Hi, my name is Daniel Howard. If you know me well, then you might also call me DHow. I am a Ph.D. student at the University of Notre Dame
in the Department of Applied & Computational Mathematics & Statistics.
My current research work focuses on computational fluid dynamics and numerical modeling of Indian monsoons utilizing High Performance Computing machinery alongside interactions between these climate dynamics and climate change.
This work is under my advisors Prof. Diogo Bolster and
Prof. David Richter
with the Environmental Fluid Dynamics Group.
TODO: Will expand upon, add images/references, and provide more in depth explanations.
Radial Basis Function Finite Difference Methods
RBF-FD Methods are an extension of spectral methods which solve partial differential equations but return to principles of standard finite difference methods for inspiration. The principle appeal of RBF-FD Methods is that they are meshless and easily scalable on supercomputing systems. In particle, they feature particular applications to geophysical flow problems, as can be found in climate modeling and numerical weather prediction.
Monsoon Dynamics and Intraseasonal Oscillations
Numerical weather predition and climate models rely on complex interconnected models which solve for the present and future atmospheric and oceanic states.