Air quality forecasts on a kilometer-scale grid over complex Spanish terrains

• Main Authors: M. T. Pay, F. Martínez, M. Guevara, J. M. Baldasano
• Format: Article
• Language: English
• Published: Copernicus Publications 2014-09-01
• Series: Geoscientific Model Development
• Online Access: http://www.geosci-model-dev.net/7/1979/2014/gmd-7-1979-2014.pdf
• ISSN: 1991-959X; 1991-9603

The CALIOPE Air Quality Forecast System (CALIOPE-AQFS) represents the current state of the art in air quality forecasting systems of high-resolution running on high-performance computing platforms. It provides a 48 h forecast of NO₂, O₃, SO₂, PM₁₀, PM_2.5, CO, and C₆H₆ at a 4 km horizontal resolution over all of Spain, and at a 1 km horizontal resolution over the most populated areas in Spain with complex terrains (the Barcelona (BCN), Madrid (MAD) and Andalusia (AND) domains). Increased horizontal resolution from 4 to 1 km over the aforementioned domains leads to finer textures and more realistic concentration maps, which is justified by the increase in NO₂/O₃ spatial correlation coefficients from 0.79/0.69 (4 km) to 0.81/0.73 (1 km). High-resolution emissions using the bottom-up HERMESv2.0 model are essential for improving model performance when increasing resolution on an urban scale, but it is still insufficient. Decreasing grid spacing does not reveal the expected improvement in hourly statistics, i.e., decreasing NO₂ bias by only ~ 2 μg m⁻³ and increasing O₃ bias by ~ 1 μg m⁻³. The grid effect is less pronounced for PM₁₀, because part of its mass consists of secondary aerosols, which are less affected than the locally emitted primary components by a decreasing grid size. The resolution increase has the highest impact over Barcelona, where air flow is controlled mainly by mesoscale phenomena and a lower planetary boundary layer (PBL). Despite the merits and potential uses of the 1-km simulation, the limitations of current model formulations do not allow confirmation of their expected superiority close to highly urbanized areas and large emissions sources. Future work should combine high grid resolutions with techniques that decrease subgrid variability (e.g., stochastic field methods), and also include models that consider urban morphology and thermal parameters.