Understanding and modeling the determinants of extreme hourly rainfall intensity is of utmost importance for the management of flash-flood risk. Increasing evidence shows that mesoscale convective systems (MCS) are the principal driver of extreme rainfall intensity in the United States. We use extreme value statistics to investigate the relationship between MCS activity and extreme hourly rainfall intensity in Greater St. Louis, an area particularly vulnerable to flash floods. Using a block maxima approach with monthly blocks, we find that the impact of MCS activity on monthly maxima is not homogeneous within the month/block. To appropriately capture this relationship, we develop a mixed-frequency extreme value regression framework accommodating a covariate sampled at a frequency higher than that of the extreme observation.

Dupuis, D.J., Trapin, L. (2023). Mixed-frequency extreme value regression: Estimating the effect of mesoscale convective systems on extreme rainfall intensity. THE ANNALS OF APPLIED STATISTICS, 17(2 (June)), 1398-1418 [10.1214/22-AOAS1675].

Mixed-frequency extreme value regression: Estimating the effect of mesoscale convective systems on extreme rainfall intensity

Trapin, Luca
2023

Abstract

Understanding and modeling the determinants of extreme hourly rainfall intensity is of utmost importance for the management of flash-flood risk. Increasing evidence shows that mesoscale convective systems (MCS) are the principal driver of extreme rainfall intensity in the United States. We use extreme value statistics to investigate the relationship between MCS activity and extreme hourly rainfall intensity in Greater St. Louis, an area particularly vulnerable to flash floods. Using a block maxima approach with monthly blocks, we find that the impact of MCS activity on monthly maxima is not homogeneous within the month/block. To appropriately capture this relationship, we develop a mixed-frequency extreme value regression framework accommodating a covariate sampled at a frequency higher than that of the extreme observation.
2023
Dupuis, D.J., Trapin, L. (2023). Mixed-frequency extreme value regression: Estimating the effect of mesoscale convective systems on extreme rainfall intensity. THE ANNALS OF APPLIED STATISTICS, 17(2 (June)), 1398-1418 [10.1214/22-AOAS1675].
Dupuis, Debbie J.; Trapin, Luca
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/925597
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