Publication

Improved rain rate estimation by combining radars, rain gauges and microwave links

Publications associées (29)

Influence of pore-scale heterogeneity on the precipitation patterns in Microbially Induced Calcite Precipitation (MICP)

The principle of tailoring material properties to improve the mechanical behaviour of soils through compaction or cement grouting dates to the 60s. The increasing trends of urbanization worldwide require new solutions for the development of resilient and s ...

EPFL2023

Combining Weather Station Data and Short-Term LiDAR Deployment to Estimate Wind Energy Potential with Machine Learning: A Case Study from the Swiss Alps

Michael Lehning, Wolf Hendrik Huwald, Franziska Gerber, Jérôme François Sylvain Dujardin, Fanny Kristianti

Wind energy potential in complex terrain is still poorly understood and difficult to quantify. With Switzerland’s current efforts to shift to renewable energy resources, it is now becoming even more crucial to investigate the hidden potential of wind energ ...

2023

Reinforcement Learning for Outdoor Balloon Navigation: A Successful Controller for an Autonomous Balloon

Mirko Kovac, Simon Jeger

Autonomous ballooning allows for energy-efficient long-range missions but introduces significant challenges for planning and control algorithms, due to their single degree of actuation: vertical rate control through either buoyancy or vertical thrust. Late ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

Role of K-feldspar and quartz in global ice nucleation by mineral dust in mixed-phase clouds

Athanasios Nenes

Ice-nucleating particles (INPs) enable ice formation, profoundly affecting the microphysical and radiative properties, lifetimes, and precipitation rates of clouds. Mineral dust emitted from arid regions, particularly potassium-containing feldspar (K-felds ...

Copernicus GmbH2023

Lightning Nowcasting Using Solely Lightning Data

Farhad Rachidi-Haeri, Marcos Rubinstein, Amirhossein Mostajabi

Lightning is directly or indirectly responsible for significant human casualties and property damage worldwide. A timely prediction of its occurrence can enable authorities and the public to take necessary precautionary actions resulting in diminishing the ...

MDPI2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Gionata Ghiggi, Anne-Claire Marie Billault--Roux

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

Human personal air pollution clouds in a naturally ventilated office during the COVID-19 pandemic

Dusan Licina, Shen Yang, Maria Viviana Gonzalez Serrano, Akila Muthalagu

Personal cloud, termed as the difference in air pollutant concentrations between breathing zone and room sites, represents the bias in approximating personal inhalation exposure that is linked to accuracy of health risk assessment. This study performed a t ...

PERGAMON-ELSEVIER SCIENCE LTD2023

RaFSIP: Parameterizing ice multiplication in models using a machine learning approach

Athanasios Nenes, Paraskevi Georgakaki

Accurately representing mixed-phase clouds (MPCs) in global climate models (GCMs) is critical for capturing climate sensitivity and Arctic amplification. Secondary ice production (SIP), can significantly increase ice crystal number concentration (ICNC) in ...

2024

An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0

Tobias Jonas, Adrien Michel

Many methods exist to model snow densification in order to calculate the depth of a single snow layer or the depth of the total snow cover from its mass. Most of these densification models need to be tightly integrated with an accumulation and melt model a ...

COPERNICUS GESELLSCHAFT MBH2023