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Blichner SM, Yli-Juuti T, Mielonen T, Pöhlker C, Holopainen E, Heikkinen L, Mohr C, Artaxo P, Carbone S, Meller BB, Quaresma Dias-Júnior C, Kulmala M, Petäjä T, Scott CE, Svenhag C, Nieradzik L, Sporre M, Partridge DG, Tovazzi E, Virtanen A, Kokkola H, Riipinen I. Process-evaluation of forest aerosol-cloud-climate feedback shows clear evidence from observations and large uncertainty in models. Nat Commun 2024; 15:969. [PMID: 38326341 PMCID: PMC10850362 DOI: 10.1038/s41467-024-45001-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 01/12/2024] [Indexed: 02/09/2024] Open
Abstract
Natural aerosol feedbacks are expected to become more important in the future, as anthropogenic aerosol emissions decrease due to air quality policy. One such feedback is initiated by the increase in biogenic volatile organic compound (BVOC) emissions with higher temperatures, leading to higher secondary organic aerosol (SOA) production and a cooling of the surface via impacts on cloud radiative properties. Motivated by the considerable spread in feedback strength in Earth System Models (ESMs), we here use two long-term observational datasets from boreal and tropical forests, together with satellite data, for a process-based evaluation of the BVOC-aerosol-cloud feedback in four ESMs. The model evaluation shows that the weakest modelled feedback estimates can likely be excluded, but highlights compensating errors making it difficult to draw conclusions of the strongest estimates. Overall, the method of evaluating along process chains shows promise in pin-pointing sources of uncertainty and constraining modelled aerosol feedbacks.
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Affiliation(s)
- Sara M Blichner
- Stockholm University, Department of Environmental Science, Stockholm, SE-106 91, Sweden.
- Stockholm University, Bolin Centre for Climate Research, Stockholm, Sweden.
| | - Taina Yli-Juuti
- University of Eastern Finland, Department of Technical Physics, 70211, Kuopio, Finland
| | - Tero Mielonen
- Finnish Meteorological Institute, Kuopio, FI-70211, Finland
| | - Christopher Pöhlker
- Max Planck Institute for Chemistry, Multiphase Chemistry Dept., 55128, Mainz, Germany
| | - Eemeli Holopainen
- University of Eastern Finland, Department of Technical Physics, 70211, Kuopio, Finland
- Finnish Meteorological Institute, Kuopio, FI-70211, Finland
- Institute for Chemical Engineering Sciences, Foundation for Research and Technology - Hellas (FORTH/ICE-HT), Patras, Greece
| | - Liine Heikkinen
- Stockholm University, Department of Environmental Science, Stockholm, SE-106 91, Sweden
- Stockholm University, Bolin Centre for Climate Research, Stockholm, Sweden
| | - Claudia Mohr
- Stockholm University, Department of Environmental Science, Stockholm, SE-106 91, Sweden
- Stockholm University, Bolin Centre for Climate Research, Stockholm, Sweden
- Department of Environmental System Science, ETH Zurich, Zurich, Switzerland
- Paul Scherrer Institute, Villigen, Switzerland
| | - Paulo Artaxo
- Universidade de Sao Paulo, Instituto de Fisica, 05508-090, Sao Paulo, Brazil
| | - Samara Carbone
- Federal University of Uberlândia, Institute of Agrarian Sciences, Uberlândia, MG, Brazil
| | - Bruno Backes Meller
- Universidade de Sao Paulo, Instituto de Fisica, 05508-090, Sao Paulo, Brazil
| | | | - Markku Kulmala
- University of Helsinki, Institute for Atmospheric and Earth System Research (INAR), Helsinki, Finland
| | - Tuukka Petäjä
- University of Helsinki, Institute for Atmospheric and Earth System Research (INAR), Helsinki, Finland
| | - Catherine E Scott
- University of Leeds, School of Earth and Environment, Leeds, LS2 9JT, UK
| | - Carl Svenhag
- Lund University, Department of Physics, 221-00, Lund, Sweden
| | - Lars Nieradzik
- Lund University, Dept of Physical Geography and Ecosystem Science, 221-00, Lund, Sweden
| | - Moa Sporre
- Lund University, Department of Physics, 221-00, Lund, Sweden
| | - Daniel G Partridge
- University of Exeter, Department of Mathematics and Statistics, Exeter, United Kingdom
| | - Emanuele Tovazzi
- University of Exeter, Department of Mathematics and Statistics, Exeter, United Kingdom
| | - Annele Virtanen
- University of Eastern Finland, Department of Technical Physics, 70211, Kuopio, Finland
| | - Harri Kokkola
- University of Eastern Finland, Department of Technical Physics, 70211, Kuopio, Finland
- Finnish Meteorological Institute, Kuopio, FI-70211, Finland
| | - Ilona Riipinen
- Stockholm University, Department of Environmental Science, Stockholm, SE-106 91, Sweden
- Stockholm University, Bolin Centre for Climate Research, Stockholm, Sweden
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2
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Yuan T, Song H, Wood R, Oreopoulos L, Platnick S, Wang C, Yu H, Meyer K, Wilcox E. Observational evidence of strong forcing from aerosol effect on low cloud coverage. SCIENCE ADVANCES 2023; 9:eadh7716. [PMID: 37939179 DOI: 10.1126/sciadv.adh7716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 10/04/2023] [Indexed: 11/10/2023]
Abstract
Aerosols cool Earth's climate indirectly by increasing low cloud brightness and their coverage (Cf), constituting the aerosol indirect forcing (AIF). The forcing partially offsets the greenhouse warming and positively correlates with the climate sensitivity. However, it remains highly uncertain. Here, we show direct observational evidence for strong forcing from Cf adjustment to increased aerosols and weak forcing from cloud liquid water path adjustment. We estimate that the Cf adjustment drives between 52% and 300% of additional forcing to the Twomey effect over the ocean and a total AIF of -1.1 ± 0.8 W m-2. The Cf adjustment follows a power law as a function of background cloud droplet number concentration, Nd. It thus depends on time and location and is stronger when Nd is low. Cf only increases substantially when background clouds start to drizzle, suggesting a role for aerosol-precipitation interactions. Our findings highlight the Cf adjustment as the key process for reducing the uncertainty of AIF and thus future climate projections.
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Affiliation(s)
- Tianle Yuan
- Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD, USA
- Sciences and Exploration Directorate, Goddard Space Flight Center, Greenbelt, MD, USA
| | - Hua Song
- Sciences and Exploration Directorate, Goddard Space Flight Center, Greenbelt, MD, USA
- SSAI Inc., Lanham, MD, USA
| | - Robert Wood
- Department of Atmospheric Sciences, University of Washington, Seattle, WA, USA
| | - Lazaros Oreopoulos
- Sciences and Exploration Directorate, Goddard Space Flight Center, Greenbelt, MD, USA
| | - Steven Platnick
- Sciences and Exploration Directorate, Goddard Space Flight Center, Greenbelt, MD, USA
| | - Chenxi Wang
- Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD, USA
- Sciences and Exploration Directorate, Goddard Space Flight Center, Greenbelt, MD, USA
| | - Hongbin Yu
- Sciences and Exploration Directorate, Goddard Space Flight Center, Greenbelt, MD, USA
| | - Kerry Meyer
- Sciences and Exploration Directorate, Goddard Space Flight Center, Greenbelt, MD, USA
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3
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Chemyakin E, Stamnes S, Hair J, Burton SP, Bell A, Hostetler C, Ferrare R, Chowdhary J, Moore R, Ziemba L, Crosbie E, Robinson C, Shook M, Thornhill L, Winstead E, Hu Y, van Diedenhoven B, Cairns B. Efficient single-scattering look-up table for lidar and polarimeter water cloud studies. OPTICS LETTERS 2023; 48:13-16. [PMID: 36563362 DOI: 10.1364/ol.474282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 11/18/2022] [Indexed: 06/17/2023]
Abstract
Combined lidar and polarimeter retrievals of aerosol, cloud, and ocean microphysical properties involve single-scattering cloud calculations that are time consuming. We create a look-up table to speed up these calculations for water droplets in the atmosphere. In our new Lorenz-Mie look-up table we tabulate the light scattering by an ensemble of homogeneous isotropic spheres at wavelengths starting from 0.35 µm. The look-up table covers liquid water cloud particles with radii in the range of 0.001-500 µm while gaining an increase of up to 104 in computational speed. The covered complex refractive indices range from 1.25 to 1.36 for the real part and from 0 to 0.001 for the imaginary part. We show that we can precisely compute inherent optical properties for the particle size distributions ranging up to 100 µm for the effective radius and up to 0.6 for the effective variance. We test wavelengths from 0.35 to 2.3 µm and find that the elements of the normalized scattering matrix as well as the asymmetry parameter, the absorption, backscatter, extinction, and scattering coefficients are precise to within 1% for 96.7%-100% of cases depending on the inherent optical property. We also provide an example of using the look-up table with in situ measurements to determine agreement with remote sensing. The table together with C++, Fortran, MATLAB, and Python codes to interpolate the complex refractive index and apply different particle size distributions are freely available online.
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4
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Aerosol effects on clouds are concealed by natural cloud heterogeneity and satellite retrieval errors. Nat Commun 2022; 13:7357. [PMID: 36446763 PMCID: PMC9708656 DOI: 10.1038/s41467-022-34948-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 11/10/2022] [Indexed: 12/02/2022] Open
Abstract
One major source of uncertainty in the cloud-mediated aerosol forcing arises from the magnitude of the cloud liquid water path (LWP) adjustment to aerosol-cloud interactions, which is poorly constrained by observations. Many of the recent satellite-based studies have observed a decreasing LWP as a function of cloud droplet number concentration (CDNC) as the dominating behavior. Estimating the LWP response to the CDNC changes is a complex task since various confounding factors need to be isolated. However, an important aspect has not been sufficiently considered: the propagation of natural spatial variability and errors in satellite retrievals of cloud optical depth and cloud effective radius to estimates of CDNC and LWP. Here we use satellite and simulated measurements to demonstrate that, because of this propagation, even a positive LWP adjustment is likely to be misinterpreted as negative. This biasing effect therefore leads to an underestimate of the aerosol-cloud-climate cooling and must be properly considered in future studies.
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5
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Manshausen P, Watson-Parris D, Christensen MW, Jalkanen JP, Stier P. Invisible ship tracks show large cloud sensitivity to aerosol. Nature 2022; 610:101-106. [PMID: 36198778 PMCID: PMC9534750 DOI: 10.1038/s41586-022-05122-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 07/19/2022] [Indexed: 11/09/2022]
Abstract
Cloud reflectivity is sensitive to atmospheric aerosol concentrations because aerosols provide the condensation nuclei on which water condenses1. Increased aerosol concentrations due to human activity affect droplet number concentration, liquid water and cloud fraction2, but these changes are subject to large uncertainties3. Ship tracks, long lines of polluted clouds that are visible in satellite images, are one of the main tools for quantifying aerosol-cloud interactions4. However, only a small fraction of the clouds polluted by shipping show ship tracks5,6. Here we show that even when no ship tracks are visible in satellite images, aerosol emissions change cloud properties substantially. We develop a new method to quantify the effect of shipping on all clouds, showing a cloud droplet number increase and a more positive liquid water response when there are no visible tracks. We directly detect shipping-induced cloud property changes in the trade cumulus regions of the Atlantic, which are known to display almost no visible tracks. Our results indicate that previous studies of ship tracks were suffering from selection biases by focusing only on visible tracks from satellite imagery. The strong liquid water path response we find translates to a larger aerosol cooling effect on the climate, potentially masking a higher climate sensitivity than observed temperature trends would otherwise suggest.
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Affiliation(s)
- Peter Manshausen
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK.
| | - Duncan Watson-Parris
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
| | | | | | - Philip Stier
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, UK
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6
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Zhang Z, Oreopoulos L, Lebsock MD, Mechem DB, Covert J. Understanding the Microphysical Control and Spatial-Temporal Variability of Warm Rain Probability Using CloudSat and MODIS Observations. GEOPHYSICAL RESEARCH LETTERS 2022; 49:e2022GL098863. [PMID: 35864819 PMCID: PMC9286621 DOI: 10.1029/2022gl098863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/22/2022] [Accepted: 05/06/2022] [Indexed: 06/15/2023]
Abstract
By combining measurements from MODIS and the CloudSat radar, we develop a parameterization scheme to quantify the combined microphysical controls by liquid water path (LWP) and cloud droplet number concentration (CDNC) of the probability of precipitation (PoP) in marine low cloud over tropical oceans. We demonstrate that the spatial-temporal variation of grid-mean in-cloud <PoP> can be largely explained by the variation of the joint probability density function of LWP and CDNC in the phase space specified by the bivariate PoP (LWP and CDNC) function. Through a series of sensitivity tests guided by this understanding, we find that in the Southeastern Pacific and Atlantic the stratocumulus to cumulus transition of the <PoP> is mainly due to the variation of CDNC while the annual cycle is mainly due to the variation of LWP. The results of this study provide a viable way to diagnose the root cause of warm rain problems in global climate models.
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Affiliation(s)
- Zhibo Zhang
- Physics DepartmentUMBCBaltimoreMDUSA
- Goddard Earth Sciences Technology and Research IIUMBCBaltimoreMDUSA
| | - Lazaros Oreopoulos
- Climate and Radiation LaboratoryNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Matthew D. Lebsock
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - David B. Mechem
- Department of Geography & Atmospheric ScienceUniversity of KansasLawrenceKSUSA
| | - Justin Covert
- Department of Geography & Atmospheric ScienceUniversity of KansasLawrenceKSUSA
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7
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Mansour K, Rinaldi M, Preißler J, Decesari S, Ovadnevaite J, Ceburnis D, Paglione M, Facchini MC, O'Dowd C. Phytoplankton Impact on Marine Cloud Microphysical Properties Over the Northeast Atlantic Ocean. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2022; 127:e2021JD036355. [PMID: 35860437 PMCID: PMC9285769 DOI: 10.1029/2021jd036355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 04/26/2022] [Accepted: 04/30/2022] [Indexed: 05/11/2023]
Abstract
The current understanding of the impact of natural cloud condensation nuclei (CCN) variability on cloud properties in marine air is low, thus contributing to climate prediction uncertainty. By analyzing cloud remote sensing observations (2009-2015) at Mace Head (west coast of Ireland), we show the oceanic biota impact on the microphysical properties of stratiform clouds over the Northeast Atlantic Ocean. During spring to summer (seasons of enhanced oceanic biological activity), clouds typically host a higher number of smaller droplets resulting from increased aerosol number concentration in the CCN relevant-size range. The induced increase in cloud droplet number concentration (+100%) and decrease in their radius (-14%) are comparable in magnitude to that generated by the advection of anthropogenically influenced air masses over the background marine boundary layer. Cloud water content and albedo respond to marine CCN perturbations with positive adjustments, making clouds brighter as the number of droplets increases. Cloud susceptibility to marine aerosols overlaps with a large variability of cloud macrophysical and optical properties primarily affected by the meteorological conditions. The above findings suggest the existence of a potential feedback mechanism between marine biota and the marine cloud-climate system.
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Affiliation(s)
- Karam Mansour
- Italian National Research Council ‐ Institute of Atmospheric Sciences and Climate (CNR‐ISAC)BolognaItaly
- Oceanography Department, Faculty of ScienceAlexandria UniversityAlexandriaEgypt
| | - Matteo Rinaldi
- Italian National Research Council ‐ Institute of Atmospheric Sciences and Climate (CNR‐ISAC)BolognaItaly
| | | | - Stefano Decesari
- Italian National Research Council ‐ Institute of Atmospheric Sciences and Climate (CNR‐ISAC)BolognaItaly
| | - Jurgita Ovadnevaite
- School of PhysicsRyan Institute's Centre for Climate and Air Pollution StudiesNational University of Ireland GalwayGalwayIreland
| | - Darius Ceburnis
- School of PhysicsRyan Institute's Centre for Climate and Air Pollution StudiesNational University of Ireland GalwayGalwayIreland
| | - Marco Paglione
- Italian National Research Council ‐ Institute of Atmospheric Sciences and Climate (CNR‐ISAC)BolognaItaly
| | - Maria C. Facchini
- Italian National Research Council ‐ Institute of Atmospheric Sciences and Climate (CNR‐ISAC)BolognaItaly
| | - Colin O'Dowd
- School of PhysicsRyan Institute's Centre for Climate and Air Pollution StudiesNational University of Ireland GalwayGalwayIreland
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8
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Machine-Learning Based Analysis of Liquid Water Path Adjustments to Aerosol Perturbations in Marine Boundary Layer Clouds Using Satellite Observations. ATMOSPHERE 2022. [DOI: 10.3390/atmos13040586] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Changes in marine boundary layer cloud (MBLC) radiative properties in response to aerosol perturbations are largely responsible for uncertainties in future climate predictions. In particular, the relationship between the cloud droplet number concentration (Nd, a proxy for aerosol) and the cloud liquid water path (LWP) remains challenging to quantify from observations. In this study, satellite observations from multiple polar-orbiting platforms for 2006–2011 are used in combination with atmospheric reanalysis data in a regional machine learning model to predict changes in LWP in MBLCs in the Southeast Atlantic. The impact of predictor variables on the model output is analysed using Shapley values as a technique of explainable machine learning. Within the machine learning model, precipitation fraction, cloud top height, and Nd are identified as important cloud state predictors for LWP, with dynamical proxies and sea surface temperature (SST) being the most important environmental predictors. A positive nonlinear relationship between LWP and Nd is found, with a weaker sensitivity at high cloud droplet concentrations. This relationship is found to be dependent on other predictors in the model: Nd–LWP sensitivity is higher in precipitating clouds and decreases with increasing SSTs.
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9
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Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol-cloud interaction. Proc Natl Acad Sci U S A 2022; 119:e2110756119. [PMID: 35235447 PMCID: PMC8915832 DOI: 10.1073/pnas.2110756119] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Aerosol–cloud interaction affects the cooling of Earth’s climate, mostly by activation of aerosols as cloud condensation nuclei that can increase the amount of sunlight reflected back to space. But the controlling physical processes remain uncertain in current climate models. We present a lidar-based technique as a unique remote-sensing tool without thermodynamic assumptions for simultaneously profiling diurnal aerosol and water cloud properties with high resolution. Direct lateral observations of cloud properties show that the vertical structure of low-level water clouds can be far from being perfectly adiabatic. Furthermore, our analysis reveals that, instead of an increase of liquid water path (LWP) as proposed by most general circulation models, elevated aerosol loading can cause a net decrease in LWP. Aerosol–cloud interaction (ACI) is complex and difficult to be well represented in current climate models. Progress on understanding ACI processes, such as the influence of aerosols on water cloud droplet formation, is hampered by inadequate observational capability. Hitherto, high-resolution and simultaneous observations of diurnal aerosol loading and cloud microphysical properties are challenging for current remote-sensing techniques. To overcome this conundrum, we introduce the dual-field-of-view (FOV) high-spectral-resolution lidar (HSRL) for simultaneously profiling aerosol and water cloud properties, especially water cloud microphysical properties. Continuous observations of aerosols and clouds using this instrument, verified by the Monte Carlo simulation and coincident observations of other techniques, were conducted to investigate the interactions between aerosol loading and water cloud microphysical properties. A case study over Beijing highlights the scientific potential of dual-FOV HSRL to become a significant contributor to the ACI investigations. The observed water cloud profiles identify that due to air entrainment its vertical structure is not perfectly adiabatic, as assumed by many current retrieval methods. Our ACI analysis shows increased aerosol loading led to increased droplet number concentration and decreased droplet effective radius—consistent with expectations—but had no discernible increase on liquid water path. This finding supports the hypothesis that aerosol-induced cloud water increase caused by suppressed rain formation can be canceled out by enhanced evaporation. Thus, these observations obtained from the dual-FOV HSRL constitute substantial and significant additions to understanding ACI process. This technique is expected to represent a significant step forward in characterizing ACI.
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10
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Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments. ATMOSPHERE 2022. [DOI: 10.3390/atmos13030370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Predicting the onset times of precipitation over densely populated cities for the purposes of timely evacuation is a challenge. This paper explored a flooding event over an urban built environment in a South Asian mega city, Chennai, where extant urban planning models rely on predicted rainwater amounts for early warning and impact assessment studies. However, the time duration of flooding events is related to the nature of the urban sprawl in the built environment. Any evacuation measure is invariably tied down to the time duration over which the precipitation event occurs, and therefore to the expected time of a precipitation event to begin. In this context, a crucial parameter useful to municipal authorities is the onset time of precipitation. This study used optimised analytical formulations to predict this time, and the derived analytical expressions for the case study yielded comparable times estimated from a computer-intensive full-scale large eddy model within an accuracy of 2%. It is suggested that municipal authorities (who are non-experts in fluid mechanics) use this early prediction for the purposes of quick alerts to a congested city’s most vulnerable citizens within urban sprawls. However, for the procedure to work at its best, it involves a two-stage procedure. The first step involves the use of a parcel model to obtain the expected cloud droplet spectral spreads based on the prevailing dynamical characterisations. The second step involves an optimisation procedure involving cloud spectral properties from the first step to quantify both the auto-conversion rates and the threshold. Thereafter, an onset time calculation based on cloud properties is estimated. These new results are cast in closed form for easy incorporation into meteorological applications over a variety of urban scales. Rain mass amounts were also predicted analytically and used to configure Aeronautical Reconnaissance Coverage Geographic Information System (ARCGIS) to compute low drainage flow rates over the vulnerable parts of Chennai city. It was found that heavy precipitation over the North Chennai region yielded discharge rates to the tune of ~250 m3s−1 during a 24 h period, causing intense flooding in the low-lying areas around the Cooum River basin with a large population density, with estimates sufficiently corroborating observations.
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11
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Christensen MW, Gettelman A, Cermak J, Dagan G, Diamond M, Douglas A, Feingold G, Glassmeier F, Goren T, Grosvenor DP, Gryspeerdt E, Kahn R, Li Z, Ma PL, Malavelle F, McCoy IL, McCoy DT, McFarquhar G, Mülmenstädt J, Pal S, Possner A, Povey A, Quaas J, Rosenfeld D, Schmidt A, Schrödner R, Sorooshian A, Stier P, Toll V, Watson-Parris D, Wood R, Yang M, Yuan T. Opportunistic experiments to constrain aerosol effective radiative forcing. ATMOSPHERIC CHEMISTRY AND PHYSICS 2022; 22:641-674. [PMID: 35136405 PMCID: PMC8819675 DOI: 10.5194/acp-22-641-2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Aerosol-cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide "opportunistic experiments" (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.
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Affiliation(s)
- Matthew W. Christensen
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, OX1 3PU, UK
- Atmospheric Science & Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99354, Washington, USA
| | | | - Jan Cermak
- Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research, Karlsruhe, Germany
- Karlsruhe Institute of Technology (KIT), Institute of Photogrammetry and Remote Sensing, Karlsruhe, Germany
| | - Guy Dagan
- Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Michael Diamond
- Department of Atmospheric Sciences, University of Washington, Seattle, USA
- NOAA Chemical Sciences Laboratory (CSL), Boulder, Colorado, USA
- Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Colorado, USA
| | - Alyson Douglas
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, OX1 3PU, UK
| | - Graham Feingold
- NOAA Chemical Sciences Laboratory (CSL), Boulder, Colorado, USA
| | - Franziska Glassmeier
- Department Geoscience and Remote Sensing, Delft University of Technology, P.O. Box 5048, 2600GA Delft, the Netherlands
| | - Tom Goren
- Institute for Meteorology, Universität Leipzig, Leipzig, Germany
| | - Daniel P. Grosvenor
- National Centre for Atmospheric Sciences, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
| | - Edward Gryspeerdt
- Space and Atmospheric Physics Group, Imperial College London, London, UK
| | - Ralph Kahn
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Zhanqing Li
- Department of Atmospheric and Oceanic Science, University of Maryland, College Park, USA
| | - Po-Lun Ma
- Atmospheric Science & Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99354, Washington, USA
| | - Florent Malavelle
- Met Office, Atmospheric Dispersion and Air Quality, Fitzroy Rd, Exeter, EX1 3PB, UK
| | - Isabel L. McCoy
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, USA
- Cooperative Programs for the Advancement of Earth System Science (CPAESS), University Corporation for Atmospheric Research, Boulder, CO, USA
| | - Daniel T. McCoy
- Department of Atmospheric Sciences, University of Wyoming, Laramie, USA
| | - Greg McFarquhar
- Cooperative Institute for Severe and High Impact Weather Research and Operations (CIWRO) and School of Meteorology, University of Oklahoma, Norman, OK, USA
- School of Meteorology, University of Oklahoma, Norman, OK, USA
| | - Johannes Mülmenstädt
- Atmospheric Science & Global Change Division, Pacific Northwest National Laboratory, Richland, WA 99354, Washington, USA
| | - Sandip Pal
- Department of Geosciences, Texas Tech University, Lubbock, TX, USA
| | - Anna Possner
- Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Adam Povey
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, OX1 3PU, UK
- National Centre for Earth Observation, University of Oxford, Oxford, OX1 3PU, UK
| | - Johannes Quaas
- Institute for Meteorology, Universität Leipzig, Leipzig, Germany
| | - Daniel Rosenfeld
- Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Anja Schmidt
- Department of Geography, University of Cambridge, Cambridge, UK
- Department of Chemistry, University of Cambridge, Cambridge, UK
| | | | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - Philip Stier
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, OX1 3PU, UK
| | - Velle Toll
- Institute of Physics, University of Tartu, Tartu, Estonia
| | - Duncan Watson-Parris
- Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, Oxford, OX1 3PU, UK
| | - Robert Wood
- Department of Atmospheric Sciences, University of Washington, Seattle, USA
| | - Mingxi Yang
- Plymouth Marine Laboratory, Prospect Place, Plymouth, PL1 3DH, UK
| | - Tianle Yuan
- Joint Center for Earth Systems Technologies, University of Maryland, Baltimore County, Baltimore, MD, USA
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
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12
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Dadashazar H, Painemal D, Alipanah M, Brunke M, Chellappan S, Corral AF, Crosbie E, Kirschler S, Liu H, Moore RH, Robinson C, Scarino AJ, Shook M, Sinclair K, Thornhill KL, Voigt C, Wang H, Winstead E, Zeng X, Ziemba L, Zuidema P, Sorooshian A. Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors. ATMOSPHERIC CHEMISTRY AND PHYSICS 2021; 21:10499-10526. [PMID: 34377145 PMCID: PMC8350960 DOI: 10.5194/acp-21-10499-2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Cloud drop number concentrations (N d) over the western North Atlantic Ocean (WNAO) are generally highest during the winter (DJF) and lowest in summer (JJA), in contrast to aerosol proxy variables (aerosol optical depth, aerosol index, surface aerosol mass concentrations, surface cloud condensation nuclei (CCN) concentrations) that generally peak in spring (MAM) and JJA with minima in DJF. Using aircraft, satellite remote sensing, ground-based in situ measurement data, and reanalysis data, we characterize factors explaining the divergent seasonal cycles and furthermore probe into factors influencing N d on seasonal timescales. The results can be summarized well by features most pronounced in DJF, including features associated with cold-air outbreak (CAO) conditions such as enhanced values of CAO index, planetary boundary layer height (PBLH), low-level liquid cloud fraction, and cloud-top height, in addition to winds aligned with continental outflow. Data sorted into high- and low-N d days in each season, especially in DJF, revealed that all of these conditions were enhanced on the high-N d days, including reduced sea level pressure and stronger wind speeds. Although aerosols may be more abundant in MAM and JJA, the conditions needed to activate those particles into cloud droplets are weaker than in colder months, which is demonstrated by calculations of the strongest (weakest) aerosol indirect effects in DJF (JJA) based on comparing N d to perturbations in four different aerosol proxy variables (total and sulfate aerosol optical depth, aerosol index, surface mass concentration of sulfate). We used three machine learning models and up to 14 input variables to infer about most influential factors related to N d for DJF and JJA, with the best performance obtained with gradient-boosted regression tree (GBRT) analysis. The model results indicated that cloud fraction was the most important input variable, followed by some combination (depending on season) of CAO index and surface mass concentrations of sulfate and organic carbon. Future work is recommended to further understand aspects uncovered here such as impacts of free tropospheric aerosol entrainment on clouds, degree of boundary layer coupling, wet scavenging, and giant CCN effects on aerosol-N d relationships, updraft velocity, and vertical structure of cloud properties such as adiabaticity that impact the satellite estimation of N d.
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Affiliation(s)
- Hossein Dadashazar
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - David Painemal
- NASA Langley Research Center, Hampton, VA, USA
- Science Systems and Applications, Inc., Hampton, VA, USA
| | - Majid Alipanah
- Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA
| | - Michael Brunke
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - Seethala Chellappan
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, USA
| | - Andrea F. Corral
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Ewan Crosbie
- NASA Langley Research Center, Hampton, VA, USA
- Science Systems and Applications, Inc., Hampton, VA, USA
| | - Simon Kirschler
- Institute of Atmospheric Physics, German Aerospace Center, Oberpfaffenhofen, Germany
| | - Hongyu Liu
- National Institute of Aerospace, Hampton, VA, USA
| | | | - Claire Robinson
- NASA Langley Research Center, Hampton, VA, USA
- Science Systems and Applications, Inc., Hampton, VA, USA
| | - Amy Jo Scarino
- NASA Langley Research Center, Hampton, VA, USA
- Science Systems and Applications, Inc., Hampton, VA, USA
| | | | - Kenneth Sinclair
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Universities Space Research Association, Columbia, MD, USA
| | | | - Christiane Voigt
- Institute of Atmospheric Physics, German Aerospace Center, Oberpfaffenhofen, Germany
| | - Hailong Wang
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Edward Winstead
- NASA Langley Research Center, Hampton, VA, USA
- Science Systems and Applications, Inc., Hampton, VA, USA
| | - Xubin Zeng
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - Luke Ziemba
- NASA Langley Research Center, Hampton, VA, USA
| | - Paquita Zuidema
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, USA
| | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
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13
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Jia H, Ma X, Yu F, Quaas J. Significant underestimation of radiative forcing by aerosol-cloud interactions derived from satellite-based methods. Nat Commun 2021; 12:3649. [PMID: 34131118 PMCID: PMC8206093 DOI: 10.1038/s41467-021-23888-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 05/17/2021] [Indexed: 02/05/2023] Open
Abstract
Satellite-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.
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Affiliation(s)
- Hailing Jia
- grid.260478.fCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, and Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China ,grid.265850.c0000 0001 2151 7947Atmospheric Sciences Research Center, University at Albany, Albany, NY USA ,grid.9647.c0000 0004 7669 9786Institute for Meteorology, Universität Leipzig, Leipzig, Germany
| | - Xiaoyan Ma
- grid.260478.fCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, and Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China
| | - Fangqun Yu
- grid.265850.c0000 0001 2151 7947Atmospheric Sciences Research Center, University at Albany, Albany, NY USA
| | - Johannes Quaas
- grid.9647.c0000 0004 7669 9786Institute for Meteorology, Universität Leipzig, Leipzig, Germany
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14
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Aldhaif AM, Lopez DH, Dadashazar H, Painemal D, Peters AJ, Sorooshian A. An Aerosol Climatology and Implications for Clouds at a Remote Marine Site: Case Study Over Bermuda. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2021; 126:e2020JD034038. [PMID: 34159044 PMCID: PMC8216143 DOI: 10.1029/2020jd034038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 02/12/2021] [Indexed: 06/13/2023]
Abstract
Aerosol characteristics and aerosol-cloud interactions remain uncertain in remote marine regions. We use over a decade of data (2000-2012) from the NASA AErosol RObotic NETwork, aerosol and wet deposition samples, satellite remote sensors, and models to examine aerosol and cloud droplet number characteristics at a representative open ocean site (Bermuda) over the Western North Atlantic Ocean (WNAO). Annual mean values were as follows: aerosol optical depth (AOD) = 0.12, Ångström Exponent (440/870 nm) = 0.95, fine mode fraction = 0.51, asymmetry factor = 0.72 (440 nm) and 0.68 (1020 nm), and Aqua-MODIS cloud droplet number concentrations = 51.3 cm-3. The winter season (December-February) was characterized by high sea salt optical thickness and the highest aerosol extinction in the lowest 2 km. Extensive precipitation over the WNAO in winter helps contribute to the low FMFs in winter (~0.40-0.50) even though air trajectories often originate over North America. Spring and summer had more pronounced influence from sulfate, dust, organic carbon, and black carbon. Volume size distributions were bimodal with a dominant coarse mode (effective radii: 1.85-2.09 μm) and less pronounced fine mode (0.14-0.16 μm), with variability in the coarse mode likely due to different characteristic sizes for transported dust (smaller) versus regional sea salt (larger). Extreme pollution events highlight the sensitivity of this site to long-range transport of urban emissions, dust, and smoke. Differing annual cycles are identified between AOD and cloud droplet number concentrations, motivating a deeper look into aerosol-cloud interactions at this site.
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Affiliation(s)
- Abdulmonam M Aldhaif
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - David H Lopez
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Hossein Dadashazar
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - David Painemal
- Science Systems and Applications, Inc., Hampton, VA, USA
- NASA Langley Research Center, Hampton, VA, USA
| | | | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
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15
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Sensitivity of Multispectral Imager Liquid Water Cloud Microphysical Retrievals to the Index of Refraction. REMOTE SENSING 2020. [DOI: 10.3390/rs12244165] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
A cloud property retrieved from multispectral imagers having spectral channels in the shortwave infrared (SWIR) and/or midwave infrared (MWIR) is the cloud effective particle radius (CER), a radiatively relevant weighting of the cloud particle size distribution. The physical basis of the CER retrieval is the dependence of SWIR/MWIR cloud reflectance on the cloud particle single scattering albedo, which in turn depends on the complex index of refraction of bulk liquid water (or ice) in addition to the cloud particle size. There is a general consistency in the choice of the liquid water index of refraction by the cloud remote sensing community, largely due to the few available independent datasets and compilations. Here we examine the sensitivity of CER retrievals to the available laboratory index of refraction datasets in the SWIR and MWIR using the retrieval software package that produces NASA’s standard Moderate Resolution Imaging Spectroradiometer (MODIS)/Visible Infrared Imaging Radiometer suite (VIIRS) continuity cloud products. The sensitivity study incorporates two laboratory index of refraction datasets that include measurements at supercooled water temperatures, one in the SWIR and one in the MWIR. Neither has been broadly utilized in the cloud remote sensing community. It is shown that these two new datasets can significantly change CER retrievals (e.g., 1–2 µm) relative to common datasets used by the community. Further, index of refraction data for a 265 K water temperature gives more consistent retrievals between the two spectrally distinct 2.2 µm atmospheric window channels on MODIS and VIIRS. As a result, 265 K values from the SWIR and MWIR index of refraction datasets were adopted for use in the production version of the continuity cloud product. The results indicate the need to better understand temperature-dependent bulk water absorption and uncertainties in these spectral regions.
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16
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Jose S, Nair VS, Babu SS. Anthropogenic emissions from South Asia reverses the aerosol indirect effect over the northern Indian Ocean. Sci Rep 2020; 10:18360. [PMID: 33110106 PMCID: PMC7591568 DOI: 10.1038/s41598-020-74897-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 09/04/2020] [Indexed: 11/19/2022] Open
Abstract
Atmospheric aerosols play an important role in the formation of warm clouds by acting as efficient cloud condensation nuclei (CCN) and their interactions are believed to cool the Earth-Atmosphere system (‘first indirect effect or Twomey effect’) in a highly uncertain manner compared to the other forcing agents. Here we demonstrate using long-term (2003–2016) satellite observations (NASA’s A-train satellite constellations) over the northern Indian Ocean, that enhanced aerosol loading (due to anthropogenic emissions) can reverse the first indirect effect significantly. In contrast to Twomey effect, a statistically significant increase in cloud effective radius (CER, µm) is observed with respect to an increase in aerosol loading for clouds having low liquid water path (LWP < 75 g m−2) and drier cloud tops. Probable physical mechanisms for this effect are the intense competition for available water vapour due to higher concentrations of anthropogenic aerosols and entrainment of dry air on cloud tops. For such clouds, cloud water content showed a negative response to cloud droplet number concentrations and the estimated intrinsic radiative effect suggest a warming at the Top of the Atmosphere. Although uncertainties exist in quantifying aerosol-cloud interactions (ACI) using satellite observations, present study indicates the physical existence of anti-Twomey effect over the northern Indian Ocean during south Asian outflow.
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Affiliation(s)
- Subin Jose
- Space Physics Laboratory, Vikram Sarabhai Space Centre, Trivandrum, India.
| | - Vijayakumar S Nair
- Space Physics Laboratory, Vikram Sarabhai Space Centre, Trivandrum, India
| | - S Suresh Babu
- Space Physics Laboratory, Vikram Sarabhai Space Centre, Trivandrum, India
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17
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McCoy IL, McCoy DT, Wood R, Regayre L, Watson-Parris D, Grosvenor DP, Mulcahy JP, Hu Y, Bender FAM, Field PR, Carslaw KS, Gordon H. The hemispheric contrast in cloud microphysical properties constrains aerosol forcing. Proc Natl Acad Sci U S A 2020; 117:18998-19006. [PMID: 32719114 PMCID: PMC7431023 DOI: 10.1073/pnas.1922502117] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
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-3 and 24 cm-3 By extension, the radiative forcing since 1850 from aerosol-cloud interactions is constrained to be -1.2 W⋅m-2 to -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.
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Affiliation(s)
- Isabel L McCoy
- Atmospheric Sciences Department, University of Washington, Seattle, WA 98105;
| | - Daniel T McCoy
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, LS2 9JT Leeds, United Kingdom
| | - Robert Wood
- Atmospheric Sciences Department, University of Washington, Seattle, WA 98105
| | - Leighton Regayre
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, LS2 9JT Leeds, United Kingdom
| | | | - Daniel P Grosvenor
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, LS2 9JT Leeds, United Kingdom
- National Center for Atmospheric Science, University of Leeds, LS2 9JT Leeds, United Kingdom
| | | | - Yongxiang Hu
- Atmospheric Composition Branch, NASA Langley Research Center, Hampton, VA 23681
| | - Frida A-M Bender
- Department of Meteorology, Stockholm University, SE-106 91 Stockholm, Sweden
- Bolin Centre for Climate Research, Stockholm University, SE-106 91 Stockholm, Sweden
| | - Paul R Field
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, LS2 9JT Leeds, United Kingdom
- Met Office, Exeter EX1 3PB, United Kingdom
| | - Kenneth S Carslaw
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, LS2 9JT Leeds, United Kingdom
| | - Hamish Gordon
- Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, LS2 9JT Leeds, United Kingdom
- College of Engineering, Carnegie-Mellon University, Pittsburgh, PA 15213
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18
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Morrison H, van Lier‐Walqui M, Fridlind AM, Grabowski WW, Harrington JY, Hoose C, Korolev A, Kumjian MR, Milbrandt JA, Pawlowska H, Posselt DJ, Prat OP, Reimel KJ, Shima S, van Diedenhoven B, Xue L. Confronting the Challenge of Modeling Cloud and Precipitation Microphysics. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2020; 12:e2019MS001689. [PMID: 32999700 PMCID: PMC7507216 DOI: 10.1029/2019ms001689] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 05/03/2020] [Accepted: 05/05/2020] [Indexed: 06/11/2023]
Abstract
In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.
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Affiliation(s)
- Hugh Morrison
- National Center for Atmospheric ResearchBoulderCOUSA
| | - Marcus van Lier‐Walqui
- NASA Goddard Institute for Space Studies and Center for Climate Systems ResearchColumbia UniversityNew YorkNYUSA
| | | | | | - Jerry Y. Harrington
- Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Corinna Hoose
- Institute of Meteorology and Climate ResearchKarlsruhe Institute of TechnologyKarlsruheGermany
| | - Alexei Korolev
- Observation Based Research SectionEnvironment and Climate Change CanadaTorontoOntarioCanada
| | - Matthew R. Kumjian
- Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Jason A. Milbrandt
- Atmospheric Numerical Prediction ResearchEnvironment and Climate Change CanadaDorvalQuebecCanada
| | - Hanna Pawlowska
- Institute of Geophysics, Faculty of PhysicsUniversity of WarsawWarsawPoland
| | - Derek J. Posselt
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - Olivier P. Prat
- North Carolina Institute for Climate StudiesNorth Carolina State UniversityAshevilleNCUSA
| | - Karly J. Reimel
- Department of Meteorology and Atmospheric ScienceThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Shin‐Ichiro Shima
- University of Hyogo and RIKEN Center for Computational ScienceKobeJapan
| | - Bastiaan van Diedenhoven
- NASA Goddard Institute for Space Studies and Center for Climate Systems ResearchColumbia UniversityNew YorkNYUSA
| | - Lulin Xue
- National Center for Atmospheric ResearchBoulderCOUSA
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19
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Christensen MW, Jones WK, Stier P. Aerosols enhance cloud lifetime and brightness along the stratus-to-cumulus transition. Proc Natl Acad Sci U S A 2020; 117:17591-17598. [PMID: 32661149 PMCID: PMC7395436 DOI: 10.1073/pnas.1921231117] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Anthropogenic aerosols are hypothesized to enhance planetary albedo and offset some of the warming due to the buildup of greenhouse gases in Earth's atmosphere. Aerosols can enhance the coverage, reflectance, and lifetime of warm low-level clouds. However, the relationship between cloud lifetime and aerosol concentration has been challenging to measure from polar orbiting satellites. We estimate two timescales relating to the formation and persistence of low-level clouds over [Formula: see text] spatial domains using multiple years of geostationary satellite observations provided by the Clouds and Earth's Radiant Energy System (CERES) Synoptic (SYN) product. Lagrangian trajectories spanning several days along the classic stratus-to-cumulus transition zone are stratified by aerosol optical depth and meteorology. Clouds forming in relatively polluted trajectories tend to have lighter precipitation rates, longer average lifetime, and higher cloud albedo and cloud fraction compared with unpolluted trajectories. While liquid water path differences are found to be negligible, we find direct evidence of increased planetary albedo primarily through increased drop concentration ([Formula: see text]) and cloud fraction, with the caveat that the aerosol influence on cloud fraction is positive only for stable atmospheric conditions. While the increase in cloud fraction can be large typically in the beginning of trajectories, the Twomey effect accounts for the bulk (roughly 3/4) of the total aerosol indirect radiative forcing estimate.
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Affiliation(s)
- Matthew W Christensen
- Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford OX1 3PU, United Kingdom
| | - William K Jones
- Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford OX1 3PU, United Kingdom
| | - Philip Stier
- Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford OX1 3PU, United Kingdom
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20
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MacDonald AB, Hossein Mardi A, Dadashazar H, Azadi Aghdam M, Crosbie E, Jonsson HH, Flagan RC, Seinfeld JH, Sorooshian A. On the relationship between cloud water composition and cloud droplet number concentration. ATMOSPHERIC CHEMISTRY AND PHYSICS 2020; 20:7645-7665. [PMID: 33273899 PMCID: PMC7709908 DOI: 10.5194/acp-20-7645-2020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Aerosol-cloud interactions are the largest source of uncertainty in quantifying anthropogenic radiative forcing. The large uncertainty is, in part, due to the difficulty of predicting cloud microphysical parameters, such as the cloud droplet number concentration (N d). Even though rigorous first-principle approaches exist to calculate N d, the cloud and aerosol research community also relies on empirical approaches such as relating N d to aerosol mass concentration. Here we analyze relationships between N d and cloud water chemical composition, in addition to the effect of environmental factors on the degree of the relationships. Warm, marine, stratocumulus clouds off the California coast were sampled throughout four summer campaigns between 2011 and 2016. A total of 385 cloud water samples were collected and analyzed for 80 chemical species. Single- and multispecies log-log linear regressions were performed to predict N d using chemical composition. Single-species regressions reveal that the species that best predicts N d is total sulfate (R adj 2 = 0.40 ). Multispecies regressions reveal that adding more species does not necessarily produce a better model, as six or more species yield regressions that are statistically insignificant. A commonality among the multispecies regressions that produce the highest correlation with N d was that most included sulfate (either total or non-sea-salt), an ocean emissions tracer (such as sodium), and an organic tracer (such as oxalate). Binning the data according to turbulence, smoke influence, and in-cloud height allowed for examination of the effect of these environmental factors on the composition-N d correlation. Accounting for turbulence, quantified as the standard deviation of vertical wind speed, showed that the correlation between N d with both total sulfate and sodium increased at higher turbulence conditions, consistent with turbulence promoting the mixing between ocean surface and cloud base. Considering the influence of smoke significantly improved the correlation with N d for two biomass burning tracer species in the study region, specifically oxalate and iron. When binning by in-cloud height, non-sea-salt sulfate and sodium correlated best with N d at cloud top, whereas iron and oxalate correlated best with N d at cloud base.
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Affiliation(s)
- Alexander B. MacDonald
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Ali Hossein Mardi
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Hossein Dadashazar
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Mojtaba Azadi Aghdam
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Ewan Crosbie
- Science Systems and Applications, Inc., Hampton, VA, USA
- NASA Langley Research Center, Hampton, VA, USA
| | | | - Richard C. Flagan
- Department of Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - John H. Seinfeld
- Department of Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
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21
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Bellouin N, Quaas J, Gryspeerdt E, Kinne S, Stier P, Watson‐Parris D, Boucher O, Carslaw KS, Christensen M, Daniau A, Dufresne J, Feingold G, Fiedler S, Forster P, Gettelman A, Haywood JM, Lohmann U, Malavelle F, Mauritsen T, McCoy DT, Myhre G, Mülmenstädt J, Neubauer D, Possner A, Rugenstein M, Sato Y, Schulz M, Schwartz SE, Sourdeval O, Storelvmo T, Toll V, Winker D, Stevens B. Bounding Global Aerosol Radiative Forcing of Climate Change. REVIEWS OF GEOPHYSICS (WASHINGTON, D.C. : 1985) 2020; 58:e2019RG000660. [PMID: 32734279 PMCID: PMC7384191 DOI: 10.1029/2019rg000660] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Revised: 09/30/2019] [Accepted: 10/03/2019] [Indexed: 05/04/2023]
Abstract
Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol-radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of -1.6 to -0.6 W m-2, or -2.0 to -0.4 W m-2 with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial-era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds.
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Affiliation(s)
- N. Bellouin
- Department of MeteorologyUniversity of ReadingReadingUK
| | - J. Quaas
- Institute for MeteorologyUniversität LeipzigLeipzigGermany
| | - E. Gryspeerdt
- Space and Atmospheric Physics GroupImperial College LondonLondonUK
| | - S. Kinne
- Max Planck Institute for MeteorologyHamburgGermany
| | - P. Stier
- Atmospheric, Oceanic and Planetary Physics, Department of PhysicsUniversity of OxfordOxfordUK
| | - D. Watson‐Parris
- Atmospheric, Oceanic and Planetary Physics, Department of PhysicsUniversity of OxfordOxfordUK
| | - O. Boucher
- Institut Pierre‐Simon Laplace, Sorbonne Université/CNRSParisFrance
| | - K. S. Carslaw
- School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - M. Christensen
- Atmospheric, Oceanic and Planetary Physics, Department of PhysicsUniversity of OxfordOxfordUK
| | - A.‐L. Daniau
- EPOC, UMR 5805, CNRS‐Université de BordeauxPessacFrance
| | - J.‐L. Dufresne
- Laboratoire de Météorologie Dynamique/IPSL, CNRS, Sorbonne Université, Ecole Normale Supérieure, PSL Research University, Ecole PolytechniqueParisFrance
| | - G. Feingold
- NOAA ESRL Chemical Sciences DivisionBoulderCOUSA
| | - S. Fiedler
- Max Planck Institute for MeteorologyHamburgGermany
- Now at Institut für Geophysik und MeteorologieUniversität zu KölnKölnGermany
| | - P. Forster
- Priestley International Centre for ClimateUniversity of LeedsLeedsUK
| | - A. Gettelman
- National Center for Atmospheric ResearchBoulderCOUSA
| | - J. M. Haywood
- CEMPSUniversity of ExeterExeterUK
- UK Met Office Hadley CentreExeterUK
| | - U. Lohmann
- Institute for Atmospheric and Climate ScienceETH ZürichZürichSwitzerland
| | | | - T. Mauritsen
- Department of MeteorologyStockholm UniversityStockholmSweden
| | - D. T. McCoy
- School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - G. Myhre
- Center for International Climate and Environmental Research‐Oslo (CICERO)OsloNorway
| | - J. Mülmenstädt
- Institute for MeteorologyUniversität LeipzigLeipzigGermany
| | - D. Neubauer
- Institute for Atmospheric and Climate ScienceETH ZürichZürichSwitzerland
| | - A. Possner
- Department of Global EcologyCarnegie Institution for ScienceStanfordCAUSA
- Now at Institute for Atmospheric and Environmental SciencesGoethe UniversityFrankfurtGermany
| | | | - Y. Sato
- Department of Applied Energy, Graduate School of Engineering, Nagoya UniversityNagoyaJapan
- Now at Faculty of Science, Department of Earth and Planetary SciencesHokkaido UniversitySapporoJapan
| | - M. Schulz
- Climate Modelling and Air Pollution Section, Research and Development DepartmentNorwegian Meteorological InstituteOsloNorway
| | - S. E. Schwartz
- Brookhaven National Laboratory Environmental and Climate Sciences DepartmentUptonNYUSA
| | - O. Sourdeval
- Institute for MeteorologyUniversität LeipzigLeipzigGermany
- Laboratoire d'Optique AtmosphériqueUniversité de LilleVilleneuve d'AscqFrance
| | - T. Storelvmo
- Department of GeosciencesUniversity of OsloOsloNorway
| | - V. Toll
- Department of MeteorologyUniversity of ReadingReadingUK
- Now at Institute of PhysicsUniversity of TartuTartuEstonia
| | - D. Winker
- NASA Langley Research CenterHamptonVAUSA
| | - B. Stevens
- Max Planck Institute for MeteorologyHamburgGermany
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22
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Fu D, Di Girolamo L, Liang L, Zhao G. Regional Biases in MODIS Marine Liquid Water Cloud Drop Effective Radius Deduced Through Fusion With MISR. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2019; 124:13182-13196. [PMID: 32025454 PMCID: PMC6988446 DOI: 10.1029/2019jd031063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 10/30/2019] [Accepted: 11/01/2019] [Indexed: 06/10/2023]
Abstract
Satellite measurements from Terra's Moderate Resolution Imaging Spectroradiometer (MODIS) represent our longest, single-platform, global record of the effective radius (Re) of the cloud drop size distribution. Quantifying its error characteristics has been challenging because systematic errors in retrieved Re covary with the structural characteristics of the cloud and the Sun-view geometry. Recently, it has been shown that the bias in MODIS Re can be estimated by fusing MODIS data with data from Terra's Multi-angle Imaging SpectroRadiometer (MISR). Here, we relate the bias to the observed underlying conditions to derive regional-scale, bias-corrected, monthly-mean Re 1.6 , Re 2.1 , and Re 3.7 values retrieved from the 1.6, 2.1, and 3.7 μm MODIS spectral channels. Our results reveal that monthly-mean bias in Re 2.1 exhibits large regional dependency, ranging from at least ~1 to 10 μm (15 to 60%) varying with scene heterogeneity, optical depth, and solar zenith angle. Regional bias-corrected monthly-mean Re 2.1 ranges from 4 to 17 μm, compared to 10 to 25 μm for uncorrected Re 2.1 , with estimated uncertainties of 0.1 to 1.8 μm. The bias-corrected monthly-mean Re 3.7 and Re 2.1 show difference of approximately +0.6 μm in the coastal marine stratocumulus regions and down to approximately -2 μm in the cumuliform cloud regions, compared to uncorrected values of about -1 to -6 μm, respectively. Bias-corrected Re values compare favorably to other independent data sources, including field observations, global model simulations, and satellite retrievals that do not use retrieval techniques similar to MODIS. This work changes the interpretation of global Re distributions from MODIS Re products and may further impact studies, which use the original MODIS Re products to study, for example, aerosol-cloud interactions and cloud microphysical parameterization.
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Affiliation(s)
- Dongwei Fu
- Department of Atmospheric SciencesUniversity of Illinois at Urbana‐ChampaignUrbanaILUSA
| | - Larry Di Girolamo
- Department of Atmospheric SciencesUniversity of Illinois at Urbana‐ChampaignUrbanaILUSA
| | | | - Guangyu Zhao
- Department of Atmospheric SciencesUniversity of Illinois at Urbana‐ChampaignUrbanaILUSA
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23
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Zhang J, Zuidema P. The diurnal cycle of the smoky marine boundary layer observed during August in the remote southeast Atlantic. ATMOSPHERIC CHEMISTRY AND PHYSICS 2019; 19:14493-14516. [PMID: 35069711 PMCID: PMC8780997 DOI: 10.5194/acp-19-14493-2019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Ascension Island (8° S, 14.5° W) is located at the northwestern edge of the south Atlantic stratocumulus deck, with most clouds in August characterized by surface observers as "stratocumulus and cumulus with bases at different levels", and secondarily as "cumulus of limited vertical extent" and occurring within a typically decoupled boundary layer. Field measurements have previously shown that the highest amounts of sunlight-absorbing smoke occur annually within the marine boundary layer during August. On more smoke-free days, the diurnal cycle in cloudiness includes a nighttime maximum in cloud liquid water path and rain, an afternoon cloud minimum, and a secondary late-afternoon increase in cumulus and rain. The afternoon low-cloud minimum is more pronounced on days with a smokier boundary layer. The cloud liquid water paths are also reduced throughout most of the diurnal cycle when more smoke is present, with the difference from cleaner conditions most pronounced at night. Precipitation is infrequent. An exception is the mid-morning, when the boundary layer deepens and liquid water paths increase. The data support a view that a radiatively enhanced decoupling persisting throughout the night is key to understanding the changes in the cloud diurnal cycle when the boundary layer is smokier. Under these conditions, the nighttime stratiform cloud layer does not always recouple to the sub-cloud layer, and the decoupling maintains more moisture within the sub-cloud layer. After the sun rises, enhanced shortwave absorption in a smokier boundary layer can drive a vertical ascent that momentarily couples the sub-cloud layer to the cloud layer, deepening the boundary layer and ventilating moisture throughout, a process that may also be aided by a shift to smaller droplets. After noon, shortwave absorption within smokier boundary layers again reduces the upper-level stratiform cloud and the sub-cloud relative humidity, discouraging further cumulus development and again strengthening a decoupling that lasts longer into the night. The novel diurnal mechanism provides a new challenge for cloud models to emulate. The lower free troposphere above cloud is more likely to be cooler, when boundary layer smoke is present, and lower free-tropospheric winds are stronger and more northeasterly, with both (meteorological) influences supporting further smoke entrainment into the boundary layer from above.
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Affiliation(s)
- Jianhao Zhang
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker Cswy, Miami, FL 33149, USA
| | - Paquita Zuidema
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, 4600 Rickenbacker Cswy, Miami, FL 33149, USA
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24
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Mardi AH, Dadashazar H, MacDonald AB, Crosbie E, Coggon MM, Aghdam MA, Woods RK, Jonsson HH, Flagan RC, Seinfeld JH, Sorooshian A. Effects of Biomass Burning on Stratocumulus Droplet Characteristics, Drizzle Rate, and Composition. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2019; 124:12301-12318. [PMID: 33274175 PMCID: PMC7709909 DOI: 10.1029/2019jd031159] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 10/29/2019] [Indexed: 05/30/2023]
Abstract
This study reports on airborne measurements of stratocumulus cloud properties under varying degrees of influence from biomass burning (BB) plumes off the California coast. Data are reported from five total airborne campaigns based in Marina, California, with two of them including influence from wildfires in different areas along the coast of the western United States. The results indicate that subcloud cloud condensation nuclei number concentration and mass concentrations of important aerosol species (organics, sulfate, nitrate) were better correlated with cloud droplet number concentration (N d) as compared to respective above-cloud aerosol data. Given that the majority of BB particles resided above cloud tops, this is an important consideration for future work in the region as the data indicate that the subcloud BB particles likely were entrained from the free troposphere. Lower cloud condensation nuclei activation fractions were observed for BB-impacted clouds as compared to non-BB clouds due, at least partly, to less hygroscopic aerosols. Relationships between N d and either droplet effective radius or drizzle rate are preserved regardless of BB influence, indicative of how parameterizations can exhibit consistent skill for varying degrees of BB influence as long as N d is known. Lastly, the composition of both droplet residual particles and cloud water changed significantly when clouds were impacted by BB plumes, with differences observed for different fire sources stemming largely from effects of plume aging time and dust influence.
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Affiliation(s)
- Ali Hossein Mardi
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Hossein Dadashazar
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Alexander B MacDonald
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Ewan Crosbie
- Science Systems and Applications, Inc., Hampton, VA, USA
- NASA Langley Research Center, Hampton, VA, USA
| | - Matthew M Coggon
- Cooperative Institute for Research in Environmental Science and National Oceanic and Atmospheric Administration, Boulder, CO, USA
| | - Mojtaba Azadi Aghdam
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
| | - Roy K Woods
- Naval Postgraduate School, Monterey, CA, USA
| | | | - Richard C Flagan
- Department of Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - John H Seinfeld
- Department of Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
- Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
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25
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Hasekamp OP, Gryspeerdt E, Quaas J. Analysis of polarimetric satellite measurements suggests stronger cooling due to aerosol-cloud interactions. Nat Commun 2019; 10:5405. [PMID: 31776336 PMCID: PMC6881401 DOI: 10.1038/s41467-019-13372-2] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 11/04/2019] [Indexed: 11/23/2022] Open
Abstract
Anthropogenic aerosol emissions lead to an increase in the amount of cloud condensation nuclei and consequently an increase in cloud droplet number concentration and cloud albedo. The corresponding negative radiative forcing due to aerosol cloud interactions (RF[Formula: see text]) is one of the most uncertain radiative forcing terms as reported in the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). Here we show that previous observation-based studies underestimate aerosol-cloud interactions because they used measurements of aerosol optical properties that are not directly related to cloud formation and are hampered by measurement uncertainties. We have overcome this problem by the use of new polarimetric satellite retrievals of the relevant aerosol properties (aerosol number, size, shape). The resulting estimate of RF[Formula: see text] = -1.14 Wm[Formula: see text] (range between -0.84 and -1.72 Wm[Formula: see text]) is more than a factor 2 stronger than the IPCC estimate that includes also other aerosol induced changes in cloud properties.
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Affiliation(s)
- Otto P Hasekamp
- SRON Netherlands Institute for Space Research, Sorbonnelaan 2, 3584 CA, Utrecht, The Netherlands.
| | - Edward Gryspeerdt
- Space and Atmospheric Physics Group, Imperial College London, London, SW7 2AZ, UK
| | - Johannes Quaas
- Universität Leipzig, Institute for Meteorology, Stephanstr. 3, D-04103, Leipzig, Germany
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26
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Zhang Y, Zhao C, Zhang K, Ke J, Che H, Shen X, Zheng Z, Liu D. Retrieving the microphysical properties of opaque liquid water clouds from CALIOP measurements. OPTICS EXPRESS 2019; 27:34126-34140. [PMID: 31878468 DOI: 10.1364/oe.27.034126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 10/01/2019] [Indexed: 06/10/2023]
Abstract
Cloud droplet effective radius (CER) and number concentration (CDNC) are two critical microphysical properties of liquid water clouds, which play essential roles in the Earth's radiative energy balance and atmospheric hydrological cycle. Even though many satellite remote sensing techniques have been developed to obtain these two properties, the observations are often limited to the daytime. In this study, a method to estimate CER and CDNC of liquid water clouds over global ocean area during both daytime and nighttime from CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) measurements is presented. The size sensitivity of the dual-wavelength (532 nm & 1064 nm) layer-integrated attenuated backscattering signals from CALIOP is checked and information content for liquid water cloud CER retrieval is found. Taking use of the artificial neural network (ANN) technique, the CER and then the CDNC are estimated from CALIOP by combining the polarization ratio and the dual wavelength attenuated backscattering signals. The comparisons with CER and CDNC estimated from MODIS (Moderate Resolution Imaging Spectroradiometer) during daytime demonstrate the feasibility of this new method. Both the daytime and nighttime CER and CDNC derived from CALIOP observations are presented in this paper and the day-night variation of liquid water cloud is discussed which would provide useful day-night variation of liquid water cloud properties.
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27
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Weak average liquid-cloud-water response to anthropogenic aerosols. Nature 2019; 572:51-55. [PMID: 31367029 DOI: 10.1038/s41586-019-1423-9] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 05/24/2019] [Indexed: 11/08/2022]
Abstract
The cooling of the Earth's climate through the effects of anthropogenic aerosols on clouds offsets an unknown fraction of greenhouse gas warming. An increase in the amount of water inside liquid-phase clouds induced by aerosols, through the suppression of rain formation, has been postulated to lead to substantial cooling, which would imply that the Earth's surface temperature is highly sensitive to anthropogenic forcing. Here we provide direct observational evidence that, instead of a strong increase, aerosols cause a relatively weak average decrease in the amount of water in liquid-phase clouds compared with unpolluted clouds. Measurements of polluted clouds downwind of various anthropogenic sources-such as oil refineries, smelters, coal-fired power plants, cities, wildfires and ships-reveal that aerosol-induced cloud-water increases, caused by suppressed rain formation, and decreases, caused by enhanced evaporation of cloud water, partially cancel each other out. We estimate that the observed decrease in cloud water offsets 23% of the global climate-cooling effect caused by aerosol-induced increases in the concentration of cloud droplets. These findings invalidate the hypothesis that increases in cloud water cause a substantial climate cooling effect and translate into reduced uncertainty in projections of future climate.
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28
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Bodas‐Salcedo A, Mulcahy JP, Andrews T, Williams KD, Ringer MA, Field PR, Elsaesser GS. Strong Dependence of Atmospheric Feedbacks on Mixed-Phase Microphysics and Aerosol-Cloud Interactions in HadGEM3. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2019; 11:1735-1758. [PMID: 31598189 PMCID: PMC6774284 DOI: 10.1029/2019ms001688] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 05/09/2019] [Accepted: 05/09/2019] [Indexed: 05/13/2023]
Abstract
We analyze the atmospheric processes that explain the large changes in radiative feedbacks between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere-only climate change simulations (amip and amip-p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme and the development of a new mixed-phase cloud scheme. Both schemes reduce the strength of the preexisting shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol-cloud interaction, and it also suppresses a negative clear-sky shortwave feedback. The mixed-phase scheme increases the amount of cloud liquid water path (LWP) in the present day and reduces the increase in LWP with warming. Both changes contribute to reducing the negative radiative feedback of the increase of LWP in the warmer climate. The mixed-phase scheme also enhances a strong, preexisting, positive cloud fraction feedback. We assess the realism of the changes by comparing present-day simulations against observations and discuss avenues that could help constrain the relevant processes.
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Affiliation(s)
| | | | | | | | | | | | - G. S. Elsaesser
- Goddard Institute for Space StudiesColumbia University/NASANew YorkNYUSA
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29
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Painemal D. Global estimates of changes in shortwave low-cloud albedo and fluxes due to variations in cloud droplet number concentration derived from CERES-MODIS satellite sensors. GEOPHYSICAL RESEARCH LETTERS 2018; 45:9288-9296. [PMID: 33414572 PMCID: PMC7787139 DOI: 10.1029/2018gl078880] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 08/23/2018] [Indexed: 05/25/2023]
Abstract
15 years of Aqua CERES and MODIS observations are combined to derive nearly global maps of shortwave albedo (A) and flux (F) response to changes in cloud droplet number concentration (Nd ). Absolute ( S a = ∂ A ∂ N d ) and relative ( S r = ∂ A ∂ ln ( N d ) ) albedo susceptibilities are computed seasonally by exploiting the linear relationship between A and ln(Nd ) for shallow liquid clouds. Subtropical stratiform clouds (eastern Pacific, eastern Atlantic, and Australia) yield the highest Sr , followed by the extratropical oceans during their hemispheric summer. When Sr is cast in terms of F, the eastern Pacific clouds dominate Sr , with a secondary maximum offshore eastern Asia. Sa is mainly governed by Nd , with more pristine environments being more susceptible to change their albedo. While both Sa and Sr are advantageous for understanding radiative aspects of the aerosol indirect effect, Sr is more suitable for calculating changes in A and F due to the linear relationship between A and ln(Nd ).
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Affiliation(s)
- David Painemal
- Science Systems and Applications, Inc., NASA Langley Research Center
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