVV). The GDM has also been used to analyze the effects of interactions between two parameters and thus obtain information on confounding meteorological effects on the aci. Over the ECS, cloud parameters are sensitive to almost all parameters considered except for cloud top pressure (CTP), and the sensitivity to AOD is larger than that to any of the meteorological factors. Among the meteorological factors, the cloud parameters are most sensitive to PVV and least sensitive to RH. Over the YRD, the explanatory power of the sensitivity of cloud parameters to AOD and meteorological parameters is much smaller than over the ECS, except for RH, which has a statistically significant influence on CTP and can explain 74 % of the variation of CTP. The results from the GDM analysis show that cloud parameters are more sensitive to the combination of aerosol and a meteorological parameter than to each parameter alone, but confounding effects due to co-variation of both parameters cannot be excluded.

A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations

Abstract. The effective radiative forcing (ERF) due to aerosol–cloud interactions (ACIs) and rapid adjustments (ERFaci) still causes the largest uncertainty in the assessment of climate change. It is understood only with medium confidence and is studied primarily for warm clouds. Here, we present a novel cloud-by-cloud (C×C) approach for studying ACI in satellite observations that combines the concentration of cloud condensation nuclei (nCCN) and ice nucleating particles (nINP) from polar-orbiting lidar measurements with the development of the properties of individual clouds by tracking them in geostationary observations. We present a step-by-step description for obtaining matched aerosol–cloud cases. The application to satellite observations over central Europe and northern Africa during 2014, together with rigorous quality assurance, leads to 399 liquid-only clouds and 95 ice-containing clouds that can be matched to surrounding nCCN and nINP respectively at cloud level. We use this initial data set for assessing the impact of changes in cloud-relevant aerosol concentrations on the cloud droplet number concentration (Nd) and effective radius (reff) of liquid clouds and the phase of clouds in the regime of heterogeneous ice formation. We find a Δln⁡Nd/Δln⁡nCCN of 0.13 to 0.30, which is at the lower end of commonly inferred values of 0.3 to 0.8. The Δln⁡reff/Δln⁡nCCN between −0.09 and −0.21 suggests that reff decreases by −0.81 to −3.78 nm per increase in nCCN of 1 cm−3. We also find a tendency towards more cloud ice and more fully glaciated clouds with increasing nINP that cannot be explained by the increasingly lower cloud top temperature of supercooled-liquid, mixed-phase, and fully glaciated clouds alone. Applied to a larger number of observations, the C×C approach has the potential to enable the systematic investigation of warm and cold clouds. This marks a step change in the quantification of ERFaci from space.

Process Modeling of Aerosol‐Cloud Interaction in Summertime Precipitating Shallow Cumulus Over the Western North Atlantic

AbstractProcess modeling of Aerosol‐cloud interaction (ACI) is essential to bridging gaps between observational analysis and climate modeling of aerosol effects in the Earth system and eventually reducing climate projection uncertainties. In this study, we examine ACI in summertime precipitating shallow cumuli observed during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). Aerosols and precipitating shallow cumuli were extensively observed with in‐situ and remote‐sensing instruments during two research flight cases on 02 June and 07 June, respectively, during the ACTIVATE summer 2021 deployment phase. We perform observational analysis and large‐eddy simulation (LES) of aerosol effect on precipitating cumulus in these two cases. Given the measured aerosol size distributions and meteorological conditions, LES is able to reproduce the observed cloud properties by aircraft such as liquid water content (LWC), cloud droplet number concentration (Nc) and effective radius reff. However, it produces smaller liquid water path (LWP) and larger Nc compared to the satellite retrievals. Both 02 and 07 June cases are over warm waters of the Gulf Stream and have a cloud top height over 3 km, but the 07 June case is more polluted and has larger LWC. We find that the Na‐induced LWP adjustment is dominated by precipitation feedback for the 2 June precipitating case and there is no clear entrainment feedback in both cases. An increase of cloud fraction due to a decrease of aerosol number concentration is also shown in the simulations for the 02 June case.

A Method for Retrieving Cloud Microphysical Properties Using Combined Measurement of Millimeter-Wave Radar and Lidar

Clouds are an important component of weather systems and are difficult to effectively characterize using current climate models and estimation of radiative forcing. Due to the limitations in observational capabilities, it remains difficult to obtain high-spatiotemporal-resolution, continuous, and accurate observations of clouds. To overcome this issue, we propose a novel and practical combined retrieval method using millimeter-wave radar and lidar, which enables the microphysical properties of thin liquid water clouds, such as cloud droplet effective radius, number concentration, and liquid water content, to be retrieved. This method was utilized to analyze the clouds observed at the Shanghai World Expo Park and was validated through synchronous observations with a microwave radiometer. Furthermore, the most suitable extinction backscatter ratio was determined through sensitivity analysis. This study provides vertical distributions of cloud microphysical properties with a time resolution of 1 min and a spatial resolution of 30 m, demonstrating the scientific potential of this combined retrieval method.

Machine Learning Approach to Investigating the Relative Importance of Meteorological and Aerosol-Related Parameters in Determining Cloud Microphysical Properties

Aerosol effects on cloud properties are notoriously difficult to disentangle from variations driven by meteorological factors. Here, a machine learning model is trained on reanalysis data and satellite retrievals to predict cloud microphysical properties, as a way to illustrate the relative importance of meteorology and aerosol, respectively, on cloud properties. It is found that cloud droplet effective radius can be predicted with some skill from only meteorological information, including estimated air mass origin and cloud top height. For ten geographical regions the mean coefficient of determination is 0.41 and normalised root-mean square error 24%. The machine learning model thereby performs better than a reference linear regression model, and a model predicting the climatological mean. A gradient boosting regression performs on par with a neural network regression model. Adding aerosol information as input to the model improves its skill somewhat, but the difference is small and the direction of the influence of changing aerosol burden on cloud droplet effective radius is not consistent across regions, and thereby also not always consistent with what is expected from cloud brightening.

Aerosol effects on liquid cloud microphysical properties in south China: Land–ocean contrasts

The aerosol effects on liquid cloud microphysical properties over South China and adjacent ocean regions are investigated by using aerosol reanalysis data from MERRA-2, cloud property data from CLARA-A2, and reanalysis data from ERA5 from 1995 to 2015. The aerosol optical depth (AOD) in South China and adjacent ocean regions shows an upward trend with obvious land–ocean contrasts. The AOD is significantly positively correlated with the liquid cloud droplet effective radius (LREF) over both land and the ocean in summer and autumn, while increasing AOD significantly suppresses the LREF in spring and winter over land. This indicates that the thermal supply is likely the reason for the differences in aerosol effects on liquid cloud properties in different seasons. The weak correlation between the AOD and LREF over the ocean in spring may be because the South China Sea monsoon onset increases the atmospheric instability, and springtime in southeastern China is characterized by high rainfall. This indicates that the effects of aerosols on clouds are not as significant as those on large-scale systems. Further analysis shows that the aerosol effects on the liquid cloud properties are strong and positive at low liquid water paths (LWP) in summer and autumn, while the effect is weak at high LWPs. This may be due to the presence of sufficient liquid water droplets with large LWPs in summer and autumn, and few liquid water droplets in spring and winter. The aerosol effects on liquid cloud properties also significantly depend on lower-tropospheric stability (LTS).

Characterization of the aerosol vertical distributions and their impacts on warm clouds based on multi-year ARM observations

Aerosol vertical distribution plays a crucial role in cloud development and thus precipitation since both aerosol indirect and semi-direct effects significantly depend on the relative position of aerosol layer in reference to cloud, but its precise influence on cloud remains unclear. In this study, we integrated multi-year Raman Lidar measurements of aerosol vertical profiles from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) facility with available Value-Added Products of cloud features to characterize aerosol vertical distributions and their impacts on warm clouds over the continental and marine ARM atmospheric observatories, i.e., Southern Great Plains (SGP) and Eastern North Atlantic (ENA). A unimodal seasonal distribution of aerosol optical depths (AODs) with a peak in summer is found at upper boundary layer over SGP, while a bimodal distribution is observed at ENA for the AODs at lower levels with a major winter-spring maximum. The diurnal mean of upper-level AOD at SGP shows a maximum in the early evening. According to the relative positions of aerosol layers to clouds we further identify three primary types of aerosol vertical distribution, including Random, Decreasing, and Bottom. It is found that the impacts of aerosols on cloud may or may not vary with aerosol vertical distribution depending on environmental conditions, as reflected by the wide variations of the relations between AOD and cloud properties. For example, as AOD increases, the liquid water paths (LWPs) tend to be reduced at SGP but enhanced at ENA. The relations of cloud droplet effective radius with AOD largely depend on aerosol vertical distributions, particularly showing positive values in the Random type under low-LWP condition (<50 g m−2). The distinct features of aerosol-cloud interactions in relation to aerosol vertical distribution are likely attributed to the continental-marine contrast in thermodynamic environments and aerosol conditions between SGP and ENA.

Detection of large-scale cloud microphysical changes within a major shipping corridor after implementation of the International Maritime Organization 2020 fuel sulfur regulations

Abstract. New regulations from the International Maritime Organization (IMO) limiting sulfur emissions from the shipping industry are expected to have large benefits in terms of public health but may come with an undesired side effect: acceleration of global warming as the climate-cooling effects of ship pollution on marine clouds are diminished. Previous work has found a substantial decrease in the detection of ship tracks in clouds after the IMO 2020 regulations went into effect, but changes in large-scale cloud properties have been more equivocal. Using a statistical technique that estimates counterfactual fields of what large-scale cloud and radiative properties within an isolated shipping corridor in the southeastern Atlantic would have been in the absence of shipping, we confidently detect a reduction in the magnitude of cloud droplet effective radius decreases within the shipping corridor and find evidence for a reduction in the magnitude of cloud brightening as well. The instantaneous radiative forcing due to aerosol–cloud interactions from the IMO 2020 regulations is estimated as O(1 W m−2) within the shipping corridor, lending credence to global estimates of O(0.1 W m−2). In addition to their geophysical significance, our results also provide independent evidence for general compliance with the IMO 2020 regulations.

Evaluation of the spectral misalignment on the Earth Clouds, Aerosols and Radiation Explorer/multi-spectral imager cloud product

Abstract. A cloud identification and profiling algorithm is being developed for the multi-spectral imager (MSI), which is one of the four instruments that the Earth Clouds, Aerosols, and Radiation Explorer (EarthCARE) spacecraft will feature. During recent work, we noticed that the MSI response function could shift substantially among some wavelengths (0.67 and 1.65 µm bands) owing to the spectral misalignment (SMILE), in which a shift in the center wavelength appears as a distortion in the spectral image. We evaluated how SMILE affects the cloud retrieval product qualitatively and quantitatively. We chose four detector pixels from bands 1 and 3 with the nadir pixel as the reference to elucidate how the SMILE error affects the cloud optical thickness (τ) and effective cloud droplet radius (re) by simulating the MSI forward radiation with Comprehensive Analysis Program for Cloud Optical Measurement (CAPCOM). We also evaluated the error in simulated scenes from a global cloud system-resolving model and a satellite simulator to measure the effect on actual observation scenes. For typical shallow warm clouds (τ = 8, re = 8 µm), the SMILE error on the cloud retrieval was not significant in most cases (up to 6 % error). For typical deep convective clouds (τ = 8, re = 40 µm), the SMILE error on the cloud retrieval was even less significant in most cases (up to 4 % error). Moreover, our results from two oceanic scenes using the synthetic MSI data agreed well with the forward radiation simulation, indicating that the SMILE error was generally within 10 %. Generally, this negligible impact of the SMILE is true for water surfaces, but it still needs to be investigated further for land surfaces in future works.

Spatial Heterogeneity of Aerosol Effect on Liquid Cloud Microphysical Properties in the Warm Season Over Tibetan Plateau

AbstractThe effect of aerosol on liquid cloud microphysical properties over the Tibetan Plateau (TP) during the warm season is investigated by using aerosol index (AI) and cloud property parameters data. Distinct differences in aerosol effect on liquid cloud microphysical properties have been found between the northern Tibetan Plateau (NTP) and southernTibetan Plateau (STP). The composite liquid cloud droplet effective radius liquid cloud droplet effective radius (LREF) anomalies for positive AI events are positive in the NTP and negative in the STP. In both NTP and STP, when the AI anomalies are positive, the LREF anomalies are also positive, which suggests that the increased aerosol loading reduces the solar radiation reaching the ground and thus enhances the atmospheric stability, which reduces the cloud base height and makes the liquid cloud area thicker, which gives cloud droplets more space to grow by collision‐coalescence. This indicates that the aerosol radiative effect is not likely the reason causing the distinct differences of aerosol effects on liquid cloud properties between NTP and STP. Further analysis shows that in the STP, the LREF first increases and then decreases with the increase of AI, while in the NTP, the LREF always increases with the increase of AI, suggesting a spatial difference in aerosol microphysical effect. In the STP, the influence of aerosol on liquid clouds is mainly dependent on liquid water path and convective available potential energy, while in the NTP, the influence of aerosol on liquid cloud is more likely related to large aerosol particles.

Impact of Aerosols on Convective System Over the North China Plain: A Numerical Case Study in Autumn

AbstractThe effects of aerosols on deep convective systems are highly uncertain. We used a coupled meteorology and chemistry model to investigate the effects of aerosols on a convective precipitation event that took place in North China from 7 to 10 October 2017. A higher concentration of aerosols can lead to more cloud condensation nuclei, which increases the condensation of water vapor and the formation of cloud droplets. Although the auto‐conversion from cloud droplets to rain can be inhibited due to the diminished effective radius of cloud droplets, more cloud droplets can be accreted by raindrops, resulting in a larger effective radius of raindrops and making them less likely to evaporate. Besides, aerosols can contribute to the vapor deposition of snow, and a larger number of cloud droplets can provide the resources needed for the riming growth of snow in the cloud, which eventually results in more and larger snow particles. Also, the net latent heat released by these microphysical processes can increase the vertical velocity and facilitate the development of the convective system. Thereby, the precipitation in North China during the study period was ultimately enhanced. We analyzed the influence of aerosols on this precipitation event from a microphysical perspective, which might improve our understanding of complex aerosol‐cloud‐precipitation interactions.

Validation of the dual field-of-view polarization LIDAR technique for the retrieval of homogeneous water cloud microphysical properties: a study based on a polarimetric Monte Carlo simulation.

This article highlights the validation of the dual fields-of-view (FOVs) polarization lidar technique for the retrieval of cloud droplet effective radius in conjunction with cloud extinction coefficient of homogeneous water cloud via simulation approach. The simulation is based on polarimetric Monte Carlo method incorporated with semianalytic features under multiple-scattering conditions. The simulation results show that the depolarization ratio measured at dual-FOVs is a function of the cloud droplet effective radius and cloud extinction coefficient. Using the method of standard deviation on extensive simulation results and then by applying the polynomial regression, two polynomial relationships are obtained expressing the retrieval of the cloud droplet effective radius and cloud extinction coefficient from the layer integrated depolarization ratio at low optical depths close to the cloud bottom. Eventually, the results those presented by Ref.[1] are validated. The water cloud microphysical properties, liquid water content and cloud droplet number concentration are the functions of these two parameters and thus can be found numerically.

Apportionment of the Pre‐Industrial to Present‐Day Climate Forcing by Methane Using UKESM1: The Role of the Cloud Radiative Effect

AbstractThe Year 1850 to 2014 increase in methane from 808 to 1831 ppb leads to an effective radiative forcing (ERF) of 0.97 ± 0.04 W m−2 in the United Kingdom's Earth System Model, UKESM1. The direct methane contribution is 0.54 ± 0.04 W m−2. It is better represented in UKESM1 than in its predecessor model HadGEM2 due to shortwave and longwave absorption improvements and the absence of an anomalous dust response in the UKESM1 simulations. An indirect ozone ERF of 0.13–0.20 W m−2 is due to the tropospheric ozone increase outweighing that of the stratospheric decrease. The indirect water vapor ERF of 0.02–0.07 W m−2 is consistent with previous estimates. The methane increase also leads to a cloud radiative effect of 0.12 ± 0.02 W m−2 from thermodynamic adjustments and aerosol‐cloud interactions (aci). Shortwave and longwave contributions of 0.23 and −0.35 W m−2 to the cloud forcing arise from radiative heating and stabilization of the upper troposphere, reducing convection and global cloud cover. The aerosol‐mediated contribution (0.28–0.30 W m−2) is due to changes in oxidants reducing new particle formation (−8%), shifting the aerosol size distribution toward fewer but larger particles. Cloud droplet number concentration decreases and cloud droplet effective radius increases. This reduction in the Twomey effect switches the cloud forcing sign (−0.14 to 0.12 W m−2) and is due to chemistry‐aerosol‐cloud coupling in UKESM1. Despite uncertainties in rapid adjustments and process representation in models, these results highlight the potential importance of chemistry‐aerosol‐cloud interactions and dynamical adjustments in climate forcing.

Cloud radar perspective on tropical warm clouds associated with summer monsoon rainfall and warm rain onset process

The role of warm clouds in monsoon rainfall and the warm rain onset process are investigated using high-resolution cloud-sensitive radar measurements. Quality controlled data from Ka-band radar consisting of 1.8 million profiles during July–August 2015, have been explored. A method is devised using the Ze profiles, for identifying warm clouds whose cloud tops are confined below 5.3 km. Warm rain microphysical parameters are examined utilizing the complemented measurements from Disdrometer, rain gauge, and CloudSat data. The strong temperature inversion of 2 to 4 K km−1 at 3 km explained the generation of shallow warm clouds. Strong low-level updraft and subsidence above the warm clouds are also evident. Contoured frequency by altitude diagram infers that 75% of Ze (velocity) dominates at −20 dBZe (−1 m s−1). Simultaneous Disdrometer measurements revealed 78% of cases with zero-drop count and zero rain rates. The dominating non-precipitating characteristics of warm clouds are also confirmed from the CloudSat inferred cloud droplet effective radius below 10 μm. During the rainy episodes, peak at 0.91 mm in the drop size distribution suggests prominence of drizzle-sized drops. The precipitation caused by warm clouds accounts for a small fraction (28%) of the total rainfall. The warm rain onset process involving the transformation of smaller cloud droplets into big raindrops is investigated using the radar's three lower-order moments. Before cloud droplet to raindrop transition an intense spike in the spectral width (SW) is observed for a brief period in 98% of the cases. Therefore, SW, which infers turbulence, triggers the collision-coalescence of cloud droplets to form raindrops. This study provides a multi-observation-based perspective on the macro- and micro-physical characteristics of monsoon warm clouds and the onset of warm rain for a better representation in the global climate models.

Effective radiative forcing of anthropogenic aerosols in E3SM version 1: historical changes, causality, decomposition, and parameterization sensitivities

Abstract. The effective radiative forcing of anthropogenic aerosols (ERFaer) is an important measure of the anthropogenic aerosol effects simulated by a global climate model. Here we analyze ERFaer simulated by the E3SM version 1 (E3SMv1) atmospheric model using both century-long free-running atmosphere–land simulations and short nudged simulations. We relate the simulated ERFaer to characteristics of the aerosol composition and optical properties, and we evaluate the relationships between key aerosol and cloud properties. In terms of historical changes from the year 1870 to 2014, our results show that the global mean anthropogenic aerosol burden and optical depth increase during the simulation period as expected, but the regional averages show large differences in the temporal evolution. The largest regional differences are found in the emission-induced evolution of the burden and optical depth of the sulfate aerosol: a strong decreasing trend is seen in the Northern Hemisphere high-latitude region after around 1970, while a continued increase is simulated in the tropics. The relationships between key aerosol and cloud properties (relative changes between pre-industrial and present-day conditions) also show evident changes after 1970, diverging from the linear relationships exhibited for the period of 1870–1969. In addition to the regional differences in the simulated relationships, a reduced sensitivity in cloud droplet number and other cloud properties to aerosol perturbations is seen when the aerosol perturbation is large. Consequently, the global annual mean ERFaer magnitude does not increase after around 1970. The ERFaer in E3SMv1 is relatively large compared to the recently published multi-model estimates; the primary reason is the large indirect aerosol effect (i.e., through aerosol–cloud interactions). Compared to other models, E3SMv1 features large relative changes in the cloud droplet effective radius in response to aerosol perturbations. Large sensitivity is also seen in the liquid cloud optical depth, which is determined by changes in both the effective radius and liquid water path. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 are found to have a strong correlation, as the evolution of anthropogenic sulfate aerosols affects both the liquid cloud formation and the homogeneous ice nucleation in cirrus clouds (that causes a large effect on longwave ERFaer). As suggested by a previous study, the large ERFaer appears to be one of the reasons why the model cannot reproduce the observed global mean temperature evolution in the second half of the 20th century. Sensitivity simulations are performed to understand which parameterization and/or parameter changes have a large impact on the simulated ERFaer. The ERFaer estimates in E3SMv1 for the shortwave and longwave components are sensitive to the parameterization changes in both liquid and ice cloud processes. When the parameterization of ice cloud processes is modified, the top-of-model forcing changes in the shortwave and longwave components largely offset each other, so the net effect is negligible. This suggests that, to reduce the magnitude of the net ERFaer, it would be more effective to reduce the anthropogenic aerosol effect through liquid or mixed-phase clouds.

Aerosol first indirect effect over narrow longitude regions of North Pacific and same-latitude lands

Aerosol first indirect effect (FIE), which causes variations of cloud droplet effective radius (re) and then cloud radiative effect (CRE), is one of the critical factors leading to uncertainties in climate model simulations. Different from most previous studies over continental regions, using 10-year observation data from CERES, this study investigates the statistical relationships between aerosol optical depth (AOD) and non-precipitating single-layer liquid phase cloud re and surface shortwave CRE (CRESW) over narrow longitude regions of North Pacific and its eastern and western lands at equal latitudes, along with the estimation of aerosol FIE. Both surface CRESW and cloud re are highly affected by aerosols. When AOD is less than 0.3–0.4 and liquid water path (LWP) is greater than 30 g/m2, positive AOD-CRESW and negative AOD-cloud re relationships are found over both ocean and land. With the increase of AOD, the sensitivity of CRESW and cloud re to aerosol is weakened, but both have greater fluctuations. The latitude dependence of the CRESW and cloud re variations with AOD are weak. The increases in liquid water path (LWP) when LWP is in a certain range (30–120 g/m2 over ocean and 30–90 g/m2 over land) can highly increase CRESW and promote the growth of cloud droplets. We also find that FIE values are positive under clean condition, while negative under polluted condition. Associated with the much less aerosol amount and more sufficient water supply, the FIE values over the ocean are distinctly larger than that over the land.

Water Cloud Detection with Circular Polarization Lidar: A Semianalytic Monte Carlo Simulation Approach.

This work presents polarization property studies of water clouds using a circular polarization lidar through a simulation approach. The simulation approach is based on a polarized, semianalytic Monte Carlo method under multiple-scattering conditions and considers three types of water clouds (namely homogeneous, inhomogeneous and partially inhomogeneous). The simulation results indicate that the layer-integrated circular depolarization ratios show similar variation trends as those of layer-integrated linear depolarization ratios. The Mishchenko–Hovenier relationship is validated to correlate the simulated layer-integrated circular and linear depolarization ratios. In addition, the cloud droplet effective radius, extinction coefficient, lidar field-of-view (FOV) and height of the cloud bottom are all found to affect the layer-integrated depolarization ratio. The current work theoretically indicates that a circular polarization lidar can efficiently perform measurements of water clouds, enjoying the advantage of higher sensitivity compared to a traditional linear polarization lidar. Hence, it should be of interest to researchers in fields of polarization lidar applications.

Importance of aerosols and shape of the cloud droplet size distribution for convective clouds and precipitation

Abstract. The predictability of deep moist convection is subject to large uncertainties resulting from inaccurate initial and boundary data, the incomplete description of physical processes, or microphysical uncertainties. In this study, we investigate the response of convective clouds and precipitation over central Europe to varying cloud condensation nuclei (CCN) concentrations and different shape parameters of the cloud droplet size distribution (CDSD), both of which are not well constrained by observations. We systematically evaluate the relative impact of these uncertainties in realistic convection-resolving simulations for multiple cases with different synoptic controls using the new icosahedral non-hydrostatic ICON model. The results show a large systematic increase in total cloud water content with increasing CCN concentrations and narrower CDSDs, together with a reduction in the total rain water content. This is related to a suppressed warm-rain formation due to a less efficient collision–coalescence process. It is shown that the evaporation at lower levels is responsible for diminishing these impacts on surface precipitation, which lies between +13 % and −16 % compared to a reference run with continental aerosol assumption. In general, the precipitation response was larger for weakly forced cases. We also find that the overall timing of convection is not sensitive to the microphysical uncertainties applied, indicating that different rain intensities are responsible for changing precipitation totals at the ground. Furthermore, weaker rain intensities in the developing phase of convective clouds can allow for a higher convective instability at later times, which can lead to a turning point with larger rain intensities later on. The existence of such a turning point and its location in time can have a major impact on precipitation totals. In general, we find that an increase in the shape parameter can produce almost as large a variation in precipitation as a CCN increase from maritime to polluted conditions. The narrowing of the CDSD not only decreases the absolute values of autoconversion and accretion but also decreases the relative role of the warm-rain formation in general, independent of the prevailing weather regime. We further find that increasing CCN concentrations reduce the effective radius of cloud droplets in a stronger manner than larger shape parameters. The cloud optical depth, however, reveals a similarly large increase with larger shape parameters when changing the aerosol load from maritime to polluted. By the frequency of updrafts as a function of height, we show a negative aerosol effect on updraft strength, leading to an enervation of deep convection. These findings demonstrate that both the CCN assumptions and the CDSD shape parameter are important for quantitative precipitation forecasting and should be carefully chosen if double-moment schemes are used for modeling aerosol–cloud interactions.

Observed Relationships Between Cloud Droplet Effective Radius and Biogenic Gas Concentrations in Summertime Marine Stratocumulus Over the Eastern North Atlantic

AbstractBiogenic gases are a prominent component of the summertime marine boundary layer (MBL) over the Eastern North Atlantic. One of these gases, dimethyl sulfide (DMS), can produce sulfate cloud condensation nuclei (CCN) that, in theory, can brighten clouds through photolysis, and produces a reaction product, methane sulfonic acid (MSA). It is also possible that DMS can interact with sea‐salt or other marine aerosols changing their CCN activation spectrum, which could also modify cloud microphysical structure. Data collected aboard the G1 aircraft during the Aerosol Cloud Experiment Eastern North Atlantic (ACE‐ENA) in well‐mixed and decoupled marine boundary layers (MBLs) were used to examine relationships between the cloud droplet effective radii, , and the concentrations of DMS and MSA in constant cloud liquid water content (LWC) bins. A weak but statistically significant negative correlation was observed between CCN concentration and in most LWC bins, regardless of the source of the CCN, while a weak but statistically significant positive correlation between and DMS was observed. No correlation between the cloud droplet number concentration and DMS was found. The presence of MSA indicated that DMS‐to‐sulfate photolysis was likely occurring, but data sparsity prevented a statistically significant conclusion regarding the relationship between MSA and . Data sparsity in decoupled conditions also prevented statistically significant conclusions. To properly address biogenic gas impacts on cloud microphysics, it is recommended that aircraft data be supplemented by long‐term biogenic gas measurements at the surface in marine locations with appropriate remote and in‐situ cloud sensing capabilities, and the analysis limited to well‐mixed MBL's.

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

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