P1.1 VERIFICATION OF SURFACE LAYER OZONE FORECASTS IN THE NOAA/EPA AIR QUALITY FORECAST SYSTEM IN DIFFERENT REGIONS UNDER DIFFERENT SYNOPTIC SCENARIOS

Transcription

1 P1.1 VERIFICATION OF SURFACE LAYER OZONE FORECASTS IN THE NOAA/EPA AIR QUALITY FORECAST SYSTEM IN DIFFERENT REGIONS UNDER DIFFERENT SYNOPTIC SCENARIOS Mrin Tsidulko 1*, Jeff T. McQueen 2, Geoff DiMego 2, Pius C. Lee 1, Rohit Mthur 3, Kenneth L. Schere 3, Jonthn E. Pleim 3, Tny L. Otte 3, Diwen Kng 6, Michel Schenk 4, Jerry Gorline 4 nd Pul M. Dvidson 5 1. INTRODUCTION An ir qulity forecst (AQF) system hs een estlished t NOAA/NCEP since 2003 s collortive effort of NOAA nd EPA. The system is sed on NCEP s Et mesoscle meteorologicl model nd EPA s CMAQ ir qulity model (Dvidson et l, 2004). The vision ehind this system is to provide ntionl guidnce for ozone, prticulte mtter nd other pollutnts with cceptle ccurcy. As first stge of the project, ozone concentrtions hve een predicted on rel-time sis since summer 2003 for the Northest US. Bsed on the initil series of experiments, n updted version of the AQF system is set to opertionl sttus y the utumn of This pper discusses detiled verifiction of the ozone forecsts for selected periods during summer Verifiction presented in this pper is done for the Northest opertionl domin (Fig. 3). To crete cpility for evluting ozone, surfce lyer ozone concentrtions from EPA AIRNOW mesurements nd CMAQ forecsts were incorported into NCEP s Forecst Verifiction System (FVS) (Brill, 2004, DiMego et l, 2004). The AIRNOW network *Corresponding Author Address: Mrin Tsidulko, NCEP/EMC, W/NP22 Room 207, 5200 Auth Rod, Cmp Springs, MD ; mrin.tsidulko@no.gov 1 Scientific Applictions Interntionl Corportion, Cmp Springs, Mrylnd. 2 Ntionl Centers for Environmentl Prediction, Cmp Springs, Mrylnd. 3 Ntionl Ocenic nd Atmospheric Administrtion, Reserch Tringle Prk, NC. (On ssignment to the Ntionl Exposure Reserch Lortory, U.S.E.P.A.) 4 Meteorologicl Development Lortory, Ntionl Wether Service, Silver Spring, MD. 5 Office of Science nd Technology, Ntionl Wether Service, Silver Spring, MD. 6 Science nd Technology Corportion, Hmpton, Virgini (On ssignment to the Ntionl Exposure Reserch Lortory, US EPA) reports 1hr verge nd 8hr verge surfce ozone concentrtions. Also, mximum vlues of these concentrtions during the dy cn e derived. All these prmeters re suject for sttisticl evlution. In this pper, however, only 1 hr verge concentrtions re verified. In FVS, the CMAQ predicted concentrtions re interpolted to the oservtion points. Averge sttistics (e.g. is, root men squre error, correltion, etc) re computed for the North Est Cost, South Est Cost, Mid-West, Gulf of Mexico nd severl other res. Sttistics for criticl thresholds of ozone concentrtion re lso computed. 2. EVALUATION OF OZONE FORECASTS IN DIFFERENT REGIONS 2.1 July The July episode ws chosen s one of the few intensive ozone periods during the summer of Figure 1 shows cold frontl pssge nd northerly flow on July 29, 12Z UTC. Air ehind the front is cold nd dry, nd ozone production in the erly morning is smll. Lter in the dy, incresed solr rdition flux over highpressure re llows the photolysis process in the tmosphere to e more intensive nd to produce more ozone. By 24 hours (Fig. 1), the front ecomes occluded, nd the ozone pek moves to the northest nd remins in the high-pressure re. The CMAQ forecst of ozone concentrtions over the Northestern US domin is shown in Figure 2. The forecst strted t 12Z UTC July 29, 2004 nd the mximum vlues of ozone concentrtion pper t 21Z UTC ( 9 hour prediction). The most intense ozone re (over 105 pp) is locted long the costl zone etween New York nd Boston, ehind the cold front shown in Fig.1.

2 NCEP is eing done. Figure 4 shows the is error nd correltion coefficient for the selected regions. Both is nd correltion coefficients re verged y forecst hour, nd only forecsts with strting times of 12 Z re verified. As we cn see in Figure 4, the is hs reltively lrge rnge over the forecst domin, ut for ll su-domins it is positive, indicting model over-prediction. The lrgest is is ssocited with the North-Est (NEC), South-Est (SEC) nd Applchin (APL) res, ut for this period men ozone concentrtions were lso highest for these regions. The highest dytime correltions (Fig. 4) re shown over the NEC region, despite the lrge dytime is. For the first 12 hours of the forecst, the NEC, SEC nd APL regions hve lmost the sme is, ut men concentrtions were decresing from north to south for the July period, which is reflected in the highest dytime correltions of out 0.7 for NEC, 0.4 for APL, nd 0.3 for SEC. On the other hnd, the Midwest (MDW) re demonstrtes the worst (out 0.1) dytime correltions despite hving low ises. During the dytime, the model seems to predict etter in res with higher ozone concentrtions, despite the reltively lrge ises. Fig.1: Wether mps for 12Z July 29, 2004 () nd 12Z July 30, 2004 () Fig.2: CMAQ 1hr verge (ckwrd) ozone concentrtion (pp) for 12Z + 9hr forecst (Vlid 21Z UTC July 29, 2004) Fig.3: Su-regions for Forecst Verifiction System t NCEP nd NE opertionl domin position. The ozone forecsts for the July period were evluted using the FVS system t NCEP. Figure 3 shows the regions in which verifiction t

3 nd lmost nothing ove 105 pp. It is clerly seen from the forecst hour sttistics (Fig. 5) tht the model predicts differently for dytime nd nighttime. For vlues ove 50 pp, the proility of detection is out in the dytime, wheres, t night it is only out Figure 6 shows only one forecst hour, the 6h forecst, ut for different regions. The est res during this period were NEC nd APL, oth ove 0.9 for the 65 pp threshold. The proility of detection ove 65 pp drops significntly for the other regions. Fig.5: CMAQ ozone proility of detection for different forecst hours, July 27-30, Oservtions counts re shown for the first trce. Fig.4: CMAQ ozone is () nd correltion () verged y forecst hour for July 27-30, 2004 The AQF model ws lso evluted for different forecst hours nd for different regions y computing sttistics for criticl ozone concentrtion thresholds. Figures 5 nd 6 show the proility of detection for threshold vlues of 50, 65, 85, 105, 125 nd 150 pp. Proility of detection is defined s H/O, where O is the numer of oserved points ove threshold, nd H is the numer of correctly forecsted points ('hits'). The July period ws one of reltively few intense episodes during the summer of 2004; there were just few oservtions ove 85 pp, Fig.6: CMAQ ozone proility of detection for different su-regions, July 27-30, Oservtions counts re shown for the first trce.

4 For further understnding of possile sources for the AQF errors, coupling issues etween meteorologicl nd chemicl models could e investigted. As n exmple of existing differences, cloud coverge for oth models is demonstrted. Figure 7 illustrtes the totl cloud frction used in the meteorologicl nd chemicl models. CMAQ computes cloud cover from Et reltive humidity profiles nd not directly from Et cloud microphysics predictions. Cloud cover is primrily used in CMAQ to estimte incoming short-wve rdition, driving chemicl photolysis (Byun nd Ching, 1999). Less cloud cover is dignosed y CMAQ (Fig.7) thn is predicted y Et (Fig. 7). Reltive to Et, CMAQ predicts more short-wve rdition nd photolytic ctivity, suggesting tht use of Et's predicted cloud cover directly in CMAQ might reduce the ozone overprediction is. Cloud coverge nd relted rdition fields re mong the hrdest meteorologicl prmeters to predict, nd oth Et nd CMAQ clouds re sujects for further evlution ginst oservtions. Fig.7: Totl cloud frction (%) 12Z + 9hr forecst (Vlid 21Z UTC July 29, 2004) for CMAQ (), Et (). 2.2 August-Septemer 2004 As further verifiction of model forecsts, the threshold sttistics were computed for the extended period of August 16 Septemer 30. Figure 8 shows tht, similr to the July period, the proility of detection is much higher for the dytime forecst, out 0.9 for the vlues ove 50 pp nd out 0.6 for the 65 pp threshold. At night, even for the 50 pp threshold, the proility of detection is not more thn 0.4. In the regionl sttistics (Fig. 8), on the other hnd, the August-Septemer period demonstrtes more consistency etween su-regions thn the short July episode. All su-regions hve proility of detection of out 0.9 for the 50 pp threshold nd for the 65 pp threshold. One possile explntion for this fct is tht the model prediction ccurcy is relted more to the synoptic conditions thn to the model constnt fields like lnd use or vegettion.

5 different regions nd for different forecst hours. The most ccurte forecsts pper to e over the Northest cost for the dytime, in high-pressure res under cler sky. In the extended period, the differences etween regions re reltively smll ut lrger differences re seen etween the dy nd night predictions. Future work will explore tighter coupling of the rdition nd cloud models within the meteorology nd chemistry models. 4. ACKNOWLEDGEMENTS AND DISCLAIMER The EPA AIRNOW progrm stff provided the oservtions necessry for quntittive model evlution. The reserch presented here ws performed under the Memorndum of Understnding etween the U.S. Environmentl Protection Agency (EPA) nd the U.S. Deprtment of Commerce s Ntionl Ocenic nd Atmospheric Administrtion (NOAA) nd under greement numer DW Although it hs een reviewed y EPA nd NOAA nd pproved for puliction, it does not necessrily reflect their policies or views. 5. REFERENCES Brill, K., 2004: Model verifiction system t NCEP [Aville from rill/fvs.txt] Fig.8: CMAQ ozone proility of detection for different forecst hours () nd for different suregions (), August 16 Septemer 30, Oservtions counts re shown for the first trce. 3. SUMMARY Verifiction of the CMAQ model forecsts for one of the high ozone episodes during the summer of 2004 hs een done. Different types of sttistics hve een computed using the NCEP s Forecst Verifiction System. Despite the over-prediction of ozone concentrtions over the whole domin, the forecsts demonstrte different ccurcies in Byun, D. W., nd J. K. S. Ching (Eds.), 1999: Science lgorithms of the EPA Models-3 Community Multiscle Air Qulity (CMAQ) Modeling System. EPA-600/R-99/030, Office of Reserch nd Development, U.S. Environmentl Protection Agency, Wshington, D.C. [Aville from U.S. EPA, ORD, Wshington, D.C ] Dvidson, P. M., N. Semn, K. Schere, R. A. Wylnd, J. L. Hyes, nd K. F. Crey, 2004: Ntionl ir qulity forecsting cpility: First steps towrd implementtion. Preprints, Sixth Conf. on Atmos. Chem., Amer. Met. Soc., Settle, WA, Jn DiMego, G., H. Chung, nd M. Hrt, 2004: NCEP Verifiction System User Guide [Aville from hung/3/verifiction.txt