The Regional Chemical Transport Model over Northeast Asia Area Operated by Japan Meteorological Agency

A. Kamada*, M. Ikegami, H. Naoe, M. Kajino, M. Deushi, T. Maki

Japan Meteorological Agency

1

Our target: surface O3

ChemistryChemistry TransportTransport

Global CTM(MRICCM2)

Meteorological data

Photochemical oxidant advisory in JapanPhotochemical oxidant advisory in Japan

Oxidant advisory Category

advisory 2 advisory 2 (over 120 ppb)(over 120 ppb)advisory 1 (over 80 ppb)advisory 0 (below 80 ppb)

Emission inventories

2015~

Regional CTM(NHM-Chem)

• JMA provide information on photochemical oxidant using daily maxima surface O3 simulated by CTM.

• We are going to operate the regional CTM in 2015.

Deushi, 2011

Kajino, 2012

2

~110 km

20 km

O3

Outline

1. The regional CTM over Northeast Asia

2. Validation of the regional CTM

3. Statistical Guidance for photochemical oxidant advisories

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1. The regional CTM over Northeast Asia1. The regional CTM over Northeast Asia

The regional CTM can•resolve the details of surface O3 distribution.•reproduce high surface O3 concentration in urban area.

Regional CTMGlobal CTM

Observationby the ministry of the environment

2nd June, 2014

200 km 4

Tokyo

Specification of the regional CTMSpecification of the regional CTMModelResolutions

20 x 20 km ( Lambert Coordinates ) /18 levels (surface – 50 hPa)

Meteorological /Chemical Module

JMANHM(Meso-Scale Model by JMA) / RAQM2 (Kajino et al., 2012)

Gas Chemistry Chemical species : 72Chemical Reactions: 214

(SAPRC; Carter, 2000)

Emission inventories

REAS1.1 anthropogenic

GFED3,MEGAN2, etc.

natural

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Emission inventories

Global model analysis and

forecast by JMA

NO2

紫外線

O2O3

O3O3

＋O

＋ O＋ O

炭化水素

NO 炭化水素（還元）

MRI-CCM2/CTM

nudgingnudging

JMANHM （ 20km ）

Emission inventories

T106L48

Horizontal 20km, 18 levels

Forecast system using regional - global CTMForecast system using regional - global CTM

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The regional CTM simulates surface ozone more accurately than global CTM especially in urban area.

2. Validation of the regional CTM2. Validation of the regional CTM

Year

Model Model-Obs. RMSE CC

Global CTM -6.7 ppb 14.5 ppb 0.42All included

Regional CTM +7.1 ppb 10.0 ppb 0.81

APR

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Ex. Tokyo grid(daily mean)

Simulation in Simulation in mountainmountain areas areasdaily mean

Year

Model Model-Obs. RMSE CCGlobal CTM -1.0 ppb 10.1 ppb 0.53

All included Regional CTM +15.2 ppb 17.3 ppb 0.71

APR

8

• Despite large overestimation, the regional CTM correlation is better than that of the global CTM.

• Considering to forecast high photochemical ozone events at urban area, this result seems reasonable.

• At night time, the regional CTM tends to underestimate the ozone value because loss of O3 by NO is too much at night in this model.

• Daily maxima during daytime are also underestimated a little.

Simulation in Simulation in urbanurban areas areas

August, 2013

hourly

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Tokyo

GuidanceObservation daily maximum

Modeldaily maximum

O3(ppb)

Guidance =bias correction

O3(ppb)frequency

(50%)

(35%)

(10%)

(5%)

67 78 85(50%) (35%) (10%) (5%)

<- category

Ⅰ

Ⅱ

Ⅲ

Ⅳ

80

100

120

Frequency Bias Correction Method

Ⅰ Ⅱ Ⅲ

Ⅳ

Ⅰ Ⅱ ⅢⅣ

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3. Statistical Guidance3. Statistical Guidance

We use this method to make statistic guidance at every prefecture and every month.

125

151

112110

173

172

151

94

70

10097

92

90

78

132

156

161124

175

181

146

An Example of Statistical GuidanceAn Example of Statistical Guidance

modelmodel

GuidanceGuidance

ObservationObservation

VS.

[ ppb ] [ ppb ]

[ ppb ]

Ex. 1st June, 2014 11

• Using the statistical guidance, we can forecast level 2 more accurately for each prefecture.

20 kmPrefecture line

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XOFXFO

FOCSITS

Its range is 0 to 1. Perfect forecast / TS=1

Spring (Apr.-May) Summer (Jun.-Sep.)Global CTM* 0.14 0.19

Regional CTM* 0.19 0.25

120ppb Threat Score （ 2009-2013 ）

Yes No

Yes

No

FO FX

XO XX

Event forecastEvent observed

Threat Score (TS) Threat Score (TS) or Critical Success Index (CSI)or Critical Success Index (CSI)

* With guidance

Summary1. We are going to start operation of a

new regional CTM (NHM-Chem) besides the global CTM in 2015.

2. The regional CTM (1)simulates surface ozone concentration with good correlation, but (2)underestimates their daily maxima in urban areas.

3. The underestimate is improved by introducing the statistical guidance method. The resulted skill exceeds the ordinary global CTM.

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Reference

•Carter, W.: Documentation of the SAPRC-99 chemical mechanism for VOC reactivity assessment. Final report to California Air Resources Board, Rep. 92-329, Univ. of Calif., Riverside, 8 May, 2000.•Deushi, M. and Shibata, K.: Development of an MRI Chemistry-Climate Model ver.2 for the study of tropospheric and strarospheric chemistry, papers in Meteor. Geophys., 62, 1-46 (2011).•Kajino, M., Y. Inomata, K. Sato, H. Ueda, Z. Han, J. An, G. Katata, M. Deushi, T. Maki, N. Oshima, J. Kurokawa, T. Ohara, A. Takami, S. Hatakeyama: Development of an aerosol chemical transport model RAQM2 and prediction of Northeast Asian aerosol mass, size, chemistry, and the mixing type. Atmos. Chem. Phys., 12, 11833-11856, 2012

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Contingency table of the Contingency table of the regionalregional CTM CTM

Observed Not Observed

Forecasted 36 80Not Forecasted

80 14,134

16

Observed Not Observed

Forecasted 289 412Not Forecasted

412 27,519

Spring (Apr.-May)

Summer (Jun.-Sep.)

Contingency table of the Contingency table of the globalglobal CTM CTM

Observed Not Observed

Forecasted 36 80Not Forecasted

80 14,134

17

Observed Not Observed

Forecasted 289 412Not Forecasted

412 27,519

Spring (Apr.-May)

Summer (Jun.-Sep.)

18

Whether chart at Northeast AsiaWhether chart at Northeast Asia

H

H

L

H

L

L

2nd June, 2014 15JST (06UTC)

Statistics averaged all global CTM gridStatistics averaged all global CTM grid

Model Model-Obs. RMSE CC

Global CTM +8.2 ppb 14.8 ppb 0.51

All included

Regional CTM +11.1 ppb 14.2 ppb 0.69

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global CTM gridglobal CTM grid

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