Name: Maria J. Molina
Type: User
Company: University of Maryland
Bio: Assistant Professor in climate and extremes data science.
Twitter: sciencebymaria
Location: College Park, MD
Blog: https://mariajmolina.github.io/
Maria J. Molina's Projects
This is the code for my senior project
Tools to manage cesm projects
Repository for project using signal processing to explore changes to global SSTs and ENSO.
Working repository for planning/execution of the "Time of Emergence" project at the CMIP6 Hackathon
Repository containing scripts associated with the NCAR Advanced Study Program (ASP) deep learning project exploring robustness to future convection of North America.
Earth Computer Hyperparameter Optimization
Recent few-shot learning methods adapted for atmospheric spatial data contained in the Deep Conus dataset
Repository contains software for analysis of annual cycle of tornadoes and changes based on ENSO phases.
Hagelslag is an object-based severe storm hazard forecasting system.
Applications of the NOAA hysplit model for climate science.
Software associated with the NSF NCAR Early Career Faculty Innovator Program for "Pathways to Mitigating Bias for Environmental Justice in Black Communities"
Repository for NASA lightning-nox ML parameterization project.
Severe weather prediction using GLM lightning data and machine learning.
UMD group website (Assistant Professor Maria Molina)
Repository for project using machine learning (ML) for precipitation extremes.
Repository for machine learning and MCS detection project.
Repository for subseasonal-to-seasonal prediction and predictability projects using machine learning.
Software associated with the NCAR Accelerated Scientific Discovery (Derecho) project tackling subseasonal bias correction of global predictions.
Project to improve forecast sharpness using ML methods
Repository for study assessing the state of Hispanic/Latinx academics and researchers in atmospheric and related fields. Project is the result of collaboration within AMS CHALA.
Repository for TC Genesis Research
Basic and frequently used terminal commands in a cheatsheet.
University of Maryland's AOSC 650 course: Neural Networks for the Physical Sciences
Prototype development by the urban HEAT map team during the Convergence Research (CORE) Institute, funded by the NSF Convergence Accelerator.
Repository for project exploring effect of different video styles in geoscience communication.
Sensitivity analysis of tornadic thunderstorms conducted using WRF.