New Features of the 2003 Release of the CMAQ Model Jonathan Pleim 1, Gerald Gipson 2, Shawn Roselle 1, and Jeffrey Young 1 1 ASMD, ARL, NOAA, RTP, NC 2.

Slides:

Advertisements

Similar presentations

POMI Po Valley Model Intercomparison Exercise CAMx model overview In cooperation with AMA - MI.

Advertisements

Use of Lidar Backscatter to Determine the PBL Heights in New York City, NY Jia-Yeong Ku, Chris Hogrefe, Gopal Sistla New York State Department of Environmental.

A PERFORMANCE EVALUATION OF THE ETA - CMAQ AIR QUALITY FORECAST MODEL FOR THE SUMMER OF 2004 CMAS Workshop Chapel Hill, NC 20 October, 2004.

Click to edit Master title style Click to edit Master subtitle style 1 Modeling of 1,3-Butadiene for Urban and Industrial Areas B. Rappenglück and B. Czader.

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

Evaluation of Secondary Organic Aerosols in Atlanta

CMAQ and REMSAD- Model Performance and Ongoing Improvements Brian Timin, Carey Jang, Pat Dolwick, Norm Possiel, Tom Braverman USEPA/OAQPS December 3, 2002.

Improving the Representation of Atmospheric Chemistry in WRF William R. Stockwell Department of Chemistry Howard University.

Christian Seigneur AER San Ramon, CA

4-km AIRPACT vs 12-km AIRPACT Both with dynamic boundary conditions from MOZART-4 Figures created on 5/29/2011 (corrected corrupted JPROC input file)

CENRAP Modeling Workgroup Mational RPO Modeling Meeting May 25-26, Denver CO Calvin Ku Missouri DNR May 25, 2004.

Transitioning CMAQ for NWS Operational AQ Forecasting Jeff McQueen*, Pius Lee*, Marina Tsildulko*, G. DiMego*, B. Katz* R. Mathur,T. Otte, J. Pleim, J.

Next Gen AQ model Need AQ modeling at Global to Continental to Regional to Urban scales – Current systems using cascading nests is cumbersome – Duplicative.

CMAQ (Community Multiscale Air Quality) pollutant Concentration change horizontal advection vertical advection horizontal dispersion vertical diffusion.

1 1 Model studies of some atmospheric aerosols and comparisons with measurements K. G e o r g i e v I P P – B A S, S o f i a, B u l g a r i a.

Air Quality, Atmospheric Deposition, and Lake Tahoe October 15, 2003 Western Regional Pollution Prevention Network Grannlibakken, Lake Tahoe Jim Pederson.

1 CCOS Seasonal Modeling: The Computing Environment S.Tonse, N.J.Brown & R. Harley Lawrence Berkeley National Laboratory University Of California at Berkeley.

A Modeling Investigation of the Climate Effects of Air Pollutants Aijun Xiu 1, Rohit Mathur 2, Adel Hanna 1, Uma Shankar 1, Frank Binkowski 1, Carlie Coats.

Comparison of three photochemical mechanisms (CB4, CB05, SAPRC99) for the Eta-CMAQ air quality forecast model for O 3 during the 2004 ICARTT study Shaocai.

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

EVALUATION AND IMPROVEMENT OF GAS/PARTICLE MASS TRANSFER TREATMENTS FOR 3-D AEROSOL SIMULATION AND FORECAST Xiaoming Hu and Yang Zhang North Carolina State.

Center for Environmental Research and Technology University of California, Riverside Bourns College of Engineering Evaluation and Intercomparison of N.

PM2.5 Model Performance Evaluation- Purpose and Goals PM Model Evaluation Workshop February 10, 2004 Chapel Hill, NC Brian Timin EPA/OAQPS.

WRAP Update. Projects Updated 1996 emissions QA procedures New evaluation tools Model updates CB-IV km MM5 Fugitive dust NH 3 emissions Model.

Synergisms in the Development of the CMAQ and CAMx PM/Ozone Models Ralph E. Morris, Greg Yarwood Chris Emery, Bonyoung Koo ENVIRON International Corporation.

Community Multiscale Air Quality Modeling System CMAQ Air Quality Data Summit February 2008.

Annual Simulations of Models-3/CMAQ: Issues and Lessons Learned Pat Dolwick, Carey Jang, Norm Possiel, Brian Timin, Joe Tikvart Air Quality Modeling Group.

1 Comparison of CAMx and CMAQ PM2.5 Source Apportionment Estimates Kirk Baker and Brian Timin U.S. Environmental Protection Agency, Research Triangle Park,

WRAP Experience: Investigation of Model Biases Uma Shankar, Rohit Mathur and Francis Binkowski MCNC–Environmental Modeling Center Research Triangle Park,

Preliminary Study: Direct and Emission-Induced Effects of Global Climate Change on Regional Ozone and Fine Particulate Matter K. Manomaiphiboon 1 *, A.

Rick Saylor 1, Barry Baker 1, Pius Lee 2, Daniel Tong 2,3, Li Pan 2 and Youhua Tang 2 1 National Oceanic and Atmospheric Administration Air Resources Laboratory.

Gas and Aerosol Partitioning Over the Equatorial Pacific Wenxian Zhang April 21, 2009.

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

Adaptation and Application of the CMAQ Modeling System for Real-time Air Quality Forecasting During the Summer of 2004 R. Mathur, J. Pleim, T. Otte, K.

Using CMAQ-AIM to Evaluate the Gas-Particle Partitioning Treatment in CMAQ Chris Nolte Atmospheric Modeling Division National Exposure Research Laboratory.

Prakash Bhave, Shawn Roselle, Frank Binkowski, Chris Nolte, Shaocai Yu, Jerry Gipson, & Ken Schere CMAS Conference – Paper #6.8 Chapel Hill, NC, October.

A detailed evaluation of the WRF-CMAQ forecast model performance for O 3, and PM 2.5 during the 2006 TexAQS/GoMACCS study Shaocai Yu $, Rohit Mathur +,

Operational Evaluation and Comparison of CMAQ and REMSAD- An Annual Simulation Brian Timin, Carey Jang, Pat Dolwick, Norm Possiel, Tom Braverman USEPA/OAQPS.

Application of the CMAQ-UCD Aerosol Model to a Coastal Urban Site Chris Nolte NOAA Atmospheric Sciences Modeling Division Research Triangle Park, NC 6.

On the interplay between upper and ground levels dynamics and chemistry in determining the surface aerosol budget Gabriele Curci 1, L. Ferrero 2, P. Tuccella.

Model & Chemistry Intercomparison CMAQ with CB4, CB4-2002, SAPRC99 Ralph Morris, Steven Lau, Bongyoung Koo ENVIRON International Corporation Gail Tonnesen,

Prakash V. Bhave, Ph.D. Physical Scientist PM Model Performance Workshop February 10, 2004 Postprocessing Model Output for Comparison to Ambient Data.

Evaluation of the VISTAS 2002 CMAQ/CAMx Annual Simulations T. W. Tesche & Dennis McNally -- Alpine Geophysics, LLC Ralph Morris -- ENVIRON Gail Tonnesen.

Time-Resolved & In-Depth Evaluation of PM and PM Precursors using CMAQ Robin L. Dennis Atmospheric Modeling Division U.S. EPA/ORD:NOAA/ARL PM Model Performance.

Center for Environmental Research and Technology/Air Quality Modeling University of California at Riverside CMAQ Model Performance Evaluation with the.

An Exploration of Model Concentration Differences Between CMAQ and CAMx Brian Timin, Karen Wesson, Pat Dolwick, Norm Possiel, Sharon Phillips EPA/OAQPS.

Jonathan Pleim 1, Shawn Roselle 1, Prakash Bhave 1, Russell Bullock 1, William Hutzell 2, Deborah Luecken 2, Chris Nolte 1, Golam Sarwar 2, Ken Schere.

GEOS-CHEM Modeling for Boundary Conditions and Natural Background James W. Boylan Georgia Department of Natural Resources - VISTAS National RPO Modeling.

Evaluation of Models-3 CMAQ I. Results from the 2003 Release II. Plans for the 2004 Release Model Evaluation Team Members Prakash Bhave, Robin Dennis,

Diagnostic Study on Fine Particulate Matter Predictions of CMAQ in the Southeastern U.S. Ping Liu and Yang Zhang North Carolina State University, Raleigh,

THE MODELS-3 COMMUNITY MULTI- SCALE AIR QUALITY (CMAQ) MODEL: 2002 RELEASE – NEW FEATURES Jonathan Pleim, Francis Binkowski, Robin Dennis, Brian Eder,

DEVELOPMENT AND APPLICATION OF MADRID: A NEW AEROSOL MODULE IN MODELS-3/CMAQ Yang Zhang*, Betty Pun, Krish Vijayaraghavan, Shiang-Yuh Wu and Christian.

Extending Size-Dependent Composition to the Modal Approach: A Case Study with Sea Salt Aerosol Uma Shankar and Rohit Mathur The University of North Carolina.

Georgia Institute of Technology SAMI Aerosol Modeling: Performance Evaluation & Future Year Simulations Talat Odman Georgia Institute of Technology SAMI.

Atmospheric Modeling and Analysis Division,

Office of Research and Development | National Exposure Research Laboratory Atmospheric Sciences Modeling and Analysis Division |Research Triangle Park,

VISTAS Modeling Overview Oct. 29, 2003

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.

W. T. Hutzell 1, G. Pouliot 2, and D. J. Luecken 1 1 Atmospheric Modeling Division, U. S. Environmental Protection Agency 2 Atmospheric Sciences Modeling.

U.S. Environmental Protection Agency Office of Research and Development Implementation of an Online Photolysis Module in CMAQ 4.7 Christopher G. Nolte.

Visualizing Winter Nitrate Formation Using CMAQ Process Analysis Charles Stanier – University of Iowa CENTER FOR.

Sensitivity of PM 2.5 Species to Emissions in the Southeast Sun-Kyoung Park and Armistead G. Russell Georgia Institute of Technology Sensitivity of PM.

Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy Jonathan Pleim, Shawn Roselle,

Development of a Multipollutant Version of the Community Multiscale Air Quality (CMAQ) Modeling System Shawn Roselle, Deborah Luecken, William Hutzell,

Lupu, Semeniuk, Kaminski, Mamun, McConnell

Performance of CMAQ for Inorganic Aerosol Compounds in Greater Tokyo

Simulation of primary and secondary (biogenic and anthropogenic) organic aerosols over the United States by US EPA Models-3/CMAQ: Evaluation and regional.

Changes to the Multi-Pollutant version in the CMAQ 4.7

Development of a 2007-Based Air Quality Modeling Platform

Deborah Luecken and Golam Sarwar U.S. EPA, ORD/NERL

Presentation transcript:

New Features of the 2003 Release of the CMAQ Model Jonathan Pleim 1, Gerald Gipson 2, Shawn Roselle 1, and Jeffrey Young 1 1 ASMD, ARL, NOAA, RTP, NC 2 AMD, NERL, USEPA, RTP, NC

What’s new in CMAQ 2003 Updates to science Updates to science Updates to Nitrate aerosol and Nitric acidUpdates to Nitrate aerosol and Nitric acid Updates to Secondary Organic AerosolsUpdates to Secondary Organic Aerosols Efficiency improvements Efficiency improvements Faster chemistry solverFaster chemistry solver Modified model time steppingModified model time stepping Other updates and corrections Other updates and corrections Air Quality Forecasting Air Quality Forecasting

Nitrate Previous release (2002) shows large overprediction of Nitrate aerosol and Nitric acid

Nitrate related changes Dry Deposition (winter) Dry Deposition (winter) Added explicit resistance to snow and ice with dependence on temperature (melting)Added explicit resistance to snow and ice with dependence on temperature (melting) Modified cuticle resistance for NH 3 as function of relative humidityModified cuticle resistance for NH 3 as function of relative humidity Added wet ground similarly to wet canopyAdded wet ground similarly to wet canopy Revised model produces much greater V d for NH 3 thus reducing ammonium nitrate aerosol concentrationsRevised model produces much greater V d for NH 3 thus reducing ammonium nitrate aerosol concentrations Heterogeneous and Gas-Phase Reactions Heterogeneous and Gas-Phase Reactions Gas-phase nitric acid also greatly overpredictedGas-phase nitric acid also greatly overpredicted Identified key pathway: N 2 O 5 + H 2 O --> 2HNO 3Identified key pathway: N 2 O 5 + H 2 O --> 2HNO 3 Revised the heterogeneous reaction rateRevised the heterogeneous reaction rate Turned off gas phase reactionTurned off gas phase reaction

Heterogeneous N 2 O 5 Reaction 2002 release 2002 release Reaction probability γ = 0.1 recommended by Dentener and Crutzen (JGR 1993)Reaction probability γ = 0.1 recommended by Dentener and Crutzen (JGR 1993) Makes a lot of HNO 3 at nightMakes a lot of HNO 3 at night Recent studies show wide range of γ values Recent studies show wide range of γ values Dependence on humidity, temperature, chemical composition - sulfate, nitrate, and organic contentDependence on humidity, temperature, chemical composition - sulfate, nitrate, and organic content Updated version Updated version Reaction probability γ = depending on NO 3 /(SO 4 +NO 3 ) according to Riemer et al. (JGR 2003) based on lab measurements of Mentel et al (PCCP 1999)Reaction probability γ = depending on NO 3 /(SO 4 +NO 3 ) according to Riemer et al. (JGR 2003) based on lab measurements of Mentel et al (PCCP 1999)

2003 release vs 2002 release Aerosol NitrateGas Phase Nitric Acid January 4 – 20, 2002

CMAQ02 vs CMAQ03 - Nitrate Average concentrations January 4 – 20, 2002 Nitrate Aerosol CMAQ02 Nitrate Aerosol diff Nitrate Aerosol CMAQ03 Total Nitrate diff

Secondary Organic Aerosols Corrections to Gas-Particle partitioning to allow reversibility Corrections to Gas-Particle partitioning to allow reversibility Lowers SOA concentrations by 60-70%Lowers SOA concentrations by 60-70% SOA precursor factors for SAPRC99 SOA precursor factors for SAPRC99 57% of ALK5 (longer chain alkanes)57% of ALK5 (longer chain alkanes) 93% of ARO1 (less reactive aromatics)93% of ARO1 (less reactive aromatics) Eliminated SOA from olefinsEliminated SOA from olefins SOA production in CB4 unchanged SOA production in CB4 unchanged No production from alkanes or olefinsNo production from alkanes or olefins 100% of aromatics100% of aromatics

Organic Carbon Aerosol June 15 – 29, 1999Jan , 2002

CMAQ02 vs CMAQ03 - SOA Total SOA CMAQ02 Total SOA CMAQ03 Total SOA diff Total SOA Ratio: 03/02 Average concentrations June 15 – 29, 1999

Changes for improved efficiency Euler Backward Iterative (EBI) solver Euler Backward Iterative (EBI) solver EBI uses analytical solution for two chemical groups rather than numerical solution used in MEBIEBI uses analytical solution for two chemical groups rather than numerical solution used in MEBI EBI about twice as fast as MEBIEBI about twice as fast as MEBI Currently for CB4 onlyCurrently for CB4 only Eliminated transport for radical species Eliminated transport for radical species Layer dependent advection time steps Layer dependent advection time steps Synchronization time step set by Courant condition in lower layers (up to sigma=0.7)Synchronization time step set by Courant condition in lower layers (up to sigma=0.7) Multiple advection steps allowed in upper layersMultiple advection steps allowed in upper layers Maximum sync time step changed to 12 min and minimum to 1 min for improved accuracyMaximum sync time step changed to 12 min and minimum to 1 min for improved accuracy

Other Updates Cloud processes and aqueous chemistry Cloud processes and aqueous chemistry Updated equilibrium constantsUpdated equilibrium constants Corrected vertical diffusion of aerosols (density -> mixing ratio) Corrected vertical diffusion of aerosols (density -> mixing ratio) Reordered operators Reordered operators Vertical diffusion with emissions Vertical diffusion with emissions Advection (x,y,z) Advection (x,y,z) Horizontal diffusion Horizontal diffusion Clouds Clouds Gas chem Gas chem Aerosols Aerosols

Updates to other system components Latest MCIP - version 2.2 Latest MCIP - version 2.2 Major corrections to layer interpolation of winds and vertical velocity (v2.1)Major corrections to layer interpolation of winds and vertical velocity (v2.1) Updated dry deposition for both M3dry and RADMdryUpdated dry deposition for both M3dry and RADMdry Emission modeling (George’s Presentation) Emission modeling (George’s Presentation)

AQF System NWS Eta model forecasts NWS Eta model forecasts Interpolated to 22 layer CMAQ gridInterpolated to 22 layer CMAQ grid Hourly output with additional variablesHourly output with additional variables AQF version of CMAQ AQF version of CMAQ Optimized for massive parallel systemOptimized for massive parallel system New version of MCIP called PremaqNew version of MCIP called Premaq Testing this past summer (2003):Testing this past summer (2003): 48 hr forecasts starting at 12z 48 hr forecasts starting at 12z 30 hr forecasts starting at 6z 30 hr forecasts starting at 6z 6 hourly cycling 6 hourly cycling

AQF Ozone – Aug 14, 2003

Future Work EBI for SAPRC99 EBI for SAPRC99 New mass conservation technique New mass conservation technique New PBL models New PBL models CB CB New advection schemes New advection schemes WRF connections WRF connections Source apportionment for primary aerosols Source apportionment for primary aerosols Coarse aerosol improvements Coarse aerosol improvements Sectional aerosol models Sectional aerosol models Continued performance improvements Continued performance improvements

Further information EPA’s CMAQ website: EPA’s CMAQ website: Click on Model changes for more detailed description of changes for the 2003 releaseClick on Model changes for more detailed description of changes for the 2003 release Click on Announcements and then on Performance Evaluation for the August 2003 Release of CMAQ for a powerpoint presentationClick on Announcements and then on Performance Evaluation for the August 2003 Release of CMAQ for a powerpoint presentation

Related ASMD Presentations Brian Eder: Evaluation results Brian Eder: Evaluation results 2003 release of CMAQ2003 release of CMAQ AQF CMAQAQF CMAQ George Pouliot: latest developments in emission modeling George Pouliot: latest developments in emission modeling Jason Ching: Air toxic modeling Jason Ching: Air toxic modeling Shaocai Yu: Shaocai Yu: Diagnostic analysis of CMAQ SOADiagnostic analysis of CMAQ SOA Poster: Primary and secondary SOAPoster: Primary and secondary SOA Poster: Thermodynamic aerosol modelsPoster: Thermodynamic aerosol models Jeff Arnold: CMAQ Sensitivity to vertical mixing Jeff Arnold: CMAQ Sensitivity to vertical mixing Jeff Young: Parallel CMAQ Jeff Young: Parallel CMAQ

AQF Ozone – Aug 15, 2003