Skip to main content

Concept and workflow for 3D visualization of atmospheric data in a virtual reality environment for analytical approaches


In the future, climate change will strongly influence our environment and living conditions. Weather and Climate simulations that predict possible changes produce big data sets. The combination of various variables of climate models with spatial data from different sources helps to identify correlations and to study key processes. In this paper, the results of the Weather Research and Forecasting model are visualized for two regions. For this purpose, a continuous workflow that leads from the integration of heterogeneous raw data to 3D visualizations that can be displayed on a desktop computer or in an interactive virtual reality environment is developed. These easy-to-understand visualizations of complex data are the basis for scientific communication and for the evaluation and verification of models as well as for interdisciplinary discussions of the research results.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15


  • Ahrens J, Geveci B, Law C (2005) ParaView: an end-user tool for large data visualization. In: Hansen C, Johnson C (eds) In the visualization handbook. Oxford, London, pp 717–732

    Chapter  Google Scholar 

  • American Meteorological Society (1993) Guidelines for using color to depict meteorological information: IIPS subcommittee for color guidelines. Bull Am Meteorol Soc 74(9):64–81

    Google Scholar 

  • Anderson J, Andres J (2010) Voyager: an interactive software for visualizing large, geospatial data sets. Mar Technol Soc J 44(4):8–19

    Article  Google Scholar 

  • Andrienko G, Andrienko N et al (2011) Challenging problems of geospatial visual analytics. J Vis Lang Comput 22(4):251–256. doi:10.1016/j.jvlc.2011.04.001

    Article  Google Scholar 

  • Autodesk: Autodesk VRED 3D (2013).

  • Barthlott C, Hauck C, Adler GS, Kalthoff N, Kottmeier C (2011) Soil moisture impacts on convective indices and precipitation over complex terrain. Meteorol Z 20(2):185–197. doi:10.1127/0941-2948/2011/0216

    Article  Google Scholar 

  • Bauer HS, Weusthoff T, Dorninger M, Wulfmeyer V, Schwitalla T, Gorgas T, Arpagaus M, Warrach-Sagi K (2011) Predictive skill of a subset of models participating in D-PHASE in the COPS region. Q J R Meteorol Soc 137(S1):287–305. doi:10.1002/qj.715

    Article  Google Scholar 

  • Behrendt A, Pal S, Wulfmeyer V, Valdebenito BAM, Lammel G (2011) A novel approach for the characterization of transport and optical properties of aerosol particles near sources part I: measurement of particle backscatter coefficient maps with a scanning UV lidar. Atmos Environ 45(16):2795–2802. doi:10.1016/j.atmosenv.2011.02.061

    Article  Google Scholar 

  • Bissinger V, Kolditz O (2008) Helmholtz interdisciplinary graduate school for environmental research (HIGRADE). GAIA-Ecol Perspect Sci 17(1):71–73

    Google Scholar 

  • Catchments As Organized Systems (CAOS) (2013).

  • Clyne J, Mininni P, Norton A, Rast M (2007) Interactive desktop analysis of high resolution simulations: application to turbulent plume dynamics and current sheet formation. New J Phys 9(8):301–301. doi:10.1088/1367-2630/9/8/301

    Article  Google Scholar 

  • Edenhofer O, Seyboth K (2013) Intergovernmental panel on climate change. Encycl Energy Nat Resour Environ Econ 1:48–56

    Google Scholar 

  • Endlicher W, Gerstengabe FW (2007) Der Klimawandel: Einblicke, Rückblicke und Ausblicke. Tech. rep., Humboldt-Universität zu Berlin, Potsdam Institute for Climate Impact Research

  • ESRI (1998) ESRI shapefile technical description. Environmental Systems Research Institute, Inc

  • Forlines C, Wittenburg K (2010) Wakame: sense making of multi-dimensional spatial-temporal data. In: Proceedings of the international conference on advanced visual interfaces—AVI ’10, ACM Press, New York, New York, USA, p 33. doi:10.1145/1842993.1843000

  • Gerstner T, Meetschen D, Crewell S, Griebel M, Simmer C (2002) A case study on multiresolution visualization of local rainfall from weather radar measurements. In: Proceedings of the conference on visualization. IEEE Computer Society, Washington, DC, USA, pp 533–536

  • Goldstone W (2011) Unity 3.x game development essentials, 2nd edn. Packt Publishing, Birmingham

    Google Scholar 

  • Grathwohl P, Rügner H, Wöhling T et al (2013) Catchments as reactors: a comprehensive approach for water fluxes and solute turn-over. Environ Earth Sci 69(2). doi:10.1007/s12665-013-2281-7

  • Gregory J (2003) The CF metadata standard.

  • Griebel M, Preusser T, Rumpf M, Schweitzer M, Telea A (2004) Flow field clustering via algebraic multigrid. In: IEEE visualization 2004. IEEE Computer Society, pp 35–42. doi:10.1109/VISUAL.2004.32

  • Grützun V, Knoth O, Simmel M (2008) Simulation of the influence of aerosol particle characteristics on clouds and precipitation with LM-SPECS: model description and first results. Atmos Res 90(2–4):233–242. doi:10.1016/j.atmosres.2008.03.002

    Article  Google Scholar 

  • Haase H, Bock M, Hergenröther E (2000) Meteorology meets computer graphics—a look at a wide range of weather visualisations for diverse audiences. Comput Gr 24:391–397

    Article  Google Scholar 

  • Helbig C, Rink K, Marx A, Priess J, Frank M, Kolditz O (2012) Visual integration of diverse environmental data : a case study in Central Germany. In: Proceedings of iEMSs Conference 2012, Leipzig, Germany, pp 1–8

  • Hibbard WL, Anderson J, Foster I et al (1996) Exploring coupled atmosphere--ocean models using Vis5D. Int J High Perform Comput Appl 10(2–3):211–222. doi:10.1177/109434209601000208

    Article  Google Scholar 

  • Illert A (2009) Infrastructure for spatial Information in Europe (INSPIRE) —status report on the development of implementing rules for geographical names data. United Nations group of experts on geographical names, pp 1–7

  • Jacob D, Petersen J, Eggert B, Alias A, Christensen OB, Bouwer LM, Braun A et al (2013) EURO-CORDEX: new high-resolution climate change projections for European impact research. Reg Environ Change. doi:10.1007/s10113-013-0499-2

  • Johnson C (2004) Top scientific visualization research problems. IEEE Comput Gr Appl 24(4):13–17. doi:10.1109/MCG.2004.20

    Article  Google Scholar 

  • Johnson C, Sanderson A (2003) A next step: visualizing errors and uncertainty. IEEE Comput Graphics Appl 23(5):6–10. doi:10.1109/MCG.2003.1231171

    Article  Google Scholar 

  • José RS, Pérez J, González R (2012) Advances in 3D visualization of air quality data. In: Usage, usability, and utility of 3D city models—European COST Action. EDP Sciences, Les Ulis, France, pp 1–9. doi:10.1051/3u3d/201202002

  • Keeling SJ (2010) Visualization of the weather-past and present. Meteorol Appl 17(2):126–133. doi:10.1002/met.208

    Article  Google Scholar 

  • Kolditz O, Bauer S, Bilke L, Böttcher N, Delfs JO, Fischer T, Görke UJ, Kalbacher T, Kosakowski G, McDermott CI, Park CH, Radu F, Rink K, Shao H, Shao HB, Sun F, Sun YY, Singh AK, Taron J, Walther M, Wang W, Watanabe N, Wu Y, Xie M, Xu W, Zehner B (2012) OpenGeoSys: an open-source initiative for numerical simulation of thermo-hydro-mechanical/chemical (THM/C) processes in porous media. Environ Earth Sci 67(2):589–599. doi:10.1007/s12665-012-1546-x

    Article  Google Scholar 

  • Kolditz O, Rink K, Shao H, Kalbacher T, Zacharias S, Dietrich P (2012) International viewpoint and news: data and modelling platforms in environmental earth sciences. Environ Earth Sci 66(4):1279–1284. doi:10.1007/s12665-012-1661-8

    Article  Google Scholar 

  • Kosara R, Healey C, Interrante V (2003) Thoughts on user studies: why, how, and when. IEEE Comput Gr Appl 23(4):20–25

    Article  Google Scholar 

  • Koutek M, van der Neut I, Lemcke K et al (2011) Exploration of severe weather events in virtual reality environments. In: European conference on applications of meteorology EMS Annual Meeting, Berlin

  • Laha B, Bowman D (2012) Identifying the benefits of immersion in virtual reality for volume data visualization. In: Immersive visualization revisited workshop of the IEEE VR conference, pp 1–2

  • Law M, Collins A (2013) Getting to know ArcGIS for desktop, 3rd edn. Esri Press, Redland, Caliornia

    Google Scholar 

  • Mahammad S, Ramakrishnan R (2003) GeoTIFF-A standard image file format for GIS applications.

  • Michalakes J, Dudhia J, Gill D (2004) The weather research and forecast model: software architecture and performance. In: 11th ECMWF workshop on the use of high performance computing in meteorology

  • Neset T, Johansson J, Linnér B (2009) State of climate visualization, CSPR Report No 09:04. Tech. rep., Centre for Climate Science and Policy Research, Norrköping, Sweden

  • Nocke T, Sterzel T, Böttinger M, Wrobel M (2008) Visualization of climate and climate change data: an overview. In: Digital earth summit on geoinformatics 2008: tools for global change research, Wichmann, pp 226–232

  • Peng Z, Laramee R (2009) Higher dimensional vector field visualization: a survey. In: Eurographic conference on theory and practice of computer graphics, pp 149–163. doi:10.2312/LocalChapterEvents/TPCG/TPCG09/149-163

  • Rew R, Davis G (1990) NetCDF: an interface for scientific data access. IEEE Comput Gr Appl 10(4):76–82

    Article  Google Scholar 

  • Rink K, Bilke L, Kolditz O (2013a) Visualisation strategies for environmental modelling data. Environ Earth Sci. doi:10.1007/s12665-013-2970-2

  • Rink K, Bilke L, Kolditz O (2013b) Visualisation strategies for modelling and simulation using geoscientific data. In: Workshop on visualisation in environmental sciences (EnvirVis). Eurographics Association, Leipzig, pp 47–51. doi:10.2312/PE.EnvirVis.EnvirVis13.047-051

  • Rink K, Fischer T, Selle B, Kolditz O (2012) A data exploration framework for validation and setup of hydrological models. Environ Earth Sci 69(2):469–477. doi:10.1007/s12665-012-2030-3

    Article  Google Scholar 

  • Schlegel S, Böttinger M, Hlawitschka M, Scheuermann G (2013) Determining and visualizing potential sources of floods. In: Workshop on visualisation in environmental sciences (EnvirVis). Eurographics Association, Leipzig, pp 65–69. doi:10.2312/PE.EnvirVis.EnvirVis13.065-069

  • Schroeder W, Martin K, Lorensen B (2006) Visualization toolkit: an object-oriented approach to 3D graphics. Kitware, New York

    Google Scholar 

  • Schulzweida U, Kornblueh L (2006) CDO user’s guide. Max-Planck-Institute for Meteorology, Hamburg

    Google Scholar 

  • Schwitalla T, Bauer HS, Wulfmeyer V, Aoshima F (2011) High-resolution simulation over central Europe: assimilation experiments during COPS IOP 9c. Q J R Meteorol Soc 137(S1):156–175. doi:10.1002/qj.721

    Article  Google Scholar 

  • Schwitalla T, Bauer HS, Wulfmeyer V, Zängl G (2008) Systematic errors of QPF in low-mountain regions as revealed by MM5 simulations. Meteorol Z 17(6):903–919. doi:10.1127/0941-2948/2008/0338

    Article  Google Scholar 

  • Sehili AM, Wolke R, Knoth O, Simmel M, Tilgner A, Herrmann H (2005) Comparison of different model approaches for the simulation of multiphase processes. Atmos Environ 39(23–24):4403–4417. doi:10.1016/j.atmosenv.2005.02.039

    Article  Google Scholar 

  • Simpson R, LaViola J, Laidlaw D, Forsberg A, van Dam A (2000) Immersive VR for scientific visualization: a progress report. IEEE Comput Gr Appl 20(6):26–52. doi:10.1109/38.888006

    Article  Google Scholar 

  • Treinish LA (1999) Task-specific visualization design. IEEE Comput Gr Appl 19(5):72–77

    Article  Google Scholar 

  • Trembilski A (2001) Two methods for cloud visualisation from weather simulation data. Vis Comput 17(3):179–184. doi:10.1007/PL00013405

    Article  Google Scholar 

  • University Corporation for Atmospheric Research: NCL (2013).

  • van Dam A, Laidlaw DH, Simpson RM (2002) Experiments in immersive virtual reality for scientific visualization. Comput Gr 26(4):535–555. doi:10.1016/S0097-8493(02)00113-9

    Article  Google Scholar 

  • Vautard R, Gobiet A, Jacob D, Belda M, Colette A, Déqué M, Fernández J et al (2013) The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project. Climate Dynamics 41(9–10):2555–2575. doi:10.1007/s00382-013-1714-z

  • Verbree E, Maren GV, Germs R, Jansen F, Kraak MJ (1999) Interaction in virtual world views-linking 3D GIS with VR. Int J Geogr Inf Sci 13(4):385–396. doi:10.1080/136588199241265

    Article  Google Scholar 

  • Walther M, Bilke L, Delfs JO, Graf T, Grundmann J, Kolditz O, Liedl R (2014) Assessing the saltwater remediation potential of a three-dimensional, heterogeneous, coastal aquifer system. Model verification, application and visualization for transient density-driven seawater intrusion. Environ Earth Sci

  • Wang W, Kolditz O (2010) Sparse matrix and solver objects for parallel finite element simulation of multi-field problems. High performance computing and applications, pp 418–425.

  • Warrach-Sagi K, Schwitalla T, Wulfmeyer V, Bauer HS (2013) Evaluation of a climate simulation in Europe based on the WRFNOAH model system: precipitation in Germany. Clim Dyn 41(3–4):755–774. doi:10.1007/s00382-013-1727-7

    Article  Google Scholar 

  • Wier S, Meertens C (2008) The GEON integrated data viewer (IDV) for exploration of geoscience data with visualizations. In: American Geophysical Union, Fall Meeting, pp 1–4

  • Wulfmeyer V, Behrendt A, Kottmeier C et al (2011) The convective and orographically-induced precipitation study (COPS): the scientific strategy, the field phase, and research highlights. Q J R Meteorol Soc 137(S1):3–30. doi:10.1002/qj.752

    Article  Google Scholar 

  • Zehner B (2008) Landscape visualization in high resolution stereoscopic visualization environments multichannel rendering. In: Digital design in landscape architecture 2008. Proceedings at Anhalt University of Applied Sciences. Wichmann, Heidelberg, pp 224–231

  • Zehner B, Watanabe N, Kolditz O (2010) Visualization of gridded scalar data with uncertainty in geosciences. Comput Geosci 36(10):1268–1275. doi:10.1016/j.cageo.2010.02.010

    Article  Google Scholar 

Download references


The first author would like to express her gratitude to the European Social Fund (ESF) as part of the program ”Europa fördert Sachsen” for the funding of the scholarship. We thank HIGRADE, the graduate school of UFZ (Bissinger and Kolditz 2008), and CompeTE+ the school for doctoral students at the HTWK. The authors gratefully acknowledge the data support of the Spatial Information and Planning System (RIPS) of the Regional Office for Environment, Measurement and Nature Protection of Baden-Württemberg. Thanks to Dr. Andreas Marx and the climate data support of CERA (Climate and Environmental Retrieving and Archiving) for providing the observation data. The presented work is part of the WESS project, WESS is supported by a grant from the Ministry of Science, Research and Arts of Baden-Württemberg (AZ Zu 33-721.3-2) and the Helmholtz Center for Environmental Research, Leipzig (UFZ). The satellite images were provided by the NERC Satellite Receiving Station, Dundee University, Scotland from

Author information

Authors and Affiliations


Corresponding author

Correspondence to Carolin Helbig.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Helbig, C., Bauer, HS., Rink, K. et al. Concept and workflow for 3D visualization of atmospheric data in a virtual reality environment for analytical approaches. Environ Earth Sci 72, 3767–3780 (2014).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


  • Visualization
  • Climate modeling
  • WRF
  • Virtual reality
  • Visualization concept
  • Visualization workflow
  • OpenGeoSys Data Explorer