scholarly journals Quantifying cloud adjustments and the radiative forcing due to aerosol–cloud interactions in satellite observations of warm marine clouds

2020 ◽  
Vol 20 (10) ◽  
pp. 6225-6241 ◽  
Author(s):  
Alyson Douglas ◽  
Tristan L'Ecuyer
Keyword(s):  
Radiative Forcing ◽  
Local Environment ◽  
Satellite Observations ◽  
Cloud Environment ◽  
Climate Scenarios ◽  
Liquid Water Path ◽  
Sources Of Uncertainty ◽  
Aerosol Cloud ◽  
Effective Radiative Forcing ◽  
Aerosol Cloud Interactions

Abstract. Aerosol–cloud interactions and their resultant forcing remains one of the largest sources of uncertainty in future climate scenarios. The effective radiative forcing due to aerosol–cloud interactions (ERFaci) is a combination of two different effects, namely how aerosols modify cloud brightness (RFaci, intrinsic) and how cloud extent reacts to aerosol (cloud adjustments CA; extrinsic). Using satellite observations of warm clouds from the NASA A-Train constellation from 2007 to 2010 along with MERRA-2 Reanalysis and aerosol from the SPRINTARS model, we evaluate the ERFaci in warm, marine clouds and its components, the RFaciwarm and CAwarm, while accounting for the liquid water path and local environment. We estimate the ERFaciwarm to be -0.32±0.16 Wm−2. The RFaciwarm dominates the ERFaciwarm contributing 80 % (-0.21±0.15 Wm−2), while the CAwarm enhances this cooling by 20 % (-0.05±0.03 Wm−2). Both the RFaciwarm and CAwarm vary in magnitude and sign regionally and can lead to opposite, negating effects under certain environmental conditions. Without considering the two terms separately and without constraining cloud–environment interactions, weak regional ERFaciwarm signals may be erroneously attributed to a damped susceptibility to aerosol.

scholarly journals Quantifying Cloud Adjustments and the Radiative Forcing due to Aerosol-Cloud Interactions in Satellite Observations of Warm Marine Clouds

2020 ◽  
Author(s):  
Alyson Douglas ◽  
Tristan L'Ecuyer
Keyword(s):  
Radiative Forcing ◽  
Local Environment ◽  
Satellite Observations ◽  
Cloud Environment ◽  
Climate Scenarios ◽  
Liquid Water Path ◽  
Sources Of Uncertainty ◽  
Aerosol Cloud ◽  
Effective Radiative Forcing ◽  
Aerosol Cloud Interactions

Abstract. Aerosol-cloud interactions and their resultant forcing remains one of the largest sources of uncertainty of future climate scenarios. The effective radiative forcing due to aerosol-cloud interactions (ERFaci) is a combination of two different effects, how aerosols modify cloud brightness (RFaci) and how cloud extent reacts to aerosol (CA). Using satellite observations of warm clouds from the NASA A-Train constellation from 2007 to 2010 along with MERRA-2 reanalysis and aerosol from the SPRINTARS model, we evaluate the ERFaci and its components, the RFaci and CA, while accounting for the liquid water path and local environment. We estimate the ERFaci to be −0.32 ± 0.16 W m−2. The RFaci dominates the ERFaci contributing 80 % (−0.21 ± 0.15 W m−2), while the CA enhances this cooling by 20 % (−0.05 ± 0.03 W m−2). Both the RFaci and CA vary in magnitude and sign regionally, and can lead to opposite, negating effects under certain environmental conditions. Without considering the two terms separately, and without constraining cloud-environment interactions, weak regional ERFaci signals may be erroneously attributed to buffering or a damped susceptibility to aerosol.

scholarly journals Untangling causality in midlatitude aerosol-cloud adjustments

2019 ◽  
Author(s):  
Daniel T. McCoy ◽  
Paul Field ◽  
Hamish Gordon ◽  
Gregory S. Elsaesser ◽  
Daniel P. Grosvenor
Keyword(s):  
Radiative Forcing ◽  
Sensible Heat Flux ◽  
Cloud Droplet ◽  
Causal Link ◽  
Cloud Microphysics ◽  
Liquid Water Path ◽  
Aerosol Cloud ◽  
Causal Pathways ◽  
Model Adjustment ◽  
Aerosol Cloud Interactions

Abstract. Aerosol-cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (Nd) (the first indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of forcing associated with changes in cloud macrophysics in response to aerosol (aerosol-cloud adjustments) remain uncertain. This uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud microphysical state to cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path averaged across cloudy and clear regions (LWP, here, characterizing the macrophysical state) and Nd (characterizing the microphysical) is the sum of two causal pathways linking Nd to LWP: Nd altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting Nd. Only the former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We hypothesize that the diversity of constraints on aerosol-cloud adjustments in the literature may be partly due to not explicitly characterizing covariance flowing from cloud to aerosol, and aerosol to cloud. Here, we restrict our analysis to the regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP, and MODIS are compared to simulations in the MetOffice Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat flux enhance LWP, while increasing subsidence, and sea surface temperature decrease it. A simulation where cloud microphysics are insensitive to changes in Nd is used to characterize covariance between Nd and LWP that is induced by factors other than aerosol-cloud adjustments. By removing variability associated with meteorology and scavenging we infer the sensitivity of LWP to changes in Nd. Application of this technique to UM GA7.1 simulations reproduces the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments and observed covariability between Nd and LWP predict a 25–30 % overestimate by the UM GA7.1 in LWP change and a 30–35% overestimate in associated radiative forcing.

scholarly journals Snow-induced buffering in aerosol–cloud interactions

2020 ◽  
Author(s):  
Takuro Michibata ◽  
Kentaroh Suzuki ◽  
Toshihiko Takemura
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
State Of The Art ◽  
General Circulation Models ◽  
Regional Pattern ◽  
Cloud Droplets ◽  
Microphysical Process ◽  
Aerosol Cloud ◽  
Effective Radiative Forcing ◽  
Aerosol Cloud Interactions

Abstract. Complex aerosol–cloud–precipitation interactions lead to large differences in estimates of aerosol impacts on climate among general circulation models (GCMs) and satellite retrievals. Typically, precipitating hydrometeors are treated diagnostically in most GCMs, and their radiative effects are ignored. Here, we quantify how the treatment of precipitation influences the simulated effective radiative forcing due to aerosol–cloud interactions (ERFaci) using a state-of-the-art GCM with a two-moment prognostic precipitation scheme that incorporates the radiative effect of precipitating particles, and investigate how microphysical process representations are related to macroscopic climate effects. Prognostic precipitation substantially weakens the magnitude of ERFaci (by approximately 75 %) compared with the traditional diagnostic scheme, and this is the result of the increased longwave (warming) and weakened shortwave (cooling) components of ERFaci. The former is attributed to additional adjustment processes induced by falling snow, and the latter stems largely from riming of snow by collection of cloud droplets. The significant reduction in ERFaci does not occur without prognostic snow, which contributes mainly by buffering the cloud response to aerosol perturbations through depleting cloud water via collection. Prognostic precipitation also alters the regional pattern of ERFaci, particularly over northern mid-latitudes where snow is abundant. The treatment of precipitation is thus a highly influential controlling factor of ERFaci, contributing more than other uncertain tunable processes related to aerosol–cloud–precipitation interactions. This change in ERFaci caused by the treatment of precipitation is large enough to explain the existing difference in ERFaci between GCMs and observations.

scholarly journals The scale problem in quantifying aerosol indirect effects

2012 ◽  
Vol 12 (2) ◽  
pp. 1031-1049 ◽  
Author(s):  
A. McComiskey ◽  
G. Feingold
Keyword(s):  
Radiative Forcing ◽  
Process Model ◽  
Full Range ◽  
Liquid Water Path ◽  
Aerosol Cloud ◽  
Cloud Properties ◽  
Wide Range ◽  
Albedo Effect ◽  
Aerosol Cloud Interactions ◽  
The Impact

Abstract. A wide range of estimates exists for the radiative forcing of the aerosol effect on cloud albedo. We argue that a component of this uncertainty derives from the use of a wide range of observational scales and platforms. Aerosol influences cloud properties at the microphysical scale, or the "process scale", but observations are most often made of bulk properties over a wide range of resolutions, or "analysis scales". We show that differences between process and analysis scales incur biases in quantification of the albedo effect through the impact that data aggregation and computational approach have on statistical properties of the aerosol or cloud variable, and their covariance. Measures made within this range of scales are erroneously treated as equivalent, leading to a large uncertainty in associated radiative forcing estimates. Issues associated with the coarsening of observational resolution particular to quantifying the albedo effect are discussed. Specifically, the omission of the constraint on cloud liquid water path and the separation in space of cloud and aerosol properties from passive, space-based remote sensors dampen the measured strength of the albedo effect. We argue that, because of this lack of constraints, many of these values are in fact more representative of the full range of aerosol-cloud interactions and their associated feedbacks. Based on our understanding of these biases we propose a new observationally-based and process-model-constrained, method for estimating aerosol-cloud interactions that can be used for radiative forcing estimates as well as a better characterization of the uncertainties associated with those estimates.

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

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 Cloud Interactions ◽  
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.

scholarly journals Deconvolution of boundary layer depth and aerosol constraints on cloud water path in subtropical stratocumulus decks

2020 ◽  
Vol 20 (6) ◽  
pp. 3609-3621
Author(s):  
Anna Possner ◽  
Ryan Eastman ◽  
Frida Bender ◽  
Franziska Glassmeier
Keyword(s):  
Boundary Layer ◽  
Radiative Forcing ◽  
Cloud Droplet ◽  
Process Modelling ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Water Path ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions ◽  
Relative Change

Abstract. The liquid water path (LWP) adjustment due to aerosol–cloud interactions in marine stratocumulus remains a considerable source of uncertainty for climate sensitivity estimates. An unequivocal attribution of LWP adjustments to changes in aerosol concentration from climatology remains difficult due to the considerable covariance between meteorological conditions alongside changes in aerosol concentrations. We utilise the susceptibility framework to quantify the potential change in LWP adjustment with boundary layer (BL) depth in subtropical marine stratocumulus. We show that the LWP susceptibility, i.e. the relative change in LWP scaled by the relative change in cloud droplet number concentration, in marine BLs triples in magnitude from −0.1 to −0.31 as the BL deepens from 300 to 1200 m and deeper. We further find deep BLs to be underrepresented in pollution tracks, process modelling, and in situ studies of aerosol–cloud interactions in marine stratocumulus. Susceptibility estimates based on these approaches are skewed towards shallow BLs of moderate LWP susceptibility. Therefore, extrapolating LWP susceptibility estimates from shallow BLs to the entire cloud climatology may underestimate the true LWP adjustment within subtropical stratocumulus and thus overestimate the effective aerosol radiative forcing in this region. Meanwhile, LWP susceptibility estimates in deep BLs remain poorly constrained. While susceptibility estimates in shallow BLs are found to be consistent with process modelling studies, they overestimate pollution track estimates.

scholarly journals Detection and attribution of aerosol–cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model

2020 ◽  
Vol 20 (9) ◽  
pp. 5657-5678 ◽  
Author(s):  
Montserrat Costa-Surós ◽  
Odran Sourdeval ◽  
Claudia Acquistapace ◽  
Holger Baars ◽  
Cintia Carbajal Henken ◽  
...  
Keyword(s):  
Liquid Water ◽  
Radiative Forcing ◽  
Reference Conditions ◽  
Liquid Water Path ◽  
Large Domain ◽  
Aerosol Cloud ◽  
Detection And Attribution ◽  
Large Eddy ◽  
Ground Based Lidar ◽  
Aerosol Cloud Interactions

Abstract. Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth’s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m−2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol–cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol–cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation −2.6 W m−2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of −0.8 W m−2.

scholarly journals Deconvolution of Boundary Layer Depth and Aerosol Constraints on Cloud Water Path in Subtropical Stratocumuli

2019 ◽  
Author(s):  
Anna Possner ◽  
Ryan Eastman ◽  
Frida Bender ◽  
Franziska Glassmeier
Keyword(s):  
Radiative Forcing ◽  
Process Modelling ◽  
Liquid Water Path ◽  
Water Path ◽  
Aerosol Radiative Forcing ◽  
Aerosol Cloud ◽  
Modelling Studies ◽  
Aerosol Cloud Interactions ◽  
Marine Boundary Layers

Abstract. The liquid water path (LWP) adjustment due to aerosol-cloud interactions in marine stratocumuli remains a considerable source of uncertainty for climate sensitivity estimates. An unequivocal attribution of LWP changes to changes in aerosol concentration from climatology remains difficult due to the considerable covariance between meteorological conditions alongside changes in aerosol concentrations. Here, we show that LWP susceptibility in marine boundary layers (BLs) inferred from climatological relationships, triples in magnitude from −0.1 to −0.33 as the BL deepens. We further find deep BLs to be underrepresented in pollution track, process modelling and in-situ studies of aerosol-cloud interactions in marine stratocumuli. Susceptibility estimates based on these approaches are skewed towards shallow BLs of moderate LWP susceptibility. Therefore, extrapolating LWP susceptibility estimates from shallow BLs to the entire cloud climatology, may underestimate the true LWP adjustment within sub-tropical stratocumuli, and thus overestimate the effective aerosol radiative forcing in this region. Meanwhile, LWP susceptibility estimates inferred from climatology in deep BLs are still poorly constrained. While susceptibility estimates in shallow BLs are found to be consistent with process modelling studies, they are overestimated as compared to pollution track estimates.

scholarly journals Separating radiative forcing by aerosol–cloud interactions and fast cloud adjustments in the ECHAM-HAMMOZ aerosol–climate model using the method of partial radiative perturbations

2019 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Edward Gryspeerdt ◽  
Marc Salzmann ◽  
Po-Lun Ma ◽  
Sudhakar Dipu ◽  
...  
Keyword(s):  
Liquid Water ◽  
Radiative Forcing ◽  
Climate Model ◽  
Cloud Fraction ◽  
Liquid Water Path ◽  
Water Path ◽  
Aerosol Cloud ◽  
Warm Cloud ◽  
Aerosol Cloud Interactions ◽  
Averaged Model

Abstract. Using the method of offline radiative transfer modelling within the partial radiative perturbations (PRP) approach, the effective radiative forcing (ERF) by aerosol–cloud interactions (ACI) in the ECHAM-HAMMOZ aerosol climate model is decomposed into a radiative forcing by anthropogenic cloud droplet number change and adjustments of the liquid water path and cloud fraction. The simulated radiative forcing and liquid water path adjustment are of approximately equal magnitude at −0.52 W m−2 and −0.53 W m−2, respectively, while the cloud fraction adjustment is somewhat weaker at −0.31 W m−2 (constituting 38 %, 39 %, and 23 % of the total ERFaci, respectively); geographically, all three ERF components in the simulation peak over China, the subtropical eastern ocean boundaries, the northern Atlantic and Pacific Ocean, Europe, and eastern North America (in order of prominence). Spatial correlations indicate that the temporal-mean liquid water path adjustment is proportional to the temporal-mean radiative forcing, while the relationship between cloud fraction adjustment and radiative forcing is less direct. While the estimate of warm-cloud ACI is relatively insensitive to the treatment of ice and mixed-phase cloud overlying warm cloud, there are indications that more restrictive treatments of ice in the column result in a low bias in the estimated magnitude of the liquid water path adjustment and a high bias in the estimated magnitude of the droplet number forcing. Since the present work is the first PRP decomposition of the aerosol ERF into RFaci and fast cloud adjustments, idealized experiments are conducted to provide evidence that the PRP results are accurate. The experiments show that using low-frequency (daily or monthly) time-averaged model output of the cloud property fields underestimates the ERF, but 3-hourly mean output is sufficiently frequent.

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