We invite applications for a postdoctoral researcher to join a cutting-edge project aimed at improving numerical weather prediction (NWP) models for urban heat island (UHI) and extreme precipitation events. The focus is on developing innovative solutions that leverage machine learning and high-resolution remote sensing data to better represent the complexity of urban land cover/land use (LCLU) and its effects on weather processes. This research directly supports NASA's Land-Earth System Digital Twins (L-ESDT) initiative.
Urban areas exhibit both high spatial complexity and significant exposure to hydrometeorological hazards. Current operational NWP models fail to accurately represent the effects of urban landscapes, particularly the influence of vertical structures and fine-scale land use variability. This project aims to design an optimal data-model pipeline to capture the effect of LCLU on UHI and precipitation extremes, using hybrid physics and machine learning models. The research will focus on four cities from the DOE’s Urban Integrated Field Laboratory (UIFL) initiative and deliver these advances to NASA’s L-ESDT.
• Develop urban surface forcing fields relevant to UHI and precipitation extremes, using remote sensing data and research-grade WRF simulations.
• Augment land surface models (LSMs) such as NOAH-MP with machine learning to capture sub-grid scale effects of urban features on meteorological processes.
• Validate and demonstrate improvements in operational NWP forecasts for UHI and extreme precipitation.
• Publish research findings and present them at national and international conferences.
• PhD in atmospheric sciences, hydrometeorology, geospatial sciences, machine learning, or a related field.
• Expertise in numerical weather modeling (e.g., WRF), geospatial data processing, machine learning, and remote sensing.
• Strong programming skills (e.g., Python and other relevant languages) and experience with high-performance computing environments.
• Familiarity with operational NWP models (e.g., NAM) and land surface models (e.g., NOAH-MP) is highly desirable.
• Excellent written and oral communication skills, with a strong publication record.
• Duration: This is a 3-year project with an initial one-year contract, renewable upon satisfactory performance.
• Location: Cornell University, Ithaca, NY
• Start Date: Jan. 1 2025 preferred (negotiable start date)
• Professional Development: Opportunities for publications, conference participation, and collaboration with leading researchers and agencies.
Interested applicants should submit the following documents to:
John D. Albertson albertson@cornell.edu
Qi Li ql56@cornell.edu
• Curriculum Vitae (CV)
• Names and contact information for references
