Page 1 – July 3, 2015 Assimilation of surface chemical species observations into the Canadian GEM-MACH model using optimal interpolation Alain Robichaud,

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Presentation transcript:

Page 1 – July 3, 2015 Assimilation of surface chemical species observations into the Canadian GEM-MACH model using optimal interpolation Alain Robichaud, Richard Ménard ASTD/AQRD Dorval, QC (with the collaboration of Yulia Zaitseva, CMC)

Page 2 – July 3, 2015 Goal of the project Methodology OA and verification Impact on AQ forecast hrs Summary and conclusions Milestones and future work Outline

Page 3 – July 3, 2015 Basic equations (OI) K = (HP f ) t * (H(HP f ) t +R) -1 1) H(HP f (k 1,k 2 )) t = σ f (k 1 )*σ f (k 2 )*exp { - |x(k 1 )- x(k 2 )|/(L c } 2) (HP f (i,j,k 1 )) t = σ f (i,j)*σ f (k 1 )*exp { - |x(i,j)- x(k 1 )|/(L c } N ~ < 1500 Error stats obtained from Hollingsworth and Lönnberg’s method (1986) Hypothesis: σ f (i,j) and L c are constant over the whole domain However, a sensitivity analysis was done: it turns out that those 2 parameters are quite sensitive and can be tuned to achieved a better optimization. A A: positive definite (trace (A) > 0; det |A| > 0) 3) Scaling of error statistics (χ2  N) and regional bias correction Robichaud and Ménard (2014), ACP 4) Obs from AIRNOW, NAPS and CAPMON network ( ~ 1200 for Ozone and 700 for PM2.5) Xa = Xb + K (y – HXb)

Page 4 – July 3, 2015 Methodology for assimilation (I) - 1) Average of partitioning ratio sub-species mass TXX1/total PM2.5 for the whole month of July 2012 (from GEMMACH-10 model outputs, v 1.3.8) (obtain pratio) - 2) Produce a RPN/standard file of the partitioning ratio TXX1/PM2.5 for TSU1,TOC1,TEC1,TPC1,TNI1,TAM1 and TCM1 (e.g. mass fraction) - 3) Use the analysis increments PM2.5 OA a) project in the vertical the analysis increment (linear decrease over n model levels) (obtain a(HY)) b) multiply by the appropriate partitioning ratio TXX1/PM a 1 n levels LzLz

Page 5 – July 3, 2015 Methodology ii INCR(HY,TXX1)=INCR(sfc) PM2.5 * a(HY)* pratio(TXX1) for PM2.5 INCR(HY,TXX1)=INCR(sfc) O3 * a(HY) for O3 - 4) store (TXX1 -1 (HY,TXX1) + INCR(HY,TXX1)) and put it in field TXX1 o and restart the model - 5) verify scores for 24 or 48 hour forecasts with independent obs O3 and PM2.5 (AIRNOW/EPA and NAPS/CAPMON data) July 2012 Weight for vertical projection Partitioning ratio

Page 6 – July 3, 2015 OA- Ozone MODELOA INCR OBS

Page 7 – July 3, 2015 OA-PM25 MODELOA INCR OBS

Page 8 – July 3, 2015 OA-PM10 MODELOA INCR OBS

Page 9 – July 3, 2015 Cross-validation Ozone-OA (July) model OA R R S S

Page 10 – July 3, 2015 Cross-validation PM2.5 – OA (July) model OA

Page 11 – July 3, 2015 Air Quality Health Index mapping Used for public forecast - Multi-pollutant index - Triggers warnings Stieb et al (2008)

Page 12 – July 3, 2015 OA- AQHI

Page 13 – July 3, 2015 Impact on forecast

Page 14 – July 3, 2015 Impact of assimilation on O3 Jul 2011 – run 00Z R S Model no assim and assim NO2 only Assim O3&NO2 and Assim O3 only Model and assim NO2 only Std dev Mean

Page 15 – July 3, 2015 RATIO Sulfates/PM2.5 (pratio)

Page 16 – July 3, 2015 Ratio Crustal Material/PM2.5 (pratio)

Page 17 – July 3, 2015 Model no assim With assim; Lz 10 or 20 levels With assim: Lz 2 levels R S 17

Page 18 – July 3, 2015 Model – no assim With assim: Lz 20 LVLS With assim: Lz 10 LVLS (avg height BL) With assim: Lz 2 LVLS 18

Page 19 – July 3, 2015 NO Assim With assim: Lz 20 LVLS With assim: Lz 10 LVLS With assim: Lz 2 LVLS 19

Page 20 – July 3, 2015 Surface assimilation of TSU1 Verification scores (24 hr avg): % improvement mean absolute bias 20

Page 21 – July 3, 2015 Surface assimilation of TSU1 Verification scores (24 hr avg): % improvement std OmP 21

Page 22 – July 3, 2015 Surface assimilation of TCM1 Verification scores (24 hr avg): % improvement mean ABSOLUTE OmP 22

Page 23 – July 3, 2015 Surface assimilation of TCM1 Verification scores (24 hr avg): % improvement std OmP 23

Page 24 – July 3, 2015 Cross section: no assim vs assim hy

Page 25 – July 3, 2015 Surface assimilation of PM2.5 (July 2012) Verification scores (24 hr avg): N ~ METRICMETRIC SUNIAMCMOCECPC MODEL (no assim) Abs Mean (OmP) Std dev (OmP) FC Z run

Page 26 – July 3, 2015 Summary & Conclusions 1) Very good results for SFC assim in GEMMACH-10 for PM2.5: very sign impact on forecast beyond 48 h. For ozone, impact on forecast is only sign. for the first 12 hours. 2) Sulfates, and crustal material give sign results for PM2.5 assim. The success of the impact for a particular PM2.5 sub- species depends on lifetime and abundance (strength of partitioning ratio) 3) on-line assimilation results are expected to give even better results ( REQUIRES FUSION OF TWO MAESTRO SUITES) 4) issues about multivariate assimilation, vertical correlation length, how this system will fit within the framework of future assim system 26

Page 27 – July 3, 2015 Milestones OA for O3 and PM2.5 (transfered to oper CMC in 2013) Historical OA available for warm season 2002-now for PM2.5 and Ozone (Robichaud and Ménard, 2014, ACP) Extending OA for NO2, NO, PM10 and SO2 (will be transfered to operations ) (Zaitseva et al, poster session nb 1058) AQHI- OA (will be transferred to oper in ) Sfc data assimilation using OA-offline (current experiment successfull for Ozone, Sulfates and Crustal material in GEM-MACH 1.3.8, Summer 2012) (Presented here) Assimilation exp. extended to other seasons, other pollutants (PM10) Fusion MAESTRO suites OA and GEM-MACH2 (on-line assim) and upgrade system for new model version Produce high resolution OA 2.5 km for PANAM games (Toronto 2015; see presentation C. Stroud et al, Wednesday 17:20 room 520A) and Alberta oil sands project

Page 28 – July 3, 2015 Additional slides

Page 29 – July 3, 2015 OA MAESTRO suite /home/pxarqj/arqj/aro/.suites/rdaqa

Page 30 – July 3, 2015 GEM2- MAESTRO suite