EGU22-12168
https://doi.org/10.5194/egusphere-egu22-12168
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Estimating tropical cyclone rainfall using the STORM dataset

Natalie Lord1,2, Nadia Bloemendaal3, Ivan Haigh2,4, Niall Quinn2, Pete Uhe2, and Chris Sampson2
Natalie Lord et al.
  • 1University of Bristol, Cabot Institute, School of Geographical Sciences, Bristol, United Kingdom of Great Britain – England, Scotland, Wales (natalie.lord@bristol.ac.uk)
  • 2Fathom, Square Works, Bristol, UK.
  • 3Lamont-Doherty Earth Observatory, Columbia Climate School, Columbia University, New York, USA.
  • 4School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, Southampton, UK.

How to cite: Lord, N., Bloemendaal, N., Haigh, I., Quinn, N., Uhe, P., and Sampson, C.: Estimating tropical cyclone rainfall using the STORM dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12168, https://doi.org/10.5194/egusphere-egu22-12168, 2022.

This abstract has been withdrawn on 10 May 2022.