Staff

Franz Kanngießer

FB 1: Ozeanzirkulation und Klimadynamik
FE Maritime Meteorologie

Office:
Phone:
+49 431 600 2492
Email:
fkanngiesser(at)geomar.de

Address:
Wischhofstraße 1-3
24148 Kiel

research topics

  • remote sensing of aerosol processes
  • aerosol optics
  • application of machine learning methods
  • impact of mineral dust on air quality and climate system

curriculum vitae

2011 - 2014 studies in meteorology (BSc), Leipzig University

2014 - 2017 studies in meteorology (MSc), Leipzig University, thesis: "Observations of glories above arctic boundary layer clouds to identify cloud phase and derive its frequency" (original title in German)

2017 - 2022 doctoral researcher in radio- und space science, Chalmers University of Technology, Schweden

2020 fil. lic., thesis: "Modelling optical properties of morphological complex soot aerosol"

2022 PhD, thesis: "Modelling optical properties of morphological complex aerosol"

2022 - 2023 postdoctoral researcher, University of Cologne

since 2023 postdoctoral researcher, GEOMAR

 

selected publications (before May 2023)

  • Michael Kahnert and Franz Kanngießer, "Optical properties of marine aerosol: modelling the transition from dry, irregularly shaped crystals to brine-coated, dissolving salt particles", J. Quant. Spectrosc. Radiat. Transfer, 295, 108408 (2023)
  • Michael Kahnert, Franz Kanngießer, Emma Järvinen and Martin Schnaiter, "Aerosol-optics model for the backscatter depolarisation ratio of mineral dust particles", J. Quant. Spectrosc. Radiat. Transfer, 254, 107177 (2020)
  • Franz Kanngiesser and Michael Kahnert, "Coating material-dependent differences in modelled lidar-measurable quantities for heavily coated soot particles," Opt. Express, 27, 36368-36387 (2019)
Number of items: 2.

Articles in a Scientific Journal - peer-reviewed

[thumbnail of Geophysical Research Letters - 2024 - Kahnert - Optical Characterization of Marine Aerosols Using a Morphologically.pdf]

Kahnert, M. and Kanngießer, F. (2024) Optical Characterization of Marine Aerosols Using a Morphologically Realistic Model With Varying Water Content: Implications for Lidar Applications and Passive Polarimetric Remote Sensing. Open Access Geophysical Research Letters, 51 (5). Art.Nr. e2023GL107541. DOI 10.1029/2023GL107541.

[thumbnail of AGU Advances - 2024 - Kanngießer - Seeing Beneath the Clouds Machine‐Learning‐Based Reconstruction of North African Dust-1.pdf]

Kanngießer, F. and Fiedler, S. (2024) “Seeing” Beneath the Clouds — Machine-Learning-Based Reconstruction of North African Dust Plumes. Open Access AGU Advances, 5 (1). Art.Nr. e2023AV001042. DOI 10.1029/2023AV001042.

This list was generated on Sat Dec 21 15:52:11 2024 CET.