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The aerosol impact on liquid water path (LWP) is a key uncertainty in the overall climate impact of aerosol. However, despite a significant effort in this area, the size of the effect remains poorly constrained, and even the sign is unclear. Recent studies have shown that the relationship between droplet number concentration (Nd) and LWP is an unreliable measure of the impact of Nd variations on LWP due to the difficulty in establishing causality. In this work, we use satellite observations of the short-term development of clouds to examine the role of Nd perturbations in LWP variations. Similar to previous studies, an increase followed by a general decrease in LWP with increasing Nd is observed, suggesting an overall negative LWP response to Nd and a warming LWP adjustment to aerosol. However, the Nd also responds to the local environment, with aerosol production, entrainment from the free troposphere and wet scavenging all acting to modify the Nd. Many of these effects act to further steepen the Nd–LWP relationship and obscure the causal Nd impact on LWP. Using the temporal development of clouds to account for these feedbacks in the Nd–LWP system, a weaker negative Nd–LWP relationship is observed over most of the globe. This relationship is highly sensitive to the initial cloud state, illuminating the roles of different processes in shaping the Nd–LWP relationship. The nature of the current observing system limits this work to a single time period for observations, highlighting the need for more frequent observations of key cloud properties to constrain cloud behaviour at process timescales.

To evaluate the SEVIRI retrieval for aerosols above clouds presented in Part 1 of the companion paper, the algorithm is applied over the south-east Atlantic Ocean during the CLARIFY-2017 field campaign period. The first step of our analysis compares the retrieved aerosol and cloud properties against equivalent products from the MODIS MOD06ACAERO retrieval (Meyer et al., 2015). While the correlation between the two satellite retrievals of the above-cloud aerosol optical thickness (AOT) is good (R = 0.78), the AOT retrieved by SEVIRI is 20.3 % smaller than that obtained from the MODIS retrieval. This difference in AOT is attributed mainly to the more absorbing aerosol model assumed for the SEVIRI retrieval compared to MODIS. The underlying cloud optical thickness (COT) derived from the two satellites is in good agreement (R = 0.90). The cloud droplet effective radius (CER) retrieved by SEVIRI is consistently smaller than MODIS by 2.2 µm, which is mainly caused by the use of different spectral bands of the satellite instruments. In the second part of our analysis, we compare the forecast water vapour profiles used for the SEVIRI atmospheric correction as well as the aforementioned aerosol and cloud products with in situ measurements made from the Facility for Airborne Atmospheric Measurements (FAAM) aircraft platform during the CLARIFY-2017 campaign. Around Ascension Island, the column water vapour used to correct the SEVIRI signal is overestimated by 3.1 mm in the forecast compared to that measured by dropsondes. However, the evidence suggests that the accuracy of the atmospheric correction improves closer to the African coast. Consistency is observed between the SEVIRI above-cloud AOT and in situ measurements (from cavity ring-down spectroscopy instruments) when the measured single-scattering albedo is close to that assumed in the retrieval algorithm. On the other hand, the satellite retrieval overestimates the AOT when the assumed aerosol model is not absorbing enough. Consistency is also found between the cloud properties retrieved by SEVIRI and the CER measured by a cloud droplet probe and the liquid water path derived from a microwave radiometer. Despite the instrumental limitations of the geostationary satellite, the consistency obtained between SEVIRI, MODIS and the aircraft measurements demonstrates the ability of the retrieval in providing additional information on the temporal evolution of the aerosol properties above clouds.

Airborne remote sensing observations over the tropical Atlantic Ocean upstream of Barbados are used to characterize trade wind shallow cumulus clouds and to benchmark two cloud-resolving ICON (ICOsahedral Nonhydrostatic) model simulations at kilometer and hectometer scales. The clouds were observed by an airborne nadir-pointing backscatter lidar, a cloud radar, and a microwave radiometer in the tropical dry winter season during daytime. For the model benchmark, forward operators convert the model output into the observational space for considering instrument-specific cloud detection thresholds. The forward simulations reveal the different detection limits of the lidar and radar observations, i.e., most clouds with cloud liquid water content greater than 10−7 kg kg−1 are detectable by the lidar, whereas the radar is primarily sensitive to the “rain” category hydrometeors in the models and can detect even low amounts of rain. The observations reveal two prominent modes of cumulus cloud top heights separating the clouds into two layers. The lower mode relates to boundary layer convection with tops closely above the lifting condensation level, which is at about 700 m above sea level. The upper mode is driven by shallow moist convection, also contains shallow stratiform outflow anvils, and is closely related to the trade inversion at about 2.3 km above sea level. The two cumulus modes are sensed differently by the lidar and the radar observations and under different liquid water path (LWP) conditions. The storm-resolving model (SRM) at a kilometer scale barely reproduces the cloud modes and shows most cloud tops being slightly above the observed lower mode. The large-eddy model (LEM) at hectometer scale reproduces better the observed cloudiness distribution with a clear bimodal separation. We hypothesize that slight differences in the autoconversion parameterizations could have caused the different cloud development in the models. Neither model seems to account for in-cloud drizzle particles that do not precipitate down to the surface but generate a stronger radar signal even in scenes with low LWP. Our findings suggest that even if the SRM is a step forward for better cloud representation in climate research, the LEM can better reproduce the observed shallow cumulus convection and should therefore in principle better represent cloud radiative effects and water cycle.

The intrinsic small spatial scales and low-reflectivity structure of oceanic warm precipitating clouds suggest that millimeter spaceborne radars are best suited to providing quantitative estimates of cloud and rain liquid water paths (LWPs). This assertion is based on their smaller horizontal footprint; high sensitivities; and a wide dynamic range of path-integrated attenuations associated with warm-rain cells across the millimeter wavelength spectrum, with diverse spectral responses to rain and cloud partitioning. State-of-the-art single-frequency radar profiling algorithms of warm rain seem to be inadequate because of their dependence on uncertain assumptions about the rain–cloud partitioning and because of the rain microphysics. Here, high-resolution cloud-resolving model simulations for the Rain in Cumulus over the Ocean field study and a spaceborne forward radar simulator are exploited to assess the potential of existing and future spaceborne radar systems for quantitative warm-rain microphysical retrievals. Specifically, the detrimental effects of nonuniform beam filling on estimates of path-integrated attenuation (PIA), the added value of brightness temperature (TB) derived adopting radiometric radar modes, and the performances of multifrequency PIA and/or TB combinations when retrieving liquid water paths partitioned into cloud (c-LWPs) and rain (r-LWPs) are assessed. Results show that (1) Ka- and W-band TB values add useful constraints and are effective at lower LWPs than the same-frequency PIAs; (2) matched-beam combined TB values and PIAs from single-frequency or multifrequency radars can significantly narrow down uncertainties in retrieved cloud and rain liquid water paths; and (3) the configuration including PIAs, TB values and near-surface reflectivities for the Ka-band–W-band pairs in our synthetic retrieval can achieve an RMSE of better than 30 % for c-LWPs and r-LWPs exceeding 100 g m−2.

The North Pacific High (NPH) is a fundamental meteorological feature present during the boreal warm season. Marine boundary layer (MBL) clouds, which are persistent in this oceanic region, are influenced directly by the NPH. In this study, we combine 11 years of reanalysis and an unsupervised machine learning technique to examine the gamut of 850 hPa synoptic-scale circulation patterns. This approach reveals two distinguishable regimes – a dominant NPH setup and a land-falling cyclone – and in between a spectrum of large-scale patterns. We then use satellite retrievals to elucidate for the first time the explicit dependence of MBL cloud properties (namely cloud droplet number concentration, liquid water path, and shortwave cloud radiative effect – CRESW) on 850 hPa circulation patterns over the northeast Pacific Ocean. We find that CRESW spans from −146.8 to −115.5 W m−2, indicating that the range of observed MBL cloud properties must be accounted for in global and regional climate models. Our results demonstrate the value of combining reanalysis and satellite retrievals to help clarify the relationship between synoptic-scale dynamics and cloud physics.

A comprehensive analysis of the water budget over the Dome C (Concordia, Antarctica) station has been performed during the austral summer 2018–2019 as part of the Year of Polar Prediction (YOPP) international campaign. Thin (∼100 m deep) supercooled liquid water (SLW) clouds have been detected and analysed using remotely sensed observations at the station (tropospheric depolarization lidar, the H2O Antarctica Microwave Stratospheric and Tropospheric Radiometer (HAMSTRAD), net surface radiation from the Baseline Surface Radiation Network (BSRN)), radiosondes, and satellite observations (CALIOP, Cloud-Aerosol LIdar with Orthogonal Polarization/CALIPSO, Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations) combined with a specific configuration of the numerical weather prediction model: ARPEGE-SH (Action de Recherche Petite Echelle Grande Echelle – Southern Hemisphere). The analysis shows that SLW clouds were present from November to March, with the greatest frequency occurring in December and January when ∼50 % of the days in summer time exhibited SLW clouds for at least 1 h. Two case studies are used to illustrate this phenomenon. On 24 December 2018, the atmospheric planetary boundary layer (PBL) evolved following a typical diurnal variation, which is to say with a warm and dry mixing layer at local noon thicker than the cold and dry stable layer at local midnight. Our study showed that the SLW clouds were observed at Dome C within the entrainment and the capping inversion zones at the top of the PBL. ARPEGE-SH was not able to correctly estimate the ratio between liquid and solid water inside the clouds with the liquid water path (LWP) strongly underestimated by a factor of 1000 compared to observations. The lack of simulated SLW in the model impacted the net surface radiation that was 20–30 W m−2 higher in the BSRN observations than in the ARPEGE-SH calculations, mainly attributable to the BSRN longwave downward surface radiation being 50 W m−2 greater than that of ARPEGE-SH. The second case study took place on 20 December 2018, when a warm and wet episode impacted the PBL with no clear diurnal cycle of the PBL top. SLW cloud appearance within the entrainment and capping inversion zones coincided with the warm and wet event. The amount of liquid water measured by HAMSTRAD was ∼20 times greater in this perturbed PBL than in the typical PBL. Since ARPEGE-SH was not able to accurately reproduce these SLW clouds, the discrepancy between the observed and calculated net surface radiation was even greater than in the typical PBL case, reaching +50 W m−2, mainly attributable to the downwelling longwave surface radiation from BSRN being 100 W m−2 greater than that of ARPEGE-SH. The model was then run with a new partition function favouring liquid water for temperatures below −20 down to −40 ∘C. In this test mode, ARPEGE-SH has been able to generate SLW clouds with modelled LWP and net surface radiation consistent with observations during the typical case, whereas, during the perturbed case, the modelled LWP was 10 times less than the observations and the modelled net surface radiation remained lower than the observations by ∼50 W m−2. Accurately modelling the presence of SLW clouds appears crucial to correctly simulate the surface energy budget over the Antarctic Plateau.

We study 41 d with daily median surface accumulation mode aerosol particle concentrations below 50 cm−3 (ultra-clean conditions) observed at Ascension Island (ASI; 7.9∘ S, 14.4∘ W) between June 2016 and October 2017 as part of the Layered Atlantic Smoke Interactions with Clouds (LASIC) campaign. Interestingly, these days occur during a period of great relevance for aerosol–cloud–radiation interactions, the southeast Atlantic (SEATL) biomass-burning season (approximately June–October). That means that these critical months can feature both the highest surface aerosol numbers, from smoke intrusion into the marine boundary layer, as well as the lowest. While carbon monoxide and refractory black carbon concentrations on ultra-clean days do not approach those on days with heavy smoke, they also frequently exceed background concentrations calculated in the non-burning season from December 2016 to April 2017. This is evidence that even what become ultra-clean boundary layers can make contact with and entrain from an overlying SEATL smoke layer before undergoing a process of rapid aerosol removal. Because many ultra-clean and polluted boundary layers observed at Ascension Island during the biomass burning season follow similar isobaric back trajectories, the variability in this entrainment is likely more closely tied to the variability in the overlying smoke rather than large-scale horizontal circulation through the boundary layer. Since exceptionally low accumulation mode aerosol numbers at ASI do not necessarily indicate the relative lack of other trace pollutants, this suggests the importance of regional variations in what constitutes an “ultra-clean” marine boundary layer. Finally, surface drizzle rates, frequencies and accumulation – as well as retrievals of liquid water path – all consistently tend toward higher values on ultra-clean days. This implicates enhanced coalescence scavenging in low clouds as the key driver of ultra-clean events in the southeast Atlantic marine boundary layer. These enhancements occur against and are likely mediated by the backdrop of a seasonal increase in daily mean cloud fraction and daily median liquid water path over ASI, peaking in September and October in both LASIC years. Therefore the seasonality in ultra-clean day occurrence seems directly linked to the seasonality in SEATL cloud properties. These results highlight the importance of two-way aerosol–cloud interactions in the region.

Base on January and July 4-times daily ECMWF Interim data from 2009 to 2018 over the Northeast Sphere (0–180E,0–90N), the condensed moisture profile of experiential methods and that of ECMWF analysis are compared. The result shows that, the meridional-height distribution of mean cloud condensed moisture has a maximum slab spreading near ground in the Arctic region in July, and the maximum takes a circular shape at 700 hPa above 30N latitude in January. The distribution feature unlike the universal profile, it distributes in a single or double peak function manner, instead of a constant value. The quick decreasing level height and thickness varies with latitude, especially in January. The second experiential profile concerning warm cloud assumes air parcel lifting adiabatically, the liquid water path (LWP) is compared for general information. The result shows that the experiential LWP is much larger than that of the reanalysis by 1 to 2 order, decreasing with latitudes. The possible reason of LWP difference is from the critic water content value of cloud boundary identification. If the value is small, the thickness of warm cloud will be large, temperature and pressure at the cloud base are both large too, results in a larger LWP. These results will enrich the knowledge of the condensed moisture characteristics of ECMWF reanalysis and the experiential moisture profile methods.

Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Thus far, no single robust method exists for assessing the calibration of past cloud radar data sets. Here, we investigate whether observations of microphysical processes in liquid clouds such as the transition of cloud droplets to drizzle drops can be used to calibrate cloud radars. Specifically, we study the relationships between the radar reflectivity factor and three variables not affected by absolute radar calibration: the skewness of the radar Doppler spectrum (γ), the radar mean Doppler velocity (W), and the liquid water path (LWP). For each relation, we evaluate the potential for radar calibration. For γ and W, we use box model simulations to determine typical radar reflectivity values for reference points. We apply the new methods to observations at the Atmospheric Radiation Measurement (ARM) sites North Slope of Alaska (NSA) and Oliktok Point (OLI) in 2016 using two 35 GHz Ka-band ARM Zenith Radars (KAZR). For periods with a sufficient number of liquid cloud observations, we find that liquid cloud processes are robust enough for cloud radar calibration, with the LWP-based method performing best. We estimate that, in 2016, the radar reflectivity at NSA was about 1±1 dB too low but stable. For OLI, we identify serious problems with maintaining an accurate calibration including a sudden decrease of 5 to 7 dB in June 2016.

The response of cloud processes to an aerosol perturbation is one of the largest uncertainties in the anthropogenic forcing of the climate. It occurs at a variety of timescales, from the near-instantaneous Twomey effect to the longer timescales required for cloud adjustments. Understanding the temporal evolution of cloud properties following an aerosol perturbation is necessary to interpret the results of so-called “natural experiments” from a known aerosol source such as a ship or industrial site. This work uses reanalysis wind fields and ship emission information matched to observations of ship tracks to measure the timescales of cloud responses to aerosol in instantaneous (or“snapshot”) images taken by polar-orbiting satellites. As in previous studies, the local meteorological environment is shown to have a strong impact on the occurrence and properties of ship tracks, but there is a strong time dependence in their properties. The largest droplet number concentration (Nd) responses are found within 3 h of emission, while cloud adjustments continue to evolve over periods of 10 h or more. Cloud fraction is increased within the early life of ship tracks, with the formation of ship tracks in otherwise clear skies indicating that around 5 %–10 % of clear-sky cases in this region may be aerosol-limited. The liquid water path (LWP) enhancement and the Nd–LWP sensitivity are also time dependent and strong functions of the background cloud and meteorological state. The near-instant response of the LWP within ship tracks may be evidence of a bias in estimates of the LWP response to aerosol derived from natural experiments. These results highlight the importance of temporal development and the background cloud field for quantifying the aerosol impact on clouds, even in situations where the aerosol perturbation is clear.

While many studies have tried to quantify the sign and the magnitude of the warm marine cloud response to aerosol loading, both remain uncertain, owing to the multitude of factors that modulate microphysical and thermodynamic processes within the cloud. Constraining aerosol–cloud interactions using the local meteorology and cloud liquid water may offer a way to account for covarying influences, potentially increasing our confidence in observational estimates of warm cloud indirect effects. A total of 4 years of collocated satellite observations from the NASA A-Train constellation, combined with reanalysis from MERRA-2, are used to partition marine warm clouds into regimes based on stability, the free atmospheric relative humidity, and liquid water path. Organizing the sizable number of satellite observations into regimes is shown to minimize the covariance between the environment or liquid water path and the indirect effect. Controlling for local meteorology and cloud state mitigates artificial signals and reveals substantial variance in both the sign and magnitude of the cloud radiative response, including regions where clouds become systematically darker with increased aerosol concentration in dry, unstable environments. A darkening effect is evident even under the most stringent of constraints. These results suggest it is not meaningful to report a single global sensitivity of cloud radiative effect to aerosol. To the contrary, we find the sensitivity can range from −0.46 to 0.11 Wm−2 ln(AI)−1 regionally.

Radiative cooling and heating impact the liquid water balance of fog and therefore play an important role in determining their persistence or dissipation. We demonstrate that a quantitative analysis of the radiation-driven condensation and evaporation is possible in real time using ground-based remote sensing observations (cloud radar, ceilometer, microwave radiometer). Seven continental fog events in midlatitude winter are studied, and the radiative processes are further explored through sensitivity studies. The longwave (LW) radiative cooling of the fog is able to produce 40–70 g m−2 h−1 of liquid water by condensation when the fog liquid water path exceeds 30 g m−2 and there are no clouds above the fog, which corresponds to renewing the fog water in 0.5–2 h. The variability is related to fog temperature and atmospheric humidity, with warmer fog below a drier atmosphere producing more liquid water. The appearance of a cloud layer above the fog strongly reduces the LW cooling relative to a situation with no cloud above; the effect is strongest for a low cloud, when the reduction can reach 100 %. Consequently, the appearance of clouds above will perturb the liquid water balance in the fog and may therefore induce fog dissipation. Shortwave (SW) radiative heating by absorption by fog droplets is smaller than the LW cooling, but it can contribute significantly, inducing 10–15 g m−2 h−1 of evaporation in thick fog at (winter) midday. The absorption of SW radiation by unactivated aerosols inside the fog is likely less than 30 % of the SW absorption by the water droplets, in most cases. However, the aerosols may contribute more significantly if the air mass contains a high concentration of absorbing aerosols. The absorbed radiation at the surface can reach 40–120 W m−2 during the daytime depending on the fog thickness. As in situ measurements indicate that 20–40 % of this energy is transferred to the fog as sensible heat, this surface absorption can contribute significantly to heating and evaporation of the fog, up to 30 g m−2 h−1 for thin fog, even without correcting for the typical underestimation of turbulent heat fluxes by the eddy covariance method. Since the radiative processes depend mainly on the profiles of temperature, humidity and clouds, the results of this paper are not site specific and can be generalised to fog under different dynamic conditions and formation mechanisms, and the methodology should be applicable to warmer and moister climates as well. The retrieval of approximate emissivity of clouds above fog from cloud radar should be further developed.

The representation of aerosol–cloud interaction (ACI) processes in climate models, although long studied, still remains the source of high uncertainty. Very often there is a mismatch between the scale of observations used for ACI quantification and the ACI process itself. This can be mitigated by using the observations from ground-based remote sensing instruments. In this paper we presented a direct application of the aerosol–cloud interaction monitoring technique (ACI monitoring). ACI monitoring is based on the standardised Cloudnet data stream, which provides measurements from ground-based remote sensing instruments working in synergy. For the data set collected at the CESAR Observatory in the Netherlands we calculate ACI metrics. We specifically use attenuated backscatter coefficient (ATB) for the characterisation of the aerosol properties and cloud droplet effective radius (re) and number concentration (Nd) for the characterisation of the cloud properties. We calculate two metrics: ACIr = ln(re)/ln(ATB) and ACIN = ln(Nd)/ln(ATB). The calculated values of ACIr range from 0.001 to 0.085, which correspond to the values reported in previous studies. We also evaluated the impact of the vertical Doppler velocity and liquid water path (LWP) on ACI metrics. The values of ACIr were highest for LWP values between 60 and 105 g m−2. For higher LWP other processes, such as collision and coalescence, seem to be dominant and obscure the ACI processes. We also saw that the values of ACIr are higher when only data points located in the updraught regime are considered. The method presented in this study allow for monitoring ACI daily and further aggregating daily data into bigger data sets.

Aerosol-induced increase of relative dispersion of cloud droplet size distribution ε exerts a warming effect and partly offsets the cooling of aerosol indirect radiative forcing (AIF) associated with increased droplet concentration by increasing the cloud droplet effective radius (Re) and enhancing the cloud-to-rain autoconversion rate (Au) (labeled as the dispersion effect), which can help reconcile global climate models (GCMs) with the satellite observations. However, the total dispersion effects on both Re and Au are not fully considered in most GCMs, especially in different versions of the Community Atmospheric Model (CAM). In order to accurately evaluate the dispersion effect on AIF, the new complete cloud parameterizations of Re and Au explicitly accounting for ε are implemented into the CAM version 5.1 (CAM5.1), and a suite of sensitivity experiments is conducted with different representations of ε reported in the literature. It is shown that the shortwave cloud radiative forcing is much better simulated with the new cloud parameterizations as compared to the standard scheme in CAM5.1, whereas the influences on longwave cloud radiative forcing and surface precipitation are minimal. Additionally, consideration of the dispersion effect can significantly reduce the changes induced by anthropogenic aerosols in the cloud-top effective radius and the liquid water path, especially in the Northern Hemisphere. The corresponding AIF with the dispersion effect considered can also be reduced substantially by a range of 0.10 to 0.21 W m−2 at the global scale and by a much bigger margin of 0.25 to 0.39 W m−2 for the Northern Hemisphere in comparison with that of fixed relative dispersion, mainly dependent on the change of relative dispersion and droplet concentrations (Δε∕ΔNc).

Aerosol–cloud interactions are explored using 1 km simulations of a case study of predominantly closed-cell SE Pacific stratocumulus clouds. The simulations include realistic meteorology along with newly implemented cloud microphysics and sub-grid cloud schemes. The model was critically assessed against observations of liquid water path (LWP), broadband fluxes, cloud fraction (fc), droplet number concentrations (Nd), thermodynamic profiles, and radar reflectivities.Aerosol loading sensitivity tests showed that at low aerosol loadings, changes to aerosol affected shortwave fluxes equally through changes to cloud macrophysical characteristics (LWP, fc) and cloud albedo changes due solely to Nd changes. However, at high aerosol loadings, only the Nd albedo change was important. Evidence was also provided to show that a treatment of sub-grid clouds is as important as order of magnitude changes in aerosol loading for the accurate simulation of stratocumulus at this grid resolution.Overall, the control model demonstrated a credible ability to reproduce observations, suggesting that many of the important physical processes for accurately simulating these clouds are represented within the model and giving some confidence in the predictions of the model concerning stratocumulus and the impact of aerosol. For example, the control run was able to reproduce the shape and magnitude of the observed diurnal cycle of domain mean LWP to within ∼ 10 g m−2 for the nighttime, but with an overestimate for the daytime of up to 30 g m−2. The latter was attributed to the uniform aerosol fields imposed on the model, which meant that the model failed to include the low-Nd mode that was observed further offshore, preventing the LWP removal through precipitation that likely occurred in reality. The boundary layer was too low by around 260 m, which was attributed to the driving global model analysis. The shapes and sizes of the observed bands of clouds and open-cell-like regions of low areal cloud cover were qualitatively captured. The daytime fc frequency distribution was reproduced to within Δfc = 0.04 for fc > ∼ 0.7 as was the domain mean nighttime fc (at a single time) to within Δfc = 0.02. Frequency distributions of shortwave top-of-the-atmosphere (TOA) fluxes from the satellite were well represented by the model, with only a slight underestimate of the mean by 15 %; this was attributed to near–shore aerosol concentrations that were too low for the particular times of the satellite overpasses. TOA long-wave flux distributions were close to those from the satellite with agreement of the mean value to within 0.4 %. From comparisons of Nd distributions to those from the satellite, it was found that the Nd mode from the model agreed with the higher of the two observed modes to within ∼ 15 %.

Aerosol–cloud interactions are one of the most uncertain processes in climate models due to their nonlinear complexity. A key complexity arises from the possibility that clouds can respond to perturbed aerosols in two opposite ways, as characterized by the traditional “cloud lifetime” hypothesis and more recent “buffered system” hypothesis. Their importance in climate simulations remains poorly understood. Here we investigate the response of the liquid water path (LWP) to aerosol perturbations for warm clouds from the perspective of general circulation model (GCM) and A-Train remote sensing, through process-oriented model evaluations. A systematic difference is found in the LWP response between the model results and observations. The model results indicate a near-global uniform increase of LWP with increasing aerosol loading, while the sign of the response of the LWP from the A-Train varies from region to region. The satellite-observed response of the LWP is closely related to meteorological and/or macrophysical factors, in addition to the microphysics. The model does not reproduce this variability of cloud susceptibility (i.e., sensitivity of LWP to perturbed aerosols) because the parameterization of the autoconversion process assumes only suppression of rain formation in response to increased cloud droplet number, and does not consider macrophysical aspects that serve as a mechanism for the negative responses of the LWP via enhancements of evaporation and precipitation. Model biases are also found in the precipitation microphysics, which suggests that the model generates rainwater readily even when little cloud water is present. This essentially causes projections of unrealistically frequent and light rain, with high cloud susceptibilities to aerosol perturbations.

The climatic relevance of aerosol–cloud interactions depends on the sensitivity of the radiative effect of clouds to cloud droplet number N, and liquid water path LWP. We derive the dependence of cloud fraction CF, cloud albedo AC, and the relative cloud radiative effect rCRE=CF⋅AC on N and LWP from 159 large-eddy simulations of nocturnal stratocumulus. These simulations vary in their initial conditions for temperature, moisture, boundary-layer height, and aerosol concentration but share boundary conditions for surface fluxes and subsidence. Our approach is based on Gaussian-process emulation, a statistical technique related to machine learning. We succeed in building emulators that accurately predict simulated values of CF, AC, and rCRE for given values of N and LWP. Emulator-derived susceptibilities ∂ln⁡rCRE/∂ln⁡N and ∂ln⁡rCRE/∂ln⁡LWP cover the nondrizzling, fully overcast regime as well as the drizzling regime with broken cloud cover. Theoretical results, which are limited to the nondrizzling regime, are reproduced. The susceptibility ∂ln⁡rCRE/∂ln⁡N captures the strong sensitivity of the cloud radiative effect to cloud fraction, while the susceptibility ∂ln⁡rCRE/∂ln⁡LWP describes the influence of cloud amount on cloud albedo irrespective of cloud fraction. Our emulation-based approach provides a powerful tool for summarizing complex data in a simple framework that captures the sensitivities of cloud-field properties over a wide range of states.

The article of record as published may be located at http://dx.doi.org/10.5194/acp-16-11395-2016 Precipitation tends to decrease as aerosol concentration increases in warm marine boundary layer clouds at fixed liquid water path (LWP). The quantitative nature of this relationship is captured using the precipitation susceptibility (Sₒ) metric. Previously published works disagree on the qualitative behavior of Sₒ in marine low clouds: Sₒ decreases monotonically with increasing LWP or cloud depth (H) in stratocumulus clouds (Sₒ), while it increases and then decreases in shallow cumulus clouds (Cu). This study uses airborne measurements from four field campaigns on Cu and Sc with similar instrument packages and flight maneuvers to examine if and why Sₒ behavior varies as a function of cloud type. The findings show that Sₒ increases with H and then decreases in both Sc and Cu. Possible reasons for why these results differ from those in previous studies of Sc are discussed. ONR grants N000140810465, N00014-10-1-0811, N00014-16-1-2567, and NSF grant AGS-1008848.

There are many contributing factors which determine the micro- and macrophysical properties of clouds, including atmospheric vertical structure, dominant meteorological conditions, and aerosol concentration, all of which may be coupled to one another. In the quest to determine aerosol effects on clouds, these potential relationships must be understood. Here we describe several observed correlations between aerosol conditions and cloud and atmospheric properties in the Indian Ocean winter monsoon season.In the CARDEX (Cloud, Aerosol, Radiative forcing, Dynamics EXperiment) field campaign conducted in February and March 2012 in the northern Indian Ocean, continuous measurements were made of atmospheric precipitable water vapor (PWV) and the liquid water path (LWP) of trade cumulus clouds, concurrent with measurements of water vapor flux, cloud and aerosol vertical profiles, meteorological data, and surface and total-column aerosol from instrumentation at a ground observatory and on small unmanned aircraft. We present observations which indicate a positive correlation between aerosol and cloud LWP only when considering cases with low atmospheric water vapor (PWV

Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysics scheme. This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.

Large eddy simulations are performed to investigate the influence of cloud microphysics on the evolution of low level clouds that form over southern West Africa during the monsoon season. We find that, even in clouds that are not precipitating, the size of cloud droplets has a non-negligible effect on liquid water path. This is explained through the effects of droplet sedimentation, which acts to remove liquid water from the entrainment zone close to cloud top, increasing liquid water path. Sedimentation also produces a more heterogeneous cloud structure and lowers cloud base height. Our results imply that an appropriate parameterization of the effects of sedimentation is required to improve the representation of the diurnal cycle of the atmospheric boundary layer over southern West Africa in large-scale models.

Ship tracks provide an ideal test bed for studying aerosol–cloud interactions (ACIs) and for evaluating their representation in model parameterisations. Regional modelling can be of particular use for this task, as this approach provides sufficient resolution to resolve the structure of the produced track including their meteorological environment whilst relying on the same formulations of parameterisations as many general circulation models. In this work we simulate a particular case of ship tracks embedded in an optically thin stratus cloud sheet which was observed by a polar orbiting satellite at 12:00 UTC on 26 January 2003 around the Bay of Biscay. The simulations, which include moving ship emissions, show that the model is indeed able to capture the structure of the track at a horizontal grid spacing of 2 km and to qualitatively capture the observed cloud response in all simulations performed. At least a doubling of the cloud optical thickness was simulated in all simulations together with an increase in cloud droplet number concentration by about 40 cm−3 (300%) and decrease in effective radius by about 5 μm (40%). Furthermore, the ship emissions lead to an increase in liquid water path in at least 25% of the track regions. We are confident in the model's ability to capture key processes of ship track formation. However, it was found that realistic ship emissions lead to unrealistic aerosol perturbations near the source regions within the simulated tracks due to grid-scale dilution and homogeneity. Combining the regional-modelling approach with comprehensive field studies could likely improve our understanding of the sensitivities and biases in ACI parameterisations, and could therefore help to constrain global ACI estimates, which strongly rely on these parameterisations.

In this study the temporal and spatial characteristics of the liquid water path (LWP) of low, middle and high level clouds are analysed using space-based observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument onboard the Meteosat Second Generation 2 (MSG 2) satellite. Both geophysical quantities are part of the CLAAS (CLoud property dAtAset using SEVIRI) data set and are generated by EUMETSAT's Satellite Application Facility on Climate Monitoring (CM SAF). In this article we focus on the statistical properties of LWP, retrieved during daylight conditions, associated with individual cloud types. We analysed the intrinsic variability of LWP, that is, the variability in only cloudy regions and the variations driven by cloud amount. The relative amplitude of the intrinsic diurnal cycle exceeded the cloud amount driven amplitude in our analysed cases. Our results reveal that each cloud type possesses a characteristic intrinsic LWP distribution. These frequency distributions are constant with time in the entire SEVIRI field of view, but vary for smaller regions like Central Europe. Generally the average LWP is higher over land than over sea; in the case of low clouds this amounts to 15–27% in 2009. The variance of the frequency distributions is enhanced as well. Also, the average diurnal cycle of LWP is related to cloud type with the most pronounced relative diurnal variations being detected for low and middle level clouds. Maps of the relative amplitude and the local time of maximum LWP show the variation throughout the SEVIRI field of view.

Identifying deep convection is of paramount importance, as it may be associated with extreme weather phenomena that have significant impact on the environment, property and populations. A new method, the hail detection tool (HDT), is described for identifying hail-bearing storms using multispectral Meteosat Second Generation (MSG) data. HDT was conceived as a two-phase method, in which the first step is the convective mask (CM) algorithm devised for detection of deep convection, and the second a hail mask algorithm (HM) for the identification of hail-bearing clouds among cumulonimbus systems detected by CM. Both CM and HM are based on logistic regression models trained with multispectral MSG data sets comprised of summer convective events in the middle Ebro Valley (Spain) between 2006 and 2010, and detected by the RGB (red-green-blue) visualization technique (CM) or C-band weather radar system of the University of León. By means of the logistic regression approach, the probability of identifying a cumulonimbus event with CM or a hail event with HM are computed by exploiting a proper selection of MSG wavelengths or their combination. A number of cloud physical properties (liquid water path, optical thickness and effective cloud drop radius) were used to physically interpret results of statistical models from a meteorological perspective, using a method based on these "ingredients". Finally, the HDT was applied to a new validation sample consisting of events during summer 2011. The overall probability of detection was 76.9 % and the false alarm ratio 16.7 %.

A cloud-resolving model (CRM) coupled to a new intermediate-complexity bulk aerosol scheme is used to study aerosol–boundary-layer–cloud–precipitation interactions and the development of pockets of open cells (POCs) in subtropical stratocumulus cloud layers. The aerosol scheme prognoses mass and number concentration of a single lognormal accumulation mode with surface and entrainment sources, evolving subject to processing of activated aerosol and scavenging of dry aerosol by clouds and rain. The CRM with the aerosol scheme is applied to a range of steadily forced cases idealized from a well-observed POC. The long-term system evolution is explored with extended two-dimensional (2-D) simulations of up to 20 days, mostly with diurnally averaged insolation and 24 km wide domains, and one 10 day three-dimensional (3-D) simulation. Both 2-D and 3-D simulations support the Baker–Charlson hypothesis of two distinct aerosol–cloud "regimes" (deep/high-aerosol/non-drizzling and shallow/low-aerosol/drizzling) that persist for days; transitions between these regimes, driven by either precipitation scavenging or aerosol entrainment from the free-troposphere (FT), occur on a timescale of ten hours. The system is analyzed using a two-dimensional phase plane with inversion height and boundary layer average aerosol concentrations as state variables; depending on the specified subsidence rate and availability of FT aerosol, these regimes are either stable equilibria or distinct legs of a slow limit cycle. The same steadily forced modeling framework is applied to the coupled development and evolution of a POC and the surrounding overcast boundary layer in a larger 192 km wide domain. An initial 50% aerosol reduction is applied to half of the model domain. This has little effect until the stratocumulus thickens enough to drizzle, at which time the low-aerosol portion transitions into open-cell convection, forming a POC. Reduced entrainment in the POC induces a negative feedback between the areal fraction covered by the POC and boundary layer depth changes. This stabilizes the system by controlling liquid water path and precipitation sinks of aerosol number in the overcast region, while also preventing boundary layer collapse within the POC, allowing the POC and overcast to coexist indefinitely in a quasi-steady equilibrium.

Cloud microphysical process rates control the amount of condensed water in clouds and impact the susceptibility of precipitation to cloud-drop number and aerosols. The relative importance of different microphysical processes in a climate model is analyzed, and the autoconversion and accretion processes are found to be critical to the condensate budget in most regions. A simple steady-state model of warm rain formation is used to illustrate that the diagnostic rain formulations typical of climate models may result in excessive contributions from autoconversion, compared to observations and large eddy simulation models with explicit bin-resolved microphysics and rain formation processes. The behavior does not appear to be caused by the bulk process rate formulations themselves, because the steady-state model with the same bulk accretion and autoconversion has reduced contributions from autoconversion. Sensitivity tests are conducted to analyze how perturbations to the precipitation microphysics for stratiform clouds impact process rates, precipitation susceptibility and aerosol–cloud interactions (ACI). With similar liquid water path, corrections for the diagnostic rain assumptions in the GCM based on the steady-state model to boost accretion indicate that the radiative effects of ACI may decrease by 20% in the GCM. Links between process rates, susceptibility and ACI are not always clear in the GCM. Better representation of the precipitation process, for example by prognosticating precipitation mass and number, may help better constrain these effects in global models with bulk microphysics schemes.

The impact of horizontal heterogeneities, liquid water path (LWP from AMSR-E), and cloud fraction (CF) on MODIS cloud effective radius (re), retrieved from the 2.1 μm (re2.1) and 3.8 μm (re3.8) channels, is investigated for warm clouds over the southeast Pacific. Values of re retrieved using the CERES algorithms are averaged at the CERES footprint resolution (∼20 km), while heterogeneities (Hσ) are calculated as the ratio between the standard deviation and mean 0.64 μm reflectance. The value of re2.1 strongly depends on CF, with magnitudes up to 5 μm larger than those for overcast scenes, whereas re3.8 remains insensitive to CF. For cloudy scenes, both re2.1 and re3.8 increase with Hσ for any given AMSR-E LWP, but re2.1 changes more than for re3.8. Additionally, re3.8–re2.1 differences are positive (Hσ < 0.2) and LWP > 45 gm−2, and negative (up to −4 μm) for larger Hσ. While re3.8–re2.1 differences in homogeneous scenes are qualitatively consistent with in situ microphysical observations over the region of study, negative differences – particularly evinced in mean regional maps – are more likely to reflect the dominant bias associated with cloud heterogeneities rather than information about the cloud vertical structure. The consequences for MODIS LWP are also discussed.

Over the southeastern Pacific (SEP), droplet concentration (Nd) in the typically unpolluted marine stratocumulus west of 80° W (> 1000 km offshore) is periodically strongly enhanced in zonally elongated "hook"-shaped features that increase albedo. Here, we examine three hook events using the chemistry version of the Weather Research and Forecasting model (WRF-Chem) with 14 km horizontal resolution, satellite data, and aircraft data from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx). A particularly strong hook yields insights into the development, decay, and radiative impact of these features. Hook development occurs with Nd increasing to polluted levels over the remote ocean primarily due to entrainment of cloud condensation nuclei (CCN) from the lower free troposphere (FT). The feature advects northwestward until the FT CCN source is depleted, after which Nd decreases over a few days due to precipitation and dilution. The model suggests that the FT CCN source supplying the hook consists of high concentrations of small accumulation-mode aerosols that contribute a relatively small amount of aerosol mass to the MBL, in agreement with near-coast VOCALS measurements of polluted layers in the FT. The aerosol particles in this hook originate mainly from a pulse of offshore flow that transports Santiago-region (33–35° S) emissions to the remote marine FT. To provide pollution CCN that can sustain hooks, the FT transport of pollution plumes to the remote ocean requires strong, deep offshore flow. Such flow is favored by a trough approaching the South American coast and a southeastward shift of the climatological subtropical high-pressure system. The model simulations show precipitation suppression in the hook and a corresponding increase in liquid water path (LWP) compared with a simulation without anthropogenic sources. LWP also increases as the hook evolves over time due to increasing stability and decreasing subsidence. WRF-Chem suggests that dimethyl sulfide (DMS) significantly influences the aerosol number and size distributions in a hook, but that hooks do not form without FT CCN. The Twomey effect contributes ~ 50–70% of the albedo increase due to the presence of the hook, while secondary aerosol indirect effects and meteorological influences also contribute significantly. The source of hook aerosols is difficult to determine with the available observations alone. The model provides further explanation of the factors influencing hook formation. Two other weaker hooks during VOCALS-REx are not as well simulated but are also associated with FT offshore flow near Santiago. Hooks demonstrate the importance of free-tropospheric transport of aerosols in modulating the droplet concentration in the southeastern Pacific stratocumulus deck, and present a formidable challenge to simulate accurately in large-scale models.

Microphysical measurements collected during eleven profiles, by the UK BAe-146 aircraft, through marine stratocumulus as part of the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) are compared to collocated overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellite platforms. The full depth of the cloud is sampled in each case using a Cloud Droplet Probe (CDP) and a Two-Dimensional Stereo Probe (2DS) together sizing cloud and precipitation droplets in the diameter range 2–1260 μm. This allows the total optical depth (τc) of the cloud and effective radius (re) of the droplet size distribution to be compared to MODIS cloud retrievals of the same quantities along with the secondarily derived total liquid water path. When compared to the effective radius at cloud top, the MODIS retrieved re using the 2.1 μm wavelength channel overestimates the in situ measurements on average by 13% with the largest overestimations coinciding with the detection by the 2DS of drizzle sized droplets. We show through consideration of the full vertical profile and penetration depths of the wavelengths used in the retrieval that the expected retrieved values are less than those at cloud top thus increasing the apparent bias in re retrievals particularly when using the 1.6 and 2.1 μm channels, with the 3.7 μm channel retrievals displaying the best agreement with in situ values. Retrievals of τc also tend to overestimate in situ values which, coupled with a high bias in re retrievals, lead to an overestimation of liquid water path. There is little apparent correlation between the variation of the three near-infrared re retrievals and the vertical structure of the cloud observed in situ. Retrievals are performed using measured profiles of water vapour and temperature along with an accurate knowledge of the width of the droplet size distribution which improve agreement between in situ and retrieved values but cannot completely explain the observed biases. Additionally we show that cloud heterogeneity and three-dimensional radiative effects may high skew the mean when averaging over comparison domains but cannot explain all of the apparent high bias. An intercomparison between in situ measurements from the BAe-146 and C-130 platforms is also presented, highlighting the uncertainties associated with in situ observations.

This empirical study demonstrates the feasibility of using 89-GHz Advanced Microwave Scanning Radiometer–Earth Observing System (AMSR-E) passive microwave brightness temperature data to detect heavily drizzling cells within subtropical marine stratocumulus. For the purpose of this paper, we define heavily drizzling cells as areas ≥ 6 km × 4 km with C-band Z > 0 dBZ; equivalent to > 0.084 mm h−1. A binary heavy drizzle product is described that can be used to determine areal and feature statistics of drizzle cells within the major marine stratocumulus regions. Current satellite liquid water path (LWP) and cloud radar products capable of detecting drizzle are either lacking in resolution (AMSR-E LWP), diurnal coverage (MODIS LWP), or spatial coverage (CloudSat). The AMSR-E 89-GHz data set at 6 km × 4 km spatial resolution is sufficient for resolving individual heavily drizzling cells. Radiant emission at 89 GHz by liquid-water cloud and precipitation particles from drizzling cells in marine stratocumulus regions yields local maxima in brightness temperature against an otherwise cloud-free background brightness temperature. The background brightness temperature is primarily constrained by column-integrated water vapor for moderate sea surface temperatures. Clouds containing ice are screened out. Once heavily drizzling pixels are identified, connected pixels are grouped into discrete drizzle cell features. The identified drizzle cells are used in turn to determine several spatial statistics for each satellite scene, including drizzle cell number and size distribution. The identification of heavily drizzling cells within marine stratocumulus regions with satellite data facilitates analysis of seasonal and regional drizzle cell occurrence and the interrelation between drizzle and changes in cloud fraction.

In this study the shortwave cloud radiative effect (SWCRE) over ocean calculated by the ECHAM 5 climate model is evaluated for the cloud property input derived from ship based measurements and satellite based estimates and compared to ship based radiation measurements. The ship observations yield cloud fraction, liquid water path from a microwave radiometer, cloud bottom height as well as temperature and humidity profiles from radiosonde ascents. Level-2 products of the Satellite Application Facility on Climate Monitoring (CM~SAF) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) have been used to characterize clouds. Within a closure study six different experiments have been defined to find the optimal set of measurements to calculate downward shortwave radiation (DSR) and the SWCRE from the model, and their results have been evaluated under seven different synoptic situations. Four of these experiments are defined to investigate the advantage of including the satellite-based cloud droplet effective radius as additional cloud property. The modeled SWCRE based on satellite retrieved cloud properties has a comparable accuracy to the modeled SWCRE based on ship data. For several cases, an improvement through introducing the satellite-based estimate of effective radius as additional information to the ship based data was found. Due to their different measuring characteristics, however, each dataset shows best results for different atmospheric conditions.

In the first part of this paper series (Meskhidze et al., 2011), a treatment of marine organic aerosols (including primary organic aerosol, secondary organic aerosols, and methane sulfonate) was implemented into the Community Atmosphere Model version 5 (CAM5) with a 7-mode Modal Aerosol Module. A series of simulations was conducted to quantify the changes in aerosol and cloud condensation nuclei concentrations in the marine boundary layer. In this study, changes in the cloud microphysical properties and radiative forcing resulting from marine organic aerosols are assessed. Model simulations show that the anthropogenic aerosol indirect forcing (AIF) predicted by CAM5 is decreased in absolute magnitude by up to ~0.10 W m−2 (8%) when marine organic aerosols are included. Changes in the AIF from marine organic aerosols are associated with small global increases in low-level in-cloud droplet number concentration and liquid water path of ~1.3 cm−3 (~1.6%) and 0.2 g m−2 (0.5%), respectively. Areas especially sensitive to changes in cloud properties due to marine organic aerosol include the Southern Ocean, North Pacific Ocean, and North Atlantic Ocean, all of which are characterized by high marine organic emission rates. As climate models are particularly sensitive to the background aerosol concentration, this small but non-negligible change in the AIF due to marine organic aerosols provides a notable link for ocean-ecosystem marine low-level cloud interactions and may be a candidate for consideration in future earth system models.

Simulations at a range of resolutions are compared to observations from the South-East Pacific taken during VOCALS-REx. It is found that increased horizontal and vertical resolution make only small improvements to the bulk properties of the simulated cloud and drizzle, but the highest resolution simulation is able to realistically represent mesoscale features in the cloud field. We focus on the highest resolution simulation and demonstrate that a poor representation of the cloud microphysics results in excessive drizzle production. This promotes persistent drizzle induced decoupling of the boundary layer, giving a poor representation of the observed diurnal cycle of stratocumulus. Two simple changes to the microphysics scheme are implemented: a modified autoconversion parametrization and a new representation of the rain drop size distribution. This results in a more realistic simulation of boundary-layer diurnal decoupling, and improvements to the cloud liquid water path and surface drizzle rate.

The article of record as published may be found at http://dx.doi.org/10.5194/acp-11-9943-2011 Aircraft observations made off the coast of northern Chile in the Southeastern Pacific (20° S, 72° W; named Point Alpha) from 16 October to 13 November 2008 during the VAMOS Ocean-Cloud- Atmosphere-Land Study- Regional Experiment (VOCALS-REx), combined with meteorological reanalysis, satellite measurements, and radiosonde data, are used to investigate the boundary layer (BL) and aerosol-cloud-drizzle variations in this region. On days without predominately synoptic and meso-scale influences, the BL at Point Alpha was typical of a non-drizzling stratocumulus-topped BL. Entrainment rates calculated from the near cloud-top fluxes and turbulence in the BL at Point Alpha appeared to be weaker than those in the BL over the open ocean west of Point Alpha and the BL near the coast of the northeast Pacific. The cloud liquid water path (LWP) varied between 15 gmˉ² and 160 gmˉ². The BL had a depth of 1140±120 m, was generally well-mixed and capped by a sharp inversion without predominately synoptic and mesoscale influences. The wind direction generally switched from southerly within the BL to northerly above the inversion. On days when a synoptic system and related mesoscale costal circulations affected conditions at Point Alpha (29 October– 4 November), a moist layer above the inversion moved over Point Alpha, and the total-water mixing ratio above the inversion was larger than that within the BL. The accumulation mode aerosol varied from 250 to 700 cmˉ³ within the BL, and CCN at 0.2% supersaturation within the BL ranged between 150 and 550 cmˉ³. The main aerosol source at Point Alpha was horizontal advection within the BL from south. The average cloud droplet number concentration ranged between 80 and 400 cmˉ³. While the mean LWP retrieved from GOES was in good agreement with the in situ measurements, the GOES-derived cloud droplet effective radius tended to be larger than that from the aircraft in situ observations near cloud top. The aerosol and cloud LWP relationship reveals that during the typical well-mixed BL days the cloud LWP increased with the CCN concentrations. On the other hand, meteorological factors and the decoupling processes have large influences on the cloud LWP variation as well. ONR grant N000140810465 NOAA/CPPA Program under grant NA08OAR4320889 ONR grant N000140810438 NASA Modeling, Analysis, and Prediction Porgram NASA Clouds and the Earth's Radiant Energy System Project Department of Energy ARM Program through DE-AI02-07ER64546 NOAA's Climate Goal

We introduce a new multispectral method for the retrieval of optical thickness and effective radius from cloud transmittance, which is less sensitive to effective radius than cloud reflectance. Based on data from the moderate spectral resolution observations of the Solar Spectral Flux Radiometer (SSFR) and Shortwave Spectroradiometer (SWS), we use the spectral shape of transmitted radiance as a means of retrieving effective radius from cloud transmittance. The observations were taken during the International Chemistry Experiment in the Arctic Lower Troposphere and at the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) Climate Research Facility. The spectral shape was quantified by fitting a slope to the normalized transmittance between 1565 nm and 1634 nm. The retrieval was performed by comparing the observed slope at 1565 nm and the transmittance at 515 nm with a pre-calculated library (lookup table). An estimate of the retrieval uncertainty was provided by propagating the uncertainty of the observations through the best-fit algorithm. We compare the new retrieval with an algorithm that uses transmittance at two wavelengths, a method often used with cloud reflectance. The liquid water path (LWP) is derived from the retrieved optical thickness and effective radius, assuming a cloud with effective radius varying linearly with altitude above cloud base, and compared to the retrieved liquid water path from a microwave radiometer. Retrievals from two MODIS overpasses of the SGP were also compared. The data taken from the SGP was under thicker cloud than the case used from ICEALOT, with average optical thickness of 44 and 22, respectively. For the time period with the thicker clouds, the dual-wavelength method and the slope method retrieved nearly indistinguishable results. The dual-wavelength method, however, resulted in slightly higher average relative effective radius uncertainty of 12.9 μm±12.8%, as compared to 12.8 μm±8.9% from the slope method. The thinner cloud case resulted in a significant difference between the dual-wavelength and slope algorithms with average retrieved effective radius and uncertainties of 12.5 μm±8.4% and 17.0 μm±21.0% for the slope and dual-wavelength methods, respectively. The retrieved optical thickness values for this case were nearly identical. The average derived LWP was within 12.5% and 20% of the MWR LWP for the ARM and ICEALOT data. For a homogeneous cloud case, the MODIS retrievals (optical depth, effective radius, and LWP) were within the uncertainty of the SWS retrievals. Inhomogeneous clouds resulted in lesser agreement between the MODIS and SWS retrievals.

Much of the large uncertainty in estimates of anthropogenic aerosol effects on climate arises from the multi-scale nature of the interactions between aerosols, clouds and dynamics, which are difficult to represent in conventional general circulation models (GCMs). In this study, we use a multi-scale aerosol-climate model that treats aerosols and clouds across multiple scales to study aerosol indirect effects. This multi-scale aerosol-climate model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each vertical column of a GCM grid. The extension allows a more physically-based treatment of aerosol-cloud interactions in both stratiform and convective clouds on the global scale in a computationally feasible way. Simulated model fields, including liquid water path (LWP), ice water path, cloud fraction, shortwave and longwave cloud forcing, precipitation, water vapor, and cloud droplet number concentration are in reasonable agreement with observations. The new model performs quantitatively similar to the previous version of the MMF model in terms of simulated cloud fraction and precipitation. The simulated change in shortwave cloud forcing from anthropogenic aerosols is −0.77 W m−2, which is less than half of that (−1.79 W m−2) calculated by the host GCM (NCAR CAM5) with traditional cloud parameterizations and is also at the low end of the estimates of other conventional global aerosol-climate models. The smaller forcing in the MMF model is attributed to a smaller (3.9 %) increase in LWP from preindustrial conditions (PI) to present day (PD) compared with 15.6 % increase in LWP in stratiform clouds in CAM5. The difference is caused by a much smaller response in LWP to a given perturbation in cloud condensation nuclei (CCN) concentrations from PI to PD in the MMF (about one-third of that in CAM5), and, to a lesser extent, by a smaller relative increase in CCN concentrations from PI to PD in the MMF (about 26 % smaller than that in CAM5). The smaller relative increase in CCN concentrations in the MMF is caused in part by a smaller increase in aerosol lifetime from PI to PD in the MMF, a positive feedback in aerosol indirect effects induced by cloud lifetime effects from aerosols. The smaller response in LWP to anthropogenic aerosols in the MMF model is consistent with observations and with high resolution model studies, which may indicate that aerosol indirect effects simulated in conventional global climate models are overestimated and point to the need to use global high resolution models, such as MMF models or global CRMs, to study aerosol indirect effects. The simulated total anthropogenic aerosol effect in the MMF is −1.05 W m−2, which is close to the Murphy et al. (2009) inverse estimate of −1.1±0.4 W m−2 (1σ) based on the examination of the Earth's energy balance. Further improvements in the representation of ice nucleation and low clouds in MMF are needed to refine the aerosol indirect effect estimate.

We use a cloud-system-resolving model to study marine-cloud brightening. We examine how injected aerosol particles that act as cloud condensation nuclei (CCN) are transported within the marine boundary layer and how the additional particles in clouds impact cloud microphysical processes, and feedback on dynamics. Results show that the effectiveness of cloud brightening depends strongly on meteorological and background aerosol conditions. Cloud albedo enhancement is very effective in a weakly precipitating boundary layer and in CCN-limited conditions preceded by heavy and/or persistent precipitation. The additional CCN help sustain cloud water by weakening the precipitation substantially in the former case and preventing the boundary layer from collapse in the latter. For a given amount of injected CCN, the injection method (i.e., number and distribution of sprayers) is critical to the spatial distribution of these CCN. Both the areal coverage and the number concentration of injected particles are key players but neither one always emerges as more important than the other. The same amount of injected material is much less effective in either strongly precipitating clouds or polluted clouds, and it is ineffective in a relatively dry boundary layer that supports clouds of low liquid water path. In the polluted case and "dry" case, the CCN injection increases drop number concentration but lowers supersaturation and liquid water path. As a result, the cloud experiences very weak albedo enhancement, regardless of the injection method.

Multiplatform airborne, ship-based, and land-based observations from 16 October–15 November 2008 during the VOCALS Regional Experiment (REx) are used to document the typical structure of the Southeast Pacific stratocumulus-topped boundary layer and lower free troposphere on a~transect along 20° S between the coast of Northern Chile and a buoy 1500 km offshore. Strong systematic gradients in clouds, precipitation and vertical structure are modulated by synoptically and diurnally-driven variability. The boundary layer is generally capped by a strong (10–12 K), sharp inversion. In the coastal zone, the boundary layer is typically 1 km deep, fairly well mixed, and topped by thin, nondrizzling stratocumulus with accumulation-mode aerosol and cloud droplet concentrations exceeding 200 cm−3. Far offshore, the boundary layer depth is typically deeper (1600 m) and more variable, and the vertical structure is usually decoupled. The offshore stratocumulus typically have strong mesoscale organization, much higher peak liquid water paths, extensive drizzle, and cloud droplet concentrations below 100 cm−3, sometimes with embedded pockets of open cells with lower droplet concentrations. The lack of drizzle near the coast is not just a microphysical response to high droplet concentrations; smaller cloud depth and liquid water path than further offshore appear comparably important. Moist boundary layer air is heated and mixed up along the Andean slopes, then advected out over the top of the boundary layer above adjacent coastal ocean regions. Well offshore, the lower free troposphere is typically much drier. This promotes strong cloud-top radiative cooling and stronger turbulence in the clouds offshore. In conjunction with a slightly cooler free troposphere, this may promote stronger entrainment that maintains the deeper boundary layer seen offshore. Winds from ECMWF and NCEP operational analyses have an rms difference of only 1 m s−1 from collocated airborne leg-mean observations in the boundary layer and 2 m s−1 above the boundary layer. This supports the use of trajectory analysis for interpreting REx observations. Two-day back-trajectories from the 20° S transect suggest that eastward of 75° W, boundary layer (and often free-tropospheric) air has usually been exposed to South American coastal aerosol sources, while at 85° W, neither boundary-layer or free-tropospheric air has typically had such contact.

The authors propose a new method for the assignment of rainfall confidences on a pixel basis using cloud properties derived from optical satellite data during daytime. This approach is based on the concept model that the probability for precipitation is a function of the liquid water path, which in turn can be computed using the satellite-retrieved cloud optical thickness and the cloud effective droplet radius. In order to evaluate the principal potential of this idea, scenes from the Terra-MODIS sensor during the severe European summer floods in 2002 have been analysed in order to derive a corresponding regression function that interlinks the liquid water path with the rainfall probability or better with the confidence that a pixel which is classified as raining does actually rain. A first evaluation against ground-based radar data during March 2004 shows good skill of this new method.

If climate models produced clouds having liquid water amounts close to those observed, they would compute a mean albedo that is often much too large, due to the treatment of clouds as plane-parallel. An approximate lower-bound for this "plane-parallel albedo bias" may be obtained from a fractal model having a range of optical thicknesses similar to those observed in marine stratocumulus, since they are more nearly plane-parallel than most other cloud types. We review and extend results from a model which produces a distribution of liquid water path having a lognormal-like probability density and a power-law wavenumber spectrum, with parameters determined by stratocumulus observations. As the spectral exponent approaches -1, the simulated cloud approaches a well-known multifractal, referred to as the "singular model", but when the exponent is -5/3, similar to what is observed, the cloud exhibits qualitatively different scaling properties, the socalled "bounded model". The mean albedo for bounded cascade clouds is a function of a fractal parameter, 0 << 1, as well as the usual plane-parallel parameters such as single scattering albedo, asymmetry, solar zenith angle, and mean vertical optical thickness. A simple expression is derived to determine from the variance of the logarithm of the vertically-integrated liquid water. The albedo is shown to be approximated well by the plane-parallel albedo of a cloud having an "effective" vertical optical thickness, smaller than the mean thickness by a factor χ(f), which is given as an analytic function of f. California stratocumulus have a mean fractal parameter (f) ≈ 0.5, relative albedo bias of 15%, and an effective thickness 30% smaller than the mean thickness (χ ≈ 0.7). For typical observed values of mean liquid water and (f), the effective thickness approximation gives a plane-parallel albedo within 3% of the mean albedo.

Observations in the subtropical south east Pacific obtained during the VOCALS-REx field experiment are used to evaluate the representation of stratocumulus cloud in the Met Office forecast model and to identify key areas where model biases exist. Marked variations in the large scale structure of the cloud field were observed during the experiment on both day to day and on diurnal timescales. In the remote maritime region the model is shown to have a good representation of synoptically induced variability in both cloud cover and marine boundary layer depth. Satellite observations show a strong diurnal cycle in cloud fraction and liquid water path in the stratocumulus with enhanced clearances of the cloud deck along the Chilean and Peruvian coasts on certain days. The model accurately simulates the phase of the diurnal cycle but is unable to capture the coastal clearing of cloud. Observations along the 20° S latitude line show a gradual increase in the depth of the boundary layer away from the coast. This trend is well captured by the model (typical low bias of 200 m) although significant errors exist at the coast where the model marine boundary layer is too shallow and moist. Drizzle in the model responds to changes in liquid water path in a manner that is consistent with previous ship-borne observations in the region although the intensity of this drizzle is likely to be too high, particularly in the more polluted coastal region where higher cloud droplet number concentrations are typical. Another mode of variability in the cloud field that the model is unable to capture are regions of pockets of open cellular convection embedded in the overcast stratocumulus deck and an example of such a feature that was sampled during VOCALS-REx is shown.