13 citations as recorded by crossref.

1. Definition of the Moist-Air Exergy Norm: A Comparison with Existing “Moist Energy Norms” P. Marquet et al. 10.1175/MWR-D-19-0081.1
2. Assimilation of Meteosat Third Generation (MTG) Lightning Imager (LI) pseudo-observations in AROME-France – proof of concept F. Erdmann et al. 10.5194/nhess-23-2821-2023
3. Improvement of mesoscale numerical weather prediction WRF-ARW in the Republic of Belarus by assimilation of radar wind and reflectivity data P. Zaiko et al. 10.33581/2521-6740-2020-2-3-13
4. Data assimilation of weather radar reflectivity with a blending hydrometer retrieval scheme for two convective storms in East China F. Shen et al. 10.1016/j.atmosres.2025.108110
5. Overview towards improved understanding of the mechanisms leading to heavy precipitation in the western Mediterranean: lessons learned from HyMeX S. Khodayar et al. 10.5194/acp-21-17051-2021
6. One‐dimensional maximum‐likelihood estimation for spaceborne precipitation radar data assimilation Y. Ikuta et al. 10.1002/qj.3950
7. Impact of WIVERN Wind Observations on ARPEGE Numerical Weather Prediction Model Forecasts Using an Ensemble of Data Assimilation Method N. Sasso et al. 10.1002/qj.4991
8. Assimilation of Moderate-Resolution Imaging Spectroradiometer Level Two Cloud Products for Typhoon Analysis and Prediction H. Zhang et al. 10.3390/rs17091635
9. Increasing model vertical resolution may not necessarily lead to improved atmospheric predictability S. Moon et al. 10.1063/5.0081734
10. Data assimilation impact studies with the AROME-WMED reanalysis of the first special observation period of the Hydrological cycle in the Mediterranean Experiment N. Fourrié et al. 10.5194/nhess-21-463-2021
11. The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6 A. Caldas-Alvarez et al. 10.5194/wcd-2-561-2021
12. Comprehensive thematic T-matrix reference database: a 2017–2019 update M. Mishchenko 10.1016/j.jqsrt.2019.106692
13. Combined use of volume radar observations and high-resolution numerical weather predictions to estimate precipitation at the ground: methodology and proof of concept T. Le Bastard et al. 10.5194/amt-12-5669-2019