Assessment of ensemble-based chemical data assimilation in an idealized setting |
| |
Institution: | 1. Institute of Physical Chemistry, Justus-Liebig-University of Giessen, Heinrich-Buff-Ring 17, 35392 Giessen, Germany;2. IFW Dresden, Institute for Complex Materials, Helmholtzstr. 20, 01069 Dresden, Germany |
| |
Abstract: | Data assimilation is the process of integrating observational data and model predictions to obtain an optimal representation of the state of the atmosphere. As more chemical observations in the troposphere are becoming available, chemical data assimilation is expected to play an essential role in air quality forecasting, similar to the role it has in numerical weather prediction (NWP). Considerable progress has been made recently in the development of variational tools for chemical data assimilation. In this paper, we assess the performance of the ensemble Kalman filter (EnKF). Results in an idealized setting show that EnKF is promising for chemical data assimilation. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|