Alex-2009-3-12工作总结 EMS PM10 for Beijing
Objective
Many previous multi-model ensemble ozone and tracer studies proved the ensemble averaging technique performance compared to any single model forecast (Straume, 2001; Delle Monache et al., 2003; Mckeen et al., 2005; O'Neill et al., 2005). As a complementary approach in air quality forecast improvement process, the present technical work tests the multi-model ensemble PM10 forecasts accuracy by comparing the ensemble single models (CMAQ, CAMx, NAQPMS) and ensemble average PM10 forecasts (ENS-AVE) to averaged hourly PM2.5 concentrations of four air quality observation sites in Beijing (Changping, Beiyi, Peking University and IAP tower). Although larges discrepancies are noted sometimes between simulated results and observed data, single ensemble models present good skill in simulating PM10 over Beijing. Forecasts on the two days (3rd and 17th August 2008, before and during the Olympics) where the largest discrepancies occur are analyzed through the statistical parameters below. This essentially aims at examining multi-model ensemble PM10 forecasting system performance on these two critical days (before and during the Olympics). The following statistical measures are calculated for individual ensemble model and ensemble average PM10 concentrations based on hourly simulated results of concerned four observation sites in Beijing:
Normalized Mean Error (NME)

[pic] and Unpaired Peak Prediction Error (UPPE) [pic] where N is the number of hourly concentrations at a given observation station, Co(x,ti) and Cp(x,t) are respectively observed and predicted concentrations at the station located at x for hour ti . Co(x,t´)max and Cp(x,t´)max are respectively maximum 1-hr observed and predicted concentrations at the observation station over each considered time sequence over the day. NME is a rigorous analysis that matches predicted and observed PM10