Articles | Volume 12, issue 12
Geosci. Model Dev., 12, 5197–5212, 2019
https://doi.org/10.5194/gmd-12-5197-2019
Geosci. Model Dev., 12, 5197–5212, 2019
https://doi.org/10.5194/gmd-12-5197-2019

Methods for assessment of models 11 Dec 2019

Methods for assessment of models | 11 Dec 2019

Algorithmic differentiation for cloud schemes (IFS Cy43r3) using CoDiPack (v1.8.1)

Manuel Baumgartner et al.

Related authors

In situ observation of new particle formation (NPF) in the tropical tropopause layer of the 2017 Asian monsoon anticyclone – Part 2: NPF inside ice clouds
Ralf Weigel, Christoph Mahnke, Manuel Baumgartner, Martina Krämer, Peter Spichtinger, Nicole Spelten, Armin Afchine, Christian Rolf, Silvia Viciani, Francesco D'Amato, Holger Tost, and Stephan Borrmann
Atmos. Chem. Phys., 21, 13455–13481, https://doi.org/10.5194/acp-21-13455-2021,https://doi.org/10.5194/acp-21-13455-2021, 2021
Short summary
In situ observation of new particle formation (NPF) in the tropical tropopause layer of the 2017 Asian monsoon anticyclone – Part 1: Summary of StratoClim results
Ralf Weigel, Christoph Mahnke, Manuel Baumgartner, Antonis Dragoneas, Bärbel Vogel, Felix Ploeger, Silvia Viciani, Francesco D'Amato, Silvia Bucci, Bernard Legras, Beiping Luo, and Stephan Borrmann
Atmos. Chem. Phys., 21, 11689–11722, https://doi.org/10.5194/acp-21-11689-2021,https://doi.org/10.5194/acp-21-11689-2021, 2021
Short summary
High Homogeneous Freezing Onsets of Sulfuric Acid Aerosol at Cirrus Temperatures
Julia Schneider, Kristina Höhler, Robert Wagner, Harald Saathoff, Martin Schnaiter, Tobias Schorr, Isabelle Steinke, Stefan Benz, Manuel Baumgartner, Christian Rolf, Martina Krämer, Thomas Leisner, and Ottmar Möhler
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-319,https://doi.org/10.5194/acp-2021-319, 2021
Revised manuscript accepted for ACP
Short summary
New investigations on homogeneous ice nucleation: the effects of water activity and water saturation formulations
Manuel Baumgartner, Christian Rolf, Jens-Uwe Grooß, Julia Schneider, Tobias Schorr, Ottmar Möhler, Peter Spichtinger, and Martina Krämer
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-320,https://doi.org/10.5194/acp-2021-320, 2021
Preprint under review for ACP
Short summary
On numerical broadening of particle size spectra: a condensational growth study using PyMPDATA 1.0
Michael Olesik, Sylwester Arabas, Jakub Banaśkiewicz, Piotr Bartman, Manuel Baumgartner, and Simon Unterstrasser
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-404,https://doi.org/10.5194/gmd-2020-404, 2021
Preprint under review for GMD

Related subject area

Atmospheric sciences
Efficient ensemble generation for uncertain correlated parameters in atmospheric chemical models: a case study for biogenic emissions from EURAD-IM version 5
Annika Vogel and Hendrik Elbern
Geosci. Model Dev., 14, 5583–5605, https://doi.org/10.5194/gmd-14-5583-2021,https://doi.org/10.5194/gmd-14-5583-2021, 2021
Short summary
Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0
Jianbing Jin, Arjo Segers, Hai Xiang Lin, Bas Henzing, Xiaohui Wang, Arnold Heemink, and Hong Liao
Geosci. Model Dev., 14, 5607–5622, https://doi.org/10.5194/gmd-14-5607-2021,https://doi.org/10.5194/gmd-14-5607-2021, 2021
Short summary
Atmosphere–ocean–aerosol–chemistry–climate model SOCOLv4.0: description and evaluation
Timofei Sukhodolov, Tatiana Egorova, Andrea Stenke, William T. Ball, Christina Brodowsky, Gabriel Chiodo, Aryeh Feinberg, Marina Friedel, Arseniy Karagodin-Doyennel, Thomas Peter, Jan Sedlacek, Sandro Vattioni, and Eugene Rozanov
Geosci. Model Dev., 14, 5525–5560, https://doi.org/10.5194/gmd-14-5525-2021,https://doi.org/10.5194/gmd-14-5525-2021, 2021
Short summary
Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021,https://doi.org/10.5194/gmd-14-5487-2021, 2021
Short summary
Mesoscale nesting interface of the PALM model system 6.0
Eckhard Kadasch, Matthias Sühring, Tobias Gronemeier, and Siegfried Raasch
Geosci. Model Dev., 14, 5435–5465, https://doi.org/10.5194/gmd-14-5435-2021,https://doi.org/10.5194/gmd-14-5435-2021, 2021
Short summary

Cited articles

Albring, T., Sagebaum, M., and Gauger, N. R.: Efficient Aerodynamic Design using the Discrete Adjoint Method in SU2, AIAA 2016-3518, 2016. a
Asai, T.: A Numerical Study of the Air-Mass Transformation over the Japan Sea in Winter, J. Meteorol. Soc. Jpn. Ser. II, 43, 1–15, 1965. a
Baumgartner, M.: Algorithmic Differentiation for Cloud Schemes using CoDiPack (v1.8.1), Zenodo, https://doi.org/10.5281/zenodo.3461483, 2019. a
Belikov, D. A., Maksyutov, S., Yaremchuk, A., Ganshin, A., Kaminski, T., Blessing, S., Sasakawa, M., Gomez-Pelaez, A. J., and Starchenko, A.: Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation, Geosci. Model Dev., 9, 749–764, https://doi.org/10.5194/gmd-9-749-2016, 2016. a
Bischof, C. H. and Eberhard, P.: Automatic differentiation of numerical integration algorithms, Math. Comp., 68, 717–731, https://doi.org/10.1090/S0025-5718-99-01027-3, 1999. a, b, c
Download
Short summary
Numerical models in atmospheric sciences need to include physical processes through parameterizations, which are not explicitly resolved, e.g., the formation of clouds. As a consequence, the parameterizations contain uncertain parameters. We suggest using the technique of algorithmic differentiation (AD) to identify the most uncertain parameters within parameterizations. In this study, we illustrate AD by analyzing a scheme for liquid clouds incorporated into a parcel model framework.