25 citations · 37 across the 8 of their papers we have counts for
8 papers
TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones
Lin Yan, Hanqi Guo, Thomas Peterka +2
Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks.…
Joint modeling of wind speed and wind direction through a conditional approach
Eva Murphy, Whitney Huang, Julie Bessac +2
Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to cl…
Station-wise statistical joint assessment of wind speed and direction under future climates across the United States
Qiuyi Wu, Julie Bessac, Whitney Huang +1
This study develops a statistical conditional approach to evaluate climate model performance in wind speed and direction and to project their future changes under the representativ…
A Deep Learning Approach to Probabilistic Forecasting of Weather
Nick Rittler, Carlo Graziani, Jiali Wang +1
We discuss an approach to probabilistic forecasting based on two chained machine-learning steps: a dimensional reduction step that learns a reduction map of predictor information t…
Efficient high-dimensional variational data assimilation with machine-learned reduced-order models
Romit Maulik, Vishwas Rao, Jiali Wang +6
Data assimilation (DA) in the geophysical sciences remains the cornerstone of robust forecasts from numerical models. Indeed, DA plays a crucial role in the quality of numerical we…
Fast and accurate learned multiresolution dynamical downscaling for precipitation
Jiali Wang, Zhengchun Liu, Ian Foster +3
This study develops a neural network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computati…
Computer Model Calibration with Time Series Data using Deep Learning and Quantile Regression
Saumya Bhatnagar, Won Chang, Seonjin Kim Jiali Wang
Computer models play a key role in many scientific and engineering problems. One major source of uncertainty in computer model experiment is input parameter uncertainty. Computer m…
Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking
Won Chang, Jiali Wang, Julian Marohnic +2
Dynamical downscaling with high-resolution regional climate models may offer the possibility of realistically reproducing precipitation and weather events in climate simulations. A…