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Assimilation of ground versus lidar observations for PM10 forecasting

by Y. Wang, K. N. Sartelet, M. Bocquet, P. Chazette
Atmospheric Chemistry and Physics ()

Abstract

This article investigates the potential impact of future ground-based\nlidar networks on analysis and short-term forecasts of particulate\nmatter with a diameter smaller than 10 mu m (PM10). To do so, an\nObserving System Simulation Experiment (OSSE) is built for PM10 data\nassimilation (DA) using optimal interpolation (OI) over Europe for one\nmonth from 15 July to 15 August 2001. First, using a lidar network with\n12 stations and representing the ``true{''} atmosphere by a simulation\ncalled ``nature run{''}, we estimate the efficiency of assimilating the\nlidar network measurements in improving PM10 concentration for analysis\nand forecast. It is compared to the efficiency of assimilating\nconcentration measurements from the AirBase ground network, which\nincludes about 500 stations in western Europe. It is found that\nassimilating the lidar observations decreases by about 54% the root\nmean square error (RMSE) of PM10 concentrations after 12 h of\nassimilation and during the first forecast day, against 59% for the\nassimilation of AirBase measurements. However, the assimilation of lidar\nobservations leads to similar scores as AirBase's during the second\nforecast day. The RMSE of the second forecast day is improved on average\nover the summer month by 57% by the lidar DA, against 56% by the\nAirBase DA. Moreover, the spatial and temporal influence of the\nassimilation of lidar observations is larger and longer. The results\nshow a potentially powerful impact of the future lidar networks.\nSecondly, since a lidar is a costly instrument, a sensitivity study on\nthe number and location of required lidars is performed to help define\nan optimal lidar network for PM10 forecasts. With 12 lidar stations, an\nefficient network in improving PM10 forecast over Europe is obtained by\nregularly spacing the lidars. Data assimilation with a lidar network of\n26 or 76 stations is compared to DA with the previously-used lidar\nnetwork. During the first forecast day, the assimilation of 76 lidar\nstations' measurements leads to a better score (the RMSE decreased by\nabout 65%) than AirBase's (the RMSE decreased by about 59%).

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