Addressing the difficulties in quantifying the Twomey effect for marine warm clouds from multi-sensor satellite observations and reanalysis

Spatio Temporal ◽

Observational Estimate ◽

Aerosol Effects

Aerosol&#8211;cloud interaction is the most uncertain component of the overall anthropogenic forcing of the climate, inwhich the Twomey effect plays a fundamental role. Satellite-based estimates of the Twomey effect are especially challenging, mainly due to the difficulty in disentangling aerosol effects on cloud droplet number concentration (Nd) from possible confounders. By combining multiple satellite observations and reanalysis, this study investigates the impacts of a) updraft, b) precipitation, c) retrieval errors, as well as (d) vertical co-location between aerosol and cloud, on the assessment of Nd-to-aerosol sensitivity (S) in the context of marine warm (liquid) clouds. Our analysis suggests that S increases remarkably with both cloud base height and cloud geometric thickness (proxies for vertical velocity at cloud base), consistent with stronger aerosol-cloud interactions at larger updraft velocity. In turn, introducing the confounding effect of aerosol&#8211;precipitation interaction can artificially amplify S by an estimated 21 %, highlighting the necessity of removing precipitating clouds from analyses on the Twomey effect. It is noted that the retrieval biases in aerosol and cloud appear to underestimate S, in which cloud fraction acts as a key modulator, making it practically difficult to balance the accuracies of aerosol&#8211;cloud retrievals at aggregate scales (e.g., 1&#9702; &#215; 1&#9702; grid). Moreover, we show that using column-integrated sulfate mass concentration (SO4C) to approximate sulfate concentration at cloud base (SO4B) can result in a degradation of correlation with Nd, along with a nearly two fold enhancement of S, mostly attributed to the inability of SO4C to capture the full spatio-temporal variability of SO4B. These findings point to several potential ways forward to account for the major influential factors practically by means of satellite observations and reanalysis, aiming at an optimal observational estimate of global radiative forcing due to the Twomey effect.

Addressing the difficulties in quantifying the Twomey effect for marine warm clouds from multi-sensor satellite observations and reanalysis

10.5194/acp-2021-999 ◽

2022 ◽

Author(s):

Hailing Jia ◽

Johannes Quaas ◽

Edward Gryspeerdt ◽

Christoph Böhm ◽

Odran Sourdeval

Keyword(s):

Radiative Forcing ◽

Cloud Droplet ◽

Influential Factors ◽

Satellite Observations ◽

Cloud Base ◽

Aerosol Cloud ◽

Spatio Temporal ◽

Observational Estimate ◽

Aerosol Effects

Abstract. Aerosol–cloud interaction is the most uncertain component of the overall anthropogenic forcing of the climate, in which the Twomey effect plays a fundamental role. Satellite-based estimates of the Twomey effect are especially challenging, mainly due to the difficulty in disentangling aerosol effects on cloud droplet number concentration (Nd) from possible confounders. By combining multiple satellite observations and reanalysis, this study investigates the impacts of a) updraft, b) precipitation, c) retrieval errors, as well as (d) vertical co-location between aerosol and cloud, on the assessment of Nd-toaerosol sensitivity (S) in the context of marine warm (liquid) clouds. Our analysis suggests that S increases remarkably with both cloud base height and cloud geometric thickness (proxies for vertical velocity at cloud base), consistent with stronger aerosol-cloud interactions at larger updraft velocity. In turn, introducing the confounding effect of aerosol–precipitation interaction can artificially amplify S by an estimated 21 %, highlighting the necessity of removing precipitating clouds from analyses on the Twomey effect. It is noted that the retrieval biases in aerosol and cloud appear to underestimate S, in which cloud fraction acts as a key modulator, making it practically difficult to balance the accuracies of aerosol–cloud retrievals at aggregate scales (e.g., 1° × 1° grid). Moreover, we show that using column-integrated sulfate mass concentration (SO4C) to approximate sulfate concentration at cloud base (SO4B) can result in a degradation of correlation with Nd, along with a nearly twofold enhancement of S, mostly attributed to the inability of SO4C to capture the full spatio-temporal variability of SO4B. These findings point to several potential ways forward to account for the major influential factors practically by means of satellite observations and reanalysis, aiming at an optimal observational estimate of global radiative forcing due to the Twomey effect.

The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data

10.5194/amt-2021-371 ◽

2021 ◽

Author(s):

Edward Gryspeerdt ◽

Daniel T. McCoy ◽

Ewan Crosbie ◽

Richard H. Moore ◽

Graeme J. Nott ◽

...

Keyword(s):

Satellite Data ◽

Radiative Forcing ◽

Sampling Strategy ◽

Cloud Droplet ◽

Number Concentration ◽

Cloud Properties ◽

Systematic Biases ◽

The Impact

Abstract. Cloud droplet number concentration (Nd) is of central importance to observation-based estimates of aerosol indirect effects, being used to quantify both the cloud sensitivity to aerosol and the base state of the cloud. However, the derivation of Nd from satellite data depends on a number of assumptions about the cloud and the accuracy of the retrievals of the cloud properties from which it is derived, making it prone to systematic biases. A number of sampling strategies have been proposed to address these biases by selecting the most accurate Nd retrievals in the satellite data. This work compares the impact of these strategies on the accuracy of the satellite retrieved Nd, using a selection of insitu measurements. In stratocumulus regions, the MODIS Nd retrieval is able to achieve a high precision (r2 of 0.5–0.8). This is lower in other cloud regimes, but can be increased by appropriate sampling choices. Although the Nd sampling can have significant effects on the Nd climatology, it produces only a 20 % variation in the implied radiative forcing from aerosol-cloud interactions, with the choice of aerosol proxy driving the overall uncertainty. The results are summarised into recommendations for using MODIS Nd products and appropriate sampling.

The hemispheric contrast in cloud microphysical properties constrains aerosol forcing

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1922502117 ◽

2020 ◽

Vol 117 (32) ◽

pp. 18998-19006 ◽

Cited By ~ 2

Author(s):

Isabel L. McCoy ◽

Daniel T. McCoy ◽

Robert Wood ◽

Leighton Regayre ◽

Duncan Watson-Parris ◽

...

Keyword(s):

Southern Ocean ◽

Northern Hemisphere ◽

Radiative Forcing ◽

Climate Models ◽

Cloud Droplet ◽

Number Concentration ◽

Global Climate Models ◽

Aerosol Cloud ◽

Aerosol Cloud Interactions

The change in planetary albedo due to aerosol−cloud interactions during the industrial era is the leading source of uncertainty in inferring Earth’s climate sensitivity to increased greenhouse gases from the historical record. The variable that controls aerosol−cloud interactions in warm clouds is droplet number concentration. Global climate models demonstrate that the present-day hemispheric contrast in cloud droplet number concentration between the pristine Southern Hemisphere and the polluted Northern Hemisphere oceans can be used as a proxy for anthropogenically driven change in cloud droplet number concentration. Remotely sensed estimates constrain this change in droplet number concentration to be between 8 cm−3and 24 cm−3. By extension, the radiative forcing since 1850 from aerosol−cloud interactions is constrained to be −1.2 W⋅m−2to −0.6 W⋅m−2. The robustness of this constraint depends upon the assumption that pristine Southern Ocean droplet number concentration is a suitable proxy for preindustrial concentrations. Droplet number concentrations calculated from satellite data over the Southern Ocean are high in austral summer. Near Antarctica, they reach values typical of Northern Hemisphere polluted outflows. These concentrations are found to agree with several in situ datasets. In contrast, climate models show systematic underpredictions of cloud droplet number concentration across the Southern Ocean. Near Antarctica, where precipitation sinks of aerosol are small, the underestimation by climate models is particularly large. This motivates the need for detailed process studies of aerosol production and aerosol−cloud interactions in pristine environments. The hemispheric difference in satellite estimated cloud droplet number concentration implies preindustrial aerosol concentrations were higher than estimated by most models.

Cloud Droplet Number Concentration

Quantification of aerosol effects on marine boundary layer clouds with machine learning

10.5194/egusphere-egu21-10754 ◽

2021 ◽

Author(s):

Lukas Zipfel ◽

Hendrik Andersen ◽

Jan Cermak

Keyword(s):

Machine Learning ◽

Boundary Layer ◽

Marine Boundary Layer ◽

Cloud Droplet ◽

Number Concentration ◽

Satellite Observations ◽

Radiative Properties ◽

Cloud Base ◽

Boundary Layer Clouds ◽

Satellite observations are used in regional machine learning models to quantify sensitivities of marine boundary-layer clouds (MBLC) to aerosol changes.MBLCs make up a large part of the global cloud coverage as they are persistently present over more than 20% of the Earth&#8217;s oceans in the annual mean.They play an important role in Earth&#8217;s energy budget by reflecting solar radiation and interacting with thermal radiation from the surface, leading to a net cooling effect. Cloud properties and their radiative characteristics such as cloud albedo, horizontal and vertical extent, lifetime and precipitation susceptibility are dependent on environmental conditions. Aerosols in their role as condensation nuclei affect these cloud radiative properties through changes in the cloud droplet number concentration and subsequent cloud adjustments to this perturbation. However, the magnitude and sign of these effects remain among the largest uncertainties in future climate predictions.In an effort to help improve these predictions a machine learning approach in combination with observational data is pursued:Satellite observations from the collocated A-Train dataset (C3M) for 2006-2011 are used in combination with ECMWF atmospheric reanalysis data (ERA5) to train regional Gradient Boosting Regression Tree (GBRT) models to predict changes in key physical and radiative properties of MBLCs. The cloud droplet number concentration (Nd) and the liquid water path (LWP) are simulated for the eastern subtropical oceans, which are characterised by a high annual coverage of MBLC due to the occurrence of semi-permanent stratocumulus sheets. Relative humidity above cloud, cloud top height and temperature below the cloud base and at the surface are identified as important predictors for both Nd and LWP.&#160; The impact of each predictor variable on the GBRT model's output is analysed using Shapley values as a method of explainable machine learning, providing novel sensitivity estimates that will improve process understanding and help constrain the parameterization of MBLC processes in Global Climate Models.

Cloud Droplet Number Concentration

On the Relation among Satellite Observed Liquid Water Path, Cloud Droplet Number Concentration and Cloud Base Rain Rate and Its Implication to the Auto-Conversion Parameterization in Stratocumulus Clouds

Journal of Climate ◽

10.1175/jcli-d-20-0473.1 ◽

2021 ◽

pp. 1

Author(s):

Yasutaka Murakami ◽

Christian D. Kummerow ◽

Susan C. van den Heever

Keyword(s):

Rain Rate ◽

Cloud Droplet ◽

Number Concentration ◽

Satellite Observations ◽

Cloud Base ◽

Liquid Water Path ◽

Warm Rain ◽

Accretion Process ◽

Stratocumulus Clouds ◽

AbstractPrecipitation processes play a critical role in the longevity and spatial distribution of stratocumulus clouds through their interaction with the vertical profiles of humidity and temperature within the atmospheric boundary layer. One of the difficulties in understanding these processes is the limited amount of observational data. In this study, robust relations among liquid water path (LWP), cloud droplet number concentration (Nd) and cloud base rain rate (Rcb) from three subtropical stratocumulus decks are obtained from A-Train satellite observations in order to obtain a broad perspective on warm rain processes. Rcb has a positive correlation with LWP/Nd and the increase of Rcb becomes larger as LWP/Nd increases. However, the increase of Rcb with respect to LWP/Nd becomes more gradual in regions with larger Nd, which indicates the relation is moderated by Nd. These results are consistent with our theoretical understanding of warm rain processes and suggest that satellite observations are capable of elucidating the average manner of how precipitation processes are modulated by LWP and Nd. The sensitivity of the auto-conversion rate to Nd is investigated by examining pixels with small LWP in which the accretion process is assumed to have little influence on Rcb. The upper limit of the dependency of auto-conversion rate on Nd is assessed from the relation between Rcb and Nd, since the sensitivity is exaggerated by the accretion process, and was found to be a cloud droplet number concentration to the power of −1.44 ± 0.12.

Impact of solar radiation on aerosol-cloud interactions in thin stratocumulus clouds

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-9-23791-2009 ◽

2009 ◽

Vol 9 (6) ◽

pp. 23791-23833 ◽

Cited By ~ 1

Author(s):

S. S. Lee ◽

J. E. Penner

Keyword(s):

Solar Radiation ◽

Climate Models ◽

Marine Boundary Layer ◽

Cloud Droplet ◽

Cloud Base ◽

Liquid Water Path ◽

Surface Precipitation ◽

Stratocumulus Clouds ◽

Aerosol Effects

Abstract. This study examines the role of solar radiation in the effect of aerosols on liquid-water path (LWP) in thin, marine stratocumulus clouds with LWP of ~50 g m−2 or less by performing four sets of simulations with different solar radiation. Each set is composed of a simulation with present-day (PD) aerosols and a simulation with preindustrial (PI) aerosols. As solar radiation increases, decoupling within the marine boundary layer (MBL) becomes stronger, leading to less condensation and less LWP and thus the absence of the surface precipitation. This enables the evaporation of rain to affect the cloud-base instability. As rain evaporation increases due to more conversion of cloud liquid to rain in the PI case, the cloud-base instability increases and thus updrafts increase which leads to larger LWP in the PI case than in the PD case. In the cases with no surface precipitation, when solar radiation decreases and thus decoupling becomes weaker, rain evaporation and cloud-base instability become larger, which increases the LWP more with PI aerosols than with PD aerosols. As solar radiation decreases further, condensation and, thus, the LWP increase, which leads to the presence of the surface precipitation. This stabilizes the entire MBL and thus prevents the interactions that cause the evaporation of rain to enhance the cloud-base instability. In cases with the surface precipitation, the in-cloud interactions among cloud droplet number concentration (CDNC), supersaturation, and updrafts play an important role in the effect of aerosols on the LWP; these in-cloud interactions produce larger LWP with the PD aerosols than with the PI aerosols. In a case with lower solar radiation and with surface precipitation, weaker decoupling induces stronger in-cloud interactions, which results in larger increases in LWP with PD aerosols compared to PI aerosols than that in a case with higher solar radiation. The results of this study demonstrate that solar radiation can act as an important environmental factor by inducing a large variation in the LWP and by changing the sign of aerosol effects on the LWP of thin stratocumulus clouds. Hence, the effect of solar radiation on decoupling and thus on the feedbacks between microphysics and dynamics needs to be included in climate models for a better prediction of the effect of aerosols on clouds and thus climate.

Role of updrafts in aerosol-cloud interactions: lidar observations of layered warm clouds over central Europe

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-31409-2014 ◽

2014 ◽

Vol 14 (22) ◽

pp. 31409-31440 ◽

Cited By ~ 2

Author(s):

J. Schmidt ◽

A. Ansmann ◽

J. Bühl ◽

U. Wandinger

Keyword(s):

Cloud Droplet ◽

Number Concentration ◽

Cloud Base ◽

Aerosol Cloud ◽

Cloud Properties ◽

Aerosol Effect ◽

Cloud Dynamics ◽

Water Cloud ◽

Aerosol Cloud Interactions

Abstract. Twenty nine cases of layered liquid-water cloud systems were observed with dual-field-of-view (dual-FOV) Raman lidar over the polluted central European site of Leipzig, Germany, between September 2010 and September 2012. For the first time, a detailed lidar-based study of aerosol-cloud-dynamics relationship was conducted. A collocated Doppler lidar provided information on vertical velocity and thus on updraft and downdraft occurrence. The novel dual-FOV lidar permits the retrieval of the particle extinction coefficient (used as aerosol proxy just below cloud base) and cloud properties such as droplet effective radius and cloud droplet number concentration in the lower part of optically thin cloud layers. Here, we present the key results of our statistical analysis of the 2010–2012 observations. Besides a clear aerosol effect on cloud droplet number concentration in the lower part of the convectively weak cloud layers during updraft periods, meteorological effects (turbulent mixing, entrainment of dry air) were found to diminish the observable aerosol effect higher up in the clouds. The corresponding aerosol-cloud interaction (ACI) parameter based on changes in cloud droplet number concentration with aerosol loading was found to be close to 0.8 at 30–70 m above cloud base during updraft periods which points to values around 1 at cloud base (0–30 m above cloud base). Our findings are extensively compared with literature values and agree well with airborne observations. As a conclusion, ACI studies over continental sites should include vertical wind observations to avoid a~bias (too low values) in the obtained ACI results.

The aerosol-cyclone indirect effect in observations and high-resolution simulations

10.5194/acp-2017-649 ◽

2017 ◽

Cited By ~ 1

Author(s):

Daniel T. McCoy ◽

Paul R. Field ◽

Anja Schmidt ◽

Daniel P. Grosvenor ◽

Frida A.-M. Bender ◽

...

Keyword(s):

High Resolution ◽

Indirect Effect ◽

Climate Models ◽

Climate Model ◽

Cloud Condensation Nuclei ◽

Cloud Droplet ◽

2014 Eruption ◽

First Time

Abstract. Aerosol-cloud interactions are a major source of uncertainty in predicting 21st century climate change. Using high-resolution, convection-permitting global simulations we predict that increased cloud condensation nuclei (CCN) interacting with midlatitude cyclones will increase their cloud droplet number concentration (CDNC), liquid water (CLWP), and albedo. For the first time this effect is shown with 13 years of satellite observations. Causality between enhanced CCN and enhanced cyclone liquid content is supported by the 2014 eruption of Holuhraun. The change in midlatitude cyclone albedo due to enhanced CCN in a surrogate climate model is around 70 % of the change in a high-resolution convection-permitting model, indicating that climate models may underestimate this indirect effect.

Droplet Clustering in Shallow Cumuli: The Effects of In–Cloud Location and Aerosol Number Concentration

10.5194/acp-2018-772 ◽

2018 ◽

Author(s):

Dillon S. Dodson ◽

Jennifer D. Small Griswold

Keyword(s):

Pair Correlation ◽

Cloud Droplet ◽

Number Concentration ◽

Atmospheric Composition ◽

Cloud Base ◽

Arrival Times ◽

Remotely Piloted Aircraft ◽

Aerosol Number Concentration ◽

Lifetime Effects

Abstract. Aerosol–cloud interactions are complex, including albedo and lifetime effects that cause modifications to cloud characteristics. With most cloud–aerosol interactions focused on the previously stated phenomena, there has been no in–situ studies that focus explicitly on how aerosols can affect droplet clustering within clouds. This research therefore aims to gain a better understanding of how droplet clustering within cumulus clouds can be influenced by in–cloud droplet location (cloud edge vs. center) and aerosol number concentration. The pair–correlation function (PCF) is used to identify the magnitude of droplet clustering from data collected onboard the Center for interdisciplinary Remotely–Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft, flown during the 2006 Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS). Time stamps (at 10−4 m spatial resolution) of cloud droplet arrival times were measured by the Artium Flight Phase–Doppler Interferometer (PDI). Using four complete days of data with 81 non–precipitating cloud penetrations organized into two flights of low (L1, L2) and high (H1, H2) pollution data shows more clustering near cloud edge as compared to cloud center for all four cases. Low pollution clouds are shown to have enhanced overall clustering, with flight L2 being solely responsible for this enhanced clustering. Analysis suggests cloud age plays a larger role in the clustering amount experienced than the aerosol number concentration, with dissipating clouds showing increased clustering as compared to growing or mature clouds. Results using a single, vertically developed cumulus cloud demonstrate more clustering near cloud top as compared to cloud base.

The effect of physical and chemical aerosol properties on warm cloud droplet activation

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-5-8507-2005 ◽

2005 ◽

Vol 5 (5) ◽

pp. 8507-8646 ◽

Cited By ~ 17

Author(s):

G. McFiggans ◽

P. Artaxo ◽

U. Baltensperger ◽

H. Coe ◽

M. C. Facchini ◽

...

Keyword(s):

Atmospheric Aerosol ◽

Radiative Forcing ◽

Cloud Droplet ◽

Size Composition ◽

Radiative Properties ◽

Atmospheric Measurements ◽

Derived Properties ◽

Aerosol Effects ◽

Physical And Chemical ◽

Aerosol Properties

Abstract. The effects of atmospheric aerosol on climate forcing may be very substantial but are quantified poorly at present; in particular, the effects of aerosols on cloud radiative properties, or the "indirect effects" are credited with the greatest range of uncertainty amongst the known causes of radiative forcing. This manuscript explores the effects that the composition and properties of atmospheric aerosol can have on the activation of droplets in warm clouds, so potentially influencing the magnitude of the indirect effect. The effects of size, composition, mixing state and various derived properties are assessed and a range of these properties provided by atmospheric measurements in a variety of locations is briefly reviewed. The suitability of a range of process-level descriptions to capture these aerosol effects is investigated by assessment of their sensitivities to uncertainties in aerosol properties and by their performance in closure studies. The treatment of these effects within global models is reviewed and suggestions for future investigations are made.