2 citations · 4 across the 4 of their papers we have counts for
5 papers
TCBench: A Benchmark for Tropical Cyclone Track and Intensity Forecasting at the Global Scale
Milton Gomez, Marie McGraw, Saranya Ganesh S. +13
TCBench is a benchmark for evaluating global, short to medium-range (1-5 days) forecasts of tropical cyclone (TC) track and intensity. To allow a fair and model-agnostic comparison…
Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting
Saranya Ganesh S, Frederick Iat-Hin Tam, Milton S. Gomez +5
Improving statistical forecasts of tropical cyclone (TC) intensity is limited by complex nonlinear interactions and difficulty in identifying relevant predictors. Conventional meth…
From Winter Storm Thermodynamics to Wind Gust Extremes: Discovering Interpretable Equations from Data
Frederick Iat-Hin Tam, Fabien Augsburger, Tom Beucler
Reliably identifying and understanding temporal precursors to extreme wind gusts is crucial for early warning and mitigation. This study proposes a simple data-driven approach to e…
Identifying Three-Dimensional Radiative Patterns Associated with Early Tropical Cyclone Intensification
Frederick Iat-Hin Tam, Tom Beucler, James H. Ruppert
Cloud radiative feedback impacts early tropical cyclone (TC) intensification, but limitations in existing diagnostic frameworks make them unsuitable for studying asymmetric or tran…
Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery
Saranya Ganesh S., Tom Beucler, Frederick Iat-Hin Tam +3
Robust feature selection is vital for creating reliable and interpretable Machine Learning (ML) models. When designing statistical prediction models in cases where domain knowledge…