1
|
Kazil J, Christensen MW, Abel SJ, Yamaguchi T, Feingold G. Realism of Lagrangian Large Eddy Simulations Driven by Reanalysis Meteorology: Tracking a Pocket of Open Cells Under a Biomass Burning Aerosol Layer. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2021; 13:e2021MS002664. [PMID: 35865715 PMCID: PMC9287006 DOI: 10.1029/2021ms002664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 10/13/2021] [Accepted: 10/24/2021] [Indexed: 06/15/2023]
Abstract
An approach to drive Lagrangian large eddy simulation (LES) of boundary layer clouds with reanalysis data is presented and evaluated using satellite (Spinning Enhanced Visible and Infrared Imager, SEVIRI) and aircraft (Cloud-Aerosol-Radiation Interactions and Forcing, CLARIFY) measurements. The simulations follow trajectories of the boundary layer flow. They track the formation and evolution of a pocket of open cells (POC) underneath a biomass burning aerosol layer in the free troposphere. The simulations reproduce the evolution of observed stratocumulus cloud morphology, cloud optical depth, and cloud drop effective radius, and capture the timing of the cloud state transition from closed to open cells seen in the satellite imagery on the three considered trajectories. They reproduce a biomass burning aerosol layer identified by the in-situ aircraft measurements above the inversion of the POC. Entrainment of aerosol from the biomass burning layer into the POC is limited to the extent of having no impact on cloud- or boundary layer properties, in agreement with the CLARIFY observations. The two-moment bin microphysics scheme used in the simulations reproduces the in-situ cloud microphysical properties reasonably well. A two-moment bulk microphysics scheme reproduces the satellite observations in the non-precipitating closed-cell state, but overestimates liquid water path and cloud optical depth in the precipitating open-cell state due to insufficient surface precipitation. A boundary layer cold and dry bias occurring in LES can be counteracted by reducing the grid aspect ratio and by tightening the large scale wind speed nudging towards the surface.
Collapse
Affiliation(s)
- Jan Kazil
- Cooperative Institute for Research in Environmental SciencesUniversity of Colorado BoulderBoulderCOUSA
- National Oceanic and Atmospheric AdministrationChemical Sciences LaboratoryBoulderCOUSA
| | | | | | - Takanobu Yamaguchi
- Cooperative Institute for Research in Environmental SciencesUniversity of Colorado BoulderBoulderCOUSA
- National Oceanic and Atmospheric AdministrationChemical Sciences LaboratoryBoulderCOUSA
| | - Graham Feingold
- National Oceanic and Atmospheric AdministrationChemical Sciences LaboratoryBoulderCOUSA
| |
Collapse
|
2
|
Chiu JC, Yang CK, van Leeuwen PJ, Feingold G, Wood R, Blanchard Y, Mei F, Wang J. Observational Constraints on Warm Cloud Microphysical Processes Using Machine Learning and Optimization Techniques. GEOPHYSICAL RESEARCH LETTERS 2021; 48:e2020GL091236. [PMID: 33678926 PMCID: PMC7900997 DOI: 10.1029/2020gl091236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 11/17/2020] [Accepted: 12/07/2020] [Indexed: 06/12/2023]
Abstract
We introduce new parameterizations for autoconversion and accretion rates that greatly improve representation of the growth processes of warm rain. The new parameterizations capitalize on machine-learning and optimization techniques and are constrained by in situ cloud probe measurements from the recent Atmospheric Radiation Measurement Program field campaign at Azores. The uncertainty in the new estimates of autoconversion and accretion rates is about 15% and 5%, respectively, outperforming existing parameterizations. Our results confirm that cloud and drizzle water content are the most important factors for determining accretion rates. However, for autoconversion, in addition to cloud water content and droplet number concentration, we discovered a key role of drizzle number concentration that is missing in current parameterizations. The robust relation between autoconversion rate and drizzle number concentration is surprising but real, and furthermore supported by theory. Thus, drizzle number concentration should be considered in parameterizations for improved representation of the autoconversion process.
Collapse
Affiliation(s)
- J. Christine Chiu
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - C. Kevin Yang
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - Peter Jan van Leeuwen
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
- Department of MeteorologyUniversity of ReadingReadingUK
| | | | - Robert Wood
- Department of Atmospheric SciencesUniversity of WashingtonSeattleWAUSA
| | - Yann Blanchard
- Department of Earth and Atmospheric SciencesESCER Centre, University of Quebec at MontrealMontrealQCCanada
| | - Fan Mei
- Pacific Northwest National LaboratoryRichlandWAUSA
| | - Jian Wang
- Center for Aerosol Science and Engineering, Department of Energy, Environmental and Chemical EngineeringWashington University in Saint LouisSaint LouisMOUSA
| |
Collapse
|
3
|
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.
Collapse
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
| |
Collapse
|
4
|
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: 86] [Impact Index Per Article: 21.5] [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.
Collapse
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
| |
Collapse
|
5
|
Grosvenor DP, Sourdeval O, Zuidema P, Ackerman A, Alexandrov MD, Bennartz R, Boers R, Cairns B, Chiu JC, Christensen M, Deneke H, Diamond M, Feingold G, Fridlind A, Hünerbein A, Knist C, Kollias P, Marshak A, McCoy D, Merk D, Painemal D, Rausch J, Rosenfeld D, Russchenberg H, Seifert P, Sinclair K, Stier P, van Diedenhoven B, Wendisch M, Werner F, Wood R, Zhang Z, Quaas J. Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives. REVIEWS OF GEOPHYSICS (WASHINGTON, D.C. : 1985) 2018; 56:409-453. [PMID: 30148283 PMCID: PMC6099364 DOI: 10.1029/2017rg000593] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 04/05/2018] [Accepted: 04/06/2018] [Indexed: 05/13/2023]
Abstract
The cloud droplet number concentration (N d) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol-cloud interactions. Current standard satellite retrievals do not operationally provide N d, but it can be inferred from retrievals of cloud optical depth (τ c) cloud droplet effective radius (r e) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel-level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high-quality ground-based observations are examined.
Collapse
Affiliation(s)
| | - Odran Sourdeval
- Leipzig Institute for MeteorologyUniversität LeipzigLeipzigGermany
| | - Paquita Zuidema
- Department of Atmospheric SciencesRosenstiel School of Marine and Atmospheric ScienceMiamiFLUSA
| | | | - Mikhail D. Alexandrov
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
- Department of Applied Physics and Applied MathematicsColumbia UniversityNew YorkNYUSA
| | - Ralf Bennartz
- Department of Earth and Environmental SciencesVanderbilt UniversityNashvilleTNUSA
- Space Science and Engineering CenterUniversity of Wisconsin‐MadisonMadisonWIUSA
| | - Reinout Boers
- Royal Netherlands Meteorological InstituteDe BiltThe Netherlands
| | - Brian Cairns
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
| | - J. Christine Chiu
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - Matthew Christensen
- Rutherford Appleton LaboratoryHarwellUK
- Department of PhysicsUniversity of OxfordOxfordUK
| | - Hartwig Deneke
- Leibniz Institute for Tropospheric ResearchLeipzigGermany
| | - Michael Diamond
- Department of Atmospheric SciencesUniversity of WashingtonSeattleWAUSA
| | - Graham Feingold
- Chemical Sciences Division, Earth System Research LaboratoryNational Oceanic and Atmospheric AdministrationBoulderCOUSA
| | - Ann Fridlind
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
| | - Anja Hünerbein
- Leibniz Institute for Tropospheric ResearchLeipzigGermany
| | | | - Pavlos Kollias
- School of Marine and Atmospheric SciencesStony Brook UniversityStony BrookNYUSA
| | | | - Daniel McCoy
- School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Daniel Merk
- Leibniz Institute for Tropospheric ResearchLeipzigGermany
| | | | - John Rausch
- Department of Earth and Environmental SciencesVanderbilt UniversityNashvilleTNUSA
| | - Daniel Rosenfeld
- Institute of Earth SciencesThe Hebrew University of JerusalemJerusalemIsrael
| | - Herman Russchenberg
- Department of Geoscience and Remote SensingDelft University of TechnologyDelftThe Netherlands
| | - Patric Seifert
- Leibniz Institute for Tropospheric ResearchLeipzigGermany
| | - Kenneth Sinclair
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
- Department of Earth and Environmental EngineeringColumbia UniversityNew YorkNYUSA
| | - Philip Stier
- Department of PhysicsUniversity of OxfordOxfordUK
| | - Bastiaan van Diedenhoven
- NASA Goddard Institute for Space StudiesNew YorkNYUSA
- Center for Climate Systems ResearchColumbia UniversityNew YorkNYUSA
| | - Manfred Wendisch
- Leipzig Institute for MeteorologyUniversität LeipzigLeipzigGermany
| | - Frank Werner
- Joint Center for Earth Systems TechnologyBaltimoreMDUSA
| | - Robert Wood
- Department of Atmospheric SciencesUniversity of WashingtonSeattleWAUSA
| | | | - Johannes Quaas
- Leipzig Institute for MeteorologyUniversität LeipzigLeipzigGermany
| |
Collapse
|
6
|
Rémillard J, Fridlind AM, Ackerman AS, Tselioudis G, Kollias P, Mechem DB, Chandler HE, Luke E, Wood R, Witte MK, Chuang PY, Ayers JK. Use of cloud radar Doppler spectra to evaluate stratocumulus drizzle size distributions in large-eddy simulations with size-resolved microphysics. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY 2017; 56:3263-3283. [PMID: 30740040 PMCID: PMC6364314 DOI: 10.1175/jamc-d-17-0100.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
A case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated with an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 μm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely.
Collapse
Affiliation(s)
| | - A. M. Fridlind
- NASA Goddard Institute for Space Studies, New York, NY
- Corresponding author:
| | | | - G. Tselioudis
- NASA Goddard Institute for Space Studies, New York, NY
| | - P. Kollias
- Stony Brook University, Stony Brook, NY
- Brookhaven National Laboratory, Brookhaven, NY
| | | | | | - E. Luke
- Brookhaven National Laboratory, Brookhaven, NY
| | - R. Wood
- University of Washington, Seattle, WA
| | | | | | - J. K. Ayers
- SSAI, NASA Langley Research Center, Langley, VA
| |
Collapse
|
7
|
Kravitz B, Wang H, Rasch PJ, Morrison H, Solomon AB. Process-model simulations of cloud albedo enhancement by aerosols in the Arctic. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2014; 372:rsta.2014.0052. [PMID: 25404677 PMCID: PMC4240951 DOI: 10.1098/rsta.2014.0052] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN), either through geoengineering or other increased sources of Arctic aerosols. An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Albedo increases are stronger for pure liquid clouds than mixed-phase clouds. Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus, the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation owing to precipitation changes are small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects.
Collapse
Affiliation(s)
- Ben Kravitz
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, PO Box 999, MSIN K9-24, Richland, WA 99352, USA
| | - Hailong Wang
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, PO Box 999, MSIN K9-24, Richland, WA 99352, USA
| | - Philip J Rasch
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, PO Box 999, MSIN K9-24, Richland, WA 99352, USA
| | - Hugh Morrison
- Mesoscale and Microscale Meteorology Division, NCAR Earth System Laboratory, National Center for Atmospheric Research, Boulder, CO 80301, USA
| | - Amy B Solomon
- University of Colorado Cooperative Institute for Research in Environmental Sciences, NOAA Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80309-0216, USA
| |
Collapse
|
8
|
Jiang H, Feingold G, Koren I. Effect of aerosol on trade cumulus cloud morphology. ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2009jd011750] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
9
|
Jiang H, Feingold G, Jonsson HH, Lu ML, Chuang PY, Flagan RC, Seinfeld JH. Statistical comparison of properties of simulated and observed cumulus clouds in the vicinity of Houston during the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS). ACTA ACUST UNITED AC 2008. [DOI: 10.1029/2007jd009304] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
10
|
Jacobson MZ, Kaufman YJ, Rudich Y. Examining feedbacks of aerosols to urban climate with a model that treats 3-D clouds with aerosol inclusions. ACTA ACUST UNITED AC 2007. [DOI: 10.1029/2007jd008922] [Citation(s) in RCA: 83] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
11
|
|
12
|
Mechem DB, Robinson PC, Kogan YL. Processing of cloud condensation nuclei by collision-coalescence in a mesoscale model. ACTA ACUST UNITED AC 2006. [DOI: 10.1029/2006jd007183] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
13
|
Jiang H, Feingold G. Effect of aerosol on warm convective clouds: Aerosol-cloud-surface flux feedbacks in a new coupled large eddy model. ACTA ACUST UNITED AC 2006. [DOI: 10.1029/2005jd006138] [Citation(s) in RCA: 108] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
14
|
Jacobson MZ. Development of mixed-phase clouds from multiple aerosol size distributions and the effect of the clouds on aerosol removal. ACTA ACUST UNITED AC 2003. [DOI: 10.1029/2002jd002691] [Citation(s) in RCA: 85] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
15
|
Jiang H, Feingold G, Cotton WR. Simulations of aerosol‐cloud‐dynamical feedbacks resulting from entrainment of aerosol into the marine boundary layer during the Atlantic Stratocumulus Transition Experiment. ACTA ACUST UNITED AC 2002. [DOI: 10.1029/2001jd001502] [Citation(s) in RCA: 79] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Hongli Jiang
- Department of Atmospheric Science Colorado State University Fort Collins Colorado USA
| | - Graham Feingold
- Environmental Technology Laboratory NOAA Boulder Colorado USA
| | - William R. Cotton
- Department of Atmospheric Science Colorado State University Fort Collins Colorado USA
| |
Collapse
|
16
|
Feingold G, Kreidenweis SM. Cloud processing of aerosol as modeled by a large eddy simulation with coupled microphysics and aqueous chemistry. ACTA ACUST UNITED AC 2002. [DOI: 10.1029/2002jd002054] [Citation(s) in RCA: 60] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Graham Feingold
- Environmental Technology Laboratory; National Oceanic and Atmospheric Administration; Boulder Colorado USA
| | - Sonia M. Kreidenweis
- Department of Atmospheric Science; Colorado State University; Fort Collins Colorado USA
| |
Collapse
|
17
|
Jiang H, Feingold G, Cotton WR, Duynkerke PG. Large-eddy simulations of entrainment of cloud condensation nuclei into the Arctic boundary layer: May 18, 1998, FIRE/SHEBA case study. ACTA ACUST UNITED AC 2001. [DOI: 10.1029/2000jd900303] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
18
|
Osborne SR, Johnson DW, Bower KN, Wood R. Modification of the aerosol size distribution within exhaust plumes produced by diesel-powered ships. ACTA ACUST UNITED AC 2001. [DOI: 10.1029/2000jd900391] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
19
|
Wurzler S, Reisin TG, Levin Z. Modification of mineral dust particles by cloud processing and subsequent effects on drop size distributions. ACTA ACUST UNITED AC 2000. [DOI: 10.1029/1999jd900980] [Citation(s) in RCA: 189] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
20
|
Zhang Y, Kreidenweis SM, Feingold G. Stratocumulus processing of gases and cloud condensation nuclei: 2. Chemistry sensitivity analysis. ACTA ACUST UNITED AC 1999. [DOI: 10.1029/1999jd900206] [Citation(s) in RCA: 23] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
21
|
Feingold G, Kreidenweis SM, Zhang Y. Stratocumulus processing of gases and cloud condensation nuclei: 1. Trajectory ensemble model. ACTA ACUST UNITED AC 1998. [DOI: 10.1029/98jd01750] [Citation(s) in RCA: 64] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
22
|
Feingold G, Boers R, Stevens B, Cotton WR. A modeling study of the effect of drizzle on cloud optical depth and susceptibility. ACTA ACUST UNITED AC 1997. [DOI: 10.1029/97jd00963] [Citation(s) in RCA: 48] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|