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Energy Happy Hour in Midland
Start:July 16, 2019 at 5:30 pm
End:
July 16, 2019 at 7:00 pm
Location:
Racquet Club, Garden Room, 3009 Racquet Club Drive, Midland, TX 79705
Contact:
Kristen Tucek, ktucek@jsg.utexas.edu, 5124712223
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Are you a University of Texas Alum working in the Midland Energy Industry?
The University of Texas would love to see you!
Stop by the Racquet Club on Tuesday, July 16th for a UT alumni and friends networking reception.
Reconnect with faculty, alumni, colleagues, and friends from the Jackson School of Geosciences, Cockrell School of Engineering, and the McCombs School of Business.
UT Alumni and Friends Networking Reception
Tuesday, July 16, 2019
5:30 p.m. – 7:00 p.m.
Racquet Club, Garden Room
3009 Racquet Club Drive, Midland, TX 79705
Dress: Business Casual
Hosted by
Doug Schmidt, McCombs School of Business MBA ‘10
Jarrod Sparks, Cockrell School of Engineering B.S. ‘08
Kris Voorhees, Jackson School of Geosciences B.S. ‘14, M.S. ‘16
Urban Climate LectureMay, 22 2026Time: 12:00 PM - 1:30 AMLocation: Barrow Conference Room (JGB 4.102) Capturing Spatial Variability of Urban Microclimate in Process-Based and Machine Learning Models by Dr. Tirthankar \"TC\" Chakraborty, Earth Scientist at the Pacific Northwest National Laboratory (PNNL) Abstract: Cities modify their local microclimate via process-level changes and through alterations in bulk radiative, morphological, and thermal properties. Cities are also highly heterogeneous, leading to spatial variability in environmental hazards, with potential disparities in climate risks for different urban residents. While significant efforts have been made to improve urban representation in models to isolate broader urban climate signals, current models often struggle to resolve intra-urban variability due to poor structural and parameter constraints at the neighborhood scale. In this seminar, I will provide an overview of this urban spatial variability and its importance, our current limitations in capturing this variability, and potential ways forward by leveraging current-generation fine-grained satellite observations. Specifically, I will highlight our past and ongoing research involving both process-based numerical modeling and machine learning approaches to capture the spatial distribution of urban heat hazards. The lessons learned from these studies can guide future urban model development efforts to enable more accurate neighborhood-scale climate mitigation and adaptation strategies. |