1. 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 O 3

2. Chemistry Transport Global CTM (MRICCM2) Meteorological data Photochemical oxidant advisory in Japan Oxidant advisory Category advisory 2 (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 O 3 simulated by CTM. We are going to operate the regional CTM in 2015. Deushi, 2011 Kajino, 2012 2 ~110 km 20 km O3O3

3. Outline 1.The regional CTM over Northeast Asia 2.Validation of the regional CTM 3.Statistical Guidance for photochemical oxidant advisories 3

4. 1. The regional CTM over Northeast Asia The regional CTM can resolve the details of surface O 3 distribution. reproduce high surface O 3 concentration in urban area. Regional CTM Global CTM Observation by the ministry of the environment 2 nd June, 2014 200 km 4 Tokyo

5. Specification of the regional CTM Model Resolutions 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 ChemistryChemical species : 72 Chemical Reactions: 214 (SAPRC; Carter, 2000) Emission inventories REAS1.1anthropogenic GFED3, MEGAN2, etc. natural 5

6. Emission inventories Global model analysis and forecast by JMA MRI-CCM2/CTM nudging NHM-Chem JMANHM （ 20km ） Emission inventories T106L48 Horizontal 20km, 18 levels Forecast system using regional - global CTM 6

7. The regional CTM simulates surface ozone more accurately than global CTM especially in urban area. 2. Validation of the regional CTM Year ModelModel-Obs.RMSECC Global CTM-6.7 ppb14.5 ppb0.42 All included Regional CTM +7.1 ppb10.0 ppb0.81 APR 7 Ex. Tokyo grid(daily mean)

8. Simulation in mountain areas daily mean Year ModelModel-Obs.RMSECC Global CTM-1.0 ppb10.1 ppb0.53 All included Regional CTM+15.2 ppb17.3 ppb0.71 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.

9. At night time, the regional CTM tends to underestimate the ozone value because loss of O 3 by NO is too much at night in this model. Daily maxima during daytime are also underestimated a little. Simulation in urban areas August, 2013 hourly 9 Tokyo

10. Guidance Observation daily maximum Model daily maximum O 3 (ppb) Guidance =bias correction O 3 (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 ⅠⅡ Ⅲ Ⅳ 10 3. Statistical Guidance We use this method to make statistic guidance at every prefecture and every month.

11. 125 151 112 110 173 172 151 94 70 100 97 92 90 78 132 156 161 124 175 181 146 An Example of Statistical Guidance model Guidance Observation VS. [ ppb ] Ex. 1 st June, 2014 11 Using the statistical guidance, we can forecast level 2 more accurately for each prefecture. 20 km Prefecture line

12. 12 Its range is 0 to 1. Perfect forecast / TS=1 Spring (Apr.-May)Summer (Jun.-Sep.) Global CTM*0.140.19 Regional CTM*0.190.25 120ppb Threat Score （ 2009-2013 ） YesNo Yes No FOFX XO XX Event forecast Event observed Threat Score (TS) or Critical Success Index (CSI) * With guidance

13. Summary 1.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. 13

14. 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 14

15. 15

16. Contingency table of the regional CTM ObservedNot Observed Forecasted 3680 Not Forecasted 8014,134 16 ObservedNot Observed Forecasted 289412 Not Forecasted 41227,519 Spring (Apr.-May) Summer (Jun.-Sep.)

17. Contingency table of the global CTM ObservedNot Observed Forecasted 3680 Not Forecasted 8014,134 17 ObservedNot Observed Forecasted 289412 Not Forecasted 41227,519 Spring (Apr.-May) Summer (Jun.-Sep.)

18. 18 Whether chart at Northeast Asia H H L H L L 2nd June, 2014 15JST (06UTC)

19. Statistics averaged all global CTM grid ModelModel-Obs.RMSECC Global CTM+8.2 ppb14.8 ppb0.51 All included Regional CTM +11.1 ppb14.2 ppb0.69 19

20. global CTM grid 20