Cloud Droplet Size Research Articles

Large‐Eddy Simulations of a Convection Cloud Chamber: Sensitivity to Bin Microphysics and Advection

AbstractBin microphysics schemes are useful tools for cloud simulations and are often considered to provide a benchmark for model intercomparison. However, they may experience issues with numerical diffusion, which are not well quantified, and the transport of hydrometeors depends on the choice of advection scheme, which can also change cloud simulation results. Here, an atmospheric large‐eddy simulation model is adapted to simulate a statistically steady‐state cloud in a convection cloud chamber under well‐constrained conditions. Two bin microphysics schemes, a spectral bin method and the method of moments, as well as several advection methods for the transport of the microphysical variables are employed for model intercomparison. Results show that different combinations of microphysics and advection schemes can lead to considerable differences in simulated cloud properties, such as cloud droplet number concentration. We find that simulations using the advection scheme that suffers more from numerical diffusion tends to have a smaller droplet number concentration and liquid water content, while simulation with the microphysics scheme that suffers more from numerical diffusion tends to have a broader size distribution and thus larger mean droplet sizes. Sensitivities of simulations to bin resolution, spatial resolution, and temporal resolution are also tested. We find that refining the microphysical bin resolution leads to a broader cloud droplet size distribution due to the advection of hydrometeors. Our results provide insight for using different advection and microphysics schemes in cloud chamber simulations, which might also help understand the uncertainties of the schemes used in atmospheric cloud simulations.

Influences of an entrainment–mixing parameterization on numerical simulations of cumulus and stratocumulus clouds

Abstract. Different entrainment–mixing processes can occur in clouds; however, a homogeneous mixing mechanism is often implicitly assumed in most commonly used microphysics schemes. Here, we first present a new entrainment–mixing parameterization that uses the grid mean relative humidity without requiring the relative humidity of the entrained air. Then, the parameterization is implemented in a microphysics scheme in a large eddy simulation model, and sensitivity experiments are conducted to compare the new parameterization with the default homogeneous entrainment–mixing parameterization. The results indicate that the new entrainment–mixing parameterization has a larger impact on the number concentration, volume mean radius, and cloud optical depth in the stratocumulus case than in the cumulus case. This is because inhomogeneous and homogeneous mixing mechanisms dominate in the stratocumulus and cumulus cases, respectively, which is mainly due to the larger turbulence dissipation rate in the cumulus case. Because stratocumulus clouds break up during the dissipation stage to form cumulus clouds, the effects of this new entrainment–mixing parameterization during the stratocumulus dissipation stage are between those during the stratocumulus mature stage and the cumulus case. A large aerosol concentration can enhance the effects of this new entrainment–mixing parameterization by decreasing the cloud droplet size and evaporation timescale. The results of this new entrainment–mixing parameterization with grid mean relative humidity are validated by the use of a different entrainment–mixing parameterization that uses parameterized entrained air properties. This study sheds new light on the improvement of entrainment–mixing parameterizations in models.

Lightning Characteristics Over Humid Regions and Arid Regions and Their Association With Aerosols Over Northern India.

The association between aerosol and lightning has been investigated with long-term decadal data (2005–2014) for lightning, aerosol optical depth (AOD), relative humidity, and effective cloud droplet size. To understand the complex relationship between aerosol and lightning, two different regions with different climatic and weather conditions, a humid region R1 (22°–29° N, 89°–92° E) and an arid region R2 (23°–28° N, 70°–76° E) of northern India, were chosen for the study domain. The results show that lightning activity was observed to occur more over the humid region R1, i.e., 1141 days (1/3 of total days), than over the arid region R2, i.e., 740 days (1/5 of total days). Also, over the humid region R1, the highest lightning flash density was recorded as nearly 4.6 × 10–4 flashes/km2/day observed for 18 days (1.5%); on the contrary, over the arid region R2, the maximum lightning flash density was observed to be 2.5 × 10–4 flashes/km2/day and occurred for about 22 days (2.9%). The analysis shows that a nonlinear relationship exists between aerosol and lightning with a highly associated influence of relative humidity. A very significant positive and negative co-relation that varies with relative humidity has been observed between AOD and lightning for both humid and arid regions. This shows relative humidity is the key factor in determining the increase or decrease of lightning activity. This study also shows that the larger the cloud droplet size, the higher the relative humidity and vice versa. This study emphasizes that aerosol concentration in the atmosphere influences cloud microphysics by modulating the size of cloud droplets and thereby regulating the lightning frequency. The atmospheric humidity is the driving factor in deciding the positive or negative co-relationship between aerosol and lightning.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00024-022-02981-6.

Influence of aerosol physico-chemical properties on cloud microphysical parameters perceived using in-situ high altitude observations

Variability in cloud microphysical parameters, aerosol physicochemical properties and their relationship were studied using in-situ ground observations from a high altitude site in Western Ghats, India, during monsoon season. Cloud microphysical parameters, such as cloud droplet number concentration (CDNC), liquid water content (LWC), and effective diameter (ED), have been analyzed. Aerosol–CCN (cloud condensation nuclei) number concentration and mass concentration of non-refractory particulate matter (NR-PM1) during summer monsoon also showed day to day and monthly variation. Cloud droplet size distribution (CDSD) showed a bimodal spectrum with two prominent peaks i.e. in 3–10 μm and 12–22 μm size ranges. The estimated spectral width of CDSD (σ) broadly varied from 0 to 4 μm and the effective radius ratio (β) from 0.6–1.8. Further, the effect of aerosol on cloud microphysical parameters and CDSD has been investigated. There was an apparent variation in CCN super saturation spectrum, aerosol chemical composition, and cloud microphysics during high and low aerosol loading daysThe aerosol chemical composition showed a higher sulphate and ammonium (organics) contribution during low (high) aerosol loading days. CCN concentration and CDNC (ED) were higher (less) during high aerosol days and vice versa during low aerosol days. A review of microphysical characteristics of monsoon clouds over various locations of the Indian region has shown that this is the first such report that provides observational evidence of how variation in aerosol physical and chemical properties affects the CCN and cloud properties derived explicitly from long-term ground-based observations.

Cloud microphysical measurements at a mountain observatory: comparison between shadowgraph imaging and phase Doppler interferometry

Abstract. The microphysical properties of cloud droplets, such as droplet size distribution and droplet number concentration, were studied. A series of field experiments was performed in the summer of 2019 at the Umweltforschungsstation Schneefernerhaus (UFS), an environmental research station located just below the peak of the Zugspitze mountain in the German Alps. A VisiSize D30 manufactured by Oxford Laser Ltd., which is a shadowgraph imaging instrument, was utilized for the first time to measure the size and velocity of cloud droplets during this campaign. Furthermore, a phase Doppler interferometer (PDI) device, manufactured by Artium Tech. Inc., was simultaneously measuring cloud droplets. After applying modifications to the built-in software algorithms, the results from the two instruments show reasonable agreement regarding droplet sizing and velocimetry for droplet diameters larger than 13 µm. Moreover, discrepancies were observed concerning the droplet number concentration results, especially with smaller droplet sizes. Further investigation by applying appropriate filters to the data allowed the attribution of the discrepancies to two phenomena: the different optical performance of the sensors with regard to small droplets and high turbulent velocity fluctuations relative to the mean flow that result in an uncertain estimate of the volume of air passing through the PDI probe volume.

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.

Effects of Air Pollutants on Summer Precipitation in Different Regions of Beijing

Many studies have shown that air pollutants have complex impacts on urban precipitation. Meteorological weather station and satellite Aerosol Optical Depth (AOD) product data from the last 20 years, combined with simulation results from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), this paper focuses on the effects of air pollutants on summer precipitation in different regions of Beijing. These results showed that air pollution intensity during the summer affected the precipitation contribution rate (PCR) of plains and mountainous regions in the Beijing area, especially in the plains. Over the past 20 years, plains PCR increased by ~10% when the AOD augmented by 0.15, whereas it decreased with lower pollution levels. In contrast, PCR in mountainous areas decreased with higher pollution levels and increased with lower pollution levels. Our analysis from model results indicated that aerosol increases reduce the effective particle size of cloud droplets and raindrops. Smaller cloud raindrops more readily transport to high air layers and participate in the generation of ice-phase substances in the clouds, increasing the total amount of cloud water in the air in a certain time, which ultimately enhanced precipitation intensity on the plains. The removal of pollutants caused by increased precipitation in the plains decreased rainfall levels in mountainous areas.

Demistify: a large-eddy simulation (LES) and single-column model (SCM) intercomparison of radiation fog

Abstract. An intercomparison between 10 single-column (SCM) and 5 large-eddy simulation (LES) models is presented for a radiation fog case study inspired by the Local and Non-local Fog Experiment (LANFEX) field campaign. Seven of the SCMs represent single-column equivalents of operational numerical weather prediction (NWP) models, whilst three are research-grade SCMs designed for fog simulation, and the LESs are designed to reproduce in the best manner currently possible the underlying physical processes governing fog formation. The LES model results are of variable quality and do not provide a consistent baseline against which to compare the NWP models, particularly under high aerosol or cloud droplet number concentration (CDNC) conditions. The main SCM bias appears to be toward the overdevelopment of fog, i.e. fog which is too thick, although the inter-model variability is large. In reality there is a subtle balance between water lost to the surface and water condensed into fog, and the ability of a model to accurately simulate this process strongly determines the quality of its forecast. Some NWP SCMs do not represent fundamental components of this process (e.g. cloud droplet sedimentation) and therefore are naturally hampered in their ability to deliver accurate simulations. Finally, we show that modelled fog development is as sensitive to the shape of the cloud droplet size distribution, a rarely studied or modified part of the microphysical parameterisation, as it is to the underlying aerosol or CDNC.

Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data

The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances in 9 spectral channels. The RSP was a prototype for the Aerosol Polarimetery Sensor (APS) launched on-board the NASA Glory satellite. Currently the retrieval algorithms developed for the RSP are being adopted for the measurements of the space-borne polarimeters on the upcoming NASA’s Plankton, Aerosol, Cloud Ocean Ecosystem (PACE) satellite mission. The RSP’s uniquely high angular resolution coupled with the high frequency of measurements allows for characterization of liquid water cloud droplet sizes using the polarized rainbow structure. It also provides geometric constraints on the cumulus cloud’s 2D cross section yielding the cloud’s geometric shape estimates. In this study we further build on the latter technique to develop a new tomographic approach to retrieval of cloud internal structure from remote sensing measurements. While tomography in the strict definition is a technique based on active measurements yielding a tomogram (directional optical thickness as a function of angle and offset of the view ray), we developed a “semi-tomographic” approach in which tomogram of the cloud is estimated from passive observations instead of being measured directly. This tomogram is then converted into 2D spatial distribution of the extinction coefficient using inverse Radon transform (filtered backprojection) which is the standard tomographic procedure used e.g., in medical CT scans. This algorithm is computationally inexpensive compared to techniques relying on highly-multi-dimensional least-square fitting; it does not require iterative 3D RT simulations. The resulting extinction distribution is defined up to an unknown constant factor, so we discuss the ways to calibrate it using additional independent measurements. In the next step we use the profile of the droplet size distribution parameters from the cloud’s side (derived by fitting the polarized rainbows) to convert the 2D extinction distribution into that of the droplet number concentration. We illustrate and validate the proposed technique using 3D-RT-simulated RSP observations of a LES-generated Cu cloud. Quantitative comparisons between the retrieved and the original optical and microphysical parameters are presented.

Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data

The remote sensing of water clouds is useful for studying their spatial and temporal variations and constraining physical processes in climate and weather prediction models. However, radar-only detection provides inadequate information for the cloud droplet size distribution. Here, we propose a novel lookup-table method, which combines lidar (1064, 532 nm) and radar (8.6 mm) to retrieve profiles of cloud optical (backscatter coefficient and extinction coefficient) and microphysical properties (effective diameter and liquid water content). Through the iteration of the extinction-to-backscatter ratio, more continuous cloud optical characteristics can be obtained. Sensitivity analysis shows that a 10% error of the lidar constant will lead to a retrieval error of up to 30%. The algorithm performed precise capture of the ideal cloud signal at a specific height and at full height and the maximum relative error of the backscatter coefficients at 1064 nm and 532 nm were 6% and 4%, respectively. With the application of the algorithm in the two observation cases on single or multiple cloud layers, the results indicate that the microphysical properties mostly agree with the empirical radar measurements but are slightly different when larger particles cause signal changes of different extents. Consequently, the synergetic algorithm is capable of computing the cloud droplet size distribution. It provides continuous profiles of cloud optical properties and captures cloud microphysical properties well for water cloud studies.

Liquid Containing Clouds at the North Slope of Alaska Demonstrate Sensitivity to Local Industrial Aerosol Emissions

AbstractCloud condensation nucleus control alter cloud solar albedo through cloud droplet size. Here, we leverage anthropogenic emissions at the North Slope of Alaska as a natural laboratory to study relationships between aerosols and Arctic liquid‐containing clouds. Averaging 14 years of MODIS observations, we found a reduction in temporally averaged cloud effective radius () of up to 1.0 μm related to localized pollution. Pronounced regional gradients in cloud frequency of occurrence and liquid water path prohibit the detection of potential changes of these variables. Observed changes of alter radiative fluxes and increase cloud‐reflected shortwave radiation by up to 0.8 W m−2 in the Prudhoe Bay area for the period covered by observations (April–September). Due to the frequent occurrence of liquid‐containing clouds, this implies that enhanced local emissions in Arctic regions can impact climate processes.

Impact of high- and low-vorticity turbulence on cloud–environment mixing and cloud microphysics processes

Abstract. Turbulent mixing of dry air affects the evolution of the cloud droplet size spectrum via various mechanisms. In a turbulent cloud, high- and low-vorticity regions coexist, and inertial clustering of cloud droplets can occur in low-vorticity regions. The nonuniformity in the spatial distribution of the size and in the number of droplets, variable vertical velocity in vortical turbulent structures, and dilution by entrainment/mixing may result in spatial supersaturation variability, which affects the evolution of the cloud droplet size spectrum via condensation and evaporation processes. To untangle the processes involved in mixing phenomena, a 3D direct numerical simulation of turbulent mixing followed by droplet evaporation/condensation in a submeter-sized cubed domain consisting of a large number of droplets was performed in this study. The analysis focused on the thermodynamic and microphysical characteristics of the droplets and the flow in high- and low-vorticity regions. The impact of vorticity generation in turbulent flows on mixing and cloud microphysics is illustrated.

Effects of the large-scale circulation on temperature and water vapor distributions in the Π Chamber

Abstract. Microphysical processes are important for the development of clouds and thus Earth's climate. For example, turbulent fluctuations in the water vapor mixing ratio, r, and temperature, T, cause fluctuations in the saturation ratio, S. Because S is the driving factor in the condensational growth of droplets, fluctuations may broaden the cloud droplet size distribution due to individual droplets experiencing different growth rates. The small-scale turbulent fluctuations in the atmosphere that are relevant to cloud droplets are difficult to quantify through field measurements. We investigate these processes in the laboratory using Michigan Tech's Π Chamber. The Π Chamber utilizes Rayleigh–Bénard convection (RBC) to create the turbulent conditions inherent in clouds. In RBC it is common for a large-scale circulation (LSC) to form. As a consequence of the LSC, the temperature field of the chamber is not spatially uniform. In this paper, we characterize the LSC in the Π Chamber and show how it affects the shape of the distributions of r, T, and S. The LSC was found to follow a single roll with an updraft and downdraft along opposing walls of the chamber. Near the updraft (downdraft), the distributions of T and r were positively (negatively) skewed. At each measuring position, S consistently had a negatively skewed distribution, with the downdraft being the most negative.

Biomass Burning Smoke and Its Influence on Clouds Over the Western U. S.

AbstractSmall cumulus clouds over the western United States were measured via airborne instruments during the wildfire season in summer of 2018. Statistics of the sampled clouds are presented and compared to smoke aerosol properties. Cloud droplet concentrations were enhanced in regions impacted by biomass burning smoke, at times exceeding 3,000 cm−3. Images and elemental composition of individual smoke particles and cloud droplet residuals are presented and show that most are dominantly organic, internally mixed with some inorganic elements. Despite their high organic content and relatively low hygroscopicity, on average about half of smoke aerosol particles >80 nm diameter formed cloud droplets. This reduced cloud droplet size in small, smoke‐impacted clouds. A number of complex and competing climatic impacts may result from wide‐spread reductions in cloud droplet size due to wildfires prevalent across the region during summer months.

Impact of entrainment-mixing and turbulent fluctuations on droplet size distributions in a cumulus cloud: An investigation using Lagrangian microphysics with a sub-grid-scale model

AbstractEntrainment-mixing and turbulent fluctuations critically impact cloud droplet size distributions (DSDs) in cumulus clouds. This problem is investigated via a new sophisticated modeling framework using the CM1 LES model and a Lagrangian cloud microphysics scheme – the “super-droplet method” (SDM) – coupled with sub-grid-scale (SGS) schemes for particle transport and supersaturation fluctuations. This modeling framework is used to simulate a cumulus congestus cloud. Average DSDs in different cloud regions show broadening from entrainment and secondary cloud droplet activation (activation above the cloud base). DSD width increases with increasing entrainment-induced dilution as expected from past work, except in the most diluted cloud regions. The new modeling framework with SGS transport and supersaturation fluctuations allows a more sophisticated treatment of secondary activation compared to previous studies. In these simulations, it contributes about 25%of the cloud droplet population and impacts DSDs in two contrastingways: narrowing in extremely diluted regions and broadening in relatively less diluted. SGS supersaturation fluctuations contribute significantly to an increase in DSD width via condensation growth and evaporation. Mixing of super-droplets from SGS velocity fluctuations also broadens DSDs. The relative dispersion (ratio of DSD dispersion and mean radius) negatively correlates with grid-scale vertical velocity in updrafts, but is positively correlated in downdrafts. The latter is from droplet activation driven by positive SGS supersaturation fluctuations in grid-mean subsaturated conditions. Finally, the sensitivity to model grid length is evaluated. The SGS schemes have greater influence as the grid length is increased, and they partially compensate for the reduced model resolution.

Volcanic Aerosol Impacts on Hawai‘i Island Rainfall

AbstractIn recent decades, a significant rainfall decline over the island of Hawai‘i has been noted, with many hypothesizing that the drying is associated with the volcanic aerosols emitted from the Kīlauea volcano. While it is clear that volcanic emissions can create hazardous air quality for Hawaiian communities, the impacts on rainfall are less clear. Here we investigate the impact of volcanic aerosol emissions on Hawai‘i Island rainfall. Based on observed daily rainfall and SO2 emissions, it is found that days with high SO2 emissions have on average 8 mm day−1 less rainfall downstream of the Kīlauea volcano. Sensitivity studies with varying volcanic aerosol emission sources from the Kīlauea vent locations have also been conducted by the Weather Research and Forecasting (WRF) Model in order to examine the detailed physical processes. Consistent with SO2 air quality observations, it is found that the diurnal change in aerosol number concentration is strongly dependent on the diurnal variation of local circulations. The added aerosols are lofted into the orographic convection where they modify the microphysical properties of the warm clouds by increasing the cloud droplet number concentration, decreasing the cloud droplet size, increasing cloud water content, and enhancing cloud evaporation. The volcanic aerosols also delay precipitation production and modify the spatial distribution of rainfall on the downstream mountainside. The modification of precipitation on an island has far-reaching consequences. For this reason, we work to quantify the sensitivity of the orographic precipitation to volcanic aerosols and move beyond hypothesized relationships to work toward understanding the underlying problem.

Droplet characteristics in monsoon clouds before rain as observed over a high altitude site in Western Ghats, India

The cloud droplet size distribution (CDSD) and microphysical properties prior to monsoon rain events is studied using in-situ ground observations over a high altitude site in Western Ghats, India. The cloud microphysical properties, such as cloud droplet number concentration (CDNC), liquid water content (LWC), cloud droplet spectrum, droplet effective diameter (ED), droplet mean radius (Rm), spectral width (σ), and relative dispersion (ε) showed a considerable variation. A detailed analysis of CDSD before rain events showed single and multi-mode patterns which varied from case to case. An apparent variation in cloud microphysical properties is noted for both single and multi-mode cases. Large cloud droplets were found in both single and multi-mode clouds, and analysis revealed the possibility of entrainment of aerosols into these clouds leading to multi modes in the CDSD. Observed rain event duration indirectly suggested higher warm rain depths (D*) when multi-mode cases are observed.

Consideration of Initial Cloud Droplet Size Distribution Shapes in Quantifying Different Entrainment‐Mixing Mechanisms

AbstractEntrainment‐mixing process significantly affects cloud micro/macrophysics and the evaluation of aerosol indirect effects. However, it is still an open question as to how to quantify entrainment‐mixing mechanism for broad cloud droplet size distributions (CDSDs). Here, CDSDs with different spectral widths are used to initialize the Explicit Mixing Parcel Model to address this problem, and microphysical properties are compared for different CDSD widths. For relatively broad CDSDs, as the number concentration and liquid water content decrease, the volume‐mean radius and mean radius increase, which is opposite to the scenario for relatively narrow CDSDs and the homogeneous/inhomogeneous conceptual model. For the relatively broad CDSDs, such relationships could be mistaken as inhomogeneous mixing with subsequent ascent in analysis of the conventional microphysical mixing diagram. This then causes traditional homogenous mixing degrees to be unrealistically negative and not applicable for relatively broad CDSDs. New measures are introduced to explicitly account for the effect of CDSD spectral shapes on quantifying entrainment‐mixing mechanism. The new measures yield reasonable ranges of values that conform to the dynamical measures such as the Damköhler and transitional scale numbers, and their temporal variation can be explained physically. This study extends the measures of homogeneous mixing degrees from narrow to broad CDSDs, and sheds new light on the consideration of CDSD shapes in parameterizations of entrainment‐mixing mechanism.

The Spectral Nature of Earth’s Reflected Radiation: Measurement and Science Applications

This paper introduces the aerosol, clouds, convection and precipitation (ACCP) program that is currently in the process of defining a number of measurement objectives for NASA that are to be implemented toward the end of the current decade. Since a (solar) visible-shortwave infrared (VSWIR) spectrometer is being considered as part of the ACCP architecture, illustrations of the different ways these measurements will contribute to this program and how these measurements can be expected to advance the science objectives of ACCP are highlighted. These contributions range from 1) constraining cloud radiative process and related estimates of radiative fluxes, 2) scene discrimination, 3) providing aerosol and cloud optical properties, and 4) providing other enhanced information such as the phase of water in clouds, and total column water vapor. The spectral measurements also offer new capabilities that will further enhance the ACCP science such as the discrimination of dust aerosol and the potential for the vertical profiling cloud droplet size in shallow clouds. The areas where the maturity of approaches is lacking is also highlighted as a way of emphasizing research topics to be a focus in the coming years.

Reduction in autumn precipitation over Southwest China by anthropogenic aerosol emissions from eastern China

Impacts of anthropogenic aerosols in China on autumn precipitation over Southwest China were investigated using version 5.1 of the Community Atmosphere Model. Simulations with and without anthropogenic aerosol emissions were compared to examine the effects of anthropogenic aerosols on surface air temperature and precipitation in East Asia. Our results show that the aerosol increase induces strong cooling over East Asia by aerosols' direct effect on radiation and indirect effect on clouds. Substantial reductions in precipitation are found across eastern China, but the largest decrease is in Southwest China. Anthropogenic aerosols cause a considerable increase in the cloud condensation nuclei number concentration and a decline in the cloud droplet effective radius in East Asia. The reduced cloud droplet sizes suppress the formation of precipitation and increase cloud depth and liquid water path. Consequently, aerosols' direct radiative effect as well as indirect effect on cloud depth and albedo significantly reduce the shortwave radiation for all sky between 20°and 40°N in China. More absorbing aerosols in the lower troposphere increase shortwave radiative heating, which possibly burns off low-level convective clouds and could cause significant reductions in condensational heating in the lower troposphere. The patterns of the shortwave heating increase and condensational heating reduction are generally consistent with significant reductions in the convective precipitation over China. We further investigated other factors governing precipitation and found moderate stability enhancement and moisture transport reductions in most of China, both of which partially contribute to a decrease in the convective precipitation in Southwest China. Aerosols' direct and indirect effects reduce the amount of solar radiation reaching the surface and cool the surface and lower troposphere between 20° and 40°N, causing anomalous subsidence and reductions in the large-scale precipitation over central and eastern China. Both convective and large-scale precipitation are suppressed over Southwest China, leading to a significant decrease in total precipitation over this area.