scholarly journals Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hailing Jia ◽  
Xiaoyan Ma ◽  
Fangqun Yu ◽  
Johannes Quaas

AbstractSatellite-based estimates of radiative forcing by aerosol–cloud interactions (RFaci) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from −0.38 to −0.59 W m−2) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RFaci further increases to −1.09 W m−2 when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RFaci, the improved one substantially increases (especially over land), resolving a major difference with models.

2019 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Edward Gryspeerdt ◽  
Marc Salzmann ◽  
Po-Lun Ma ◽  
Sudhakar Dipu ◽  
...  

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.


2019 ◽  
Vol 59 ◽  
pp. 11.1-11.72 ◽  
Author(s):  
Sonia M. Kreidenweis ◽  
Markus Petters ◽  
Ulrike Lohmann

Abstract This chapter reviews the history of the discovery of cloud nuclei and their impacts on cloud microphysics and the climate system. Pioneers including John Aitken, Sir John Mason, Hilding Köhler, Christian Junge, Sean Twomey, and Kenneth Whitby laid the foundations of the field. Through their contributions and those of many others, rapid progress has been made in the last 100 years in understanding the sources, evolution, and composition of the atmospheric aerosol, the interactions of particles with atmospheric water vapor, and cloud microphysical processes. Major breakthroughs in measurement capabilities and in theoretical understanding have elucidated the characteristics of cloud condensation nuclei and ice nucleating particles and the role these play in shaping cloud microphysical properties and the formation of precipitation. Despite these advances, not all their impacts on cloud formation and evolution have been resolved. The resulting radiative forcing on the climate system due to aerosol–cloud interactions remains an unacceptably large uncertainty in future climate projections. Process-level understanding of aerosol–cloud interactions remains insufficient to support technological mitigation strategies such as intentional weather modification or geoengineering to accelerating Earth-system-wide changes in temperature and weather patterns.


2021 ◽  
Author(s):  
Jianhao Zhang ◽  
Paquita Zuidema

Abstract. Many studies examining shortwave-absorbing aerosol-cloud interactions over the southeast Atlantic apply a seasonal averaging. This disregards a meteorology that raises the mean altitude of the smoke layer from July to October. This study details the month-by-month changes in cloud properties and the large-scale environment as a function of the biomass-burning aerosol loading at Ascension Island from July to October, based on measurements from Ascension Island (8º S, 14.5º W), satellite retrievals and reanalysis. In July and August, variability in the smoke loading predominantly occurs in the boundary layer. During both months, the low-cloud fraction is less and is increasingly cumuliform when more smoke is present, with the exception of a late morning boundary layer deepening that encourages a short-lived cloud development. The meteorology varies little, suggesting aerosol-cloud interactions consistent with a boundary-layer semi-direct effect can explain the cloudiness changes. September marks a transition month during which mid-latitude disturbances can intrude into the Atlantic subtropics, constraining the land-based anticyclonic circulation transporting free-tropospheric aerosol to closer to the coast. Stronger boundary layer winds help deepen, dry, and cool the boundary layer near the main stratocumulus deck compared to that on days with high smoke loadings, with stratocumulus reducing everywhere but at the northern deck edge. Longwave cooling rates generated by a sharp water vapor gradient at the aerosol layer top facilitates small-scale vertical mixing, and could help to maintain a better-mixed September free troposphere. The October meteorology is more singularly dependent on the strength of the free-tropospheric winds advecting aerosol offshore. Free-tropospheric aerosol is less, and moisture variability more, compared to September. Low-level clouds increase and are more stratiform, when the smoke loadings are higher. The increased free-tropospheric moisture can help sustain the clouds through reducing evaporative drying during cloud-top entrainment. Enhanced subsidence above the coastal upwelling region increasing cloud droplet number concentrations may further prolong cloud lifetime through microphysical interactions. Reduced subsidence underneath stronger free-tropospheric winds at Ascension supports slightly higher cloud tops during smokier conditions. Overall the monthly changes in the large-scale aerosol and moisture vertical structure act to amplify the seasonal cycle in low-cloud amount and morphology, raising a climate importance as cloudiness changes dominate changes in the top-of-atmosphere radiation budget.


2021 ◽  
Author(s):  
Arshad Nair ◽  
Fangqun Yu ◽  
Pedro Campuzano Jost ◽  
Paul DeMott ◽  
Ezra Levin ◽  
...  

Abstract Cloud condensation nuclei (CCN) are mediators of aerosol–cloud interactions, which contribute to the largest uncertainty in climate change prediction. Here, we present a machine learning/artificial intelligence model that quantifies CCN from variables of aerosol composition, atmospheric trace gases, and meteorology. Comprehensive multi-campaign airborne measurements, covering varied physicochemical regimes in the troposphere, confirm the validity of and help probe the inner workings of this machine learning model: revealing for the first time that different ranges of atmospheric aerosol composition and mass correspond to distinct aerosol number size distributions. Machine learning extracts this information, important for accurate quantification of CCN, additionally from both chemistry and meteorology. This can provide a physicochemically explainable, computationally efficient, robust machine learning pathway in global climate models that only resolve aerosol composition; potentially mitigating the uncertainty of effective radiative forcing due to aerosol–cloud interactions (ERFaci) and improving confidence in assessment of anthropogenic contributions and climate change projections.


2020 ◽  
Vol 20 (10) ◽  
pp. 6225-6241 ◽  
Author(s):  
Alyson Douglas ◽  
Tristan L'Ecuyer

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.


2020 ◽  
Vol 20 (2) ◽  
pp. 995-1020 ◽  
Author(s):  
Yufei Zou ◽  
Yuhang Wang ◽  
Yun Qian ◽  
Hanqin Tian ◽  
Jia Yang ◽  
...  

Abstract. Large wildfires exert strong disturbance on regional and global climate systems and ecosystems by perturbing radiative forcing as well as the carbon and water balance between the atmosphere and land surface, while short- and long-term variations in fire weather, terrestrial ecosystems, and human activity modulate fire intensity and reshape fire regimes. The complex climate–fire–ecosystem interactions were not fully integrated in previous climate model studies, and the resulting effects on the projections of future climate change are not well understood. Here we use the fully interactive REgion-Specific ecosystem feedback Fire model (RESFire) that was developed in the Community Earth System Model (CESM) to investigate these interactions and their impacts on climate systems and fire activity. We designed two sets of decadal simulations using CESM-RESFire for present-day (2001–2010) and future (2051–2060) scenarios, respectively, and conducted a series of sensitivity experiments to assess the effects of individual feedback pathways among climate, fire, and ecosystems. Our implementation of RESFire, which includes online land–atmosphere coupling of fire emissions and fire-induced land cover change (LCC), reproduces the observed aerosol optical depth (AOD) from space-based Moderate Resolution Imaging Spectroradiometer (MODIS) satellite products and ground-based AErosol RObotic NETwork (AERONET) data; it agrees well with carbon budget benchmarks from previous studies. We estimate the global averaged net radiative effect of both fire aerosols and fire-induced LCC at -0.59±0.52 W m−2, which is dominated by fire aerosol–cloud interactions (-0.82±0.19 W m−2), in the present-day scenario under climatological conditions of the 2000s. The fire-related net cooling effect increases by ∼170 % to -1.60±0.27 W m−2 in the 2050s under the conditions of the Representative Concentration Pathway 4.5 (RCP4.5) scenario. Such considerably enhanced radiative effect is attributed to the largely increased global burned area (+19 %) and fire carbon emissions (+100 %) from the 2000s to the 2050s driven by climate change. The net ecosystem exchange (NEE) of carbon between the land and atmosphere components in the simulations increases by 33 % accordingly, implying that biomass burning is an increasing carbon source at short-term timescales in the future. High-latitude regions with prevalent peatlands would be more vulnerable to increased fire threats due to climate change, and the increase in fire aerosols could counter the projected decrease in anthropogenic aerosols due to air pollution control policies in many regions. We also evaluate two distinct feedback mechanisms that are associated with fire aerosols and fire-induced LCC, respectively. On a global scale, the first mechanism imposes positive feedbacks to fire activity through enhanced droughts with suppressed precipitation by fire aerosol–cloud interactions, while the second one manifests as negative feedbacks due to reduced fuel loads by fire consumption and post-fire tree mortality and recovery processes. These two feedback pathways with opposite effects compete at regional to global scales and increase the complexity of climate–fire–ecosystem interactions and their climatic impacts.


2019 ◽  
Author(s):  
Daniel T. McCoy ◽  
Paul Field ◽  
Hamish Gordon ◽  
Gregory S. Elsaesser ◽  
Daniel P. Grosvenor

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.


2020 ◽  
Author(s):  
Takuro Michibata ◽  
Kentaroh Suzuki ◽  
Toshihiko Takemura

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.


2016 ◽  
Vol 113 (21) ◽  
pp. 5812-5819 ◽  
Author(s):  
Graham Feingold ◽  
Allison McComiskey ◽  
Takanobu Yamaguchi ◽  
Jill S. Johnson ◽  
Kenneth S. Carslaw ◽  
...  

The topic of cloud radiative forcing associated with the atmospheric aerosol has been the focus of intense scrutiny for decades. The enormity of the problem is reflected in the need to understand aspects such as aerosol composition, optical properties, cloud condensation, and ice nucleation potential, along with the global distribution of these properties, controlled by emissions, transport, transformation, and sinks. Equally daunting is that clouds themselves are complex, turbulent, microphysical entities and, by their very nature, ephemeral and hard to predict. Atmospheric general circulation models represent aerosol−cloud interactions at ever-increasing levels of detail, but these models lack the resolution to represent clouds and aerosol−cloud interactions adequately. There is a dearth of observational constraints on aerosol−cloud interactions. We develop a conceptual approach to systematically constrain the aerosol−cloud radiative effect in shallow clouds through a combination of routine process modeling and satellite and surface-based shortwave radiation measurements. We heed the call to merge Darwinian and Newtonian strategies by balancing microphysical detail with scaling and emergent properties of the aerosol−cloud radiation system.


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