Grid-scale indirect radiative forcing of climate due to aerosols over the northern hemisphere simulated by the integrated

WRF-CMAQ model: Preliminary results

Shaocai Yu*, Kiran Alapaty, Jonathan Pleim, Rohit Mathur, David Wong, and Jia Xing

Atmospheric Modeling and Analysis Division, National Exposure Research Lab, U.S. EPA, RTP, NC 27711

*now ORAU at Atmospheric Modeling Branch, Army Research Lab, WSMR, NM 88002

Approved for Public Release; Distribution Unlimited

Introduction (Motivation)

Aerosol-Cloud-Climate Interaction (Yu, 1999)

Aerosol-radiation interaction

Cloud-radiation interaction

Aerosol-Cloud interaction

Indirect aerosol forcing (IAF)

First: cloud number

Second: cloud life

Glaciation IAF: Ice nuclei

Largest uncertainty (IPCC, 2007): indirect aerosol forcing

Objectives

Simulate Grid-scale indirect aerosol effects using the newly-developed 2-way coupled WRF-CMAQ over northern hemisphere

Evaluate model performance on cloud properties (SWCF, LWCF, etc) and PM2.5 with observations

Model Description (Configuration)

WRF, CMAQ models

Weather Research Forecast (WRF) model Most popular meteorological model (V3.4)

U.S. EPA CMAQ: (public release)most popular air quality CTM model (V5.0)

Indirect aerosol effects on grid-scale clouds have been implemented in the two-way coupled WRF-CMAQ model:

“Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF-CMAQ: model description, development, evaluation and regional analysis” by Yu et al., (Atmos. Chem. Phys. Discuss., 13, 25649–25739, 2013)

Aerosols: number, size, chemical composition

CCN, Cloud droplet number

Cloud microphysics (Morrison): cloud vapor and water, rain, ice, snow, graupel

Cloud effective radius (re), COD

The 1st and 2nd IAF

Coupled WRF-CMAQ aerosol simulation

Aerosol activation scheme (Abdul-Razzak and Ghan, 2000, 2002)

Updraft velocity, liquid water content (WRF)

Radiative transfer model:

RRTMg: re(2-60) m

Met fields (WRF)

Sulfate, BC, OC, dust

Ice number Conc., IN

Ice effective radius (rie), IOD

Glaciation IAF

Model Description (Configuration)Calculation of indirect aerosol forcing in WRF-CMAQ (Yu et al., 2013)

Updraft velocity, ice water content (WRF), temperature

CAM ice nucleation scheme (Liu et al. 2007)

Model Description (Configuration)

Hemispheric WRF-CMAQ simulations

WPS runs: NCEP/NCAR Reanalysis

Surface analysis nudging: NCEP ADP Operational Global Surface Obs

Emissions over the Northern Hemisphere:

Anthropogenic: Emissions Database for Global Atmospheric Research (EDGAR)

Biogenic VOC and lightning NOx: GEIA (Global Emission Inventory Activity)

For detailed model configurations:

See next presentation of Xing Jia

Observations

Satellite observations

CERES data: • COD, cloud fraction, cloud and ice effective radius

• Shortwave cloud forcing (SWCF), longwave cloud forcing (LWCF)

SWCF= reflected SWclr-reflected SWtot at TOA, negative

LWCF= outgoing LWclr-outgoing LWtot at TOA, positive

MODIS, MISR, CALIOP data:

• AOD, LWC, cloud effective radius, COD, ice particle size

Model domain

108 km domain over the northern hemisphere

Simulation period: August of 2006

Results (SWCF) (preliminary results)

WRF (only)

WRF-CMAQ

CERES Obs

August 1, 2006

WRF (only) with subgrid cloud-radiation effect (Alapaty et al. 2012)

Daily Monthly

Results (SWCF) (preliminary results)

WRF (only)

WRF-CMAQ

CERES Obs

WRF (only) with subgrid cloud-radiation effect (Alapaty et al. 2012)

August 2, 2006

MonthlyDaily

Results (SWCF) (preliminary results)

WRF (only)

WRF-CMAQ (Aug 1-3 mean)

CERES Obs

WRF (only) with subgrid cloud-radiation effect (Alapaty et al. 2012)

Monthly Mean for August, 2006

WRF-CMAQ significantly improves relative to WRF

Results (Shortwave cloud forcing)Comparison of Monthly means SWCF (August) over the continental U.S. (Yu et al., 2013)

12-km simulations with both indirect and direct aerosol forcing (WRF-CMAQ) are the best with very good correlation coefficients

12-km runs still underestimate SWCF over land

Land Ocean Obs (CERES) Corr NMB (%) Corr NMB (%)CAMWRF-CMAQ 0.96 -18.18 0.90 1.21WRF (only) 0.50 -5.01 -0.55 53.86RRTMGWRF-CMAQ 0.96 -27.44 0.93 -18.91WRF (only) 0.72 -30.45 -0.48 14.90

Ocean

Land

Results Possible use of NH simulation results for Army Research Lab’s (ARL) globally relocatable limited-area convective-scale WRF FDDA nowcasting project

ARL is developing Weather Running Estimate-Nowcast (WRE-N) (Dumais et al., 2013)

Based on WRF-ARW model

Observation nudging-based 4-D data assimilation (FDDA) methodology

WRF-CMAQ NH simulations can provide ARL NH WRE-N nowcasting for specific locations and regions:

Initial conditions and boundary conditions

Aerosol fields

Contacts:

Brian K. Eder

email: eder@hpcc.epa.gov

www.arl.noaa.gov/

www.epa.gov/asmdnerl

Conclusions (Preliminary) Indirect aerosol forcing with both cloud drop and ice numbers

estimated from the CMAQ-predicted aerosols has been successfully implemented in WRF-CMAQ (Yu et al., 2013).

On the basis of simulations over the NH for August1-2 of 2006 for SWCF Including the subgrid cloud-radiation interaction improved

the model simulationsWRF-CMAQ produces much better results than WRF onlyHope to finish the NH simulations for August of 2006 and

do monthly mean model evaluations.

When we run the model at the coarse resolution (>12 km)

Need to consider the aerosol effects on the subgrid convective clouds (on-going project in Kiran’s group)

Meteorological ModelWRF modeling System:

x=12 km, 4km34 layersLand-Surface: PX LSMPBL: ACM2Cloud Physics: MorrisonCumulus: Kain-Fritsch, not for 4kmShortwave: RRTMg, or CAMLongwave: RRTMg, or CAM

Coupler

Chemical Transport ModelCMAQ Modeling System:

Photochemistry: CB05 59 organic and inorganic species, 156 chemical reactions

Aerosol module: AE6 3 lognormal modes, organic and inorganicEmission: SMOKE In-line emission for biogenic species

AQPREPPrepares virtual CMAQ compatible input met. files

CMAQ-mixactivate:cloud drop, ice number conc.

Direct forcing:Aerosol size, composition, conc.

Two-way coupled WRF-CMAQ modeling System (Interaction and feedback)