Cities generally have higher temperatures compared to their background climate. Depending on scale, this urban warming can have public health consequences, prompting the need for urban-scale heat mitigation and adaptation. Cities are also highly heterogeneous, leading to spatial variability in heat hazard, with warmer areas often coinciding with where disadvantaged populations live, particularly in the U.S. In this talk, I will give an overview of urban warming across scales — from city to regional to global — using multiple lines of evidence, including satellite observations, in situ measurements, and numerical modeling. I will also discuss distributional inequality in heat hazard within cities and how it relates to overall urban heat risk. All these results will be framed around a major inconsistency in estimates of the urban warming signal across scales i.e. the variability of surface temperature versus air temperature versus moist heat stress within urban areas and their urban-rural differences (or heat islands) across cities. The talk will summarize the lessons learned from multiple past and ongoing studies to guide future urban climate research priorities and provide some recommendations on how to get more actionable quantitative estimates of physiologically relevant urban heat to inform policy.
SPEAKER BIO
Dr. Tirthankar Chakraborty (goes by TC) is an Earth Scientist at the Pacific Northwest National Laboratory (PNNL) with expertise in atmosphere-biosphere interactions. Before joining PNNL, TC finished his PhD from Yale University, where he developed a surface-energy budget perspective on aerosol-climate interactions. He has also worked extensively on impacts of urbanization on weather and climate by leveraging satellite measurements, crowdsourced weather station data, and modeling frameworks. TC is interested in the role of big data, machine learning, and urban informatics to better understand cities and their complexities. His past contributions include developing the most comprehensive global urban heat island dataset, conducting some of the first large-scale studies on urban heat disparities, examining the impact of urban humidity feedback on heat stress across scales, and isolating urban warming signals from regional to continental scales. He is currently working on improving urban representation in land models and examining extreme events over coastal cities. He often uses the Google Earth Engine (GEE) cloud computing platform for geospatial analyses and was one of 26 inaugural GEE Google Developer Experts in the world. TC’s work has been featured in high impact scientific publications like Nature Geoscience, Nature Communications, Science Advances, One Earth, Lancet Planetary Health, etc. as well as in popular media outlets like the New York Times and the Washington Post. He received the U.S. Department of Energy Early Career grant last year to improve urban representation in Earth system models through planetary-scale data-model integration. TC is also the PNNL institutional PI for a NASA Interdisciplinary Research in Earth Science project to combine machine learning and remote sensing to examine disparities in heat hazards within U.S. cities and a recently funded DOE Climate Resilience Center focused on optimizing climate adaptation during the energy transition for the city of Lowell in Massachusetts.