Max-Infinitely Divisible Models and Inference for Spatial Extremes, with Application to Non-Stationary Heatwave Hazard Assessment
Date: 07 June 2021, Monday
Time: 4pm AEDT
Speaker: Dr Raphaël Huser (King Abdullah University of Science and Technology)
Abstract:
The modeling of spatio-temporal trends in temperature extremes can help better understand the structure and frequency of heatwaves in a changing climate. Here, we study annual temperature maxima over Southern Europe using a century-spanning dataset observed at 44 monitoring stations. Extending the spectral representation of max-stable processes, our modeling framework relies on a novel construction of max-infinitely divisible processes, which include covariates to capture spatio-temporal non-stationarities. Our new model keeps a popular max-stable process on the boundary of the parameter space, while flexibly capturing weakening extremal dependence at increasing quantile levels and asymptotic independence. This is achieved by linking the overall magnitude of a spatial event to its spatial correlation range, in such a way that more extreme events become less spatially dependent, thus more localized. Our model reveals salient features of the spatio-temporal variability of European temperature extremes, and it clearly outperforms natural alternative models. Results show that the spatial extent of heatwaves is smaller for more severe events at higher altitudes, and that recent heatwaves are moderately wider. Our probabilistic assessment of the 2019 annual maxima confirms the severity of the 2019 heatwaves both spatially and at individual sites, especially when compared to climatic conditions prevailing in 1950–1975.
Related papers:
Date: 07 June 2021, Monday
Time: 4pm AEDT
Speaker: Dr Raphaël Huser (King Abdullah University of Science and Technology)
Abstract:
The modeling of spatio-temporal trends in temperature extremes can help better understand the structure and frequency of heatwaves in a changing climate. Here, we study annual temperature maxima over Southern Europe using a century-spanning dataset observed at 44 monitoring stations. Extending the spectral representation of max-stable processes, our modeling framework relies on a novel construction of max-infinitely divisible processes, which include covariates to capture spatio-temporal non-stationarities. Our new model keeps a popular max-stable process on the boundary of the parameter space, while flexibly capturing weakening extremal dependence at increasing quantile levels and asymptotic independence. This is achieved by linking the overall magnitude of a spatial event to its spatial correlation range, in such a way that more extreme events become less spatially dependent, thus more localized. Our model reveals salient features of the spatio-temporal variability of European temperature extremes, and it clearly outperforms natural alternative models. Results show that the spatial extent of heatwaves is smaller for more severe events at higher altitudes, and that recent heatwaves are moderately wider. Our probabilistic assessment of the 2019 annual maxima confirms the severity of the 2019 heatwaves both spatially and at individual sites, especially when compared to climatic conditions prevailing in 1950–1975.
Related papers:
- Zhong, P, Huser, R., and Opitz, T. (2020+), Modeling Non-stationary temperature maxima based on extremal dependence changing with event magnitude, arXiv preprint 2006.01569 [arXiv][PDF]
- Huser, R., Opitz, T., and Thibaud, E. (2020+), Max-infinitely divisible models and inference for spatial extremes, Scandinavian Journal of Statistics 48, 321-348 [journal][PDF preprint]
- Bopp, G., Shaby, B., and Huser, R. (2020+), A hierarchical max-infinitely divisible spatial model for extreme precipitation, Journal of the American Statistical Association 116, 93-106 [journal][PDF preprint]
- Huser, R., Opitz, T., and Thibaud, E. (2020+), Max-infinitely divisible models and inference for spatial extremes, Scandinavian Journal of Statistics 48, 321-348 [journal][PDF preprint]
- Bopp, G., Shaby, B., and Huser, R. (2020+), A hierarchical max-infinitely divisible spatial model for extreme precipitation, Journal of the American Statistical Association 116, 93-106 [journal][PDF preprint]