Abstract

Many efforts have been taken to investigate aerosol–cloud interactions from space, but only a few studies have examined the response of vertical cloud structure to aerosol perturbations. Three-dimensional cloud climatologies of eight different cloud types identified from the CloudSat level-2 cloud product during the warm season (May–September) in 2008–10 over eastern China were first generated and analyzed. Using visibility as a proxy for cloud condensation nuclei, in combination with satellite-observed radar reflectivity, normalized contoured frequency by altitude diagrams of the differences in cloud radar reflectivity Z profiles under polluted and clean conditions were constructed. For shallow cumulus clouds (shallow Cu) Z tends to be inhibited, and it is enhanced in the upper layers for deep cumulus (deep Cu), nimbostratus (Ns), and deep convective clouds (DCC) under polluted conditions. Overall, analyses of the modified center of gravity (MCOG) and cloud-top height (CTH) also point to a similar aerosol effect, except for the nonsignificant changes in MCOGs and CTHs in deep Cu. The impacts of environmental factors such as lower-tropospheric stability and vertical velocity are also discussed for these types of clouds. Although consistent aerosol-induced elevations in MCOGs and CTHs for Ns and DCC clouds are observed, the effect of meteorology cannot be completely ruled out, which merits further analysis.

Abstract

A continental cloud complex, consisting of shallow cumuli, a deep convective cloud (DCC), and stratus, is simulated by a cloud-resolving Weather Research and Forecasting Model to investigate the aerosol microphysical effect (AME) and aerosol radiative effect (ARE) on the various cloud regimes and their transitions during the Department of Energy Routine Atmospheric Radiation Measurement Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) campaign. Under an elevated aerosol loading with AME only, a reduced cloudiness for the shallow cumuli and stratus resulted from more droplet evaporation competing with suppressed precipitation, but an enhanced cloudiness for the DCC is attributed to more condensation. With the inclusion of ARE, the shallow cumuli are suppressed owing to the thermodynamic effects of light-absorbing aerosols. The responses of DCC and stratus to aerosols are monotonic with AME only but nonmonotonic with both AME and ARE. The DCC is invigorated because of favorable convection and moisture conditions at night induced by daytime ARE, via the so-called aerosol-enhanced conditional instability mechanism. The results reveal that the overall aerosol effects on the cloud complex are distinct from the individual cloud types, highlighting that the aerosol–cloud interactions for diverse cloud regimes and their transitions need to be evaluated to assess the regional and global climatic impacts.

Abstract

The suggested impact of pollution on deep convection dynamics, referred to as the convective invigoration, is investigated in simulations applying microphysical piggybacking and a comprehensive double-moment bulk microphysics scheme. The setup follows the case of daytime convective development over land based on observations during the Large-Scale Biosphere–Atmosphere (LBA) experiment in Amazonia. In contrast to previous simulations with single-moment microphysics schemes and in agreement with results from bin microphysics simulations by others, the impact of pollution simulated by the double-moment scheme is large for the upper-tropospheric convective anvils that feature higher cloud fractions in polluted conditions. The increase comes from purely microphysical considerations: namely, the increased cloud droplet concentrations in polluted conditions leading to the increased ice crystal concentrations and, consequently, smaller fall velocities and longer residence times. There is no impact on convective dynamics above the freezing level and thus no convective invigoration. Polluted deep convective clouds precipitate about 10% more than their pristine counterparts. The small enhancement comes from smaller supersaturations below the freezing level and higher buoyancies inside polluted convective updrafts with velocities between 5 and 10 m s⁻¹. The simulated supersaturations are large, up to several percent in both pristine and polluted conditions, and they call into question results from deep convection simulations applying microphysical schemes with saturation adjustment. Sensitivity simulations show that the maximum supersaturations and the upper-tropospheric anvil cloud fractions strongly depend on the details of small cloud condensation nuclei (CCN) that can be activated in strong updrafts above the cloud base.

Abstract

This paper furthers previous investigations into the zenith angular effect of cloud contamination within infrared (IR) window radiance observations commonly used in the retrieval of environmental data records (EDRs). Here analyses were performed of clear-sky forward radiance calculations versus observations obtained under clear to partly cloudy conditions over ocean. The authors utilized high-resolution IR spectra observed by the aircraft-based National Polar-Orbiting Partnership (NPP) Aircraft Sounder Test Bed-Interferometer (NAST-I) during the Joint Airborne Infrared Atmospheric Sounding Interferometer (IASI) Validation Experiment (JAIVEx) and performed forward calculations using collocated dropsondes. An aerosol optical depth EDR product derived from Geostationary Operational Environmental Satellite (GOES) was then applied to detect clouds within NAST-I fields of view (FOVs). To calculate the angular variation of clouds, expressions were derived for estimating cloud aspect ratios from visible imagery where cloud shadow lengths can be estimated relative to cloud horizontal diameters. In agreement with sensitivity calculations, it was found that a small cloud fraction within window radiance observations can have a measurable impact on the angular agreement with clear-sky calculations on the order of 0.1–0.4 K in brightness temperature. It was also found that systematic sun-glint contamination can likewise have an impact on the order of 0.1 K. These results are germane to IR sensor data record (SDR) calibration/validation and EDR retrieval schemes depending upon clear-sky SDRs, as well as radiative transfer modeling involving randomly distributed broken cloud fields.

Abstract

Ice nucleating particle (INP) concentrations were measured at the High Altitude Research Station Jungfraujoch, Switzerland, 3580 m above mean sea level during the winter months of 2012, 2013, and 2014 with the Portable Ice Nucleation Chamber (PINC). During the measurement periods, the research station was mostly located in the free troposphere, and particle concentrations were low. At temperature T = 241 K, INP concentrations in the deposition regime [relative humidity with respect to water (RH _w ) = 93%] were, on average, below 1.09 per standard liter of air (stdL⁻¹; normalized to 1013 hPa and 273 K) and 4.7 ± 8.3 stdL⁻¹ in the condensation regime (RH _w = 103%) in winter 2014. The deployment of a particle concentrator upstream of PINC decreased the limit of detection (LOD) by a factor of 3 compared to earlier measurements. The authors discuss a potential bias of INP measurements toward higher concentrations if data below the LOD are disregarded and thus recommend reporting subLOD data in future publications. Saharan dust and more local, basaltic dust mixed with marine aerosol were found to constitute the dominant INP type. Bioaerosols were not observed to play a role in ice nucleation during winter because of their low concentration during this period. The INP concentrations at Jungfraujoch are low in comparison to other studies of INP at this temperature. This represents the first study addressing interannual variations of INP concentrations during winter at one location.

Abstract

Taking Typhoon Usagi (2013) as an example, this study used the Weather Research and Forecasting Model with Chemistry to investigate the influence of anthropogenic aerosols on typhoons. Three simulations (CTL, CLEAN, EXTREME) were designed according to the emission intensity of the anthropogenic pollution. The results showed that although anthropogenic pollution did not demonstrate clear influence on the track and strength of the typhoon, it clearly changed the precipitation, distribution of water hydrometeors, and microphysical processes. In the CLEAN experiment, the precipitation rate declined because cloud water collected by the rain decreased. Similarly, the precipitation rate decreased in the EXTREME experiment, because the autoconversion of cloud water to rain was restrained. Regarding precipitation type, the rate of stratiform precipitation in both the CLEAN and the EXTREME simulations was suppressed because the ice-phase microphysical processes weakened. Compared with the CTL run, the rate of stratiform precipitation at the periphery of the typhoon was reduced by about 28% in both the CLEAN and the EXTREME simulations. Moreover, the rate of convective precipitation within 140–160 km of the center of the typhoon in the EXTREME experiment was about 33% greater than in the CTL simulation. This increase was triggered by new convection at the periphery in the EXTREME simulation related to cloud water reevaporation. Finally, compared with the CTL experiment, the peaks of both convective and mixed precipitation in the CLEAN and EXTREME experiments shifted 10 km toward the typhoon periphery.

Abstract

A significant reduction in precipitation in the past decades has been documented over many mountain ranges such as those in central and eastern China. Consistent with the increase of air pollution in these regions, it has been argued that the precipitation trend is linked to the aerosol microphysical effect on suppressing warm rain. Rigorous quantitative investigations on the reasons responsible for the precipitation reduction are lacking. In this study, an improved Weather Research and Forecasting (WRF) Model with online coupled chemistry (WRF-Chem) is applied and simulations are conducted at the convection-permitting scale to explore the major mechanisms governing changes in precipitation from orographic clouds in the Mt. Hua area in central China. It is found that anthropogenic pollution contributes to a ~40% reduction of precipitation over Mt. Hua during the 1-month summertime period. The reduction is mainly associated with precipitation events associated with valley–mountain circulation and a mesoscale cold-front event. In this paper (Part I), the mechanism leading to a significant reduction for the cases associated with valley–mountain circulation is scrutinized. It is found that the valley breeze is weakened by aerosols as a result of absorbing aerosol-induced warming aloft and cooling near the surface as a result of aerosol–radiation interaction (ARI). The weakened valley breeze and the reduced water vapor in the valley due to reduced evapotranspiration as a result of surface cooling significantly reduce the transport of water vapor from the valley to mountain and the relative humidity over the mountain, thus suppressing convection and precipitation in the mountain.

Abstract

The nucleation of cloud droplets from the ambient aerosol is a critical physical process that must be resolved for global models to faithfully predict aerosol–cloud interactions and aerosol indirect effects on climate. To better represent droplet nucleation from a complex, multimodal, and multicomponent aerosol population within the context of a global model, a new metamodeling framework is applied to derive an efficient and accurate activation parameterization. The framework applies polynomial chaos expansion to a detailed parcel model in order to derive an emulator that maps thermodynamic and aerosol parameters to the supersaturation maximum achieved in an adiabatically ascending parcel and can be used to diagnose droplet number from a single lognormal aerosol mode. The emulator requires much less computational time to build, store, and evaluate than a high-dimensional lookup table. Compared to large sample sets from the detailed parcel model, the relative error in the predicted supersaturation maximum and activated droplet number computed with the best emulator is and (one standard deviation), respectively. On average, the emulators constructed here are as accurate and between 10 and 17 times faster than a leading physically based activation parameterization. Because the underlying parcel model being emulated resolves size-dependent droplet growth factors, the emulator captures kinetic limitations on activation. The results discussed in this work suggest that this metamodeling framework can be extended to accurately account for the detailed activation of a complex aerosol population in an arbitrary coupled global aerosol–climate model.

Abstract

A midlatitude hail storm was simulated using a new version of the spectral bin microphysics Hebrew University Cloud Model (HUCM) with a detailed description of time-dependent melting and freezing. In addition to size distributions of drops, plate-, columnar-, and branch-type ice crystals, snow, graupel, and hail, new distributions for freezing drops as well as for liquid water mass within precipitating ice particles were implemented to describe time-dependent freezing and wet growth of hail, graupel, and freezing drops.

Simulations carried out using different aerosol loadings show that an increase in aerosol loading leads to a decrease in the total mass of hail but also to a substantial increase in the maximum size of hailstones. Cumulative rain strongly increases with an increase in aerosol concentration from 100 to about 1000 cm⁻³. At higher cloud condensation nuclei (CCN) concentrations, the sensitivity of hailstones’ size and surface precipitation to aerosols decreases. The physical mechanism of these effects was analyzed. It was shown that the change in aerosol concentration leads to a change in the major mechanisms of hail formation and growth. The main effect of the increase in the aerosol concentration is the increase in the supercooled cloud water content. Accordingly, at high aerosol concentration, the hail grows largely by accretion of cloud droplets in the course of recycling in the cloud updraft zone. The main mechanism of hail formation in the case of low aerosol concentration is freezing of raindrops.

Abstract

It has been widely recognized that aerosols can modify cloud properties, but it remains uncertain how much the changes and associated variations in cloud radiative forcing are related to aerosol loading. Using 4 yr of A-Train satellite products generated from CloudSat, the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite, and the Aqua satellite, the authors investigated the systematic changes of deep cloud properties and cloud radiative forcing (CRF) with respect to changes in aerosol loading over the entire tropics. Distinct correlations between CRF and aerosol loading were found. Systematic variations in both shortwave and longwave CRF with increasing aerosol index over oceans and aerosol optical depth over land for mixed-phase clouds were identified, but little change was seen in liquid clouds. The systematic changes are consistent with the microphysical effect and the aerosol invigoration effect. Although this study cannot fully exclude the influence of other factors, attempts were made to explore various possibilities to the extent that observation data available can offer. Assuming that the systematic dependence originates from aerosol effects, changes in CRF with respect to aerosol loading were examined using satellite retrievals. Mean changes in shortwave and longwave CRF from very clean to polluted conditions ranged from −192.84 to −296.63 W m⁻² and from 18.95 to 46.12 W m⁻² over land, respectively, and from −156.12 to −170.30 W m⁻² and from 6.76 to 11.67 W m⁻² over oceans, respectively.