J10.5
Ensemble air quality Multi-model forecast System for Beijing (EMS-Beijing): Description and Application
Zifa Wang, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; and Q. Wu, J. Zhu, P. Yan, X. Tang, A. Gbaguidi, and L. Gan
An Ensemble air quality Multi-model forecast System for Beijing (EMS-Beijing) has been developed and applied to Beijing EPA since March 2008. introduced in this paper. It includes the IAP/CAS Nested Air Quality Prediction Modeling System (NAQPMS), the US/EPA Community Multiscale Air Quality (CMAQ) modeling system and the US Environ company three dimensional Comprehensive Air Quality Model with extensions (CAMx). The system used the unified meteorological field and emissions inventory provided respectively by the fifth-generation NCAR/Penn State Meso-scale Model (MM5) and the Sparse Matrix Operator Kernel Emissions (SMOKE). All the models adopted the same nested domains, with same grid size and resolution. The EMS-Beijing has been used for Beijing daily air quality routine real-time forecast since March 2008, especially, successfully supported the air quality forecast for the Beijing Olympic Games 2008. Various ensemble methods including the Ensemble Kalman Filter method, arithmetic mean and weight integrated methods are compared and the results indicate that: 1) the emission inventory in August 2008 (Olympic Games) processed by SMOKE is close to the actual, the model bias (MB) of each air quality model is -3%~17% for August 2008; 2) the arithmetic mean ensemble method has better performance than any single model in forecast daily PM10 concentration; 3) according to the daily PM10 concentration results during April - November 2008, the weight mean integrated method is better than the arithmetic mean method; (4) the Ensemble Kalman Filter method can best forecast results, with the performance increase of 61%, but costs more computer resources.
Joint Session 10, Air Quality Forecasting I
Thursday, 21 January 2010, 1:30 PM-3:00 PM, B316
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