Data Collection
Data collection in the Red Sea before spatio-temporal statistical analysis
Functional Boxplot
of monthly sea surface temperatures (1951-2007) over the east-central tropical Pacific Ocean (Sun & Genton, 2011, JCGS)
Spatial Autocorrelation of Eastern Siberia Data
empirical (blue) and Whittle model (red) fit (North, Wang & Genton, 2011, Journal of Climate)
Emulation of Global 3D Spatio-Temporal Temperature
with a distributed computing approach to model one billion data points (Castruccio & Genton, 2014)
Paleoclimate Temperature Reconstruction
in Northern Hemisphere: OLS and attenuation corrected OLS (Ammann, Genton & Li, 2010, Climate of the Past)
Genton (2004)'s Book Cover
Theory and applications of multivariate skew-elliptical distributions
Wind and Solar Power Forecasting
with spatio-temporal statistical models (Hering & Genton, 2010, JASA)


The group of Prof. Marc G. Genton works on the statistical analysis, modeling, prediction, and uncertainty quantification of spatio-temporal data, with applications in environmental and climate science, renewable energies, geophysics, and marine science. 

Our research activities include the following topics:

  • Spatio-temporal statistics
  • Spatial extremes
  • Geostatistics for large datasets
  • Non-Gaussian random fields
  • Multivariate spatial statistics
  • Nonstationary models
  • Wind and solar power forecasting
  • Multivariate data analysis
  • Data mining and machine learning
  • Visualization of functional and image data
  • Skew-elliptical distributions
  • Robustness
  • Data assimilation