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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 2 | Copyright
Geosci. Model Dev., 11, 561-573, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 08 Feb 2018

Model description paper | 08 Feb 2018

BEATBOX v1.0: Background Error Analysis Testbed with Box Models

Christoph Knote1, Jérôme Barré2, and Max Eckl1,a Christoph Knote et al.
  • 1Meteorological Institute, LMU, 80333 Munich, Germany
  • 2European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
  • anow at: Institute of Atmospheric Physics, DLR, 82234 Oberpfaffenhofen, Germany

Abstract. The Background Error Analysis Testbed (BEATBOX) is a new data assimilation framework for box models. Based on the BOX Model eXtension (BOXMOX) to the Kinetic Pre-Processor (KPP), this framework allows users to conduct performance evaluations of data assimilation experiments, sensitivity analyses, and detailed chemical scheme diagnostics from an observation simulation system experiment (OSSE) point of view. The BEATBOX framework incorporates an observation simulator and a data assimilation system with the possibility of choosing ensemble, adjoint, or combined sensitivities. A user-friendly, Python-based interface allows for the tuning of many parameters for atmospheric chemistry and data assimilation research as well as for educational purposes, for example observation error, model covariances, ensemble size, perturbation distribution in the initial conditions, and so on. In this work, the testbed is described and two case studies are presented to illustrate the design of a typical OSSE experiment, data assimilation experiments, a sensitivity analysis, and a method for diagnosing model errors. BEATBOX is released as an open source tool for the atmospheric chemistry and data assimilation communities.

Publications Copernicus
Short summary
The Background Error Analysis Testbed with Box Models (BEATBOX) is a toy model to investigate the effects of data assimilation on systems like tropospheric photochemistry in a box model fashion. We present the model system and show its application in a case study using data from a recent field campaign and employing commonly used tropospheric chemistry mechanisms.
The Background Error Analysis Testbed with Box Models (BEATBOX) is a toy model to investigate...