A comparison of reanalysis techniques: Applying optimal interpolation and Ensemble Kalman Filtering to improve air quality monitoring at mesoscale
Academic Article
Publication Date:
2013
abstract:
To fulfill the requirements of the 2008/50 Directive, which allows member states and regional authorities to use a combination of measurement and modeling to monitor air pollution concentration, a key approach to be properly developed and tested is the data assimilation one. In this paper, with a focus on regional domains, a comparison between optimal interpolation and Ensemble Kalman Filter is shown, to stress pros and drawbacks of the two techniques. These approaches can be used to implement a more accurate monitoring of the long-term pollution trends on a geographical domain, through an optimal combination of all the available sources of data.
Iris type:
01.01 Articolo in rivista
Keywords:
Data assimilation; Optimal interpolation; Ensemble Kalman Filter; Particulate matter
List of contributors:
Candiani, Gabriele
Published in: