Modal Aerosol Treatment in CAM: Evaluation and Indirect Effect X. Liu, S. J. Ghan, R. Easter (PNNL) J.-F. Lamarque, P. Hess, N. Mahowald, F. Vitt, H. Morrison,

Slides:

Advertisements

Similar presentations

SOLAS Dust workshop (Reading) Overview of dust modelling from Leeds global aerosol group Graham Mann, Ken Carslaw, Dominick Spracklen,

Advertisements

Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009.

Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009 Geophysical Fluid Dynamics Laboratory Review June 30 - July 2, 2009.

Aerosol Lifetimes at High Latitudes Betty Croft 1, Jeff Pierce 1,2 and Randall Martin 1,3 1 Dalhousie University, Halifax, Canada 2 Colorado State University,

VIII. Aerosols Size distribution Formation and Processing Composition Aerosol phase chemistry.

By : Kerwyn Texeira. Outline Definitions Introduction Model Description Model Evaluation The effect of dust nuclei on cloud coverage Conclusion Questions.

Proposed Aerosol Treatment for CAM4 Steve Ghan, Richard Easter, Xiaohong Liu, Rahul Zaveri Pacific Northwest National Laboratory precursor emissions coagulation.

Incorporation of the Model of Aerosol Dynamics, Reaction, Ionization and Dissolution (MADRID) into CMAQ Yang Zhang, Betty K. Pun, Krish Vijayaraghavan,

Aerosols By Elizabeth Dahl (2005) Edited by Ted Dibble (2008)

Global Aerosol Microphysics With TOMAS Peter J. Adams Acknowledgments: Win Trivitayanurak GEOS-CHEM User’s Meeting April 7, 2009 Center for Atmospheric.

Ultrafine Particles and Climate Change Peter J. Adams HDGC Seminar November 5, 2003.

Implementation of Sulfate and Sea-Salt Aerosol Microphysics in GEOS-Chem Hi everyone. My name is Win Trivitayanurak… I’m a PhD student working with Peter.

Colette Heald Fangqun Yu Aerosol Processes Working Group.

1 High Time-Resolution Size- Resolved Aerosol Predictions: Learning about CCN from Aerosol Field Campaigns Win Trivitayanurak GEOS-CHEM Meeting Harvard.

SETTING THE STAGE FOR: BIOSPHERE, CHEMISTRY, CLIMATE INTERACTIONS.

Assimilation of Aerosol Optical Depth Gé Verver 1, Bas Henzing 1, Peter van Velthoven 1 Cristina Robles-Gonzalez 2, Gerrit de Leeuw 2 1 KNMI, De Bilt,

Aerosols. Atmospheric Aerosols Bibliography Seinfeld & Pandis, Atmospheric Chemistry and Physics, Chapt Finlayson-Pitts & Pitts, Chemistry of the.

Effects of size resolved aerosol microphysics on photochemistry and heterogeneous chemistry Gan Luo and Fangqun Yu ASRC, SUNY-Albany

Modeling BC Sources and Sinks - research plan Charles Q. Jia and Sunling Gong University of Toronto and Environment 1 st annual NETCARE workshop.

Aerosol Working Group The 7 th International GEOS-Chem User’s Meeting May 4, 2015 Aerosol WG Co-Chairs Colette Heald: Jeff Pierce (outgoing):

Processes Controlling the Seasonal Cycle of Arctic Aerosol Number and Size B. Croft 1, J. R. Pierce 2, R. V. Martin 1,3, R. Leaitch 4, T. Breider 5, A.

QUESTIONS 1.Is the rate of reaction of S(IV) more likely to be slower than calculated for a cloud droplet or a rain droplet? Why? 2.If you wanted to determine.

Global Simulation of the Indirect Aerosol Effect With the ECHAM5 GCM III LBA Scientific Conference Brasilia 28/07/2004 P. Stier (1), J. Feichter (1), S.

Simulation of Below-cloud and In-cloud Aerosol Scavenging in ECHAM5-HAM Betty Croft, Ulrike Lohmann, Philip Stier, Sabine Wurzler, Sylvaine Ferrachat,

Aerosol Microphysics: Plans for GEOS-CHEM

School of something FACULTY OF OTHER 1 Lecture 2: Aerosol sources and sinks Ken Carslaw.

Evaluation of Wildfire Impacts in CAM5 Yufei Zou

Improving Black Carbon (BC) Aging in GEOS-Chem Based on Aerosol Microphysics: Constraints from HIPPO Observations Cenlin He Advisers: Qinbin Li, Kuo-Nan.

Global models. Content Principles of Earth System Models and global models Global aerosol models as part of Earth System Models Model input Computation.

Properties of Particulate Matter Physical, Chemical and Optical Properties Size Range of Particulate Matter Mass Distribution of PM vs. Size: PM10, PM2.5.

Biosphere/Atmosphere Interactions in the Tropics.

Progress on Application of Modal Aerosol Dynamics to CAM Xiaohong Liu, Steve Ghan, Richard Easter, Rahul Zaveri, Yun Qian (Pacific Northwest National.

Modeling of aerosol processes in the atmosphere Peter Tunved Department of Environmental Science and Analytical Chemistry Stockholm University Sweden.

Influences of In-cloud Scavenging Parameterizations on Aerosol Concentrations and Deposition in the ECHAM5-HAM GCM Betty Croft - Dalhousie University,

Aerosols in WRF-CHEM Eric Stofferahn George Mason University _07:00:00 (UTC)

Microphysical simulations of large volcanic eruptions: Pinatubo and Toba Jason M. English National Center for Atmospheric Research (LASP/University of.

Coupling between the aerosols and hydrologic cycles Xiaoyan Jiang Climatology course, 387H Dec 5, 2006.

Representation of Sea Salt Aerosol in CAM coupled with a Sectional Aerosol Microphysical Model CARMA Tianyi Fan, Owen Brian Toon LASP/ATOC, University.

Linking Anthropogenic Aerosols, Urban Air Pollution and Tropospheric Chemistry to Climate ( actually, to CAM/CCSM ) Chien Wang Massachusetts Institute.

Morrison/Gettelman/GhanAMWG January 2007 Two-moment Stratiform Cloud Microphysics & Cloud-aerosol Interactions in CAM H. Morrison, A. Gettelman (NCAR),

Aerosol Size-Dependent Impaction Scavenging in Warm, Mixed, and Ice Clouds in the ECHAM5-HAM GCM Betty Croft, and Randall V. Martin – Dalhousie University,

Betty Croft, and Randall V. Martin – Dalhousie University, Canada

Influences of In-cloud Scavenging and Cloud Processing on Aerosol Concentrations in ECHAM5-HAM Betty Croft - Dalhousie University, Halifax, Canada Ulrike.

K.S Carslaw, L. A. Lee, C. L. Reddington, K. J. Pringle, A. Rap, P. M. Forster, G.W. Mann, D. V. Spracklen, M. T. Woodhouse, L. A. Regayre and J. R. Pierce.

An Interactive Aerosol-Climate Model based on CAM/CCSM: Progress and challenging issues Chien Wang and Dongchul Kim (MIT) Annica Ekman (U. Stockholm) Mary.

Global Simulations of Below-Cloud and In-Cloud Aerosol Scavenging

Observational Constraints on Aerosol Deposition and Optical Depth Mark Flanner 1 Phil Rasch 1 Jim Randerson 2 Joe McConnell 3 Tami Bond 4 1 NCAR 2 University.

Black Carbon Ageing in the CCCma GCM Betty Croft and Ulrike Lohmann Department of Physics and Atmospheric Science Dalhousie University, Halifax, N.S. Canada.

Using WRF-Chem to understand interactions between synoptic and microphysical variability during VOCALS Rhea George, Robert Wood University of Washington.

GEOS-CHEM Activities at NIA Hongyu Liu National Institute of Aerospace (NIA) at NASA LaRC June 2, 2003.

Update on the 2-moment stratiform cloud microphysics scheme in CAM Hugh Morrison and Andrew Gettelman National Center for Atmospheric Research CCSM Atmospheric.

Understanding The Effect Of Anthropogenic Aerosol Weekly Cycles Upon The Climate Using A Global Model Of Aerosol Processes (GLOMAP) Introduction GLOMAP.

Simulation of the indirect radiative forcing of climate due to aerosols by the two-way coupled WRF-CMAQ model over the continental United States: Preliminary.

Aerosol Indirect Effects in CAM and MIRAGE Steve Ghan Pacific Northwest National Laboratory Jean-Francois Lamarque, Peter Hess, and Francis Vitt, NCAR.

Application of Ice Microphysics to CAM Xiaohong Liu, S. J. Ghan (Pacific Northwest National Laboratory) M. Wang, J. E. Penner (University of Michigan)

March 31, 2004BGC Working Group Interactive chemistry in CAM Jean-François Lamarque, D. Kinnison and S. Walters Atmospheric Chemistry Division NCAR.

What Were We Supposed to Have Done in CAM4 with Chemistry? Who will do what?

Simulated species SO 2, SO 4, DMS NH 3, NH 4, NH 4 NO 3 OC (hydrophobic, hydrophilic) BC (hydrophobic, hydrophilic) Sea-salt (4 bins) SOA same as Phil.

Aerosol 1 st indirect forcing in the coupled CAM-IMPACT model: effects from primary-emitted particulate sulfate and boundary layer nucleation Minghuai.

Aerosol Indirect Effects in CAM A. Gettelman (NCAR), F. Vitt (NCAR), P. Hess (Cornell) H. Morrison (NCAR), P. R. Field (Met Office), S.J. Ghan (PNNL)

March 9, 2004CCSM AMWG Interactive chemistry in CAM Jean-François Lamarque, D. Kinnison S. Walters and the WACCM group Atmospheric Chemistry Division NCAR.

H. Morrison, A. Gettelman (NCAR) , S. Ghan (PNL)

Impacts of Dust Mixing State on Cloud Microphysics

Atmospheric Modeling and Analysis Division,

Latest Development on Modal Aerosol Formulation and Indirect Effects

AEROSOLS REDUCE ATMOSPHERIC OXIDATION

Influences of Wet Scavenging on Aerosol Concentrations and Deposition in the ECHAM5-HAM Global Climate Model Betty Croft1 Ulrike.

Update on CAM and the AMWG. Recent activities and near-term priorities. by the AMWG.

A. Gettelman, X. Liu, H. Morrison, S. Ghan

Particle formation and growth

Presentation transcript:

Modal Aerosol Treatment in CAM: Evaluation and Indirect Effect X. Liu, S. J. Ghan, R. Easter (PNNL) J.-F. Lamarque, P. Hess, N. Mahowald, F. Vitt, H. Morrison, A. Gettelman, P. Rasch, (NCAR) P. Cameron-Smith, C. Chuang (LLNL) Annica Ekman (Stockholm University)

Current Aerosol Treatment in CAM3 sulfate hydrophobic black carbon sea salt 1soil dust 1 nitrate ammonium hydrophilic black carbon hydrophilic organic carbon hydrophobic organic carbon sea salt 4 sea salt 3 sea salt 2soil dust 2 soil dust 4 soil dust 3 secondary organic carbon

Current Weaknesses in CAM Aerosol species are externally mixed (individual particles are composed of only a single species). Their size distribution is prescribed (number is diagnosed from the predicted mass). –Processes that should only affect mass (condensation, chemistry) also affect number. –Processes that only affect number (nucleation, coagulation) are neglected. Hydrophobic carbon ages to hydrophilic with prescribed timescale

Benchmark Aerosol Treatment for CAM4 Aitken number water sulfate ammmonium secondary OC sea salt Accumulation number water sulfate ammonium secondary OC hydrophobic OC BC sea salt Primary Carbon number hydrophobic OC BC Fine Soil Dust number water soil dust sulfate ammonium Fine Sea Salt number water sea salt sulfate ammonium Coarse Soil Dust number water soil dust sulfate ammonium Coarse Sea Salt number water sea salt sulfate ammonium coagulation condensation All modes log-normal with prescribed width. Total transported aerosol tracers: 38 Cloud-borne aerosol predicted but not transported.

New Processes New particle formation Coagulation within, between modes Dynamic condensation of trace gas (H2SO4, NH3) on aerosols Water uptake to internally mixed particles Intermode transfer (renaming) due to condensation, coagulation, and cloud chemistry Aging of primary carbon to accumulation mode based on sulfate coating from condensation & coagulation Aerosol number emissions Aerosol activation

Revised Processes Wet scavenging (stratiform & convective cloud) In-cloud rainout based on activated (cloud phase) aerosol; Below-cloud impaction scavenging rates (mass & no.) using a look-up table (wet size, precipitation rate). Size-dependent dry deposition (Zhang et al., 2001) Cloud sulfur chemistry Sulfate mass produced distributed to modes based on number of activated aerosols in modes. Include contribution from H2SO4 (g) uptakes NH3 dissolution on pH Optical properties of internally-mixed hydrated aerosol. Emissions of sea salt with diameters of um from Martensson et al. (2003)

Modal aerosol (1.9x2.5), 3 years - benchmark present-day (PD) simulations - benchmark pre-industrial (PI) simulations Bulk aerosol (1.9x2.5), 3 years, present-day (PD) simulations CAM Simulations (CAM3.5.03) Same emissions (OC, BC, DMS, SO2, SO4) for PD Same emission schemes (dust and coarse sea salt) - ultrafine sea salt emission for Modal aerosol Same oxidant fields for PD and PI (Modal and Bulk) We can specify different MOZART chemistry mechanisms in the pre-processor to enable aerosol-chemistry coupling

BC Column Burden Accumulation modePrimary carbon mode Accumulation modePrimary carbon mode CB1CB2 Modal Bulk

BC zonal mean Accumulation modePrimary carbon mode Modal CB1CB2 Bulk aerosol hygroscopacity

BC Budgets (Modal) Primary Accum. Total Others Emission (Tg/yr) Dry deposition (Tg/yr) Wet deposition (Tg/yr) Total sink (Tg/yr) 6.8 Burden (Tg) 0.024(0.02) 0.084(0.086) 0.11(0.11) Lifetime (days) Results from bulk model in blue

OC Column Burden Accumulation modePrimary carbon mode Modal OC1OC2 Bulk

OC zonal mean Accumulation modePrimary carbon mode Modal CB1CB2 OC1OC2 Bulk

OC Budgets (Modal) Primary Accum. Total Others Emission (Tg/yr) Dry deposition (Tg/yr) Wet deposition (Tg/yr) Total sink (Tg/yr) 27.8 Burden (Tg) 0.16(0.08) 0.38(0.38) 0.54(0.46) Lifetime (days) Results from bulk model in blue

Fine mode (0.1-2 um)Coarse mode (2-10 um) Dust column burden Modal Fine mode ( um)Coarse mode ( um) Emission? Bulk

Dust Budgets (Modal) Fine Coarse Total Others Emission (Tg/yr) (1567) Dry deposition (Tg/yr) Wet deposition (Tg/yr) Total sink (Tg/yr) 1477 Burden (Tg) 3.0(5.4) 6.2(8.2) 9.2(13.7) 4-36 Lifetime (days) Modal: um (fine), 2-10 um (coarse); Bulk: um (fine), um (coarse)

Fine mode ( um)Coarse mode (1-10 um) Sea salt column burden Modal Fine mode (0.2-1 um)Coarse mode (1-20 um) below-cld scavenging coefficient ! Bulk

Sea salt zonal mean Modal Fine mode ( um)Coarse mode (1-10 um) Fine mode (0.2-1 um)Coarse mode (1-20 um) ug/kg Bulk

Sea Salt Budgets (Modal) Fine Coarse Total Others Emission (Tg/yr) (3758) Dry deposition (Tg/yr) Wet deposition (Tg/yr) by below cloud 1046(149) Total sink (Tg/yr) 3854 Burden (Tg) 0.62(0.63) 5.1(11.0) 5.7(11.6) Lifetime (days) Modal: um (fine), 1-10 um (coarse); Bulk: um (fine), 1-10 um (coarse)

SO4 ModalBulk Column burden Zonal sol_fraci !

Burden (Tg S): 0.43 (0.56) Lifetime (days) : 3.3 Global dry deposition (Tg S/yr) : 8.8 Global wet deposition (Tg S/yr) : 38.7 Global SO4 sources (Tg S/yr) : by H2SO4 condensation 9.5 by H2O by O SO4 burden by reservoir (%): by SO4 nuclei mode 2.5% by SO4 accumulation mode 92% by Dust 3% by Sea Salt 2.5% SO4 Budgets (Modal) Results from bulk model in blue

Modal - Compared with RSMAS SO4 Data

Compared with RSMAS SO4 Data ModalBulk

Modal - Compared with IMPROVE SO4 Data

Compared with IMPROVE SO4 Data ModalBulk

Compared with IMPROVE BC Data Modal Bulk Emissions?!

CCN (S=0.1%)

ModalBulkOBS LWP, g m IWP, g m SWCF, W m (ERBE) LWCF, W m (ERBE) FLNTC, W m (ERBE) CLDTOT, % (ISCCP) CLDLOW, % /33.6 (ISCCP/SAGE) Global Annual Means (Present Day)

Aerosol Indirect Effect Global Mean = -1.1 W/m2 Present – Past Shortwave Cloud Forcing (W/m2) Present – Past Liquid Water Path (g/m2)

Timing

Remaining issues Simulation with Morrison microphysics and Modal aerosol reduces the simulated SWCF to -47 W/m2, which is 7-10 W/m2 too small. Simulations with Morrison microphysics and Mozart aerosol using the UW PBL scheme produce excessively large SWCF. Simulations coupling Modal aerosols with Morrison microphysics and the UW PBL scheme should be performed. The simpler version of Modal aerosol should be evaluated. Improvements in primary carbon emissions are needed. A secondary organic aerosol mechanism for modal aerosol is under development. Evaluate simulated aerosol optical depth.

THANKS!

SO4 column burden (Modal) Accumulation modeAitken mode Associated with dustAssociated with sea salt (>0.3 um)