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

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