Name: Laura Mansfield
Type: User
Company: Stanford Doerr School of Sustainability
Bio: Postdoc at Stanford University in Earth Systems Science. Machine learning, uncertainty quantification, Bayesian statistics for climate science.
Twitter: lau_mansfield
Location: California, U.S
Blog: https://lm2612.github.io/
Laura Mansfield's Projects
Stochastic Optimization, Learning, Uncertainty and Sampling
CliMT dask stuff from pangeo
Code and assignment repository for the Imperial College Mathematics department Deep Learning course
Calibrate AD99 tropical gravity wave parameters (cw_tropics, Bt_eq) in MiMA to observations of the QBO (period, amplitude) using Ensemble Kalman Inversion
Emulator
Implements Optimization and approximate uncertainty quantification algorithms, Ensemble Kalman Inversion, and Ensemble Kalman Processes.
Introduction to programming for new students in the Centre for Doctoral Training in Mathematics of Planet Earth. Based on the book "A Primer on Scientific Programming with Python" by Hans Petter Langtangen.
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
C++ & R code for Markov Chain Monte Carlo estimation (Gibbs sampling, MH random walk, various flavors of adaptive MCMC, etc), and functions relevant to the truncated multivariate Gaussian distribution
Model of an idealized Moist Atmosphere: Intermediate-complexity General Circulation Model with full radiation
Repo for analyzing outputs of MiMA. Allows plots of zonal mean zonal winds, QBO, SSWs, and gwd. Also calculates of number of SSWs and period and amplitude of QBO.
Coupled MiMA Version
Jamboree group A AIR
coursework for Numerical Modelling of Atmospheres and Oceans
Planetary repository
PRML algorithms implemented in Python
Official repository for Citation Style Language (CSL) citation styles.
WaveNet with Uncertainty Quantification. We use deep ensembles of neural networks to estimate parametric uncertainty in the gravity wave emulator, WaveNet (Espinosa et al., 2022). These emulate the gravity wave parameterization (Alexander & Dunkerton, 1999; AD99) within the climate model MiMA.
A Python library for spherical harmonic computations on vector winds.