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 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 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.

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 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 Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

2016 ◽  
Vol 113 (21) ◽  
pp. 5781-5790 ◽  
Author(s):  
John H. Seinfeld ◽  
Christopher Bretherton ◽  
Kenneth S. Carslaw ◽  
Hugh Coe ◽  
Paul J. DeMott ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Forcing ◽  
General Circulation ◽  
Climate Models ◽  
Large Range ◽  
General Circulation Models ◽  
Radiative Properties ◽  
Aerosol Cloud ◽  
Aerosol Cloud Interactions

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

scholarly journals Untangling causality in midlatitude aerosol–cloud adjustments

2020 ◽  
Vol 20 (7) ◽  
pp. 4085-4103 ◽  
Author(s):  
Daniel T. McCoy ◽  
Paul Field ◽  
Hamish Gordon ◽  
Gregory S. Elsaesser ◽  
Daniel P. Grosvenor
Keyword(s):  
Liquid Water ◽  
Radiative Forcing ◽  
Sensible Heat Flux ◽  
Cloud Droplet ◽  
Causal Link ◽  
Cloud Microphysics ◽  
Liquid Water Path ◽  
Water Path ◽  
Aerosol Cloud ◽  
Causal Pathways

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 the cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path (LWP) averaged across cloudy and clear regions (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 (Multisensor Advanced Climatology of Liquid Water Path) and MODIS are compared to simulations in the Met Office 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 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 Unveiling aerosol–cloud interactions – Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data

2017 ◽  
Vol 17 (21) ◽  
pp. 13165-13185 ◽  
Author(s):  
David Neubauer ◽  
Matthew W. Christensen ◽  
Caroline A. Poulsen ◽  
Ulrike Lohmann
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Liquid Water Path ◽  
Large Variability ◽  
Water Path ◽  
Cloud Albedo ◽  
Aerosol Cloud ◽  
Aerosol Processing ◽  
Wet Scavenging ◽  
Aerosol Cloud Interactions

Abstract. Aerosol–cloud interactions (ACIs) are uncertain and the estimates of the ACI effective radiative forcing (ERFaci) magnitude show a large variability. Within the Aerosol_cci project the susceptibility of cloud properties to changes in aerosol properties is derived from the high-resolution AATSR (Advanced Along-Track Scanning Radiometer) data set using the Cloud–Aerosol Pairing Algorithm (CAPA) (as described in our companion paper) and compared to susceptibilities from the global aerosol climate model ECHAM6-HAM2 and MODIS–CERES (Moderate Resolution Imaging Spectroradiometer – Clouds and the Earth's Radiant Energy System) data. For ECHAM6-HAM2 the dry aerosol is analysed to mimic the effect of CAPA. Furthermore the analysis is done for different environmental regimes. The aerosol–liquid water path relationship in ECHAM6-HAM2 is systematically stronger than in AATSR–CAPA data and cannot be explained by an overestimation of autoconversion when using diagnostic precipitation but rather by aerosol swelling in regions where humidity is high and clouds are present. When aerosol water is removed from the analysis in ECHAM6-HAM2 the strength of the susceptibilities of liquid water path, cloud droplet number concentration and cloud albedo as well as ERFaci agree much better with those of AATSR–CAPA or MODIS–CERES. When comparing satellite-derived to model-derived susceptibilities, this study finds it more appropriate to use dry aerosol in the computation of model susceptibilities. We further find that the statistical relationships inferred from different satellite sensors (AATSR–CAPA vs. MODIS–CERES) as well as from ECHAM6-HAM2 are not always of the same sign for the tested environmental conditions. In particular the susceptibility of the liquid water path is negative in non-raining scenes for MODIS–CERES but positive for AATSR–CAPA and ECHAM6-HAM2. Feedback processes like cloud-top entrainment that are missing or not well represented in the model are therefore not well constrained by satellite observations. In addition to aerosol swelling, wet scavenging and aerosol processing have an impact on liquid water path, cloud albedo and cloud droplet number susceptibilities. Aerosol processing leads to negative liquid water path susceptibilities to changes in aerosol index (AI) in ECHAM6-HAM2, likely due to aerosol-size changes by aerosol processing. Our results indicate that for statistical analysis of aerosol–cloud interactions the unwanted effects of aerosol swelling, wet scavenging and aerosol processing need to be minimised when computing susceptibilities of cloud variables to changes in aerosol.

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.

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