Cloud Microphysical Properties Research Articles

A Novel Multiple-Scattering Lidar for Detecting Optical and Microphysical Properties of Clouds

A Novel Multiple-Scattering Lidar for Detecting Optical and Microphysical Properties of Clouds

An assessment of macrophysical and microphysical cloud properties driving radiative forcing of shallow trade-wind clouds

Abstract. The clouds in the Atlantic trade-wind region are known to have an important impact on the global climate system. Acquiring a comprehensive characterization of these clouds based on observations is a challenge, but it is necessary for the evaluation of their representation in models. An exploration of how the macrophysical and microphysical cloud properties and organization of the cloud field impact the large-scale cloud radiative forcing is presented here. In situ measurements of the cloud radiative effects based on the Broadband AirCrAft RaDiometer Instrumentation (BACARDI) on board the High Altitude and LOng Range Research Aircraft (HALO) and cloud observations from the GOES-16 satellite collected during the ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte (EUREC4A) campaign demonstrate what drives the cloud radiative effects in shallow trade-wind clouds. We find that the solar and terrestrial radiative effects of these clouds are largely driven by their macrophysical properties (cloud fraction and a scene-averaged liquid water path). We also conclude that the microphysical properties, cloud top height and organization of the cloud field increasingly determine the cloud radiative effects as the cloud fraction increases.

How Do Marine Gases Affect Cloud Formation?

By using novel aircraft measurements over the eastern North Atlantic Ocean, researchers shed light on the relationship between common marine biogenic gases and the microphysical properties of clouds.

Free amino acid quantification in cloud water at the Puy de Dôme station (France)

Abstract. Eighteen free amino acids (FAAs) were quantified in cloud water sampled at the Puy de Dôme station (PUY – France) during 13 cloud events. This quantification has been performed without concentration or derivatization, using liquid chromatography hyphened to mass spectrometry (LC-MS) and the standard addition method to correct for matrix effects. Total concentrations of FAAs (TCAAs) vary from 1.2 to 7.7 µM, Ser (serine) being the most abundant AA (23.7 % on average) but with elevated standard deviation, followed by glycine (Gly) (20.5 %), alanine (Ala) (11.9 %), asparagine (Asn) (8.7 %), and leucine/isoleucine (Leu/I)​​​​​​​ (6.4 %). The distribution of AAs among the cloud events reveals high variability. TCAA constitutes between 0.5 and 4.4 % of the dissolved organic carbon measured in the cloud samples. AA quantification in cloud water is scarce, but the results agree with the few studies that investigated AAs in this aqueous medium. The environmental variability is assessed through a statistical analysis. This work shows that AAs are correlated with the time spent by the air masses within the boundary layer, especially over the sea surface before reaching the PUY. The cloud microphysical properties' fluctuation does not explain the AA variability in our samples, confirming previous studies at the PUY. We finally assessed the sources and the atmospheric processes that potentially explain the prevailing presence of certain AAs in the cloud samples. The initial relative distribution of AAs in biological matrices (proteins extracted from bacterial cells or mammalian cells, for example) could explain the dominance of Ala, Gly, and Leu/I. AA composition of aquatic organisms (i.e., diatom species) could also explain the high concentrations of Ser in our samples. The analysis of the AA hygroscopicity also indicates a higher contribution of AAs (80 % on average) that are hydrophilic or neutral, revealing the fact that other AAs (hydrophobic) are less favorably incorporated into cloud droplets. Finally, the atmospheric aging of AAs has been evaluated by calculating atmospheric lifetimes considering their potential transformation in the cloud medium by biotic or abiotic (mainly oxidation) processes. The most concentrated AAs encountered in our samples present the longest atmospheric lifetimes, and the less dominant ones are clearly efficiently transformed in the atmosphere, potentially explaining their low concentrations. However, this cannot fully explain the relative contribution of several AAs in the cloud samples. This reveals the high complexity of the bio-physico-chemical processes occurring in the multiphase atmospheric environment.

Coincident in situ and triple-frequency radar airborne observations in the Arctic

Abstract. The dataset collected during the Radar Snow Experiment (RadSnowExp) presents the first-ever airborne triple-frequency radar observations combined with almost perfectly co-located and coincident airborne microphysical measurements from a single platform, the National Research Council Canada (NRC) Convair-580 aircraft. The potential of this dataset is illustrated using data collected from one flight during an Arctic storm, which covers a wide range of snow habits from pristine ice crystals and low-density aggregates to heavily rimed particles with maximum size exceeding 10 mm. Three different flight segments with well-matched in situ and radar measurements were analyzed, giving a total of 49 min of triple-frequency observations. The in situ particle imagery data for this study include high-resolution imagery from the Cloud Particle Imager (CPI) probe, which allows accurate identification of particle types, including rimed crystals and large aggregates, within the dual-frequency ratio (DFR) plane. The airborne triple-frequency radar data are grouped based on the dominant particle compositions and microphysical processes (level of aggregation and riming). The results from this study are consistent with the main findings of previous modeling studies, with specific regions of the DFR plane associated with unique scattering properties of different ice habits, especially in clouds where the radar signal is dominated by large aggregates. Moreover, the analysis shows close relationships between the triple-frequency signatures and cloud microphysical properties (particle characteristic size, bulk density, and level of riming).

Use of large-eddy simulations to design an adaptive sampling strategy to assess cumulus cloud heterogeneities by remotely piloted aircraft

Abstract. Trade wind cumulus clouds have a significant impact on the Earth's radiative balance due to their ubiquitous presence and significant coverage in subtropical regions. Many numerical studies and field campaigns have focused on better understanding the thermodynamic, microphysical, and macroscopic properties of cumulus clouds with ground-based and satellite remote sensing as well as in situ observations. Aircraft flights have provided a significant contribution, but their resolution remains limited by rectilinear transects and fragmented temporal data for individual clouds. To provide a higher spatial and temporal resolution, remotely piloted aircraft (RPA) can now be employed for direct observations using numerous technological advances to map the microphysical cloud structure and to study entrainment mixing. In fact, the numerical representation of mixing processes between a cloud and the surrounding air has been a key issue in model parameterizations for decades. To better study these mixing processes as well as their impacts on cloud microphysical properties, the paper aims to improve exploration strategies that can be implemented by a fleet of RPA. Here, we use a large-eddy simulation (LES) of shallow maritime cumulus clouds to design adaptive sampling strategies. An implementation of the RPA flight simulator within high-frequency LES outputs (every 5 s) allows tracking individual clouds. A rosette sampling strategy is used to explore clouds of different sizes that are static in time and space. The adaptive sampling carried out by these explorations is optimized using one or two RPA and with or without Gaussian process regression (GPR) mapping by comparing the results obtained with those of a reference simulation, in particular the total liquid water content (LWC) and the LWC distribution in a horizontal cross section. Also, a sensitivity test of length scale for GPR mapping is performed. The results of exploring a static cloud are then extended to a dynamic case of a cloud evolving with time to assess the application of this exploration strategy to study the evolution of cloud heterogeneities. While a single RPA coupled to GPR mapping remains insufficient to accurately reconstruct individual clouds, two RPA with GPR mapping adequately characterize cloud heterogeneities on scales small enough to quantify the variability of important parameters such as total LWC.

Insights into tropical cloud chemistry in Réunion (Indian Ocean): results from the BIO-MAÏDO campaign

Abstract. We present here the results obtained during an intensive field campaign conducted in the framework of the French “BIO-MAÏDO” (Bio-physico-chemistry of tropical clouds at Maïdo (Réunion Island): processes and impacts on secondary organic aerosols' formation) project. This study integrates an exhaustive chemical and microphysical characterization of cloud water obtained in March–April 2019 in Réunion (Indian Ocean). Fourteen cloud samples have been collected along the slope of this mountainous island. Comprehensive chemical characterization of these samples is performed, including inorganic ions, metals, oxidants, and organic matter (organic acids, sugars, amino acids, carbonyls, and low-solubility volatile organic compounds, VOCs). Cloud water presents high molecular complexity with elevated water-soluble organic matter content partly modulated by microphysical cloud properties. As expected, our findings show the presence of compounds of marine origin in cloud water samples (e.g. chloride, sodium) demonstrating ocean–cloud exchanges. Indeed, Na+ and Cl− dominate the inorganic composition contributing to 30 % and 27 %, respectively, to the average total ion content. The strong correlations between these species (r2 = 0.87, p value: < 0.0001) suggest similar air mass origins. However, the average molar Cl-/Na+ ratio (0.85) is lower than the sea-salt one, reflecting a chloride depletion possibly associated with strong acids such as HNO3 and H2SO4. Additionally, the non-sea-salt fraction of sulfate varies between 38 % and 91 %, indicating the presence of other sources. Also, the presence of amino acids and for the first time in cloud waters of sugars clearly indicates that biological activities contribute to the cloud water chemical composition. A significant variability between events is observed in the dissolved organic content (25.5 ± 18.4 mg C L−1), with levels reaching up to 62 mg C L−1. This variability was not similar for all the measured compounds, suggesting the presence of dissimilar emission sources or production mechanisms. For that, a statistical analysis is performed based on back-trajectory calculations using the CAT (Computing Atmospheric Trajectory Tool) model associated with the land cover registry. These investigations reveal that air mass origins and microphysical variables do not fully explain the variability observed in cloud chemical composition, highlighting the complexity of emission sources, multiphasic transfer, and chemical processing in clouds. Even though a minor contribution of VOCs (oxygenated and low-solubility VOCs) to the total dissolved organic carbon (DOC) (0.62 % and 0.06 %, respectively) has been observed, significant levels of biogenic VOC (20 to 180 nmol L−1) were detected in the aqueous phase, indicating the cloud-terrestrial vegetation exchange. Cloud scavenging of VOCs is assessed by measurements obtained in both the gas and aqueous phases and deduced experimental gas-/aqueous-phase partitioning was compared with Henry's law equilibrium to evaluate potential supersaturation or unsaturation conditions. The evaluation reveals the supersaturation of low-solubility VOCs from both natural and anthropogenic sources. Our results depict even higher supersaturation of terpenoids, evidencing a deviation from thermodynamically expected partitioning in the aqueous-phase chemistry in this highly impacted tropical area.

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.

Vertical Distributions of Aerosol and Cloud Microphysical Properties and the Aerosol Impact on a Continental Cumulus Cloud Based on Aircraft Measurements From the Loess Plateau of China

Based on aircraft measurements of aerosols and continental cumulus clouds made over the Loess Plateau of China (Xinzhou, Shanxi Province) on 30 July 2020, this study focuses on the vertical profiles of microphysical properties of aerosols and cumulus clouds, and use them to study aerosol-cloud interactions. During the study period, the boundary layer was stable with a height ∼1,500 m above sea level. Aerosols in the boundary layer mainly came from local emissions, while aerosols above this layer were mostly dust aerosols transported over long distances. Vertical profiles of aerosols and cloud condensation nuclei were obtained, and aerosol activation ratios at different supersaturation (SS) levels ranged from 0.16 to 0.32 at 0.2% SS and 0.70 to 0.85 at 0.8% SS. A thick cumulus cloud in the development stage was observed from the bottom to the top with the horizontal dimension of 10 km by 7 km, the cloud-base height of 2,450 m (15.8°C), and the cloud-top height of 5,400 m (−3°C). The maximum updraft velocity near the cloud top was 13.45 m s−1, and the maximum downdraft velocity occuring in the upper-middle part of the cloud was 4.44 ms−1. The temperature inside the cloud was higher than the outside, with their difference being positively correlated with the cloud water content. The temperature lapse rate inside the cloud was about −6.5°C km−1. The liquid water content and droplet effective radius (Re) increased with increasing height. The cloud droplet number concentration (Nc) increased first then decreased, peaking in the middle and lower part of the cloud, the average values of Nc and Re were 767.9 cm−3 and 5.17 μm, respectively. The cloud droplet spectrum had a multi-peak distribution, with the first appearing at ∼4.5 μm. SS in the cloud first increased then decreased with height. The maximum SS is ∼0.7% appearing at ∼3,800 m. The conversion rate of intra-cloud aerosols to cloud droplets was between 0.2 and 0.54, with the ratio increasing gradually with increasing height. The cloud droplet spectral dispersion and Nc were positively correlated. The aerosol indirect effect (AIE) was estimated to be 0.245 and 0.16, based on Nc and Re, respectively. The cloud droplet dispersion mainly attenuated the AIE, up to ∼34.7%.

Aerosol–cloud–precipitation interactions during a Saharan dust event – A summertime case‐study from the Alps

AbstractChanges in the ambient aerosol concentration are known to affect the microphysical properties of clouds. Especially regarding precipitation formation, increasing aerosol concentrations are assumed to delay the precipitation onset, but may increase precipitation rates via convective invigoration and orographic spillover further downstream. In this study, we analyse the effect of increased aerosol concentrations on a heavy precipitation event observed in summer 2017 over northeastern Switzerland, an event which was considerably underestimated by the operational weather forecast model. Preceding the precipitation event, Saharan dust was advected towards the Alps, which could have contributed to increased precipitation rates north of the Alpine ridge. To investigate the potential impact of the increased ambient aerosol concentrations on surface precipitation, we perform a series of sensitivity simulations using the Consortium for Small‐scale Modeling (COSMO) model with different microphysical parametrizations and prognostic aerosol perturbations. The results show that the choice of the microphysical parametrization scheme in terms of a one‐ or two‐moment scheme has the relatively largest impact on surface precipitation rates. In the one‐moment scheme, surface precipitation is strongly reduced over the Alpine ridge and increased further downstream. Simulated changes in surface precipitation in response to aerosol perturbations remain smaller in contrast to the impact of the microphysics scheme. Elevated cloud condensation nuclei (CCN) concentrations lead to increased cloud water and decreased cloud ice mass, especially in regions of high convective activity south of the Alps. These altered cloud properties indeed increase surface precipitation further downstream, but the simulated change is too small to explain the observed heavy precipitation event. Additional ice‐nucleating particles (INPs) increase cloud ice mass, but only trigger local changes in downstream surface precipitation. Thus, increased aerosol number concentrations during the Saharan dust outbreak are unlikely to have caused the heavy precipitation event in summer 2017.

Assessing Synergistic Radar and Radiometer Retrievals of Ice Cloud Microphysics for the Atmosphere Observing System (AOS) Architecture

After exploring numerous observing system designs, the NASA aerosols, clouds, convection, and precipitation (ACCP) study team arrived at the top candidate architecture referred to as the atmosphere observing system (AOS) that is composed of a suite of spaceborne instruments in two orbital inclinations to characterize the complexity of hydrometeors and aerosols in the Earth’s atmosphere. This study proposes hybrid Bayesian retrieval algorithms that combine the Monte Carlo integration (MCI) and cost function optimization approaches to quantitatively evaluate the AOS architecture for skill in constraining the ice cloud microphysical properties. The remote sensor candidates under evaluation include multiple-frequency radars with W-, Ka-, and Ku-band channels and a submillimeter-wave radiometer. Two optimization techniques, the optimal estimation method (OEM) and Markov chain Monte Carlo (MCMC), are developed to maximize the posterior distribution function to retrieve ice cloud microphysical quantities with uncertainty estimates. Observing system simulation experiments are conducted using simulated synergistic radar and radiometer observations to determine the pixel-level retrieval accuracies by comparing the retrieved parameters to the true values. Results demonstrate that the low-frequency Ka-/Ku-band radar observations are complementary to the W-band channel since they provide more constraints on the condensed cloud scenes that are composed of large particles. The brightness temperature measurements exhibit sensitivities to the ice cloud layers with large water content (WC), and the synergistic active and passive observations improve the ice water path retrieval accuracies significantly. The scores measuring how well the AOS architecture satisfies the desired retrieval uncertainties for different ice cloud geophysical variables are also derived.

Comparison of Macro- and Microphysical Properties in Precipitating and Non-Precipitating Clouds over Central-Eastern China during Warm Season

The macro- and microphysical properties of clouds can reflect their vertical physical structure and evolution and are important indications of the formation and development of precipitation. We used four-year merged CloudSat-CALIPSO-MODIS products to distinguish the macro- and microphysical properties of precipitating and non-precipitating clouds over central-eastern China during the warm season (May–September). Our results showed that the clouds were dominated by single- and double-layer forms with occurrence frequencies > 85%. Clouds with a low probability of precipitation (POP) were usually geometrically thin. The POP showed an increasing trend with increases in the cloud optical depth, liquid water path, and ice water path, reaching maxima of 50%, 60%, and 75%, respectively. However, as cloud effective radius (CER) increased, the POP changed from an increasing to a decreasing trend for a CER > 22 μm, in contrast with our perception that large particles fall more easily against updrafts, but this shift can be attributed to the transition of the cloud phase from mixed clouds to ice clouds. A high POP > 60% usually occurred in mixed clouds with vigorous ice-phase processes. There were clear differences in the microphysical properties of non-precipitating and precipitating clouds. In contrast with the vertical evolution of non-precipitating clouds with weaker reflectivity, precipitating clouds were present above 0 dBZ with a significant downward increase in reflectivity, suggesting inherent differences in cloud dynamical and microphysical processes. Our findings highlight the differences in the POP of warm and mixed clouds, suggesting that the low frequency of precipitation from water clouds should be the focus of future studies.

The Effect of Using a New Parameterization of Nucleation in the WRF-Chem Model on New Particle Formation in a Passive Volcanic Plume

We investigated the role of the passive volcanic plume of Mount Etna (Italy) in the formation of new particles in the size range of 2.5–10 nm through the gas-to-particle nucleation of sulfuric acid (H2SO4) precursors, formed from the oxidation of SO2, and their evolution to particles with diameters larger than 100 nm. Two simulations were performed using the Weather Research and Forecasting Model coupled with chemistry (WRF-Chem) under the same configuration, except for the nucleation parameterization implemented in the model: the activation nucleation parameterization (JS1 = 2.0 × 10−6 × (H2SO4)) in the first simulation (S1) and a new parameterization for nucleation (NPN) (JS2 = 1.844 × 10−8 × (H2SO4)1.12) in the second simulation (S2). The comparison of the numerical results with the observations shows that, on average, NPN improves the performance of the model in the prediction of the H2SO4 concentrations, newly-formed particles (~2.5–10 nm), and their growth into larger particles (10–100 nm) by decreasing the rates of H2SO4 consumption and nucleation relative to S1. In addition, particles formed in the plume do not grow into cloud condensation nuclei (CCN) sizes (100–215 nm) within a few hours of the vent (tens of km). However, tracking the size evolution of simulated particles along the passive plume indicates the downwind formation of particles larger than 100 nm more than 100 km far from the vent with relatively high concentrations relative to the background (more than 1500 cm−3) in S2. These particles, originating in the volcanic source, could affect the chemical and microphysical properties of clouds and exert regional climatic effects over time.

Mass of different snow crystal shapes derived from fall speed measurements

Abstract. Meteorological forecast and climate models require good knowledge of the microphysical properties of hydrometeors and the atmospheric snow and ice crystals in clouds, for instance, their size, cross-sectional area, shape, mass, and fall speed. Especially shape is an important parameter in that it strongly affects the scattering properties of ice particles and consequently their response to remote sensing techniques. The fall speed and mass of ice particles are other important parameters for both numerical forecast models and the representation of snow and ice clouds in climate models. In the case of fall speed, it is responsible for the rate of removal of ice from these models. The particle mass is a key quantity that connects the cloud microphysical properties to radiative properties. Using an empirical relationship between the dimensionless Reynolds and Best numbers, fall speed and mass can be derived from each other if particle size and cross-sectional area are also known. In this study, ground-based in situ measurements of snow particle microphysical properties are used to analyse mass as a function of shape and the other properties particle size, cross-sectional area, and fall speed. The measurements for this study were done in Kiruna, Sweden, during snowfall seasons of 2014 to 2019 and using the ground-based in situ Dual Ice Crystal Imager (D-ICI) instrument, which takes high-resolution side- and top-view images of natural hydrometeors. From these images, particle size (maximum dimension), cross-sectional area, and fall speed of individual particles are determined. The particles are shape-classified according to the scheme presented in our previous study, in which particles sort into 15 different shape groups depending on their shape and morphology. Particle masses of individual ice particles are estimated from measured particle size, cross-sectional area, and fall speed. The selected dataset covers sizes from about 0.1 to 3.2 mm, fall speeds from 0.1 to 1.6 m s−1, and masses from 0.2 to 450 µg. In our previous study, the fall speed relationships between particle size and cross-sectional area were studied. In this study, the same dataset is used to determine the particle mass, and consequently, the mass relationships between particle size, cross-sectional area, and fall speed are studied for these 15 shape groups. Furthermore, the mass relationships presented in this study are compared with the previous studies. For certain crystal habits, in particular columnar shapes, the maximum dimension is unsuitable for determining Reynolds number. Using a selection of columns, for which the simple geometry allows the verification of an empirical Best-number-to-Reynolds-number relationship, we show that Reynolds number and fall speed are more closely related to the diameter of the basal facet than the maximum dimension. The agreement with the empirical relationship is further improved using a modified Best number, a function of an area ratio based on the falling particle seen in the vertical direction.

Ice and Supercooled Liquid Water Distributions Over the Southern Ocean Based on In Situ Observations and Climate Model Simulations

AbstractThree climate models are evaluated using in situ airborne observations from the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) campaign. The evaluation targets cloud phases, microphysical properties, thermodynamic conditions, and aerosol indirect effects from −40°C to 0°C. Compared with 580‐s averaged observations (i.e., 100 km horizontal scale), the Community Atmosphere Model version 6 (CAM6) shows the most similar result for cloud phase frequency distribution and allows more liquid‐containing clouds below −10°C compared with its predecessor—CAM5. The Energy Exascale Earth System Model (E3SM) underestimates (overestimates) ice phase frequencies below (above) −20°C. CAM6 and E3SM show liquid and ice water contents (i.e., LWC and IWC) similar to observations from −25°C to 0°C, but higher LWC and lower IWC than observations at lower temperatures. Simulated in‐cloud RH shows higher minimum values than observations, possibly restricting ice growth during sedimentation. As number concentrations of aerosols larger than 500 nm (Na500) increase, observations show increases of LWC, IWC, liquid, and ice number concentrations (Nliq, Nice). Number concentrations of aerosols larger than 100 nm (Na100) only show positive correlations with LWC and Nliq. From −20°C to 0°C, higher aerosol number concentrations are correlated with lower glaciation ratio and higher cloud fraction. From −40°C to −20°C, large aerosols show positive correlations with glaciation ratio. CAM6 shows small increases of LWC and Nliqwith Na500and Na100. E3SM shows small increases of Nicewith Na500. Overall, CAM6 and E3SM underestimate aerosol indirect effects on ice crystals and supercooled liquid droplets over the Southern Ocean.

Preliminary results of water cloud and aerosol properties in the Yinchuan area using a Multi-wavelength lidar based on dual field of view

Aerosol-cloud interaction has an extremely important impact on regional and even global climate and environmental change. It is undoubtedly of great scientific significance and research value to study its impact and mechanism on atmospheric radiation balance and climate change. As a active remote sensing, lidar can be employed to study aerosol-cloud interaction. In this paper, A novel multi-wavelength lidar system equipped with a dual field of view device is developed to measure the optical and microphysical parameters of water clouds. The scattered light is detected by the inner and outer field of view, respectively. For verifying the feasibility of the novel lidar system, some preliminary experiments were carried out at North Minzu University (106°06′E, 38°29′N) in the Yinchuan, China. The experiments shows that the novel lidar system can effective detect the optical and microphysical property parameters of water clouds, including extinction coefficient, effective particle radius and liquid water content, with a cloud base height of less than 5 km. Compared with traditional lidar systems that detect optical properties alone, it can use return signals from different fields of view to detect the microphysical properties of warm clouds and thin layered clouds, therefore, it is of great practical significance to develop the cloud water resources efficiently and improve the accuracy of artificial rainfall operations.

Measurement report: Impact of African aerosol particles on cloud evolution in a tropical montane cloud forest in the Caribbean

Abstract. African aerosol particles, traveling thousands of kilometers before reaching the Americas and the Caribbean, directly scatter and absorb solar radiation and indirectly impact climate by serving as cloud condensation nuclei (CCN) or ice-nucleating particles (INPs) that form clouds. These particles can also affect the water budget by altering precipitation patterns that subsequently affect ecosystems. As part of the NSF-funded Luquillo Critical Zone Observatory, field campaigns were conducted during the summers of 2013 (23 d), 2014 (11 d), and 2015 (92 d) at Pico del Este, a site in a tropical montane cloud forest on the Caribbean Island of Puerto Rico. Cloud microphysical properties, which included liquid water content, droplet number concentration, and droplet size, were measured. Using products from models and satellites, as well as in situ measurements of aerosol optical properties, periods of high- and low-dust influence were identified. The results from this study suggest that meteorology and air mass history have a more important effect on cloud processes than aerosols transported from Africa. In contrast, air masses that arrived after passing over the inhabited islands to the southeast led to clouds with much higher droplet concentrations, presumably due to aerosols formed from anthropogenic emissions.

Geometrical and Microphysical Properties of Clouds Formed in the Presence of Dust above the Eastern Mediterranean

In this work, collocated lidar–radar observations are used to retrieve the vertical profiles of cloud properties above the Eastern Mediterranean. Measurements were performed in the framework of the PRE-TECT experiment during April 2017 at the Greek atmospheric observatory of Finokalia, Crete. Cloud geometrical and microphysical properties at different altitudes were derived using the Cloudnet target classification algorithm. We found that the variable atmospheric conditions that prevailed above the region during April 2017 resulted in complex cloud structures. Mid-level clouds were observed in 38% of the cases, high or convective clouds in 58% of the cases, and low-level clouds in 2% of the cases. From the observations of cloudy profiles, pure ice phase occurred in 94% of the cases, mixed-phase clouds were observed in 27% of the cases, and liquid clouds were observed in 8.7% of the cases, while Drizzle or rain occurred in 12% of the cases. The significant presence of Mixed-Phase Clouds was observed in all the clouds formed at the top of a dust layer, with three times higher abundance than the mean conditions (26% abundance at −15 °C). The low-level clouds were formed in the presence of sea salt and continental particles with ice abundance below 30%. The derived statistics on clouds’ high-resolution vertical distributions and thermodynamic phase can be combined with Cloudnet cloud products and lidar-retrieved aerosol properties to study aerosol-cloud interactions in this understudied region and evaluate microphysics parameterizations in numerical weather prediction and global climate models.

Realism of Lagrangian Large Eddy Simulations Driven by Reanalysis Meteorology: Tracking a Pocket of Open Cells Under a Biomass Burning Aerosol Layer.

An approach to drive Lagrangian large eddy simulation (LES) of boundary layer clouds with reanalysis data is presented and evaluated using satellite (Spinning Enhanced Visible and Infrared Imager, SEVIRI) and aircraft (Cloud‐Aerosol‐Radiation Interactions and Forcing, CLARIFY) measurements. The simulations follow trajectories of the boundary layer flow. They track the formation and evolution of a pocket of open cells (POC) underneath a biomass burning aerosol layer in the free troposphere. The simulations reproduce the evolution of observed stratocumulus cloud morphology, cloud optical depth, and cloud drop effective radius, and capture the timing of the cloud state transition from closed to open cells seen in the satellite imagery on the three considered trajectories. They reproduce a biomass burning aerosol layer identified by the in‐situ aircraft measurements above the inversion of the POC. Entrainment of aerosol from the biomass burning layer into the POC is limited to the extent of having no impact on cloud‐ or boundary layer properties, in agreement with the CLARIFY observations. The two‐moment bin microphysics scheme used in the simulations reproduces the in‐situ cloud microphysical properties reasonably well. A two‐moment bulk microphysics scheme reproduces the satellite observations in the non‐precipitating closed‐cell state, but overestimates liquid water path and cloud optical depth in the precipitating open‐cell state due to insufficient surface precipitation. A boundary layer cold and dry bias occurring in LES can be counteracted by reducing the grid aspect ratio and by tightening the large scale wind speed nudging towards the surface.

The first global 883 GHz cloud ice survey: IceCube Level 1 data calibration, processing and analysis

Abstract. Sub-millimeter (200–1000 GHz) wavelengths contribute a unique capability to fill in the sensitivity gap between operational visible–infrared (VIS–IR) and microwave (MW) remote sensing for atmospheric cloud ice and snow. Being able to penetrate clouds to measure cloud ice mass and microphysical properties in the middle to upper troposphere, a critical spectrum range, is necessary for us to understand the connection between cloud ice and precipitation processes. As the first spaceborne 883 GHz radiometer, the IceCube mission was NASA's latest spaceflight demonstration of commercial sub-millimeter radiometer technology. Successfully launched from the International Space Station, IceCube is essentially a free-running radiometer and collected valuable 15-month measurements of atmosphere and cloud ice. This paper describes the detailed procedures for Level 1 (L1) data calibration, processing and validation. The scientific quality and value of IceCube data are then discussed, including radiative transfer model validation and evaluation, as well as the unique spatial distribution and diurnal cycle of cloud ice that are revealed for the first time on a quasi-global scale at this frequency. IceCube Level 1 dataset is publicly available at Gong and Wu (2021) (https://doi.org/10.25966/3d2p-f515).