Impact of Meteorological Inputs on Surface O3 Prediction

Jianping Huang

9th CMAS Annual Conference

Oct. 12, 2010, Chapel, NC

Co-Authors Jeff McQueen1, Youhua Tang1,2, Binbin Zhou1,2,

Marina Tsidulko1,2, Ho-Chun Huang1,2, Sarah Lu1,2, Brad Ferrier1,2, Bill Lapenta1, Geoff DiMego1 (1: NOAA/NCEP/EMC, 2: IMSG)

Daewon Byun3, Pius Lee3, Daniel Tong3,4 (3: NOAA/ARL, 4: ERT)

Ivanka Stajner (NOAA/NWS/OST)

Motivation and objectives Motivation

- O3 over-predicted especially by CB05 and in coastal regions

Objectives

- to evaluate meteorological inputs

- to reduce O3 over-prediction

Outline National Air Quality Forecasting

Capability Current issue of O3 forecasting Verification of meteorological inputs Sensitivity ofO3 prediction to cloud

parameters Summary

National Air Quality Forecasting CapabilityNational Air Quality Forecasting Capability

Emission model: SMOKE - NEI 2005

- BEIS V3 Met model: WRF/NMM (NAM,

12 km/L60)

- T, RH, Wind, etc.

- Cloud, PBL (re-calculated by PreMAQ)

AQ model: CMAQ (12km/L22) - Oper: CONUS(CB04),

AK/HI(CB05/Aero-4)

- Exper/Dev: CONUS(CB05/ Aero-4)

http: www.weather.gov/aqhttp: www.weather.gov/aq

Current issue of O3 forecasting

6

8-hr max O3 significantly over-predicted in NE coastal region as compared to AIRNOW

5x (Exp.) 8-hr max O3 Aug-31-10 5x (Exp.) 8-hr max O3 Aug-31-10

ppb

ppb

Current issue of O3 forecasting (cont.)

7

Daily 8-hr max O3 (exp.) over-predicted (CONUS)Time period: July 1st to August 31st, 2010

Date (12 UTC Cycle) Date (12 UTC Cycle)

obs

fcst

bias

rmse

Emissions - NEI 2005 Meteorological inputs - wind, etc. - cloud, PBL height (re-diagnosed in PreMAQ) CMAQ - deposition velocity, etc. - CB05 mechanism Lateral boundary condition - static

Causes of O3 over-prediction

Verification tool and data Verification tool: Forecast Verification System (FVS)

- Grid2obs

- Grid2grid

- Statistics (e.g., rmse, bias) and FHO (e.g., csi, ets, far) Met observational data

- T, RH, Wind: ANYSFC, ADPUPA, ONLYSF, VADWND

- Cloud: AFWA (global, 10 x 1o, 1-hr), CLAVR-x (global, 0.5o x 0.5o, 6-hr) O3 data

- AIRNOW Studied time period

- O3 and met verification: Jul. 1 to Aug. 31, 2010

- Sensitivity testing: Aug. 5 – 31, 2010

FVS statistics parameters

FVS Statistics variables: F.H.O. F = grid fraction of forecasted > threshold O = grid faction of observed > threshold H = grid fraction of both forecasted and

observed > threshold Basic statistics scores Bias=F/O=(a+b)/(a+c) Critical Success Index CSI=H/(F+O-H)=a/(a+b+c) Probability of Detection POD=H/O=a/(a+c) False Alarm Ratio FAR =1-H/F=b/(a+b) Thresholds: O3: > 55, 65, 75, 85, 105, 125, 150 (ppb)

N=a+b+c+d

F=a+b

O=a+c

H=a

b

c

d

a

Verification of met inputs

Date

Date

Date

black: rmsered: bias

Date

T (o

C)

rmse

, b

ias

of

T (o

C)

Relative humidity (RH)Temperature (T) black: obs meanred: fcst mean

RH

(%

)rm

se ,

bia

s o

f R

H (

%)

Domain: CONUS

Verification of met inputs (cont.)

WS

(m

/s)

rmse

, b

ias

of

WS

(m

/s)

Date

Date

black: rmsered: bias

Wind speed (WS) black: obs meanred: fcst mean

Cloud cover (%)

Date

Date

rmse

, b

ias

of

TC

LD

(%

)T

CL

D (

%)

Domain: CONUS

How does cloud impact O3 prediction?

Photolysis rate

Jcld=J0[1+Cf(1.6trcos()-1] below cloud,

Jcld=J0[1+Cfi(1-tr)cos()] above cloud,

where J0 is the clear sky photolysis rate, Cf is cloud cover, is the zenith angle, αi is a reaction dependent coefficient, and tr is cloud transmissivity, which is a function of cloud water content and cloud thickness.

Cloud parameterization in PreMAQ

- Cloud cover: Geleyn et al. (1982) (below PBL); Schumann (1989), Wyngaard and Brost (1984) (above PBL)

- Liquid water content: Welcek and Taylor (1986), Change et al. (1987, 1990).

NAM Cloud: more complicated cloud parameterization schemes (Ferrier et al. 2002)

13

Cloud cover FHO statistics

Against AFWA for CONUS, Aug 05-31, 2010

Total cloud cover threshold Total cloud cover threshold

black: defaultred: modified

% %

Cloud cover FHO statistics (cont.)

Total cloud cover threshold

black: defaultred: modified

Total cloud cover threshold

Against CLAVR-x for CONUS, Aug 05-31, 2010

% %

Sensitivity run: default vs. Modified PreMAQ

08-31-2010: 13 UTC 08-31-2010: 19 UTC

Hourly-mean O3 difference (modified-default)

ppb ppb

8-hr max O3 verification: CONUS

black dash: default-fcstred dash: modified-fcst solid: obs

obs

fcstrmse

bias

Date (12 UTC Cycle) Date (12 UTC Cycle)

black: defaultred: modifiedsolid: rmsedash: bias

8-hr max O3 verification: NEUS

black: defaultred: modifiedsolid: rmsedash: bias

black dash: default-fcstred dash: modified-fcst solid: obs

Date (12 UTC Cycle) Date (12 UTC Cycle)

8-hr max O3 FHO comparison: CONUS

8-hr max O3 threshold

black: defaultred: modified

8-hr max O3 threshold (ppb)

ppb

ppb

8-hr max O3 FHO comparison: NEUS

8-hr max O3 threshold 8-hr max O3 threshold

black: defaultred: modified

ppb

ppb

Summary O3 over-prediction is often observed especially near

North-eastern coastal region. Met verification results present that while temperature,

relative humidity, and total cloud cover simulated by NAM show very good agreement with observations, NAM does not capture the time variability of the observed wind well.

The sensitivity study indicates that direct taking cloud parameters (cloud cover, liquid water content, cloud base and top) from NAM outputs may slightly improve surface O3 prediction especially over the NE coastal region.

Future work The role of cloud parameters will be

examined further in the coupling of the new NMMB meteorological model with CMAQ.

PBL schemes more suitable for stable atmospheric condition and marine boundary layer will be explored.