Articles | Volume 17, issue 23
https://doi.org/10.5194/acp-17-14253-2017
https://doi.org/10.5194/acp-17-14253-2017
Research article
 | 
01 Dec 2017
Research article |  | 01 Dec 2017

Multifractal evaluation of simulated precipitation intensities from the COSMO NWP model

Daniel Wolfensberger, Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer, and Alexis Berne

Related authors

Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024,https://doi.org/10.5194/amt-17-2539-2024, 2024
Short summary
On the polarimetric backscatter by a still or quasi-still wind turbine
Marco Gabella, Martin Lainer, Daniel Wolfensberger, and Jacopo Grazioli
Atmos. Meas. Tech., 16, 4409–4422, https://doi.org/10.5194/amt-16-4409-2023,https://doi.org/10.5194/amt-16-4409-2023, 2023
Short summary
RainForest: a random forest algorithm for quantitative precipitation estimation over Switzerland
Daniel Wolfensberger, Marco Gabella, Marco Boscacci, Urs Germann, and Alexis Berne
Atmos. Meas. Tech., 14, 3169–3193, https://doi.org/10.5194/amt-14-3169-2021,https://doi.org/10.5194/amt-14-3169-2021, 2021
Short summary
From model to radar variables: a new forward polarimetric radar operator for COSMO
Daniel Wolfensberger and Alexis Berne
Atmos. Meas. Tech., 11, 3883–3916, https://doi.org/10.5194/amt-11-3883-2018,https://doi.org/10.5194/amt-11-3883-2018, 2018
Short summary

Related subject area

Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Impact of secondary ice production on thunderstorm electrification under different aerosol conditions
Shiye Huang, Jing Yang, Jiaojiao Li, Qian Chen, Qilin Zhang, and Fengxia Guo
Atmos. Chem. Phys., 25, 1831–1850, https://doi.org/10.5194/acp-25-1831-2025,https://doi.org/10.5194/acp-25-1831-2025, 2025
Short summary
Model analysis of biases in the satellite-diagnosed aerosol effect on the cloud liquid water path
Harri Kokkola, Juha Tonttila, Silvia M. Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo Henrik Virtanen, Pekka Kolmonen, and Antti Arola
Atmos. Chem. Phys., 25, 1533–1543, https://doi.org/10.5194/acp-25-1533-2025,https://doi.org/10.5194/acp-25-1533-2025, 2025
Short summary
Evaluation of biases in mid-to-high-latitude surface snowfall and cloud phase in ERA5 and CMIP6 using satellite observations
Franziska Hellmuth, Tim Carlsen, Anne Sophie Daloz, Robert Oscar David, Haochi Che, and Trude Storelvmo
Atmos. Chem. Phys., 25, 1353–1383, https://doi.org/10.5194/acp-25-1353-2025,https://doi.org/10.5194/acp-25-1353-2025, 2025
Short summary
Dynamical imprints on precipitation cluster statistics across a hierarchy of high-resolution simulations
Claudia Christine Stephan and Bjorn Stevens
Atmos. Chem. Phys., 25, 1209–1226, https://doi.org/10.5194/acp-25-1209-2025,https://doi.org/10.5194/acp-25-1209-2025, 2025
Short summary
Role of a key microphysical factor in mixed-phase stratocumulus clouds and their interactions with aerosols
Seoung Soo Lee, Chang Hoon Jung, Jinho Choi, Young Jun Yoon, Junshik Um, Youtong Zheng, Jianping Guo, Manguttathil G. Manoj, and Sang-Keun Song
Atmos. Chem. Phys., 25, 705–726, https://doi.org/10.5194/acp-25-705-2025,https://doi.org/10.5194/acp-25-705-2025, 2025
Short summary

Cited articles

Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational convective-scale numerical weather prediction with the COSMO model: description and sensitivities, Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011.
Bohme, T., Van Lipzig, N., Delobbe, L., and Seifert, A.: Precipitation patterns above Belgium using weather radar and COSMO model reflectivity data, in: Proceedings of the 8th International Symposium on Tropospheric Profiling, Delft, the Netherlands, available at: http://www.ch2011.ch/pdf/CH2011reportHIGH.pdf (last access: 13 August 2017), 2009.
COSMO: COSMO namelists and variables, available at: http://www.cosmo-model.org/content/tasks/operational/nmlDoc/cosmoDefault.htm?ver=3&mode=printerFriendly (last access: 8 July 2017), 2015.
Davis, C., Brown, B., and Bullock, R.: Object-based verification of precipitation forecasts. part i: methodology and application to mesoscale rain areas, Mon. Weather Rev., 134, 1772–1784, https://doi.org/10.1175/MWR3145.1, 2006.
Deidda, R.: Rainfall downscaling in a space-time multifractal framework, Water Resour. Res., 36, 1779–1794, https://doi.org/10.1029/2000WR900038, 2000.
Download
Short summary
Precipitation intensities simulated by the COSMO weather prediction model are compared to radar observations over a range of spatial and temporal scales using the universal multifractal framework. Our results highlight the strong influence of meteorological and topographical features on the multifractal characteristics of precipitation. Moreover, the influence of the subgrid parameterizations of COSMO is clearly visible by a break in the scaling properties that is absent from the radar data.
Share
Altmetrics
Final-revised paper
Preprint