Skip this Video
Download Presentation
Simultaneous forecasts of air quality and weather using WRF/Chem & Ensemble air quality modeling and its economic value

Loading in 2 Seconds...

play fullscreen
1 / 17

Simultaneous forecasts of air quality and weather using WRF - PowerPoint PPT Presentation

  • Uploaded on

Simultaneous forecasts of air quality and weather using WRF/Chem & Ensemble air quality modeling and its economic value. Georg A. Grell, Steven E. Peckham, Mariusz Pagowski The Cooperative Institute for Research in Environmental Sciences, The Cooperative Institute for Research in

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Simultaneous forecasts of air quality and weather using WRF' - akio

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Simultaneous forecasts of air quality and weather using WRF/Chem&Ensemble air quality modeling and its economic value

Georg A. Grell, Steven E. Peckham,

Mariusz Pagowski

The Cooperative Institute for Research in

Environmental Sciences,

The Cooperative Institute for Research in

the Atmosphere


NOAA Earth System Research Laboratory, Global System Division

  • WRF Chemistry model (WRF/Chem)
    • Current status, latest additions
  • Ensemble modeling during ICARTT/NEAQS experiment
wrf chem

“Online” (also called “inline”) chemistry

  • Consistent: all transport done by meteorology model
    • Same vertical and horizontal coordinates (no horizontal and vertical interpolation)
    • Same physics parameterization for subgrid scale
    • No interpolation in time
  • Easy handling (Data management)
  • Least amount of computing time if only doing one simulation
Directly involved in major WRF/Chem development


Georg Grell, Steven Peckham, Stuart McKeen


Jerome Fast, Bill Gustafson, Rahul A. Zaveri, James C. Barnard


Bill Skamarock

Rainer Schmitz (University of Chile – Santiago, Chile)

Marc Salzmann (Max Planck Institute for Chemistry – Mainz, Germany)


Many more national and international collaborators

About 250 registered users

wrf chem chemistry package v2 1 2
WRF/Chem Chemistry Package – V2.1.2
  • Chemical mechanisms:
    • RADM2, Carbon Bond (CBMZ)
  • Photolysis (coupled with hydrometeors and aerosols):
    • Madronich, Fast-j (coupled to aerosols and microphysics)
  • Deposition:
    • Dry deposition (coupled with soil/veg scheme, “flux-resistance” analogy)
    • Simplified wet deposition by convective parameterization
  • Biogenic emissions:
    • Guenther – online calculation based on USGS landuse, T and radiation
    • BEISv3.11 (modify reference fields produced from complex landuse data)
wrf chem aerosols v2 1 2
WRF/Chem Aerosols – V2.1.2
  • Modal approach – Binkowski and Shankar 1995, Ackermann et al. 1998, Schell et al. 2001
    • Modal Aerosol Dynamics Model for Europe (MADE)

modified to include Secondary Organic Aerosols (SOA)

  • Sectional approach - Zaveri et al., 2005, 2006
    • Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) (4 or 8 bins)
wrf chemv2 1 2 aerosol direct effect
WRF/ChemV2.1.2: Aerosol direct effect

Aerosols coupled to the Goddard atmospheric

radiation scheme

  • July 23, 2004, 2100Z

From Chung et al. 2007, submitted

Surface temperature difference from run with/without aerosols

Aerosol absorption induce cloud changes via radiation but no account for effect on nucleation in clouds


Comparison with 350 Ozone monitors during ICARTT/NEAQS experiment – 8hr peak

Evaluation period: July 12 – July 31, 2004

Continuous model improvement over the last 2 years

additions in wrf chem v2 2
Additions in WRF/Chem V2.2
  • Kinetic PreProcessor (KPP), MPI Mainz
  • Improved convective (non-resolved) transport, coupling of convective parameterization with atmospheric and photolysis radiation (ESRL/GSD)
  • Non-resolved and resolved aqueous phase chemistry, wet deposition, (NOAA/ARL/EPA, PNNL,ESRL/GSD)
  • 2-way nesting (PNNL, ESRL/GSD)
  • Cloud-aerosol interaction (indirect effect) with Lin et al. 6-class microphysics scheme (PNNL)
  • Lateral boundary conditions from global models (U of Chile, ESRL/GSD)
  • Urban parameterizations (NCAR, coming soon Spain)
  • Positive definite advection (NCAR)
  • NMM and ARW dynamic cores (ESRL/GSD)
  • Offline version for the ARW core (to be released shortly, C-DAC, India and ESRL/GSD))
ICARTT/NEAQS(International Consortium for Atmospheric Research on Transport and Transformation/ New England Air Quality Study)
  • From 6 July to 30 August 2004.
  • Over 350 observation sites measuring 1-hr average ozone concentrations - 16480 observations.
  • Only 87 exceedances of 85 ppbv threshold, no exceedances of 125 ppbv threshold.
icartt neaqs
  • Models participating
    • AURAMS (MSC, Canada)
    • CHRONOS (MSC, Canada)
    • CMAQ (EPA, USA)
    • MAQSIP at two resolutions (BAMS, USA)
    • STEM-2K3 (U of Iowa, USA)
    • WRF/Chem (NOAA/ESRL, USA)
  • Different chemical mechanisms, meteorological drivers, emission inventories, horizontal and vertical resolutions.
  • 24-hour forecasts issued at 0000 UTC (0600 UTC – CMAQ)
economic value of forecasts
Economic Value of Forecasts

Contingency table:


Yes No

Yes a (C) b (C)


No c (L) d (0)

C - cost of preventive action

L - loss due to lack of prevention

Probabilistic forecasts: need to assign thresholds for probability.

Decision analytic model: Murphy (1977)

economic value of forecasts13
Economic Value of Forecasts

Relative economic value of forecasts - Richardson (2000, 2003)

economic value of forecasts ecv
Economic Value of Forecasts (ECV)

Optimum decision level (ECV maximized) when forecast

probability equals cost-loss ratio.

economic value of forecasts15
Economic Value of Forecasts

50 ppbv

70 ppbv

85 ppbv

8hr daily

max O3

black - individual models, green - ensemble average, blue - deterministic ensemble DLR,

red – probabilistic, purple – probabilistic DLR

1hr daily

max O3



  • Economic value of deterministic forecasts derived from the

ensemble of models is superior to the results obtained for

the individual models.

  • Maximum economic value is achieved by converting forecasts

of ensemble members to probabilistic framework. The

economic value of probabilistic forecasts is superior to the

deterministic forecasts over a wide range of cost-loss ratios

and for nearly all thresholds analyzed.



  • Data Assimilation (3DVAR, 4DVAR)
  • Global WRF/Chem
  • SMOKE emission module
  • Aerosols – direct and indirect effects

Contact:, User Group and Support