Articles | Volume 8, issue 8
https://doi.org/10.5194/gmd-8-2569-2015
https://doi.org/10.5194/gmd-8-2569-2015
Model description paper
 | 
13 Aug 2015
Model description paper |  | 13 Aug 2015

The LAGRANTO Lagrangian analysis tool – version 2.0

M. Sprenger and H. Wernli

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Cited articles

Aemisegger, F., Pfahl, S., Sodemann, H., Lehner, I., Seneviratne, S. I., and Wernli, H.: Deuterium excess as a proxy for continental moisture recycling and plant transpiration, Atmos. Chem. Phys., 14, 4029–4054, https://doi.org/10.5194/acp-14-4029-2014, 2014.
Austin, J. and Tuck, A. F.: The calculation of stratospheric air parcel trajectories using satellite data, Q. J. Roy. Meteor. Soc., 111, 279–307, 1985.
Baldauf, M., Seifert, A., Foerstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational convective-scale numerical weather prediction with the COSMO-model: Description and sensitivities, Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011.
Bevis, M. and Chatelain, J.-L.: Locating a point on a spherical surface relative to a spherical polygon of arbitrary shape, Math. Geol., 21, 811–828, 1989.
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