Continuous Development and Application of Global-

Through-Urban WRF/Chem (GU-WRF/Chem)

Yang Zhang, Ying Pan, Yao-Sheng Chen, and Priya R. Pillai

North Carolina State University, Raleigh, NC

R83337601

• Background and Motivation

• Development and Application of GU-WRF/Chem

• Model Development and Evaluation Highlights

• Climate-Chemistry-Aerosol-Cloud-Radiation Feedbacks

– Direct Effects on Shortwave Radiation

– Semi-Direct Effects on PBL Meteorology

– Indirect Effects on CCN

• Simulation of Future Air Quality

• Summary and Future Work

Development and Application of Global-through-Urban

Weather Research and Forecasting Model with Chemistry

(GU-WRF/Chem)• Key Model Development

– Globalize WRF/Chem and compile global emissions with regional updates

– Project 2050 emission changes based on IPCC A1B scenario

– Develop/improve model treatments for global-through-urban applications

– Incorporate SAPRC99/CB05/CB05GE, MADRID, aero. act., nucleation

– Couple gaseous mechanisms with default and new aerosol/cloud modules

– Improve other treatments (e.g., FTUV, dust, SOA, plume-in-grid)

• Model Evaluation of Current-Year (2001) Simulations

– Met: T, QV, Precip, Radiation from NCEP/NCAR, NCDC, CMAP, TRMM,

BSRN

– Chem: O3 and PM2.5 from CASTNET, STN, IMPROVE, AIRS-AQS, SEARCH

col. CO, NO2, and TOR from MOPITT, GOME, OMI, TOMS/SBUV

– Other: AOD, CCN, CDNC, Cld. Fraction, COD, CER from MODIS• Model Intercomparison and Trend Study of Future-Year (2050) Simulations

– Intercomparison: 2050 GU-WRF/Chem vs. 2046-2055 10-yr average CCSM

– Trend Analysis: 2050 vs. 2001 GU-WRF/Chem

– Comparisons with other models (e.g., IPCC)

Gases-Aerosols-Clouds-Precipitation Interactions

EvaporationActivation

CCN

Aerosols

Cloud droplets Cloud processed aerosols

Below-Cloud ScavengingFalling PrecipitationWet Deposition

Aerosol Growth to Form CCNCoalescence of Droplets and AerosolsAqueous-Phase/Heterogeneous ReactionsAutoconversionIn-Cloud Scavenging

Binary Homogeneous NucleationTernary Homogeneous NucleationActivation/Kinetic NucleationIon-Induced/Mediated Nucleation

New particlesAerosols

CondensationCoagulationHetero. Nucleation

Gas molecules

Initial growth

Nucleation:���� McMurry and Friedlander, 1979 (MF79, base)���� Sihto et al., 2006 (SI06)���� Yu, 2009 (YU09)

Aerosol Activation:

���� Abdul Razzak-Ghan 2000 (AR-G00, base)���� Fountoukis-Nenes 2005 (F-N05)

Nested GU-WRF/Chem Simulations(Base Configurations: FTUV/CB05GE/MADRID/CMU/Abdul Razzak-Ghan)

D01: Global D02: Trans-Pacific D03: CONUS and China D04: E. US

• Domain: D01: 4˚̊̊̊ ×××× 5˚̊̊̊, 45 (latitude) × 72 (longitude) (Global)

D02: 1.0˚̊̊̊ ×××× 1.25˚̊̊̊, 44 × 192 (Trans-Pacific)

D03: 0.33˚̊̊̊ ×××× 0.42˚̊̊̊, 84× 168 (CONUS), 99× 177 (China)

D04: 0.08˚̊̊̊ ×××× 0.10˚̊̊̊, 136× 144 (E. US)

D02

D01

D03 - CHINA D03 - CONUS

D04 - EUS

• Period: Met only: 2001/2050 full-year

Gas and PM; w and w/o Asian Emis:

2001 Jan/Jul

Gas and PM : 2050 Jan/Jul

Simulated PM Number Concentration (cm-3)

Base

SI06

F-N05

YU09

Simulated Cloud Condensation Nuclei (CCN) at S = 0.5%

Base

SI06

F-N05

YU09

Simulated Cloud Droplet Number Conc. (CDNC) (cm-3)

Base

SI06

F-N05

YU09

Base

(M-F79,

AR-G00)

F-N05

Observation

Obs vs. Sim Cloud-Related Variables

SI06 (EPL1)

YU09 (IMN)

CDNC at 937 mb (cm-3)CCN at S=0.5% (10 x 109 cm-2) Total Precipitation (mm/day)

CMAPUWM/MODISMODIS

NMB=6.3% NMB=4.2%NMB=-55.7%

NMB=26.4%

NMB=583.1%

NMB=39.3%

NMB=-38.4%

NMB=-47.3%

NMB=-64.6%

NMB=2.1%

NMB=-10.2%

NMB=-9.3%

Direct Effects of PM on Shortwave Radiation in July 2001

Absolute Difference

PM decreases

net shortwave

radiation (up to

43 W m-2 or 29%)

over most US,

China, and many

other polluted

regions

Semi-Direct Effects of PM on PBL Height (PBLH) in 2001Absolute Difference

PM decreases

PBLH (up to 200

m or 24%) over

polluted regions,

indicating a

more stable PBL

that exacerbates

existing air

pollution

January July

Indirect Effects of PM on Surface CCN (S=1%) in 2001

PM enhances

CCN (by up to

44500 cm-3 at

S=1.0%) over

many polluted

regions; higher

CCN conc. in

Jan. due to

higher PM

conc.

January July

Simulated Changes in Monthly-Mean PM2.5 Concentrations: 2050 vs. 2001

2050

Jan.

Jul.

2050-2001, % Diff

GU-WRF/Chem gives higher PM2.5 in Jan/Jul over most continents

Simulated Changes in Monthly-Mean CCN and CDNC: 2050 vs. 2001

Jan.

Jul.

Column CCN (% change)

GU-WRF/Chem gives higher CCN and CDNC in Jan/Jul over most continents

Column CDNC

Summary and Future Work

� Simulated aerosol, radiation, and cloud properties exhibit small-to-high

sensitivity to nucleation and aerosol activation parameterizations

� Higher sensitivity to nucleation parameterizations: PM mass and number, CCN, Precip

� Higher sensitivity to activation parameterizations: AOD, COT, CDNC, LWP, Reff

� Small sensitivity: OLR, GLW, GSW, SWDOWN, RSWTOA, CF

� A difference of 2-9 orders of magnitude in nucleation rates leads to

differences by factors of 2-7 in PM num. conc., 4-7 in CCN, and up to ~3 in

CDNC; a difference by factors of ~1-4 in activation fractions leads to

differences by up to ~20% in CCN and a factor of ~4 in CDNC.

� Feedbacks to climate potentially important yet not fully understood; observations needed to verify feedbacks and improve models

� Use feedbacks to guide win-win emission control strategies for CC/AQ� Isolate and quantify complex speciated feedbacks: GHGs, cooling and warming PM� Assess the effectiveness of O3 and PM attainment plans under different future emission

scenarios and a changing climate

Acknowledgments� Project sponsor: US EPA STAR #R83337601

� Mark Richardson, Caltech, William C. Skamarock, NCAR, for sharing global WRF, and Louisa Emmons & Francis Vitt, NCAR, for CAM4 emissions

� Georg Grell, Steve Peckham, and Stuart McKeen, NOAA/ESRL, for public release of WRF/Chem

� Jerome Fast, Steve Ghan, Richard Easter, and Rahul Zaveri, PNNL, for public release of PNNL’s version of WRF/Chem

� Ken Schere, Golam Sarwar, and Shawn Roselle, U.S. EPA, for providing CB05 and CB05Cltx

� Prakash Karamchandani, AER, Inc., for co-developing CB05_GE

� Athanasios Nenes, Georgia Tech., for providing FN05 aerosol activation code

� Fangqun Yu, State University of New York, Albany, NY, for providing ion-mediated nucleation code

� Peter McMurry, Univ. of Minnesota, for providing observed PM number conc.

� Jack Fishman and John K. Creilson, NASA Langley Research Center, for providing TOR data