Going to extremes to predict natural disasters

July 10, 2017

Predicting natural disasters remains one of the most challenging problems in simulation science because not only are they rare but also because only few of the millions of entries in datasets relate to extreme events. A systematic method for comparing the accuracy of different types of simulation models for such prediction problems has recently been developed by a working group at KAUST.

"Extreme events like dust storms, droughts and floods can affect communities and damage infrastructure," said Sabrina Vettori, a doctoral student cosupervised by Distinguished Professor Marc Genton and Assistant Professor Raphaël Huser of Applied Mathematics and Computational Science. "Modeling and forecasting extremes is very challenging and requires flexible, yet interpretable, models with sound theoretical underpinning—criteria that are exponentially more difficult to meet as the data dimensionality increases," she explained.

Increasing the dimensionality or number of observation variables (like temperature and wind speed) dramatically increases the predictive power of a simulation model, but the statistical dexterity needed to correctly pick out and predict the combination of conditions leading to extreme events is immense.

"We are exploring the boundaries of extreme value theory," said Genton. "The aim of our work is to provide a greater understanding of the performance of existing estimators for modeling extreme events over multiple variables and to develop a new statistical for nonparametric estimation in higher dimensions."

Multivariate simulations generally follow one of two approaches. The first are parametric approaches that configure the model by using a set of variables to best approximate the behavior described by the data. The second are nonparametric approaches, which are statistical methods that fit a function to data but use no underlying assumptions or constraints.

Both approaches have pros and cons, and the best method depends on the application," said Huser.

"Nonparametric methods are typically more flexible than parametric methods, making them less prone to bias, but they are usually limited to small dimensions," explained Huser. "Parametric methods can be applied to much higher-dimensional problems, such as spatial applications with data recorded at a large number of monitoring sites, but are sensitive to errors in the underlying parameters and assumptions.

In their research, the team developed a computational tool to implement nonparametric methods and conducted a vast and systematic to compare nonparametric and parametric estimator performance in up to five dimensions under various scenarios. These methods provided significant insight into higher dimensional settings.

"These estimators can be used to better the location and magnitude of and to assist in risk assessment and the identification of trends and variability estimates," said Vettori.

Explore further: Improving connections for spatial analysis

More information: Sabrina Vettori et al, A comparison of dependence function estimators in multivariate extremes, Statistics and Computing (2017). DOI: 10.1007/s11222-017-9745-7

Related Stories

Improving connections for spatial analysis

March 7, 2017

A statistical model that accounts for common dependencies in spatial data yields more realistic results for studies of temperature, wind and pollution levels.

Getting a handle on extremes

June 24, 2016

By tapping into the power of extreme value theory, an international team of researchers including Raphaël Huser from King Abdullah University of Science and Technology's Computer, Electrical and Mathematical Science and ...

Making space for climate simulations

July 29, 2016

A statistics-based data compression scheme cuts data storage requirements for large-scale climate simulations by as much as 98 percent.

Study examines increasing likelihood of extreme sea levels

July 7, 2017

Scientists at the University of Southampton are warning that future coastal impact studies must take account of extreme sea levels – a phenomenon expected to occur more frequently as rising waters combine with high tides ...

Recommended for you

Clues to ancient past—baby mummy, dinosaur skulls scanned

September 22, 2017

The mummified remains of a 7-month-old baby boy and pieces of skull from two teenage Triceratops underwent computed tomography (CT) scans Saturday, Sept. 16, at Washington University School of Medicine in St. Louis, in hopes ...

Neanderthal boy's skull grew like a human child's: study

September 21, 2017

The first analysis of a Neanderthal boy's skull uncovered in Spain suggests that he grew much like a modern boy would, in another sign that our extinct ancestors were similar to us, researchers said Thursday.

Early trilobites had stomachs, new fossil study finds

September 21, 2017

Exceptionally preserved trilobite fossils from China, dating back to more than 500 million years ago, have revealed new insights into the extinct marine animal's digestive system. Published today in the journal PLOS ONE, ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.