[Eoas-seminar] MET Seminar - TUESDAY February 27 - Dr. Jangho Lee (University of Illinois Chicago)

[eoas-seminar at lists.fsu.edu]

Dear all,

First - a reminder of this week’s MET seminar tomorrow Feb 22 at 3:15 PM, given by Dr. Jhordanne Jones who will speak about "Is sub-seasonal to seasonal tropical cyclone predictability changing under global warming?”.

Second - please join us for next week’s MET seminar on the special day of TUESDAY February 27 at 3:15 PM (snacks at 3 PM), which will be given by Dr. Jangho Lee<https://jangholee.com/> of the University of Chicago Illinois. Dr. Lee will speak about "Urban Land Surface Temperatures: Importance, Measurement, and Multidisciplinary Applications” (abstract below).

Dr. Lee is joining us in person. Please contact Prof. Chelsea Nam (ccnam at fsu.edu<mailto:ccnam at fsu.edu>) if you are interested in meeting with Dr. Lee.

DATE: Tuesday February 27
SEMINAR TIME: Refreshments at 3 PM, Talk 3:15 - 4:15 PM
SEMINAR LOCATION: EOA 1044 (Speaker in person)
SPEAKER: Dr. Jangho Lee<https://jangholee.com/>

TITLE: Urban Land Surface Temperatures: Importance, Measurement, and Multidisciplinary Applications

ABSTRACT: Land Surface Temperature (LST) measurements are crucial, particularly in urban settings, due to the fact that over 80% of the U.S. population resides in cities, which occupy only 3% of the country's land area. In this seminar, the significance of temperature monitoring within urban environments will be discussed, alongside an exploration of various methodologies currently employed. A particular focus will be placed on the use of satellite technology for urban temperature monitoring. Initially, the seminar will showcase the application of GOES-R satellites in analyzing the diurnal characteristics of the Surface Urban Heat Island (SUHI) effect across 120 major U.S. cities. A clustering method will be employed to categorize SUHI patterns and identify underlying factors influencing these patterns. Subsequently, the seminar will show the integration of GOES-R and ECOSTRESS LST estimates, highlighting a novel approach that employs a machine-learning (specifically, XGBoost) based method for downscaling GOES-R data to ECOSTRESS resolution. This technique's potential to mitigate socioeconomic disparities within the Chicago area will also be examined, showcasing the broader implications of advanced LST measurement technologies.

--------------------------------------------
Allison A. Wing, Ph.D.
Werner A. and Shirley B. Baum Professor
Associate Professor, Department of Earth, Ocean, and Atmospheric Science
Florida State University
awing at fsu.edu

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