A SEASONAL AND YEARLY POLLUTION STUDY BY USING WRF/CHEM AND WRF-CMAQ NESTED WITH CCSM3 GLOBAL MODEL
Abstract: The importance of relating the climate variables with the air pollution concentrations in different areas in Europe is an area which is receiving a high level of attention by researchers during the last years. The climate global models are successfully reproducing the yearly and seasonal c...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Text |
| Language: | English |
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| Online Access: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.604.3854 http://www.harmo.org/Conferences/Proceedings/_Cavtat/publishedSections/O_S6-05.pdf |
| Summary: | Abstract: The importance of relating the climate variables with the air pollution concentrations in different areas in Europe is an area which is receiving a high level of attention by researchers during the last years. The climate global models are successfully reproducing the yearly and seasonal changes in meteorological variables successfully during the last 20-30 years. The air pollution concentration changes within the same period are also simulated by using last generation of air pollution models. Statistical analysis of both variables has been carried out in the present contribution. We have simulated with the CCSM3 (NCAR, USA) global model the period between 1995-2005 and compared with observational data produced by NNRP2 and other observational data sets. The CCSM3 is applied in coupled form so that the CAM3 atmospheric model is coupled with the CSIM3 model (Sea Ice Model), the Land Model CLM3 and the ocean model CCSM POP model. The POP model has been simulated during the period 1985-2005. We have simulated the 10 year period with WRF-CHEM (NCAR, USA) and WRF-CMAQ (EPA, USA) over the European domain nested within CCSM3 global model. The model simulation domain includes the whole Europe with 54 km spatial horizontal resolution and 23 vertical layers. The results show that pollution concentrations and meteorological variables are correlated for seasonal and yearly periods. The PM10 and PM2.5 aerosol concentration feedbacks as a response to temperature changes are also shown. |
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