Articles | Volume 14, issue 3
Geosci. Model Dev., 14, 1237–1252, 2021
Geosci. Model Dev., 14, 1237–1252, 2021

Development and technical paper 08 Mar 2021

Development and technical paper | 08 Mar 2021

On the model uncertainties in Bayesian source reconstruction using an ensemble of weather predictions, the emission inverse modelling system FREAR v1.0, and the Lagrangian transport and dispersion model Flexpart v9.0.2

Pieter De Meutter et al.

Related subject area

Atmospheric sciences
Evaluation of the interactive stratospheric ozone (O3v2) module in the E3SM version 1 Earth system model
Qi Tang, Michael J. Prather, Juno Hsu, Daniel J. Ruiz, Philip J. Cameron-Smith, Shaocheng Xie, and Jean-Christophe Golaz
Geosci. Model Dev., 14, 1219–1236,,, 2021
Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications
Basit Khan, Sabine Banzhaf, Edward C. Chan, Renate Forkel, Farah Kanani-Sühring, Klaus Ketelsen, Mona Kurppa, Björn Maronga, Matthias Mauder, Siegfried Raasch, Emmanuele Russo, Martijn Schaap, and Matthias Sühring
Geosci. Model Dev., 14, 1171–1193,,, 2021
Short summary
The Vertical City Weather Generator (VCWG v1.3.2)
Mohsen Moradi, Benjamin Dyer, Amir Nazem, Manoj K. Nambiar, M. Rafsan Nahian, Bruno Bueno, Chris Mackey, Saeran Vasanthakumar, Negin Nazarian, E. Scott Krayenhoff, Leslie K. Norford, and Amir A. Aliabadi
Geosci. Model Dev., 14, 961–984,,, 2021
Short summary
A zero-dimensional view of atmospheric degradation of levoglucosan (LEVCHEM_v1) using numerical chamber simulations
Loredana G. Suciu, Robert J. Griffin, and Caroline A. Masiello
Geosci. Model Dev., 14, 907–921,,, 2021
Short summary
The Nonhydrostatic ICosahedral Atmospheric Model for CMIP6 HighResMIP simulations (NICAM16-S): experimental design, model description, and impacts of model updates
Chihiro Kodama, Tomoki Ohno, Tatsuya Seiki, Hisashi Yashiro, Akira T. Noda, Masuo Nakano, Yohei Yamada, Woosub Roh, Masaki Satoh, Tomoko Nitta, Daisuke Goto, Hiroaki Miura, Tomoe Nasuno, Tomoki Miyakawa, Ying-Wen Chen, and Masato Sugi
Geosci. Model Dev., 14, 795–820,,, 2021
Short summary

Cited articles

Becker, A., Wotawa, G., De Geer, L.-E., Seibert, P., Draxler, R. R., Sloan, C., D'Amours, R., Hort, M., Glaab, H., Heinrich, P., Grillon Vyacheslav Shershakov, Y., Katayama, K., Zhang, Y., Stewart, P., Hirtl, M., Jean, M., and Chen, P.: Global backtracking of anthropogenic radionuclides by means of a receptor oriented ensemble dispersion modelling system in support of Nuclear-Test-Ban Treaty verification, Atmos. Environ., 41, 4520–4534,, 2007. a
Bocquet, M.: High-resolution reconstruction of a tracer dispersion event: application to ETEX, Q. J. Roy. Meteor. Soc., 133, 1013–1026,, 2007. a
Bonavita, M., Hólm, E., Isaksen, L., and Fisher, M.: The evolution of the ECMWF hybrid data assimilation system, Q. J. Roy. Meteor. Soc., 142, 287–303,, 2016. a
Bossew, P., Gering, F., Petermann, E., Hamburger, T., Katzlberger, C., Hernandez-Ceballos, M., De Cort, M., Gorzkiewicz, K., Kierepko, R., and Mietelski, J.: An episode of Ru-106 in air over Europe, September–October 2017–Geographical distribution of inhalation dose over Europe, J. Environ. Radioactiv., 205, 79–92,, 2019. a, b
Currie, L. A.: Limits for qualitative detection and quantitative determination. Application to radiochemistry, Analyt. Chem., 40, 586–593,, 1968. a, b
Short summary
Inverse atmospheric transport modelling is an important tool in several disciplines. However, the specification of atmospheric transport model error remains challenging. In this paper, we employ a state-of-the-art ensemble technique combined with a state-of-the-art Bayesian inference algorithm to infer point sources. Our research helps to fill the gap in our understanding of model error in the context of inverse atmospheric transport modelling.