-
Sara Shamekh
New York UniversityMeeting roles in:
Data-Driven Discovery of Thermodynamic Controls on South Asian Monsoon Precipitation
Precipitation Intensity Sensitivity to Large-Scale Thermodynamic State
Investigating how Different Large-Scale Environmental Conditions impact the Shallow-to-Deep Transition of Convection
Advances in Data Assimilation, Data Fusion, Machine Learning, Predictability, and Uncertainty Quantification in the Geosciences III: Developments in Machine Learning Across Earth System Modeling: Subgrid-Scale Parameterizations, Emulation, and Hybrid Modeling III Oral
Towards a Unified Data-Driven Boundary Layer Parameterization for Ocean and Atmosphere
Developments in Machine Learning Across Earth System Modeling: Subgrid-Scale Parameterizations, Emulation, and Hybrid Modeling I Oral
Developments in Machine Learning Across Earth System Modeling: Subgrid-Scale Parameterizations, Emulation, and Hybrid Modeling II Poster
Data-driven models of a coefficient in a higher-order closure of atmospheric boundary layer turbulence
Multivariate Estimation of Vertical Profiles to Better Understand the Shallow-to-Deep Transition of Convection in the Bankhead National Forest
Physically-Constrained Deep Generative Modeling
WaveSim: A Multi-Scale Wavelet-Based Similarity Metric for Climate Field Comparison
Enter Note
Go to previous page in this tab
Author/Chair
