slide1
Download
Skip this Video
Download Presentation
The Development of a Hybrid Meteorological Field

Loading in 2 Seconds...

play fullscreen
1 / 17

The Development of a Hybrid Meteorological Field - PowerPoint PPT Presentation


  • 73 Views
  • Uploaded on

The Development of a Hybrid Meteorological Field to Improve Ozone Simulation Results in the CCOS Domain. Bruce Jackson * , Kemal Gurer, Daniel Chau, and Ajith Kaduwela California Environmental Protection Agency/Air Resources Board

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

PowerPoint Slideshow about ' The Development of a Hybrid Meteorological Field ' - aquarius


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
slide1

The Development of a Hybrid Meteorological Field

to Improve Ozone Simulation Results in the CCOS Domain

Bruce Jackson*, Kemal Gurer, Daniel Chau, and Ajith Kaduwela

California Environmental Protection Agency/Air Resources Board

Planning and Technical Support Division

California Air Resources Board/PTSD April, 2005

slide2

Pacific

Ocean

Central California Ozone Study (CCOS) Modeling Domain

and RWP/RASS Locations

California Air Resources Board/PTSD April, 2005

slide3

Why Use Hybrid Meteorological Fields?

Prognostic Models are:

-- “the latest science”

-- “the state-of-the-art”

-- observational FDDA to

improve simulations

California Air Resources Board/PTSD April, 2005

slide4

Prognostic Model Contributions to CCOS Episodes

California Air Resources Board

NOAA/ETL

Bay Area Air Quality Management District

ENVIRON

Desert Research Institute

Alpine Geophysics

California Air Resources Board/PTSD April, 2005

slide5

CCOS MM5 Simulations

MM5 Domain

Lambert Projection at 30 N, 60 N, and 120.5 W

36-km, 12-km, and 4-km nested domains

4-km domain, 189x189 grid cells

50 vertical layers -- first layer ~ 23 m

MM5_N1: observational FDDA included

Land Surface Module

ETA Boundary Layer Module

MM5_N2: no observational FDDA

5-Layer Soil Module

ETA Boundary Layer Module

California Air Resources Board/PTSD April, 2005

slide6

Simulated surface winds for August 02, 2000 at 0200 PDT using

the MM5 model without observational FDDA (MM5_N2)

California Air Resources Board/PTSD April, 2005

slide7

Simulated surface winds for August 02, 2000 at 0200 PDT using

the MM5 model with observational FDDA (MM5_N1)

California Air Resources Board/PTSD April, 2005

slide8

Simulated 500 magl winds for August 01, 2000 at 0200 PDT using

the MM5 model without observational FDDA (MM5_N2)

California Air Resources Board/PTSD April, 2005

slide9

Simulated 500 magl winds for August 01, 2000 at 0600 PDT using

the MM5 model with observational FDDA (MM5_N1)

California Air Resources Board/PTSD April, 2005

slide10

Objective/Prognostic Hybrid Wind Fields

S ( Uk *1/Rk2 ) * (1 - W) + ( Upij * 1/Rp2 ) * W

Uij =

S (1/Rk2) * (1 - W) + 1/Rp2 * W

where: Uij wind component for cell ‘ij’

Uk observed wind component for site ‘k’

Rk radial distance to site ‘k’

Upij prognostic wind component for cell ‘ij’

Rp effective radial distance for prognostic component

W relative weighting factor for prognostic wind

components

California Air Resources Board/PTSD April, 2005

slide11

Objective/Prognostic Hybrid Meteorology

CALMET Diagnostic Model

The horizontal coordinate system for the objective analysis is

identical to that used in MM5

Surface winds extrapolated vertically to 200 magl

Air temperatures adjusted for height prior to extrapolation

Interpolation barriers were added along the crests of the

mountain ranges

California Air Resources Board/PTSD April, 2005

slide12

CCOS Air Quality Modeling Domain

Horizontal Domain: 185 x 185, 4-km cells

Vertical Domain: 16 vertical layers to 5000 magl

Air Quality Model: CAMx/SAPRC99

Episode Period: July 31 - August 02, 2000

Simulation Period: July 29 - August 02, 2000

Model Performance

Subregions: San Francisco Bay Area

Sacramento and Sacramento

River Delta

Southern San Joaquin Valley

California Air Resources Board/PTSD April, 2005

slide13

SAC

SF

So.SJV

CCOS Domain Model Performance Subregions

California Air Resources Board/PTSD April, 2005

slide14

Maximum Ozone Concentrations* Observed During the

July/August, 2000 CCOS Episode

Jul 31 Aug 01 Aug 02

Subregion ppb ppb ppb

------------------------------------------------

SF Bay Area 126 109 100

Sacramento Area 110 134 131

So. San Joaquin 115 116 151

------------------------------------------------

* the peak concentrations for the episode have been highlighted

California Air Resources Board/PTSD April, 2005

slide15

USEPA (1991) Model Performance Guidelines for Ozone

Statistical Measure Acceptance Range

Unpaired Peak Ratio (UPkR) : 0.80 - 1.20

Paired Normalized Bias (NB) **: +/- 15%

** for observed ozone concentrations in excess of 60 ppb

California Air Resources Board/PTSD April, 2005

slide16

Ozone Model Performance (USEPA, 1991)* for the CCOS

July/August, 2000 Episode Using CAMx/SAPRC99f

Jul 31 Aug 01 Aug 02

UPkR NB UPkR NB UPKR NB

ppb % ppb % ppb %

---------------------------------------------------

CMHb Model

SF Bay Area 0.97 +061.14 -04 1.16 -41

Sacramento 1.35 +09 0.99 00 0.99 -10

Southern SJV 1.10 -02 1.03 -10 0.88 -09

MM5_N1 Model (w/ FDDA)

SF Bay Area 0.88 +01 1.05 -11 1.04 -37

Sacramento 1.22 +02 1.00 -10 0.90 -18

Southern SJV 0.95 -07 0.88 -17 0.73 -19

MM5_N2 Model (wo/ FDDA)

SF Bay Area 0.98 +03 1.11 -23 1.16 -14

Sacramento 1.32 +08 0.93 -18 0.96 -03

Southern SJV 1.06 -03 1.03 -11 0.78 -19

---------------------------------------------------

UPkR -- Unpaired Peak Ratio

NB -- Paired Mean Normalized Bias

* simulations meeting USEPA model performance guidelines are highlighted

California Air Resources Board/PTSD April, 2005

slide17

Conclusions

Hybrid meteorological fields using objective analysis can result in

better agreement with observed winds, resulting in improved air

quality model performance.

Prognostic model results are not a substitute for meteorological

fields built on a good observational network.

Prognostic models such as MM5 should not be promoted to

the exclusion of alternative methodologies.

California Air Resources Board/PTSD April, 2005

ad