Post on 01-Apr-2015
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
7
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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15
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
19
global CTM gridglobal CTM grid
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