Marc Genton, Chair and Distinguished Professor of the Statistics Program of KAUST and Head of the Spatio-Temporal Statistics and Data Science Research Group, received an International Statistical Institute (ISI) Service Award 2019 for his efforts and leadership as Editor-in-Chief of the journal Stat. Professor Genton received his award at the Awards Ceremony during the World Statistical Congress (WSC) 2019 held in Kuala Lumpur, Malaysia, 18-23 August 2019.
“The three years spent as Editor-in-Chief were truly gratifying because the journal is fairly new and unique in the world of statistics,” said Genton. “Stat’s ambition is to maintain exceptional quality standards while pledging very fast review times. I enjoyed leading this journal in its infancy and look forward to seeing it grow further.”
At KAUST, Professor Genton and his team are currently working to find solutions to global issues that also closely touch the future of Saudi Arabia. In view of the end of the oil-era and under increasing environmental constraints, the Kingdom is rethinking its energy security strategy by diversifying its GDP and investing in renewable resources. Genton, as one of the leading minds in statistics, is actively engaged in the challenge.
“We are trying to develop tools that will help governments and policymakers close the gap between vision and implementation,” said Genton. “The plan is using Saudi Arabia as a case study, but we believe that the results will be relevant for most of the Middle East economies.”
In a joint effort with the University of Notre Dame, USA, Genton is currently devising the logical framework for implementing the Kingdom’s wind energy outlook. Optimal sites for the development of wind farms, as well as the primary technical details about turbine models, hub heights and the associated costs, have been identified by statistically analyzing a large volume of high-resolution climate model data as well as financial and logistics figures. “We demonstrated that wind-power plants could be both achievable and cost-competitive here in Saudi Arabia. The Kingdom is well-positioned to become a role model for wind energy infrastructure development within the Middle East,” argued Genton. “I’m proud to be able to help Saudi Arabia in this economic transition.”
Professor Genton is also involved in the assessment of an infrastructural plan to provide NEOM, the mega-city currently under construction in the Northwest of the Kingdom, with an aeolian grid. “We have been assessing the risk of disruption of wind turbine operations in NEOM,” said Genton. “For this specific problem, we have used two state-of-the-art spatial extremes hierarchical modeling approaches geared to analyze wind speed in the region.” Thanks to this approach and the use of a unique Weather Research and Forecasting (WRF) dataset, Genton’s team is providing the first high-resolution risk assessment of wind extremes, with comparison from two spatial extreme models, and with computational efficiency improved by parallel computing.
“Under the Bayesian hierarchical framework, we measure the uncertainty of return levels from the posterior Markov Chain Monto Carlo (MCMC) samples, and produce probability maps of return levels exceeding the cut-out wind speed of wind turbines within their lifetime,” Genton argued.
The resulting probability maps have revealed that the coastal region in Western NEOM may be ill-suited for wind-energy farming without additional considerations. According to the first model, the coastal area presents a very high risk of disruption of wind turbine operations. The second model gave extra insight, suggesting that also further locations inland may present wind speed patterns incompatible with wind-farming at the industrial level. “Nowadays, statistics and the availability of big data sets can save a huge amount of time and money by simulating the outcomes of investments ahead of any strategical decision,” concluded Genton. “In a Big Data world, statisticians are the Wizards of Odds!”
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