Articles | Volume 12, issue 10
https://doi.org/10.5194/gmd-12-4387-2019
https://doi.org/10.5194/gmd-12-4387-2019
Development and technical paper
 | 
18 Oct 2019
Development and technical paper |  | 18 Oct 2019

A Lagrangian convective transport scheme including a simulation of the time air parcels spend in updrafts (LaConTra v1.0)

Ingo Wohltmann, Ralph Lehmann, Georg A. Gottwald, Karsten Peters, Alain Protat, Valentin Louf, Christopher Williams, Wuhu Feng, and Markus Rex

Related authors

Air mass transport to the tropical western Pacific troposphere inferred from ozone and relative humidity balloon observations above Palau
Katrin Müller, Peter von der Gathen, and Markus Rex
Atmos. Chem. Phys., 24, 4693–4716, https://doi.org/10.5194/acp-24-4693-2024,https://doi.org/10.5194/acp-24-4693-2024, 2024
Short summary
Transport parameterization of the Polar SWIFT model (version 2)
Ingo Wohltmann, Daniel Kreyling, and Ralph Lehmann
Geosci. Model Dev., 15, 7243–7255, https://doi.org/10.5194/gmd-15-7243-2022,https://doi.org/10.5194/gmd-15-7243-2022, 2022
Short summary
Pollution trace gas distributions and their transport in the Asian monsoon upper troposphere and lowermost stratosphere during the StratoClim campaign 2017
Sören Johansson, Michael Höpfner, Oliver Kirner, Ingo Wohltmann, Silvia Bucci, Bernard Legras, Felix Friedl-Vallon, Norbert Glatthor, Erik Kretschmer, Jörn Ungermann, and Gerald Wetzel
Atmos. Chem. Phys., 20, 14695–14715, https://doi.org/10.5194/acp-20-14695-2020,https://doi.org/10.5194/acp-20-14695-2020, 2020
Short summary
Stratospheric ozone loss in the Arctic winters between 2005 and 2013 derived with ACE-FTS measurements
Debora Griffin, Kaley A. Walker, Ingo Wohltmann, Sandip S. Dhomse, Markus Rex, Martyn P. Chipperfield, Wuhu Feng, Gloria L. Manney, Jane Liu, and David Tarasick
Atmos. Chem. Phys., 19, 577–601, https://doi.org/10.5194/acp-19-577-2019,https://doi.org/10.5194/acp-19-577-2019, 2019
Short summary
The Extrapolar SWIFT model (version 1.0): fast stratospheric ozone chemistry for global climate models
Daniel Kreyling, Ingo Wohltmann, Ralph Lehmann, and Markus Rex
Geosci. Model Dev., 11, 753–769, https://doi.org/10.5194/gmd-11-753-2018,https://doi.org/10.5194/gmd-11-753-2018, 2018
Short summary

Related subject area

Atmospheric sciences
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024,https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024,https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024,https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024,https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Observational operator for fair model evaluation with ground NO2 measurements
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024,https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary

Cited articles

Arakawa, A.: The cumulus parameterization problem: past, present, and future, J. Climate, 17, 2493–2525, 2004. a
Arakawa, A. and Wu, C.-M.: A Unified Representation of Deep Moist Convection in Numerical Modeling of the Atmosphere. Part I, J. Atmos. Sci., 70, 1977–1992, 2013. a
Alfred Wegener Institute: Fusion Forge, https://swrepo1.awi.de/, last access: 16 October 2019. a, b
Bechtold, P., Chaboureau, J.-P., Beljaars, A., Betts, A. K., Köhler, M., Miller, M., and Redelsperger, J.-L.: The simulation of the diurnal cycle of convective precipitation over land in a global model, Q. J. Roy. Meteor. Soc., 130, 3119–3137, 2004. a
Berglen, T. F., Berntsen, T. K., Isaksen, I. S. A., and Sundet, J. K.: A global model of the coupled sulfur/oxidant chemistry in the troposphere: The sulfur cycle, J. Geophys. Res., 109, D19310, https://doi.org/10.1029/2003JD003948, 2004. a, b, c, d, e
Download
Short summary
We present a trajectory-based model for simulating the transport of air parcels by convection. Our model extends the approach of existing models by explicitly simulating vertical updraft velocities inside the clouds and the time that an air parcel spends inside the convective event.