Dr. Christopher Jung

Dr. Christopher Jung
Wissenschaftlicher Mitarbeiter (Post-doc)

Werthmannstrasse 10
79085 Freiburg
Raum 00 007

Biographie

Christopher Jung studierte von 2009 bis 2012 „B.Sc. Umweltnaturwissenschaften“ an der Albert-Ludwigs-Universität Freiburg. Von 2012-2015 absolvierte er das Studium „M.Sc. Umweltwissenschaften“ in Freiburg. Seit 2015 ist er wissenschaftlicher Mitarbeiter an der Professur für Umweltmeteorologie. Die Promotion schloss er im Februar 2018 ab.

Forschungsschwerpunkt

Christopher Jungs Forschungsschwerpunkt liegt in der kleinskaligen Modellierung statistischer Eigenschaften der bodennahen Strömung. Die wichtigsten Ziele seiner Forschung sind die Optimierung der Windenergienutzung und die Minderung des Sturmschadensrisikos in Wäldern.

Publikationen

Originalarbeiten in wissenschaftlichen Fachzeitschriften

• Jung C, Schindler D, Grau L, 2018: Achieving Germany's wind energy expansion target with an improved wind turbine siting approach. Energy Conversion and Management, 173: 383-398.
• Jung C, Schindler D, 2018: 3D statistical mapping of Germany’s wind resource using WSWS.  Energy Conversion and Management, 159: 96-108.
• Jung C, Schindler D, Laible J, 2018: National and global wind resource assessment under six wind turbine installation scenarios. Energy Conversion and Management, 156: 403-415.
• Schindler D, Jung C, 2018: Copula-based estimation of directional wind energy yield: A case study from Germany. Energy Conversion and Management, 169: 359-370.
• Grau L, Jung C, Schindler D, 2017: On the Annual Cycle of Meteorological and Geographical Potential of Wind Energy: A Case Study from Southwest Germany. Sustainability, 9: 1169.
• Jung C, Schindler D, 2017: Development of a statistical bivariate wind speed-wind shear model (WSWS) to quantify the height-dependent wind resource. Energy Conversion and Management, 149: 303-317.
• Jung C, Schindler D, 2017: Global comparison of the goodness-of-fit of wind speed distributions. Energy Conversion and Management, 133: 216-234.
• Jung C, Schindler D, Buchholz A, Laible J, 2017: Global gust climate evaluation and its influence on wind turbines. Energies,10: 1474.
• Jung C, Schindler D, Laible J, Buchholz A, 2017: Introducing a system of wind speed distributions for modeling properties of wind speed regimes around the world. Energy Conversion and Management, 144: 181-192.
• Jung C, 2016: High spatial resolution simulation of annual wind yield using near-surface wind speed time series  Energies, 9 (5): 344. 
• Jung C, Schindler D, 2016: Modelling monthly near-surface maximum daily gust speed distributions in Southwest Germany. International Journal of Climatology, 36: 4058-4070.
• Jung C, Schindler D, Albrecht AT, Buchholz A., 2016: The Role of Highly-Resolved Gust Speed in Simulations of Storm Damage in Forests at the Landscape Scale: A Case Study from Southwest Germany. Atmosphere, 7: 7.
• Schindler D, Jung C, Buchholz, A, 2016: Using highly resolved maximum gust speed as predictor for forest storm damage caused by the high-impact winter storm Lothar in Southwest Germany. Atmospheric Science Letters, 17: 462-469.
• Jung C, Schindler D, 2015: Statistical modeling of near-surface wind speed: A case study from Baden-Wuerttemberg (Southwest Germany). Austin Journal of Earth Science, 2015; 2 (1) (online): 1006. 

Konferenzbeiträge

• Jung C, Schindler D, 2017: Global return Level estimation of the most severe tropical cyclones and European winter storms in the last decades. International Congress of Biometeorology 2017; Durham UK.
• Schindler D, Jung C, 2017: Empirical modelling of forest storm damage in Southwest Germany. International Congress of Biometeorology 2017; Durham UK.
• Albrecht A, Jung C, Schindler D, 2017: Testing correlations between modeled gust speed and empirical storm in Southwest German forests. 8th International conference on Wind and Trees; Boulder, CO.
• Jung C, Schindler D, Albrecht AT, Buchholz A, 2015: The Role of Highly-Resolved Gust Speed in Simulations of Storm Damage in Forest at the Landscape Scale: A case Study from Southwest Germany. Mathematical Modelling of Wind Damage Risk to Forests 2015; Arcachon Frankreich.