Published January 25, 2024
| Version v1
Dataset
Open
Data and scripts for the RaFSIP scheme
Description
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
Files
Analysis.zip
Additional details
Related works
- Is described by
- Preprint: 10.22541/essoar.170365383.34520011/v1 (DOI)