Data and scripts for the RaFSIP scheme

Athanasios Nenes, Paraskevi Georgakaki
2024
Ensemble de données

Résumé

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by Paraskevi Georgakaki and Athanasios Nenes. RaFSIP is a data-driven parameterization designed to streamline the representation of Secondary Ice Production (SIP) in large-scale models. Preprint available on Authorea: https://doi.org/10.22541/essoar.170365383.34520011/v1

Source officielle

https://infoscience.epfl.ch/record/307308?ln=fr

À propos de ce résultat

Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Data and scripts for the RaFSIP scheme

Data and scripts for "Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling"

Nanoindentation hardness and modulus of Al2O3-SiO2-CaO and MnO-SiO2-FeO inclusions in iron

Validating functional redundancy with mixed generative adversarial networks

Nanoindentation hardness and modulus of Al2O3-SiO2-CaO and MnO-SiO2-FeO inclusions in iron

Validating functional redundancy with mixed generative adversarial networks

Data and scripts for "Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling"