BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20250623T044657EDT-11070r4UK3@132.216.98.100 DTSTAMP:20250623T084657Z DESCRIPTION:\n \n \n Title: Spatio-temporal methods for estimating subsurface ocean thermal response to tropical cyclones.\n\n \n \n Abstract:\n\n Tropical cyclones (TCs)\, driven by heat exchange between the air and sea\, pose a substantial risk to many communities around the world. Accurate characteri zation of the subsurface ocean thermal response to TC passage is crucial f or accurate TC intensity forecasts and for understanding the role TCs play in the global climate system\, yet that characterization is complicated b y the high-noise ocean environment\, correlations inherent in spatio-tempo ral data\, relative scarcity of in situ observations and the entanglement of the TC-induced signal with seasonal signals. We present a general metho dological framework that addresses these difficulties\, integrating existi ng techniques in seasonal mean field estimation\, Gaussian process modelin g\, and nonparametric regression into a functional ANOVA model. Importantl y\, we improve upon past work by properly handling seasonality\, providing rigorous uncertainty quantification\, and treating time as a continuous v ariable\, rather than producing estimates that are binned in time. This fu nctional ANOVA model is estimated using in situ subsurface temperature pro files from the Argo fleet of autonomous floats through a multi-step proced ure\, which (1) characterizes the upper ocean seasonal shift during the TC season\; (2) models the variability in the temperature observations\; (3) fits a thin plate spline using the variability estimates to account for h eteroskedasticity and correlation between the observations. This spline fi t reveals the ocean thermal response to TC passage. Through this framework \, we obtain new scientific insights into the interaction between TCs and the ocean on a global scale\, including a three-dimensional characterizati on of the near-surface and subsurface cooling along the TC storm track and the mixing-induced subsurface warming on the track’s right side. Joint wo rk with Addison Hu\, Ann Lee\, Donata Giglio and Kimberly Wood.\n\n Speaker \n\n Dr. Mikael Kuusela is an Assistant Professor of Statistics and Data Sc ience at Carnegie Mellon University. His research focuses on developing st atistical methods for analyzing large and complex datasets in the physical sciences. He is particularly interested in questions related to ill-posed inverse problems\, spatio-temporal data\, uncertainty quantification and statistical learning in climate science\, oceanography\, remote sensing an d particle physics.\n \n \n\n \n \n \n \n Zoom Link\n\n Meeting ID: 939 8331 3215 \n\n Passcode: 096952\n \n \n\n  \n\n  \n\n  \n \n \n \n \n\n DTSTART:20210212T203000Z DTEND:20210212T213000Z SUMMARY:Mikael Kuusela (Carnegie Mellon University) URL:/mathstat/channels/event/mikael-kuusela-carnegie-m ellon-university-328538 END:VEVENT END:VCALENDAR