Hendrik Elbern

TL;DR: In this paper, the authors assess the potential and limits of an advanced inversion method to estimate pollutant pre- cursor sources mainly from observations, using the four dimensional variational data assimilation technique.

TL;DR: In this article, the authors describe the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (summer 2014) European projects to provide air quality services for the European continent.

TL;DR: The Global and Regional Earth System Monitoring Using Satellite and In Situ Data (GEMS) project is combining the manifold expertise in atmospheric composition research and numerical weather prediction of 32 European institutes to build a comprehensive monitoring and forecasting system for greenhouse gases, reactive gases, aerosol and regional air quality as discussed by the authors.

TL;DR: In this article, the authors review the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data-assimilation in Coupled Chemistry Meteorology Models (CCMM).

TL;DR: It is shown that the space–time variational approach is able to analyze emission rates of NO directly, for volatile organic compounds (VOC), regularization techniques must be introduced, however.