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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-103
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-103
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 07 Jun 2019

Submitted as: model description paper | 07 Jun 2019

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Geoscientific Model Development (GMD).

Overview of the PALM model system 6.0

Björn Maronga1,2, Sabine Banzhaf3, Cornelia Burmeister4, Thomas Esch5, Renate Forkel6, Dominik Fröhlich7, Vladimir Fuka8, Katrin Frieda Gehrke1, Jan Geletič9, Sebastian Giersch1, Tobias Gronemeier1, Günter Groß1, Wieke Heldens5, Antti Hellsten10, Fabian Hoffmann1,11, Atsushi Inagaki12, Eckhard Kadasch13, Farah Kanani-Sühring1, Klaus Ketelsen14, Basit Ali Khan6, Christoph Knigge1,13, Helge Knoop1, Pavel Krč9, Mona Kurppa15, Halim Maamari16, Andreas Matzarakis7, Matthias Mauder6, Matthias Pallasch16, Dirk Pavlik4, Jens Pfafferott17, Jaroslav Resler9, Sascha Rissmann17, Emmanuele Russo3,18,19, Mohamed Salim20,21, Michael Schrempf1, Johannes Schwenkel1, Gunther Seckmeyer1, Sebastian Schubert20, Matthias Sühring1, Robert von Tils1,4, Lukas Vollmer22,23, Simon Ward1, Björn Witha22, Hauke Wurps22, Julian Zeidler5, and Siegfried Raasch1 Björn Maronga et al.
  • 1Leibniz University Hannover, Institute of Meteorology and Climatology, Hannover, Germany
  • 2University of Bergen, Geophysical Institute, Bergen, Norway
  • 3Freie Universität Berlin, Institut für Meteorologie, Berlin, Germany
  • 4GEO-NET Environmental Services GmbH, Hannover/Dresden, Germany
  • 5German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, Germany
  • 6Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
  • 7Deutscher Wetterdienst, Research Center Human Biometeorology, Freiburg, Germany
  • 8Charles University, Department of Atmospheric Physics, Faculty of Mathematics and Physics, Prague, Czech Republic
  • 9The Czech Academy of Sciences, Institute of Computer Science, Prague, Czech Republic
  • 10Finnish Meteorological Institute, Helsinki, Finland
  • 11current affiliation: Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, USA;NOAA Earth Systems Research Laboratory, Chemical Sciences Division, Boulder, Colorado, USA
  • 12School of Environment and Society, Tokyo Institute of Technology, Tokyo, Japan
  • 13Deutscher Wetterdienst, Offenbach, Germany
  • 14Software Consultant, Berlin, Germany
  • 15Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
  • 16Ingenieurgesellschaft Prof. Dr. Sieker mbH, Hoppegarten, Germany
  • 17Hochschule Offenburg, Offenburg, Germany
  • 18current affiliation: Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
  • 19current affiliation: Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
  • 20Humboldt-Universität zu Berlin, Berlin, Germany
  • 21Faculty of Energy Engineering, Aswan University, Aswan, Egypt
  • 22Carl von Ossietzky Universität Oldenburg, ForWind – Research Center of Wind Energy, Oldenburg, Germany
  • 23current affiliation: Fraunhofer Institute for Wind Energy Systems, Oldenburg, Germany

Abstract. In this paper we describe the PALM model system 6.0. PALM is a Fortran based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model by components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.

Björn Maronga et al.
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Short summary
In this paper we describe the PALM model system 6.0. PALM is a Fortran based turbulence-resolving code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. During the last years, PALM has been significantly improved and now offers a variety of new components that are especially designed to simulate the urban atmosphere at building-resolving resolution.
In this paper we describe the PALM model system 6.0. PALM is a Fortran based...
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