Data assimilation and statistical post-processing for numerical air quality predictions

Abstract

This is a joint report based on work by NILU and NR on the use of data assimilation and statistical post-processing tools to improve the air quality prediction in the context of the Bedre Byluft programme. The objective is to improve Bedre Byluft air quality prediction at both the short and long-term (hours and days to weeks), in particular for meteorological conditions associated with high pressures, which historically have been difficult to predict. We present the tools; present first results and quantify the performance of the tools; and outline further work needed to make these tools operational.