20 citations · 87 across the 12 of their papers we have counts for
14 papers
A Bayesian hierarchical model for methane emission source apportionment
William S. Daniels, Douglas W. Nychka, Dorit M. Hammerling
Reducing methane emissions from the oil and gas sector is a key component of short-term climate action. Emission reduction efforts are often conducted at the individual site-level,…
DSSIM: a structural similarity index for floating-point data
Allison H. Baker, Alexander Pinard, Dorit M. Hammerling
Data visualization is a critical component in terms of interacting with floating-point output data from large model simulation codes. Indeed, postprocessing analysis workflows on s…
Nonstationary Spatial Modeling of Massive Global Satellite Data
Huang Huang, Lewis R. Blake, Matthias Katzfuss +1
Earth-observing satellite instruments obtain a massive number of observations every day. For example, tens of millions of sea surface temperature (SST) observations on a global sca…
Modeling massive highly-multivariate nonstationary spatial data with the basis graphical lasso
Mitchell Krock, William Kleiber, Dorit Hammerling +1
We propose a new modeling framework for highly-multivariate spatial processes that synthesizes ideas from recent multiscale and spectral approaches with graphical models. The basis…
HECT: High-Dimensional Ensemble Consistency Testing for Climate Models
Niccolò Dalmasso, Galen Vincent, Dorit Hammerling +1
Climate models play a crucial role in understanding the effect of environmental and man-made changes on climate to help mitigate climate risks and inform governmental decisions. La…
Combining interdependent climate model outputs in CMIP5: A spatial Bayesian approach
Huang Huang, Dorit Hammerling, Bo Li +1
Projections of future climate change rely heavily on climate models, and combining climate models through a multi-model ensemble is both more accurate than a single climate model a…