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The global methane pledge paves a fresh, critical way toward carbon neutrality. However, it remains largely invisible and highly controversial due to the fact that planet-scale and plant-level methane retrievals have rarely been coordinated. This has never been more essential within the narrow window to reach the Paris target. Here we present a two-tiered spaceborne architecture to address this issue. Using this framework, we focused on the United States, China, the Middle East, and North Africa, and simultaneously uncovered methane-abundant regions and plumes. These include new super-emitters, potential leakages, and unprecedented multiple plumes in a single source. More importantly, this framework is shown to challenge official emission reports that possibly mislead estimates from global, regional, and site scales, particularly by missing super-emitters. Our results show that, in principle, the above framework can be extended to be multi-tiered by adding upcoming stereoscopic measurements and suitable artificial intelligence, and thus it is sufficiently versatile for immediate and future monitoring of the global methane pledge.

A method to derive the 3D cloud envelope and the cloud development velocity from high spatial and temporal resolution satellite imagery is presented. The CLOUD instrument of the recently proposed C3IEL mission lends itself well to observing at high spatial and temporal resolutions the development of convective cells. Space-borne visible cameras simultaneously image, under multiple view angles, the same surface domain every 20 s over a time interval of 200 s. In this paper, we present a method for retrieving cloud development velocity from simulated multi-angular, high-resolution top of the atmosphere (TOA) radiance cloud fields. The latter are obtained via the image renderer Mitsuba for a cumulus case generated via the atmospheric research model SAM and via the radiative transfer model 3DMCPOL, coupled with the outputs of an orbit, attitude, and camera simulator for a deep convective cloud case generated via the atmospheric research model Meso-NH. Matching cloud features are found between simulations via block matching. Image coordinates of tie points are mapped to spatial coordinates via 3D stereo reconstruction of the external cloud envelope for each acquisition. The accuracy of the retrieval of cloud topography is quantified in terms of RMSE and bias that are, respectively, less than 25 and 5 m for the horizontal components and less than 40 and 25 m for the vertical components. The inter-acquisition 3D velocity is then derived for each pair of tie points separated by 20 s. An independent method based on minimising the RMSE for a continuous horizontal shift of the cloud top, issued from the atmospheric research model, allows for the obtainment of a ground estimate of the velocity from two consecutive acquisitions. The mean values of the distributions of the stereo and ground velocities exhibit small biases. The width of the distributions is significantly different, with higher a distribution width for the stereo-retrieved velocity. An alternative way to derive an average velocity over 200 s, which relies on tracking clusters of points via image feature matching over several acquisitions, was also implemented and tested. For each cluster of points, mean stereo and ground positions were derived every 20 s over 200 s. The mean stereo and ground velocities, obtained as the slope of the line of best fit to the mean positions, are in good agreement.

Condensable particulate matter (CPM) emitted from stationary combustion and mobile sources exhibits high emissions and a large proportion of organic components. However, CPM is not generally measured when conducting emission surveys of PM in most countries, including China. Consequently, previous emission inventories have not included emission rates for CPM. Here, we construct an emission inventory of CPM in China with a focus on organic aerosols (OAs) based on collected CPM emission information. Results show that OA emissions are enhanced twofold after the inclusion of CPM in a new inventory for China for the years 2014 and 2017. Considering organic CPM emissions and model representations of secondary OA (SOA) formation from CPM, a series of sensitivity cases have been simulated here using the three-dimensional Community Multiscale Air Quality (CMAQ) model to estimate the contributions of CPM emissions to atmospheric OA and fine PM (PM2.5, particulate matter with aerodynamic diameter not exceeding 2.5 µm) concentrations in China. Compared with observations at a Beijing site during a haze episode from 14 October to 14 November 2014, estimates of the temporal average primary OA (POA) and SOA concentrations were greatly improved after including the CPM effects. These scenarios demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to the POA (51 %–85 %​​​​​​​), SOA (42 %–58 %), and total OA concentrations (45 %–75 %). Furthermore, the contributions of CPM emissions to total OA concentrations were demonstrated over the 2 major cities and 26 other cities of the Beijing–Tianjin–Hebei region (hereafter referred to as the “BTH2 + 26 cities”) in December 2018, with average contributions of up to 49 %, 53 %, 54 %, and 50 % for Handan, Shijiazhuang, Xingtai, and Dezhou, respectively. Correspondingly, the inclusion of CPM emissions also narrowed the gap between simulated and observed PM2.5 concentrations over the BTH2 + 26 cities. These results improve the simulation performance of atmospheric OA and PM2.5 and may also provide important implications for the sources of OA.

Aerosols significantly affect the Earth–atmosphere energy balance and climate change by acting as cloud condensation nuclei. Specifically, the susceptibility of cloud and precipitation to aerosols is stronger when aerosols are faint but tends to be saturated in polluted conditions. However, previous methodologies generally miss these faint aerosols based on instantaneous observations because they are too optically thin to be detected and are therefore usually unretrieved. This result in a large underestimation when quantifying aerosol climate impacts. Here, we focus on retrieving and verifying the instantaneous extinction of undetected faint aerosol by the CALIPSO layer detection algorithm on a global scale. Using the observations during the Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) as constraints, the lidar ratios of undetected faint aerosol are estimated with a global median of 42.2 and 24.5 sr at the stratosphere and the troposphere, respectively. The retrieved extinction of undetected aerosol during night-time shows good agreement with the independent 12-month SAGE III/ISS product on a 1∘ average. The corresponding correlation coefficient and averaged normalized root-mean-square error are 0.66 % and 100.6 %, respectively. The minimum retrieved extinction coefficients can be extended to 10−3 and 10−4 km−1 with an uncertainty of 35 % and 125 % during night-time, respectively. The CALIPSO retrieval during daytime has a positive bias and relatively low agreement with SAGE III/ISS due to the low signal-to-noise ratio caused by sunlight. This study has great potential for improving the understanding of aerosol variations and the quantification of aerosol impacts on global climate change.

Aerosol–cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide “opportunistic experiments” (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

Aerosol–cloud interactions contribute to the large uncertainties in current estimates of climate forcing. We investigated the effect of aerosol particles on cloud droplet formation by model calculations and aircraft measurements over the Amazon and over the western tropical Atlantic during the ACRIDICON–CHUVA campaign in September 2014. On the HALO (High Altitude Long Range Research) research aircraft, cloud droplet number concentrations (Nd) were measured near the base of clean and polluted growing convective cumuli using a cloud combination probe (CCP) and a cloud and aerosol spectrometer (CAS-DPOL). An adiabatic parcel model was used to perform cloud droplet number closure studies for flights in differently polluted air masses. Model input parameters included aerosol size distributions measured with an ultra-high sensitive aerosol spectrometer (UHSAS), in combination with a condensation particle counter (CPC). Updraft velocities (w) were measured with a boom-mounted Rosemount probe. Over the continent, the aerosol size distributions were dominated by accumulation mode particles, and good agreement between measured and modeled Nd values was obtained (deviations ≲ 10 %) assuming an average hygroscopicity of κ∼0.1, which is consistent with Amazonian biomass burning and secondary organic aerosol. Above the ocean, fair agreement was obtained assuming an average hygroscopicity of κ∼0.2 (deviations ≲ 16 %) and further improvement was achieved assuming different hygroscopicities for Aitken and accumulation mode particles (κAit=0.8, κacc=0.2; deviations ≲ 10 %), which may reflect secondary marine sulfate particles. Our results indicate that Aitken mode particles and their hygroscopicity can be important for droplet formation at low pollution levels and high updraft velocities in tropical convective clouds.

Urban on-road vehicle emissions affect air quality and human health locally and globally. Given uneven sources, they typically exhibit distinct spatial heterogeneity, varying sharply over short distances (10 m–1 km). However, all-around observational constraints on the emission sources are limited in much of the world. Consequently, traditional emission inventories lack the spatial resolution that can characterize the on-road vehicle emission hotspots. Here we establish a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at a spatial resolution 1–3 orders of magnitude higher than current emission inventories. We interconnect all-around traffic monitoring (including traffic fluxes, vehicle-specific categories, and speeds) via an intelligent transportation system (ITS) over Xiaoshan District in the Yangtze River Delta (YRD) region. This enables us to calculate single-vehicle-specific emissions over each fine-scale (10 m–1 km) road segment. Thus, the most hyperfine emission dataset of its type is achieved, and on-road emission hotspots appear. The resulting map shows that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74.01, 40.35, 8.13, and 1.68 kg, respectively. More importantly, widespread and persistent emission hotspots emerged. They are of significantly sharp small-scale variability, up to 8–15 times within individual hotspots, attributable to distinct traffic fluxes, road conditions, and vehicle categories. On this basis, we investigate the effectiveness of routine traffic control strategies on on-road vehicle emission mitigation. Our results have important implications for how the strategies should be designed and optimized. Integrating our traffic-monitoring-based approach with urban air quality measurements, we could address major data gaps between urban air pollutant emissions and concentrations.

Quantifying the precipitation within clouds is a crucial challenge to improve our current understanding of the Earth's hydrological cycle. We have investigated the relationship between the effective radius of droplets and ice particles (re) and precipitation water content (PWC) measured by cloud probes near the top of growing convective cumuli. The data for this study were collected during the ACRIDICON–CHUVA campaign on the HALO research aircraft in clean and polluted conditions over the Amazon Basin and over the western tropical Atlantic in September 2014. Our results indicate a threshold of re∼13 µm for warm rain initiation in convective clouds, which is in agreement with previous studies. In clouds over the Atlantic Ocean, warm rain starts at smaller re, likely linked to the enhancement of coalescence of drops formed on giant cloud condensation nuclei. In cloud passes where precipitation starts as ice hydrometeors, the threshold of re is also shifted to values smaller than 13 µm when coalescence processes are suppressed and precipitating particles are formed by accretion. We found a statistically significant linear relationship between PWC and re for measurements at cloud tops, with a correlation coefficient of ∼0.94. The tight relationship between re and PWC was established only when particles with sizes large enough to precipitate (drizzle and raindrops) are included in calculating re. Our results emphasize for the first time that re is a key parameter to determine both initiation and amount of precipitation at the top of convective clouds.

Satellite-based cloud base and top height (CBH and CTH) and cloud geometrical thickness (CGT) are validated against ground-based lidar measurements and provide new scientific insights. The satellite measurements are done by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The retrieval methodology is built on the 333 m resolution low-level water cloud data obtained from the Vertical Feature Mask product of CALIPSO. The methodology is based on the definition that CBH of boundary layer clouds is the lowest cloud base over an area of several tens of kilometers. This allows taking the CBH of the neighboring penetrable shallower cloud as having CBH representative for the entire cloud field. The methodology over the ocean was validated based on observations from two surface-based ceilometer measurements in the islands of Barbados and the Azores, with an error standard deviation of ±115 m. Validation over land was based on 4 years data of 138 terrestrial ceilometer sites with an error standard deviation of ±220 m. The unprecedented accurate CBH allows us to obtain CGT, which is an essential parameter in the understanding of the aerosol–cloud interaction. Based on this newly developed methodology, we retrieved the annual, seasonal, and diurnal distributions of global CBH, CTH, and CGT for two years and analyzed the variations of CBH and CTH over the ocean and land. Climatology of the annual mean cloud geometrical properties shows the following. (1) The lowest CBH occurs over the eastern margins of the subtropical oceans and increases westward from 300–400 to 800–900 m. The CGT increases from 300 to 1200 m, respectively. In the western part of the tropical oceans, CBH is 500–600 m and CGT is ∼ 1500 m. (2) A narrow band of lower CBH and CGT occurs over the Equator, especially over the eastern parts of the oceans. (3) CBH and CGT over the tropical rain forests (Amazon and Congo) are 1200 and 1500 m, respectively. CBH over the drier tropical land is 1500–2000 m, with CGT of 800–1000 m. (4) CBH decreases towards Antarctica in the Southern Ocean, while CGT deepens. (5) Seasonally, the mid-latitude global oceans have the lowest CBH (mostly below 500 m) and CGT in summer seasons and the highest values in winter. (6) There is just an obvious difference between day and night for the maximum CTH and CGT over the tropics. Over the ocean, there is no discernible difference in CBH, but during night CTH is higher by ∼ 300 m.

Convective clouds are common and play a major role in Earth's water cycle and energy balance; they may even develop into storms and cause severe rainfall events. To understand the convective cloud development process, this study investigates the impact of aerosols on convective clouds by considering the influence of both topography and diurnal variation in radiation. By combining texture analysis, clustering, and thresholding methods, we identify all convective clouds in two warm seasons (May–September, 2016/17) in eastern China based on Himawari-8 Level 1 data. Having large diurnally resolved cloud data together with surface meteorological and environmental measurements, we investigate convective cloud properties and their variation, stratified by elevation and diurnal change. We then analyze the potential impact of aerosol on convective clouds under different meteorological conditions and topographies. In general, convective clouds tend to occur preferentially under polluted conditions in the morning, which reverses in the afternoon. Convective cloud fraction first increases then decreases with aerosol loading, which may contribute to this phenomenon. Topography and diurnal meteorological variations may affect the strength of aerosol microphysical and radiative effects. Updraft is always stronger along the windward slopes of mountains and plateaus, especially in northern China. The prevailing southerly wind near the foothills of mountains and plateaus is likely to contribute to this windward strengthening of updraft and to bring more pollutant into the mountains, thereby strengthening the microphysical effect, invigorating convective clouds. By comparison, over plain, aerosols decrease surface heating and suppress convection by blocking solar radiation reaching the surface.

Aerosol–cloud interactions remain largely uncertain with respect to predicting their impacts on weather and climate. Cloud microphysics parameterization is one of the factors leading to large uncertainty. Here, we investigate the impacts of anthropogenic aerosols on the convective intensity and precipitation of a thunderstorm occurring on 19 June 2013 over Houston with the Chemistry version of Weather Research and Forecast model (WRF-Chem) using the Morrison two-moment bulk scheme and spectral bin microphysics (SBM) scheme. We find that the SBM predicts a deep convective cloud that shows better agreement with observations in terms of reflectivity and precipitation compared with the Morrison bulk scheme that has been used in many weather and climate models. With the SBM scheme, we see a significant invigoration effect on convective intensity and precipitation by anthropogenic aerosols, mainly through enhanced condensation latent heating. Such an effect is absent with the Morrison two-moment bulk microphysics, mainly because the saturation adjustment approach for droplet condensation and evaporation calculation limits the enhancement by aerosols in (1) condensation latent heat by removing the dependence of condensation on droplets and aerosols and (2) ice-related processes because the approach leads to stronger warm rain and weaker ice processes than the explicit supersaturation approach.

The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd, ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd, ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, ΔNd, ant, remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of metres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining ΔNd, ant, namely the quantification of (i) the cloud-active aerosol – the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) Nd, (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd-to-CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

Ambient fine particulate matter (PM2.5) mitigation relies strongly on anthropogenic emission control measures, the actual effectiveness of which is challenging to pinpoint owing to the complex synergies between anthropogenic emissions and meteorology. Here, observational constraints on model simulations allow us to derive not only reliable PM2.5 evolution but also accurate meteorological fields. On this basis, we isolate meteorological factors to achieve reliable estimates of surface PM2.5 responses to both long-term and emergency emission control measures from 2016 to 2019 over the Yangtze River Delta (YRD), China. The results show that long-term emission control strategies play a crucial role in curbing PM2.5 levels, especially in the megacities and other areas with abundant anthropogenic emissions. The G20 summit hosted in Hangzhou in 2016 provides a unique and ideal opportunity involving the most stringent, even unsustainable, emergency emission control measures. These emergency measures lead to the largest decrease (∼ 35 µg m−3, ∼ 59 %) in PM2.5 concentrations in Hangzhou. The hotspots also emerge in megacities, especially in Shanghai (32 µg m−3, 51 %), Nanjing (27 µg m−3, 55 %), and Hefei (24 µg m−3, 44 %) because of the emergency measures. Compared to the long-term policies from 2016 to 2019, the emergency emission control measures implemented during the G20 Summit achieve more significant decreases in PM2.5 concentrations (17 µg m−3 and 41 %) over most of the whole domain, especially in Hangzhou (24 µg m−3, 48 %) and Shanghai (21 µg m−3, 45 %). By extrapolation, we derive insight into the magnitude and spatial distribution of PM2.5 mitigation potential across the YRD, revealing significantly additional room for curbing PM2.5 levels.

Changes in land cover and aerosols resulting from urbanization may impact convective clouds and precipitation. Here we investigate how Houston urbanization can modify sea-breeze-induced convective cloud and precipitation through the urban land effect and anthropogenic aerosol effect. The simulations are carried out with the Chemistry version of the Weather Research and Forecasting model (WRF-Chem), which is coupled with spectral-bin microphysics (SBM) and the multilayer urban model with a building energy model (BEM-BEP). We find that Houston urbanization (the joint effect of both urban land and anthropogenic aerosols) notably enhances storm intensity (by ∼ 75 % in maximum vertical velocity) and precipitation intensity (up to 45 %), with the anthropogenic aerosol effect more significant than the urban land effect. Urban land effect modifies convective evolution: speed up the transition from the warm cloud to mixed-phase cloud, thus initiating surface rain earlier but slowing down the convective cell dissipation, all of which result from urban heating-induced stronger sea-breeze circulation. The anthropogenic aerosol effect becomes evident after the cloud evolves into the mixed-phase cloud, accelerating the development of storm from the mixed-phase cloud to deep cloud by ∼ 40 min. Through aerosol–cloud interaction (ACI), aerosols boost convective intensity and precipitation mainly by activating numerous ultrafine particles at the mixed-phase and deep cloud stages. This work shows the importance of considering both the urban land and anthropogenic aerosol effects for understanding urbanization effects on convective clouds and precipitation.

The realistic representation of aerosol–cloud interactions is of primary importance for accurate climate model projections. The investigation of these interactions in strongly contrasting clean and polluted atmospheric conditions in the Amazon region has been one of the motivations for several field campaigns, including the airborne “Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems–Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (Global Precipitation Measurement) (ACRIDICON-CHUVA)” campaign based in Manaus, Brazil, in September 2014. In this work we combine in situ and remotely sensed aerosol, cloud, and atmospheric radiation data collected during ACRIDICON-CHUVA with regional, online-coupled chemistry-transport simulations to evaluate the model's ability to represent the indirect effects of biomass burning aerosol on cloud microphysical and optical properties (droplet number concentration and effective radius). We found agreement between the modeled and observed median cloud droplet number concentration (CDNC) for low values of CDNC, i.e., low levels of pollution. In general, a linear relationship between modeled and observed CDNC with a slope of 0.3 was found, which implies a systematic underestimation of modeled CDNC when compared to measurements. Variability in cloud condensation nuclei (CCN) number concentrations was also underestimated, and cloud droplet effective radii (reff) were overestimated by the model. Modeled effective radius profiles began to saturate around 500 CCN cm−3 at cloud base, indicating an upper limit for the model sensitivity well below CCN concentrations reached during the burning season in the Amazon Basin. Additional CCN emitted from local fires did not cause a notable change in modeled cloud droplet effective radii. Finally, we also evaluate a parameterization of CDNC at cloud base using more readily available cloud microphysical properties, showing that we are able to derive CDNC at cloud base from cloud-side remote-sensing observations.

Open biomass burning (OBB) has a high potential to trigger local and regional severe haze with elevated fine particulate matter (PM2.5) concentrations and could thus deteriorate ambient air quality and threaten human health. Open crop straw burning (OCSB), as a critical part of OBB, emits abundant gaseous and particulate pollutants, especially in fields with intensive agriculture, such as in central and eastern China (CEC). This region includes nine provinces, i.e., Hubei, Anhui, Henan, Hunan, Jiangxi, Shandong, Jiangsu, Shanghai, and Fujian. The first four ones are located inland, while the others are on the eastern coast. However, uncertainties in current OCSB and other types of OBB emissions in chemical transport models (CTMs) lead to inaccuracies in evaluating their impacts on haze formations. Satellite retrievals provide an alternative that can be used to simultaneously quantify emissions of OCSB and other types of OBB, such as the Fire INventory from NCAR version 1.5 (FINNv1.5), which, nevertheless, generally underestimates their magnitudes due to unresolved small fires. In this study, we selected June 2014 as our study period, which exhibited a complete evolution process of OBB (from 1 to 19 June) over CEC. During this period, OBB was dominated by OCSB in terms of the number of fire hotspots and associated emissions (74 %–94 %), most of which were located at Henan and Anhui (> 60 %) with intensive enhancements from 5 to 14 June (> 80 %). OCSB generally exhibits a spatiotemporal correlation with regional haze over the central part of CEC (Henan, Anhui, Hubei, and Hunan), while other types of OBB emissions had influences on Jiangxi, Zhejiang, and Fujian. Based on these analyses, we establish a constraining method that integrates ground-level PM2.5 measurements with a state-of-art fully coupled regional meteorological and chemical transport model (the two-way coupled WRF-CMAQ) in order to derive optimal OBB emissions based on FINNv1.5. It is demonstrated that these emissions allow the model to reproduce meteorological and chemical fields over CEC during the study period, whereas the original FINNv1.5 underestimated OBB emissions by 2–7 times, depending on specific spatiotemporal scales. The results show that OBB had substantial impacts on surface PM2.5 concentrations over CEC. Most of the OBB contributions were dominated by OCSB, especially in Henan, Anhui, Hubei, and Hunan, while other types of OBB emissions also exerted an influence in Jiangxi, Zhejiang, and Fujian. With the concentration-weighted trajectory (CWT) method, potential OCSB sources leading to severe haze in Henan, Anhui, Hubei, and Hunan were pinpointed. The results show that the OCSB emissions in Henan and Anhui can cause haze not only locally but also regionally through regional transport. Combining with meteorological analyses, we can find that surface weather patterns played a cardinal role in reshaping spatial and temporal characteristics of PM2.5 concentrations. Stationary high-pressure systems over CEC enhanced local PM2.5 concentrations in Henan and Anhui. Then, with the evolution of meteorological patterns, Hubei and Hunan in the low-pressure system were impacted by areas (i.e., Henan and Anhui) enveloped in the high-pressure system. These results suggest that policymakers should strictly undertake interprovincial joint enforcement actions to prohibit irregular OBB, especially OCSB over CEC. Constrained OBB emissions can, to a large extent, supplement estimations derived from satellite retrievals as well as reduce overestimates of bottom-up methods.

To probe the potential value of a radar-driven field campaign to constrain simulation of isolated convection subject to a strong aerosol perturbation, convective cells observed by the operational KHGX weather radar in the vicinity of Houston, Texas, are examined individually and statistically. Cells observed in a single case study of onshore flow conditions during July 2013 are first examined and compared with cells in a regional model simulation. Observed and simulated cells are objectively identified and tracked from observed or calculated positive specific differential phase (KDP) above the melting level, which is related to the presence of supercooled liquid water. Several observed and simulated cells are subjectively selected for further examination. Below the melting level, we compare sequential cross sections of retrieved and simulated raindrop size distribution parameters. Above the melting level, we examine time series of KDP and radar differential reflectivity (ZDR) statistics from observations and calculated from simulated supercooled rain properties, alongside simulated vertical wind and supercooled rain mixing ratio statistics. Results indicate that the operational weather radar measurements offer multiple constraints on the properties of simulated convective cells, with substantial value added from derived KDP and retrieved rain properties. The value of collocated three-dimensional lightning mapping array measurements, which are relatively rare in the continental US, supports the choice of Houston as a suitable location for future field studies to improve the simulation and understanding of convective updraft physics. However, rapid evolution of cells between routine volume scans motivates consideration of adaptive scan strategies or radar imaging technologies to amend operational weather radar capabilities. A 3-year climatology of isolated cell tracks, prepared using a more efficient algorithm, yields additional relevant information. Isolated cells are found within the KHGX domain on roughly 40 % of days year-round, with greatest concentration in the northwest quadrant, but roughly 5-fold more cells occur during June through September. During this enhanced occurrence period, the cells initiate following a strong diurnal cycle that peaks in the early afternoon, typically follow a south-to-north flow, and dissipate within 1 h, consistent with the case study examples. Statistics indicate that ∼ 150 isolated cells initiate and dissipate within 70 km of the KHGX radar during the enhanced occurrence period annually, and roughly 10 times as many within 200 km, suitable for multi-instrument Lagrangian observation strategies. In addition to ancillary meteorological and aerosol measurements, robust vertical wind speed retrievals would add substantial value to a radar-driven field campaign.

Our knowledge is still poor regarding the response of the precipitation vertical structure to aerosols, partly due to the ignorance of precipitation occurring at different spatial scales. A total of 6 years of collocated ground-based PM10 and satellite-based (Tropical Rainfall Measuring Mission, TRMM) radar data, along with ERA-Interim reanalysis, are used in this study to investigate the aerosol effects on three localized rain regimes (shallow, stratiform, and convective rain) over the Pearl River Delta region of China. A subjective analysis method is proposed to discriminate between the localized and synoptic-scale precipitations based on weather composite charts where daily averaged wind field at 850 hPa is overlaid with the geopotential height at 500 hPa. In general, average rain rate tends to be greater under polluted conditions than under clean conditions. But such potential aerosol effects are regime dependent: as the atmosphere becomes slightly polluted (PM10 ≤ 38 µg m−3), the top 1 % radar reflectivity (Z) for all regimes initially increases, followed by continued increases and weak decreases for convective and stratiform/shallow rain regimes, respectively. As the atmosphere becomes much more polluted, such regime dependences of aerosol effects are more significant. From a perspective of the vertical Z structure, comparisons between polluted conditions (days with the highest third of PM10 concentration) and clean conditions (days with the lowest third of PM10 concentration) show that the convective rain regime exhibits a deeper and stronger Z pattern, whereas a much shallower and weaker Z pattern is observed for stratiform and shallow precipitation regimes. In particular, the top height of the 30 dBZ rain echo increases by ∼ 29 % ( ∼ 1.27 km) for the convective regime, but decreases by ∼ 10.8 % ( ∼ 0.47 km) for the stratiform regime. However, no noticeable changes are observed for the shallow precipitation regime. Impacts of meteorological factors are further studied on both rain top height (RTH) and the center of gravity of Z, including vertical velocity, vertical wind shear, convection available potential energy, and vertically integrated moisture flux divergence (MFD). The possible invigoration effect on convective precipitation seems dependent on wind shear, in good agreement with previous findings. Overall, the observed dependence of the precipitation vertical structure on ground-based PM10 supports the notion of aerosol invigoration or suppression effect on cold or warm rain and adds new insights into the nature of the complex interactions between aerosol and various localized precipitation regimes.

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. This study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weighted mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.

Airborne observations over the Amazon Basin showed high aerosol particle concentrations in the upper troposphere (UT) between 8 and 15 km altitude, with number densities (normalized to standard temperature and pressure) often exceeding those in the planetary boundary layer (PBL) by 1 or 2 orders of magnitude. The measurements were made during the German–Brazilian cooperative aircraft campaign ACRIDICON–CHUVA, where ACRIDICON stands for Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems and CHUVA is the acronym for Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (global precipitation measurement), on the German High Altitude and Long Range Research Aircraft (HALO). The campaign took place in September–October 2014, with the objective of studying tropical deep convective clouds over the Amazon rainforest and their interactions with atmospheric trace gases, aerosol particles, and atmospheric radiation. Aerosol enhancements were observed consistently on all flights during which the UT was probed, using several aerosol metrics, including condensation nuclei (CN) and cloud condensation nuclei (CCN) number concentrations and chemical species mass concentrations. The UT particles differed sharply in their chemical composition and size distribution from those in the PBL, ruling out convective transport of combustion-derived particles from the boundary layer (BL) as a source. The air in the immediate outflow of deep convective clouds was depleted of aerosol particles, whereas strongly enhanced number concentrations of small particles ( 90 nm) particles in the UT, which consisted mostly of organic matter and nitrate and were very effective CCN. Our findings suggest a conceptual model, where production of new aerosol particles takes place in the continental UT from biogenic volatile organic material brought up by deep convection and converted to condensable species in the UT. Subsequently, downward mixing and transport of upper tropospheric aerosol can be a source of particles to the PBL, where they increase in size by the condensation of biogenic volatile organic compound (BVOC) oxidation products. This may be an important source of aerosol particles for the Amazonian PBL, where aerosol nucleation and new particle formation have not been observed. We propose that this may have been the dominant process supplying secondary aerosol particles in the pristine atmosphere, making clouds the dominant control of both removal and production of atmospheric particles.

The behavior of tropical clouds remains a major open scientific question, resulting in poor representation by models. One challenge is to realistically reproduce cloud droplet size distributions (DSDs) and their evolution over time and space. Many applications, not limited to models, use the gamma function to represent DSDs. However, even though the statistical characteristics of the gamma parameters have been widely studied, there is almost no study dedicated to understanding the phase space of this function and the associated physics. This phase space can be defined by the three parameters that define the DSD intercept, shape, and curvature. Gamma phase space may provide a common framework for parameterizations and intercomparisons. Here, we introduce the phase space approach and its characteristics, focusing on warm-phase microphysical cloud properties and the transition to the mixed-phase layer. We show that trajectories in this phase space can represent DSD evolution and can be related to growth processes. Condensational and collisional growth may be interpreted as pseudo-forces that induce displacements in opposite directions within the phase space. The actually observed movements in the phase space are a result of the combination of such pseudo-forces. Additionally, aerosol effects can be evaluated given their significant impact on DSDs. The DSDs associated with liquid droplets that favor cloud glaciation can be delimited in the phase space, which can help models to adequately predict the transition to the mixed phase. We also consider possible ways to constrain the DSD in two-moment bulk microphysics schemes, in which the relative dispersion parameter of the DSD can play a significant role. Overall, the gamma phase space approach can be an invaluable tool for studying cloud microphysical evolution and can be readily applied in many scenarios that rely on gamma DSDs.

We have investigated how aerosols affect the height above cloud base of rain and ice hydrometeor initiation and the subsequent vertical evolution of cloud droplet size and number concentrations in growing convective cumulus. For this purpose we used in situ data of hydrometeor size distributions measured with instruments mounted on HALO aircraft during the ACRIDICON–CHUVA campaign over the Amazon during September 2014. The results show that the height of rain initiation by collision and coalescence processes (Dr, in units of meters above cloud base) is linearly correlated with the number concentration of droplets (Nd in cm−3) nucleated at cloud base (Dr ≈ 5 ⋅ Nd). Additional cloud processes associated with Dr, such as GCCN, cloud, and mixing with ambient air and other processes, produce deviations of ∼ 21 % in the linear relationship, but it does not mask the clear relationship between Dr and Nd, which was also found at different regions around the globe (e.g., Israel and India). When Nd exceeded values of about 1000 cm−3, Dr became greater than 5000 m, and the first observed precipitation particles were ice hydrometeors. Therefore, no liquid water raindrops were observed within growing convective cumulus during polluted conditions. Furthermore, the formation of ice particles also took place at higher altitudes in the clouds in polluted conditions because the resulting smaller cloud droplets froze at colder temperatures compared to the larger drops in the unpolluted cases. The measured vertical profiles of droplet effective radius (re) were close to those estimated by assuming adiabatic conditions (rea), supporting the hypothesis that the entrainment and mixing of air into convective clouds is nearly inhomogeneous. Additional CCN activation on aerosol particles from biomass burning and air pollution reduced re below rea, which further inhibited the formation of raindrops and ice particles and resulted in even higher altitudes for rain and ice initiation.

Top-down and bottom-up aerosol–cloud shortwave radiative flux closures were conducted at the Mace Head Atmospheric Research Station in Galway, Ireland, in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) European collaborative project, with the goal of understanding key processes affecting aerosol–cloud shortwave radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based unmanned aerial vehicles (UAVs)1 and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1-D microphysical aerosol–cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction or a five-hole probe for 3-D wind vectors. UAV cloud measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 and 60 W m−2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNCs) were within 30 % of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m−2 after accounting for cloud-top entrainment and up to 50 W m−2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m−2, even high (> 30 W m−2) after accounting for cloud-top entrainment. This work demonstrates the need to take in situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux. 1The regulatory term for UAV is remotely piloted aircraft (RPA).

The effects of aerosol particles and updraft speed on warm-phase cloud microphysical properties are studied in the Amazon region as part of the ACRIDICON-CHUVA experiment. Here we expand the sensitivity analysis usually found in the literature by concomitantly considering cloud evolution, putting the sensitivity quantifications into perspective in relation to in-cloud processing, and by considering the effects on droplet size distribution (DSD) shape. Our in situ aircraft measurements over the Amazon Basin cover a wide range of particle concentration and thermodynamic conditions, from the pristine regions over coastal and forested areas to the southern Amazon, which is highly polluted from biomass burning. The quantitative results show that particle concentration is the primary driver for the vertical profiles of effective diameter and droplet concentration in the warm phase of Amazonian convective clouds, while updraft speeds have a modulating role in the latter and in total condensed water. The cloud microphysical properties were found to be highly variable with altitude above cloud base, which we used as a proxy for cloud evolution since it is a measure of the time droplets that were subject to cloud processing. We show that DSD shape is crucial in understanding cloud sensitivities. The aerosol effect on DSD shape was found to vary with altitude, which can help models to better constrain the indirect aerosol effect on climate.

Vertical profiles of cloud particle phase in tropical deep convective clouds (DCCs) were investigated using airborne solar spectral radiation data collected by the German High Altitude and Long Range Research Aircraft (HALO) during the ACRIDICON-CHUVA campaign, which was conducted over the Brazilian rainforest in September 2014. A phase discrimination retrieval based on imaging spectroradiometer measurements of DCC side spectral reflectivity was applied to clouds formed in different aerosol conditions. From the retrieval results the height of the mixed-phase layer of the DCCs was determined. The retrieved profiles were compared with in situ measurements and satellite observations. It was found that the depth and vertical position of the mixed-phase layer can vary up to 900 m for one single cloud scene. This variability is attributed to the different stages of cloud development in a scene. Clouds of mature or decaying stage are affected by falling ice particles resulting in lower levels of fully glaciated cloud layers compared to growing clouds. Comparing polluted and moderate aerosol conditions revealed a shift of the lower boundary of the mixed-phase layer from 5.6 ± 0.2 km (269 K; moderate) to 6.2 ± 0.3 km (267 K; polluted), and of the upper boundary from 6.8 ± 0.2 km (263 K; moderate) to 7.4 ± 0.4 km (259 K; polluted), as would be expected from theory.

The objective of this study is to validate parameterizations that were recently developed for satellite retrievals of cloud condensation nuclei supersaturation spectra, NCCN(S), at cloud base alongside more traditional parameterizations connecting NCCN(S) with cloud base updrafts and drop concentrations. This was based on the HALO aircraft measurements during the ACRIDICON–CHUVA campaign over the Amazon region, which took place in September 2014. The properties of convective clouds were measured with a cloud combination probe (CCP), a cloud and aerosol spectrometer (CAS-DPOL), and a CCN counter onboard the HALO aircraft. An intercomparison of the cloud drop size distributions (DSDs) and the cloud water content (CWC) derived from the different instruments generally shows good agreement within the instrumental uncertainties. To this end, the directly measured cloud drop concentrations (Nd) near cloud base were compared with inferred values based on the measured cloud base updraft velocity (Wb) and NCCN(S) spectra. The measurements of Nd at cloud base were also compared with drop concentrations (Na) derived on the basis of an adiabatic assumption and obtained from the vertical evolution of cloud drop effective radius (re) above cloud base. The measurements of NCCN(S) and Wb reproduced the observed Nd within the measurements uncertainties when the old (1959) Twomey's parameterization was used. The agreement between the measured and calculated Nd was only within a factor of 2 with attempts to use cloud base S, as obtained from the measured Wb, Nd, and NCCN(S). This underscores the yet unresolved challenge of aircraft measurements of S in clouds. Importantly, the vertical evolution of re with height reproduced the observation-based nearly adiabatic cloud base drop concentrations, Na. The combination of these results provides aircraft observational support for the various components of the satellite-retrieved methodology that was recently developed to retrieve NCCN(S) under the base of convective clouds. This parameterization can now be applied with the proper qualifications to cloud simulations and satellite retrievals.

How orographic mixed-phase clouds respond to the change in cloud condensation nuclei (CCN) and ice nucleating particles (INPs) are highly uncertain. The main snow production mechanism in warm and cold mixed-phase orographic clouds (referred to as WMOCs and CMOCs, respectively, distinguished here as those having cloud tops warmer and colder than −20 °C) could be very different. We quantify the CCN and INP impacts on supercooled water content, cloud phases, and precipitation for a WMOC case and a CMOC case, with sensitivity tests using the same CCN and INP concentrations between the WMOC and CMOC cases. It was found that deposition plays a more important role than riming for forming snow in the CMOC case, while the role of riming is dominant in the WMOC case. As expected, adding CCN suppresses precipitation, especially in WMOCs and low INPs. However, this reverses strongly for CCN of 1000 cm−3 and larger. We found a new mechanism through which CCN can invigorate mixed-phase clouds over the Sierra Nevada and drastically intensify snow precipitation when CCN concentrations are high (1000 cm−3 or higher). In this situation, more widespread shallow clouds with a greater amount of cloud water form in the Central Valley and foothills west of the mountain range. The increased latent heat release associated with the formation of these clouds strengthens the local transport of moisture to the windward slope, invigorating mixed-phase clouds over the mountains, and thereby producing higher amounts of snow precipitation. Under all CCN conditions, increasing the INPs leads to decreased riming and mixed-phase fraction in the CMOC as a result of liquid-limited conditions, but has the opposite effects in the WMOC as a result of ice-limited conditions. However, precipitation in both cases is increased by increasing INPs due to an increase in deposition for the CMOC but enhanced riming and deposition in the WMOC. Increasing the INPs dramatically reduces supercooled water content and increases the cloud glaciation temperature, while increasing CCN has the opposite effect with much smaller significance.

VIIRS (Visible Infrared Imaging Radiometer Suite), onboard the Suomi NPP (National Polar-orbiting Partnership) satellite, has an improved resolution of 750 m with respect to the 1000 m of the Moderate Resolution Imaging Spectroradiometer for the channels that allow retrieving cloud microphysical parameters such as cloud drop effective radius (re). VIIRS also has an imager with five channels of double resolution of 375 m, which was not designed for retrieving cloud products. A methodology for a high-resolution retrieval of re and microphysical presentation of the cloud field based on the VIIRS imager was developed and evaluated with respect to MODIS in this study. The tripled microphysical resolution with respect to MODIS allows obtaining new insights for cloud–aerosol interactions, especially at the smallest cloud scales, because the VIIRS imager can resolve the small convective elements that are sub-pixel for MODIS cloud products. Examples are given for new insights into ship tracks in marine stratocumulus, pollution tracks from point and diffused sources in stratocumulus and cumulus clouds over land, deep tropical convection in pristine air mass over ocean and land, tropical clouds that develop in smoke from forest fires and in heavy pollution haze over densely populated regions in southeastern Asia, and for pyro-cumulonimbus clouds. It is found that the VIIRS imager provides more robust physical interpretation and refined information for cloud and aerosol microphysics as compared to MODIS, especially in the initial stage of cloud formation. VIIRS is found to identify significantly more fully cloudy pixels when small boundary layer convective elements are present. This, in turn, allows for a better quantification of cloud–aerosol interactions and impacts on precipitation-forming processes.

Mineral dust aerosols often observed over California in winter and spring, associated with long-range transport from Asia and the Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical model coupled with the Weather Research and Forecasting (WRF) model in order to examine the relative and combined impacts of dust and local pollution particles on cloud properties and precipitation type and intensity. Simulations are carried out for two cloud cases (from the CalWater 2011 field campaign) with contrasting meteorology and cloud dynamics that occurred on 16 February (FEB16) and 2 March (MAR02). In both cases, observations show the presence of dust and biological particles in a relative pristine environment. The simulated cloud microphysical properties and precipitation show reasonable agreement with aircraft and surface measurements. Model sensitivity experiments indicate that in the pristine environment, the dust and biological aerosol layers increase the accumulated precipitation by 10–20% from the Central Valley to the Sierra Nevada for both FEB16 and MAR02 due to a ~40% increase in snow formation, validating the observational hypothesis. Model results show that local pollution increases precipitation over the windward slope of the mountains by a few percent due to increased snow formation when dust is present, but reduces precipitation by 5–8% if dust is removed on FEB16. The effects of local pollution on cloud microphysics and precipitation strongly depend on meteorology, including cloud dynamics and the strength of the Sierra Barrier Jet. This study further underscores the importance of the interactions between local pollution, dust, and environmental conditions for assessing aerosol effects on cold-season precipitation in California.

The cloud-mediated aerosol radiative forcing is widely recognized as the main source of uncertainty in our knowledge of the anthropogenic forcing on climate. The current challenges for improving our understanding are (1) global measurements of cloud condensation nuclei (CCN) in the cloudy boundary layer from space, and (2) disentangling the effects of aerosols from the thermodynamic and meteorological effects on the clouds. Here, we present a new conceptual framework to help us overcome these two challenges, using relatively simple passive satellite measurements in the visible and infared (IR). The idea is to use the clouds themselves as natural CCN chambers by retrieving simultaneously the number of activated aerosols at cloud base, Na, and the cloud base updraft speed. The Na is obtained by analyzing the distribution of cloud drop effective radius in convective elements as a function of distance above cloud base. The cloud base updraft velocities are estimated by double stereoscopic viewing and tracking of the evolution of cloud surface features just above cloud base. In order to resolve the vertical dimension of the clouds, the field of view will be 100 m for the microphysical retrievals, and 50 m for the stereoscopic measurements. The viewing geometry will be eastward and 30 degrees off nadir, with the Sun in the back at 30 degrees off zenith westward, requiring a Sun-synchronous orbit at 14 LST. Measuring simultaneously the thermodynamic environment, the vertical motions of the clouds, their microstructure and the CCN concentration will allow separating the dynamics from the CCN effects. This concept is being applied in the proposed satellite mission named Clouds, Hazards and Aerosols Survey for Earth Researchers (CHASER).

The number concentration of activated CCN (Na) is the most fundamental microphysical property of a convective cloud. It determines the rate of droplet growth with cloud depth and conversion into precipitation-sized particles and affects the radiative properties of the clouds. However, measuring Na is not always possible, even in the cores of the convective clouds, because entrainment of sub-saturated ambient air deeper into the cloud lowers the concentrations by dilution and may cause partial or total droplet evaporation, depending on whether the mixing is homogeneous or extreme inhomogeneous, respectively. Here we describe a methodology to derive Na based on the rate of cloud droplet effective radius (Re) growth with cloud depth and with respect to the cloud mixing with the entrained ambient air. We use the slope of the tight linear relationship between the adiabatic liquid water mixing ratio and Re3 (or Rv3) to derive an upper limit for Na assuming extreme inhomogeneous mixing. Then we tune Na down to find the theoretical relative humidity that the entrained ambient air would have for each horizontal cloud penetration, in case of homogeneous mixing. This allows us to evaluate both the entrainment and mixing process in the vertical dimension in addition to getting a better estimation for Na. We found that the derived Na from the entire profile data is highly correlated with the independent CCN measurements from below cloud base. Moreover, it was found that mixing of sub-saturated ambient air into the cloud at scales of ~100 m and above is inclined towards the extreme inhomogeneous limit, i.e. that the time scale of droplet evaporation is significantly smaller than that for turbulent mixing. This means that ambient air that entrains the cloud is pre-moistened by total evaporation of cloud droplets before it mixes deeper into the clouds where it can hardly change the droplet size distribution, hence Re remains close to its adiabatic value at any given cloud depth. However, the tendency towards the extreme inhomogeneous mixing appeared to slightly decrease with altitude, possibly due to enhanced turbulence and larger cloud drops aloft. Quantifying these effects, based on more examples from other projects and high resolution cloud models is essential for improving our understanding of the interactions between the cloud and its environment. These interactions may play an important role in cloud dynamics and microphysics, by affecting cloud depth and droplet size spectra, for example, and may therefore influence the cloud precipitation formation processes.

In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. These achievements and related studies have substantially improved our understanding and reduced the uncertainties of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies.

Cloud-aerosol interaction is a key issue in the climate system, affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and their consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei. Here we propose and demonstrate a new experimental approach (the cloud scanner instrument) that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil. The CLAIM-3D (3-Dimensional Cloud Aerosol Interaction Mission) satellite concept proposed here combines several techniques to simultaneously measure the vertical profile of cloud microphysics, thermodynamic phase, brightness temperature, and aerosol amount and type in the neighborhood of the clouds. The wide wavelength range, and the use of multi-angle polarization measurements proposed for this mission allow us to estimate the availability and characteristics of aerosol particles acting as cloud condensation nuclei, and their effects on the cloud microphysical structure. These results can provide unprecedented details on the response of cloud droplet microphysics to natural and anthropogenic aerosols in the size scale where the interaction really happens.

Experimental and theoretical studies of cloud microstructure modification with hygroscopic particles for obtaining additional precipitation amounts from convective clouds are performed. The experiment used salt powder with the particle sizes that gave the greatest effectiveness according to the simulations of Segal et al. (2004). The experiments were carried out in a cloud chamber at the conditions corresponding to the formation of convective clouds. The results have shown that the introduction of the salt powder before a cloud medium is formed in the chamber results in the formation on a "tail" of additional large drops. In this case seeding with the salt powder leads also to enlargement of the whole population of cloud drops and to a decrease of their total concentration as compared to a cloud medium that is formed on background aerosols. These results are the positive factors for stimulating coagulation processes in clouds and for subsequent formation of precipitation in them. An overseeding effect, which is characterized by increased droplet concentration and decreased droplet size, was not observed even at high salt powder concentrations. The results of numerical simulations have shown that the transformation of cloud drop spectra induced by the introduction of the salt powder results in more intense coagulation processes in clouds as compared to the case of cloud modification with hygroscopic particles with relatively narrow particle size distributions, and for the distribution of the South African hygroscopic flares. The calculation results obtained with a one-dimensional model of a warm convective cloud demonstrated that the effect of salt powder on clouds (total amounts of additional precipitation) is significantly higher than the effect caused by the use of hygroscopic particles with narrow particle size distributions at comparable consumptions of seeding agents, or with respect to the hygroscopic flares. Here we show that seeding at rather low consumption rate of the salt powder initiates precipitation from otherwise non precipitating warm convective clouds, mainly by the effect of adding large cloud drops to the tail of the distribution.

A methodology for representing much of the physical information content of the METEOSAT Second Generation (MSG) geostationary satellite using red-green-blue (RGB) composites of the computed physical values of the picture elements is presented. The physical values are the solar reflectance in the solar channels and brightness temperature in the thermal channels. The main RGB compositions are (1) "Day Natural Colors", presenting vegetation in green, bare surface in brown, sea surface in black, water clouds as white, ice as magenta; (2) "Day Microphysical", presenting cloud microstructure using the solar reflectance component of the 3.9 μm, visible and thermal IR channels; (3) "Night Microphysical", also presenting clouds microstructure using the brightness temperature differences between 10.8 and 3.9 μm; (4) "Day and Night", using only thermal channels for presenting surface and cloud properties, desert dust and volcanic emissions; (5) "Air Mass", presenting mid and upper tropospheric features using thermal water vapor and ozone channels. The scientific basis for these rendering schemes is provided, with examples for the applications. The expanding use of these rendering schemes requires their proper documentation and setting as standards, which is the main objective of this publication.

The SEVIRI instrument on the Meteosat Second Generation satellite with both fine spatial and temporal resolution allows to detect and follow the dynamics of fast developing meteorological events like spreading smoke plumes and the lifecycles of convective clouds. Smoke plumes have the ability to change the atmospheric heat content due to absorption and reduced reflection of solar radiation. By these means they can trigger formation of shallow convective clouds at their edge. A heavy smoke plume emerging from burning Lebanese oil tanks and spreading over adjacent deserts on 17 July 2006 has been observed as an example of such an effect. This study suggests a physical explanation of the observed convection along the edge of the smoke plume, namely the strong thermal contrast resulting from solar heating of the smoke layer.

In-situ measurements in convective clouds (up to the freezing level) over the Amazon basin show that smoke from deforestation fires prevents clouds from precipitating until they acquire a vertical development of at least 4 km, compared to only 1–2 km in clean clouds. The average cloud depth required for the onset of warm rain increased by ~350 m for each additional 100 cloud condensation nuclei per cm3 at a super-saturation of 0.5% (CCN0.5%). In polluted clouds, the diameter of modal liquid water content grows much slower with cloud depth (at least by a factor of ~2), due to the large number of droplets that compete for available water and to the suppressed coalescence processes. Contrary to what other studies have suggested, we did not observe this effect to reach saturation at 3000 or more accumulation mode particles per cm3. The CCN0.5% concentration was found to be a very good predictor for the cloud depth required for the onset of warm precipitation and other microphysical factors, leaving only a secondary role for the updraft velocities in determining the cloud drop size distributions. The effective radius of the cloud droplets (re) was found to be a quite robust parameter for a given environment and cloud depth, showing only a small effect of partial droplet evaporation from the cloud's mixing with its drier environment. This supports one of the basic assumptions of satellite analysis of cloud microphysical processes: the ability to look at different cloud top heights in the same region and regard their re as if they had been measured inside one well developed cloud. The dependence of re on the adiabatic fraction decreased higher in the clouds, especially for cleaner conditions, and disappeared at re≥~10 μm. We propose that droplet coalescence, which is at its peak when warm rain is formed in the cloud at re=~10 μm, continues to be significant during the cloud's mixing with the entrained air, cancelling out the decrease in re due to evaporation.

The feasibility of hurricane modification was investigated for hurricane Katrina using the Weather Research and Forecasting Model (WRF). The possible impact of seeding of clouds with submicron cloud condensation nuclei (CCN) on hurricane structure and intensity as measured by nearly halving of the area covered by hurricane force winds was simulated by "turning–off" warm rain formation in the clouds at Katrina's periphery (where wind speeds were less than 22 m s−1). This simplification of the simulation of aerosol effects is aimed at evaluating the largest possible response. This resulted in the weakening of the hurricane surface winds compared to the "non-seeded" simulated storm during the first 24 h within the entire tropical cyclone (TC) area compared to a control simulation without warm rain suppression. Later, the seeding-induced evaporative cooling at the TC periphery led to a shrinking of the eye and hence to some increase in the wind within the small central area of the TC. Yet, the overall strength of the hurricane, as defined by the area covered by hurricane force winds, decreased in response to the suppressed warm rain at the periphery, as measured by a 25% reduction in the radius of hurricane force winds. In a simulation with warm rain suppression throughout the hurricane, the radius of the hurricane force winds was reduced by more than 42%, and although the diameter of the eye shrunk even further the maximum winds weakened. This shows that the main mechanism by which suppressing warm rain weakens the TC is the low level evaporative cooling of the un-precipitated cloud drops and the added cooling due to melting of precipitation that falls from above.

We have used the MODIS satellite data and two global aerosol models to investigate the relationships between aerosol optical depth (AOD) and cloud parameters that may be affected by the aerosol concentration. The relationships that are studied are mainly between AOD, on the one hand, and cloud cover, cloud liquid water path, and water vapour, on the other. Additionally, cloud droplet effective radius, cloud optical depth, cloud top pressure and aerosol Ångström exponent, have been analysed in a few cases. In the MODIS data we found, as in earlier studies, an enhancement in the cloud cover with increasing AOD. We find it likely that most of the strong increase in cloud cover with AOD, at least for AOD0.2 can be explained by larger water uptake close to the clouds since relative humidity is higher in regions with higher cloud cover. The efficiency of the hygroscopic growth depends on aerosol type, the hygroscopic nature of the aerosol, the relative humidity, and to some extent the cloud screening. By analysing the Ångström exponent we find that the hygroscopic growth of the aerosol is not likely to be a main contributor to the cloud cover increase with AOD. Since the largest increase in cloud cover with AOD is for low AOD (~0.2) and thus also for low cloud cover, we argue that cloud contamination is not likely to play a large role. However, interpretation of the complex relationships between AOD and cloud parameters should be made with great care and further work is clearly needed.

A fire storm that occurred on 28 May 2001 and devastated the town of Chisholm, ~150 km north of Edmonton, Alberta, induced a violent fire-invigorated cumulonimbus cloud. This pyro-cumulonimbus (pyro-Cb) had overshooting tops of 2.5–3 km above the tropopause, and injected massive amounts of smoke into the lower stratosphere. Fortunately, this event occurred under good coverage of radar, rain gauge, lightning and satellite measurements, which allowed in-depth documentation of the event, and gave us an opportunity to study the cloud top morphology and microstructure, precipitation and cloud electrification of the pyro-Cb. The combination of heat and smoke created a cloud with extremely small drops, which ascended rapidly in violent updrafts. There appeared to be little freezing up to the homogeneous freezing isotherm level of −38°C. A cloud with such small and short-lived highly supercooled drops is incapable of producing precipitation except for few large graupel and hail, which produced the observed radar echoes and charged the cloud with positive lightning. The small cloud drops froze homogeneously to equally small ice particles, for which there is no mechanism to aggregate into precipitation particles, and which hence remain in the anvil. The lack of significant precipitation implies that only a small fraction of the smoke is scavenged, so that most of it is exhausted through the anvil to the upper troposphere and lower stratosphere. Comparisons with other cases suggest that a pyro-Cb does not have to be as violent as the Chisholm case for precipitation to be strongly suppressed. However, this level of convective vigor is necessary to create the overshooting updraft that injects the smoke into the lower stratosphere.

A 3-minute 3-km rapid scan of the METEOSAT Second Generation geostationary satellite over southern Africa was applied to tracking the evolution of cloud top temperature (T) and particle effective radius (re) of convective elements. The evolution of T-re relations showed little dependence on time, leaving re to depend almost exclusively on T. Furthermore, cloud elements that fully grew to large cumulonimbus stature had the same T-re relations as other clouds in the same area with limited development that decayed without ever becoming a cumulonimbus. Therefore, a snap shot of T-re relations over a cloud field provides the same relations as composed from tracking the time evolution of T and re of individual clouds, and then compositing them. This is the essence of exchangeability of time and space scales, i.e., ergodicity, of the T-re relations for convective clouds. This property has allowed inference of the microphysical evolution of convective clouds with a snap shot from a polar orbiter. The fundamental causes for the ergodicity are suggested to be the observed stability of re for a given height above cloud base in a convective cloud, and the constant renewal of growing cloud tops with cloud bubbles that replace the cloud tops with fresh cloud matter from below.

The dynamic structure of the weakly sheared atmospheric marine boundary layer (MBL) supports three distinct states of cloud cover, which are associated with the concentrations of cloud condensation nuclei (CCN) aerosols in the MBL: (i) CCN rich MBL with closed Benard cellular convection that forms nearly full cloud cover; (ii) CCN depleted MBL with open cellular convection that forms

No abstract available.