An Observing System Simulation Experiment (OSSE) for Aerosol Optical Depth from Satellites

Monitoring aerosols over wide areas is a scientific challenge with important applications for human health and the understanding of climate. Aerosol optical depth (AOD) measurements from satellites can improve the highly needed analyzed and forecasted distributions of ground-level aerosols in combination with models and ground-based measurements. To assess the benefit of future satellite AOD measurements, an observing system simulation experiment (OSSE) is developed. In this pilot study, the OSSE is applied to total AOD measurements from a flexible combined imager (FCI) proposed to fly on a geostationary satellite. OSSEs are widely used in the meteorological research community, but their use for air quality applications and specifically for aerosols is new. In this paper, the functionality and potential of the developed OSSE for evaluation of aerosol data from future satellite missions are demonstrated. The results show a positive impact of adding AOD observations next to in situ observations for the analysis of PM2.5 (particles smaller than 2.5 μm in median diameter) distributions. However, the development of an OSSE for aerosols presents a number of further challenges, as discussed in this paper, which prohibits a detailed quantitative analysis of the results of this pilot study. © 2009 American Meteorological Society.

[1]  G. Leeuw,et al.  Spatial variation of aerosol properties over Europe derived from satellite observations and comparison with model calculations , 2003 .

[2]  Bruce Denby,et al.  Comparison of two data assimilation methods for assessing PM10 exceedances on the European scale , 2008 .

[3]  Philippe Thunis,et al.  Evaluation and intercomparison of Ozone and PM10 simulations by several chemistry transport models over four European cities within the CityDelta project , 2007 .

[4]  G. Leeuw,et al.  Comparison between AATSR and MODIS AOD and assimilation in a regional chemistry transport model , 2007 .

[5]  Hendrik Elbern,et al.  Emission rate and chemical state estimation by 4-dimensional variational inversion , 2007 .

[6]  R. Koelemeijer,et al.  Comparison of spatial and temporal variations of aerosol optical thickness and particulate matter over Europe , 2006 .

[7]  J. Terry,et al.  Observing system simulation experiments at NCEP , 2005 .

[8]  A.J.H. Visschedijk,et al.  Anthropogenic black carbon and fine aerosol distribution over Europe , 2004 .

[9]  B. Brunekreef,et al.  Air pollution and health , 2002, The Lancet.

[10]  Renske Timmermans,et al.  The LOTOS?EUROS model: description, validation and latest developments , 2008 .

[11]  Yves M. Govaerts,et al.  Optimal estimation applied to the retrieval of aerosol load using MSG/SEVIRI observations , 2007, SPIE Remote Sensing.

[12]  Jun Wang,et al.  Intercomparison between satellite‐derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies , 2003 .

[13]  Martijn Schaap,et al.  Testing the capability of the chemistry transport model LOTOS-EUROS to forecast PM10 levels in the Netherlands , 2009 .

[14]  J. Kiehl,et al.  The Relative Roles of Sulfate Aerosols and Greenhouse Gases in Climate Forcing , 1993, Science.

[15]  Geir Evensen,et al.  Advanced Data Assimilation for Strongly Nonlinear Dynamics , 1997 .

[16]  Nadège Blond,et al.  Three-dimensional ozone analyses and their use for short-term ozone forecasts , 2004 .