About

Professor Lei Zhao leads the Urban Climate AI Lab at the University of Illinois at Urbana-Champaign, focusing on the dynamic feedbacks between land and the atmosphere that significantly influence climate variability and climate change. His research addresses how anthropogenic activities alter biogeochemical and biophysical processes at the Earth's surface, which can either exacerbate or mitigate the impacts of climate change. This work is critical for understanding surface-atmosphere coupling, global atmospheric dynamics, future climate projections, and strategies for climate change adaptation. The group's research centers on the physical and engineering processes within the Atmospheric Boundary Layer, a region where most human activities and environmental systems are concentrated. By studying these dynamics, Professor Zhao's work provides important insights into human-environment interactions, global atmospheric behavior, climate change, and sustainable development. The research approach integrates theory, numerical modeling, remote sensing, in situ observations, and advanced Artificial Intelligence methods to investigate environmental fluid mechanics and land-atmosphere dynamics related to urban environments, hydroclimatology, climate change, climate impacts, and adaptation.

Research topics

• Geology
• Geography
• Meteorology
• Environmental science
• Climatology
• Atmospheric sciences
• Computer Science
• Ecology
• Environmental resource management
• Engineering
• Civil engineering
• Mathematics

Selected publications

• Rising rainfall variability amplifies hydroclimate extremes in eastern China

  Environmental Research Letters · 2026-04-15

  articleOpen access

  Abstract Global warming drives increased rainfall variability, fundamentally because of enlarged moisture holding capacity of the atmosphere. But what does this increase mean in practical terms for rainfall spectrum? Here, we explore the link between changes in rainfall variability and rainfall spectrum and project hydroclimate volatility changes over eastern China, using a combination of long-term observed daily precipitation records and multiple decadal convection-permitting climate simulations. The increase in rainfall variability is reflected in a shift in the rainfall spectrum—from light to more intense precipitation—indicating heightened hazards of both droughts and flash floods. These wider swings between wet and dry extremes are driven by more frequent occurrences of high daily convective available potential energy and convective inhibition values, and intensified by stronger East Asian summer monsoon circulations. Using a combined measure of precipitation intensity and dry spell duration, we project a 29.4% increase in the precipitation volatility index by the end of the 21st century under a high emissions scenario. Our findings highlight the growing importance of rainfall variability in shaping regional hydroclimate volatility and underscore the need to accelerate a shift in water management strategies toward integrated drought and flood risk management.

  PublisherDOI

• Time-domain electrical heating for broad-range and anisotropic thermophysical characterization of semiconductors

  AIP Publishing · 2026-04-15

  datasetOpen access1st authorCorresponding

  Supplementary Figure S1 to Supplementary Figure S12 Supplementary Table 1 to Supplementary Table 3 Supplementary Note 1 to Supplementary Note 6

  PublisherDOI

• <strong>Time-domain electrical heating for broad-range and anisotropic thermophysical characterization of semiconductors</strong>

  AIP Publishing · 2026-04-15

  otherOpen access

  As transistor scaling approaches physical limits, the accurate quantification of thermal conductivity and interfacial thermal conductance for semiconductor materials within chips has emerged as a critical bottleneck for next-generation integrated circuit design and thermal management. Existing thermal measurement techniques are challenged by devices exhibiting concurrent high thermal conductivity, multilayer structures, and pronounced anisotropy, often requiring complex procedures, prolonged measurement times, and multi-method integration-yet still yielding unsatisfactory accuracy. To overcome these limitations, we propose a time-domain electrical heating (TDEH) method that enables simultaneous high-resolution characterization of out-of-plane and in-plane thermal conductivity as well as heat capacity. The TDEH method was validated across a broad thermal conductivity range (1-4000 W/(m·K)), showing excellent agreement between the measured thermal conductivity, heat capacity and other standard references. Furthermore, the successful application of TDEH to both strongly anisotropic low-thermal-conductivity Ga₂O₃ thin films and polycrystalline diamond demonstrates its versatility for comprehensive thermal characterization of semiconductor materials. Our work provides a versatile, high-precision, and easily implementable solution for chip's thermal characterization, offering an essential tool for thermal management design in high-power and highly integrated chips.

  PublisherDOI

• Fine-Grained Extraction of Social Media Disaster Information and Spatiotemporal Evolution Analysis: A Spatiotemporal Information Mining Method Integrating LDA-BERT and BiLSTM-CRF Topic Modeling

  Research Square · 2026-04-15

  preprintOpen access
  PublisherDOI

• Time-domain electrical heating for broad-range and anisotropic thermophysical characterization of semiconductors

  AIP Publishing · 2026-04-15

  datasetOpen access1st authorCorresponding

  Supplementary Figure S1 to Supplementary Figure S12 Supplementary Table 1 to Supplementary Table 3 Supplementary Note 1 to Supplementary Note 6

  PublisherDOI

• <strong>Time-domain electrical heating for broad-range and anisotropic thermophysical characterization of semiconductors</strong>

  AIP Publishing · 2026-01-01

  otherOpen access1st authorCorresponding

  As transistor scaling approaches physical limits, the accurate quantification of thermal conductivity and interfacial thermal conductance for semiconductor materials within chips has emerged as a critical bottleneck for next-generation integrated circuit design and thermal management. Existing thermal measurement techniques are challenged by devices exhibiting concurrent high thermal conductivity, multilayer structures, and pronounced anisotropy, often requiring complex procedures, prolonged measurement times, and multi-method integration—yet still yielding unsatisfactory accuracy. To overcome these limitations, we propose a time-domain electrical heating (TDEH) method that enables simultaneous high-resolution characterization of out-of-plane and in-plane thermal conductivity as well as heat capacity. The TDEH method was validated across a broad thermal conductivity range (1–4000 W/(m·K)), showing excellent agreement between the measured thermal conductivity, heat capacity and other standard references. Furthermore, the successful application of TDEH to both strongly anisotropic low-thermal-conductivity Ga₂O₃ thin films and polycrystalline diamond demonstrates its versatility for comprehensive thermal characterization of semiconductor materials. Our work provides a versatile, high-precision, and easily implementable solution for chip’s thermal characterization, offering an essential tool for thermal management design in high-power and highly integrated chips.

  PublisherDOI

• Heat transfer optimization in oil shale rotary retorting via DEM and BP neural network

  Oil Shale · 2026-04-15

  articleOpen accessSenior author

  To enhance heat transfer between shale ash and oil shale particles in a rotary retorting furnace, this study coupled the discrete element method (DEM) with a particle heat conduction model to simulate mixing and heat transfer, examining the effects of particle filling ratio, furnace rotational speed, and baffle structures. A backpropagation neural network (BP-NN) model was built from simulation data to map furnace operation time with key parameters, and a genetic algorithm was used to optimize parameters to minimize operation time. The research results show that lower filling degrees and higher rotation speeds significantly strengthen particle mixing and heat exchange, which accelerate the system’s stabilization, improve temperature field uniformity, and reduce the temperature standard deviation. The mixing and heat transfer effect of the straight baffle is between that of the right-angle baffle and the inclined baffle, but it causes the largest temperature standard deviation. In contrast, the right-angle baffle demonstrates stronger advantages in heat transfer uniformity during particle lifting and throwing. The constructed BP-NN prediction model achieves a relative error accuracy within 0.25%, effectively solving the long computation time problem of DEM simulation. The optimized parameter combination provides a theoretical basis for the development of high-efficiency and energy-saving rotary retorting furnaces.

  PublisherDOI

• CMIP7 data request: impacts and adaptation priorities and opportunities

  Geoscientific model development · 2025-12-04 · 2 citations

  articleOpen access

  Abstract. The Coupled Model Intercomparison Project Phase 7 (CMIP7) undertook an extensive process to gather community input and refine data requests related to impacts and adaptation applications of Earth System Model (ESM) outputs. The Impacts and Adaptation (I&amp;amp;A) Data Request Team worked with CMIP7 leadership to distribute an open solicitation across many communities that use climate model outputs requesting inputs for new and existing variables, the most applicable temporal characteristics, and groupings of variables that together allow for specific application opportunities. This input was then collated and translated into CMIP7 standard templates for inclusion in the broader data request, leading to 13 I&amp;amp;A data request opportunities, 60 variable groups and 539 unique variables sought by vulnerability, impacts, adaptation, and climate services user communities. Here, we describe these opportunities and variable groups, as well as new insights into how ESM groups can prioritize outputs that set off a chain of further analyses, ultimately informing decisions impacting society and natural systems. These include an emphasis on high-resolution outputs to allow further modeling of climate impacts at regional and local scales, improved representation of extreme weather events, enhanced accuracy of downscaling and bias-adjustment techniques, and support for more detailed assessments for decision-making in adaptation and mitigation strategies. There is also broad interest in more extensive provisioning of two-dimensional variables at the Earth's surface, prioritizing experiments that enhance our understanding of both the recent past and future scenarios, and providing outputs that allow further downscaling and bias adjustment. We emphasize that variable groups are the fundamental level at which to engage with the I&amp;amp;A data request, matching the scale of input and the way output provision enables specific I&amp;amp;A applications. Given resource constraints, we applaud CMIP7 efforts to foster strong engagement and communication between ESM groups and the I&amp;amp;A team to build consensus around prudent compromises in priority variables, temporal resolutions, simulation experiments, time subsets, and ensemble members.

  PublisherOA PDFDOI

• Enhancing Global‐Scale Urban Land Cover Representation Using Local Climate Zones in the Community Earth System Model

  Journal of Advances in Modeling Earth Systems · 2025-11-01 · 2 citations

  articleOpen access

  Abstract Urban areas are increasingly vulnerable to the impacts of climate change, necessitating accurate simulations of urban climates in Earth system models (ESMs) in support of large‐scale urban climate adaptation efforts. ESMs underrepresent urban areas due to their small spatial extent and the lack of detailed urban landscape data. To enhance the accuracy of urban representation, this study integrated the local climate zones (LCZs) scheme within the Community Earth System Model (CESM) to better represent urban heterogeneity. We adopted a modular approach to incorporate the 10 built LCZ classes into CESM as a new option in addition to the default urban three‐class scheme (i.e., tall building district, high density, and medium density). CESM simulations using the LCZ‐based urban characteristics were validated globally at 20 flux tower sites, showing site‐averaged improvement in modeling upward longwave radiation () and anthropogenic heat flux (), but increased uncertainties in modeling sensible heat flux (). The root‐mean‐square error between the observed and simulated using the LCZ decreased by 4% compared to using the default. Model sensitivity experiments revealed that and had comparable sensitivity to LCZ urban morphological and thermal parameter subsets. This study assessed and demonstrated the implementation as the starting point for future work on better resolving urban areas in Earth system modeling.

  PublisherDOI

• Global Mapping of Informal Settlements using Satellite Imagery and Open Datasets

  2025-05-21

  preprintOpen accessCorresponding

  Informal settlements, where groups of asylum-seekers, refugees, or internally displaced people settle in self-identified, spontaneous locations, often lack basic services and are highly vulnerable to climate-driven risks. Approximately 1 billion people currently live in informal settlements, driving significant research attention to issues such as property rights and governance strategies. However, the lack of large-scale location and boundary data for informal settlements poses a major obstacle to conducting in-depth quantitative analyses. Existing approaches to identifying informal settlements have been constrained to individual cities or districts due to their reliance on costly imagery, field survey, and localized expertise. To address this gap, we develop a novel, global framework to identify permanent informal settlements using satellite imagery and publicly available datasets. First, building footprint and nighttime light datasets were combined to isolate human settlements with low energy availability, effectively narrowing the focus to potential settlement areas and significantly reducing computational costs. Next, leveraging high-resolution Sentinel-2 imagery, we estimated the similarity of each pixel's spectral principal components to those of high-confidence samples, allowing us to distinguish informal settlements from broader human settlement areas. Finally, nearly 10,000 informal settlement points provided by the United Nations were used to refine our results, ensuring that only officially recognized informal settlements were retained. This fast and scalable framework overcomes the data scarcity challenges typically faced in resource-poor regions, where informal settlements are most prevalent. The results of this study provide an unprecedented foundation for deeper quantitative analyses of informal settlement areas, supporting global efforts to achieve the Sustainable Development Goals and address urban vulnerabilities.

  PublisherDOI

Recent grants

• CAREER: CAS-Climate: Climate Driven Risks to Urban Environment – Hybrid Modeling and Adaptation Strategies

  NSF · $510k · 2022–2027

Frequent coauthors

• Keith W. Oleson

  42 shared

• Xuhui Lee

  39 shared

• Phong V. V. Le

  Oak Ridge National Laboratory

  36 shared

• Andrew W. Taylor‐Robinson

  University of Pennsylvania

  36 shared

• Brian F. Allan

  University of Illinois Urbana-Champaign

  36 shared

• Praveen Kumar

  University of Illinois Urbana-Champaign

  36 shared

• Thanh H. Nguyen

  University of Illinois Urbana-Champaign

  36 shared

• Jinhui Yan

  University of Illinois Urbana-Champaign

  36 shared

Awards & honors

• NSF CAREER Award
• Timothy Oke Award from the International Association for Urb…
• AGU Global Environmental Change Early Career Award from the…