Team Members:
Person Name | Person role on project | Affiliation |
---|---|---|
Xiaojing Tang | Principal Investigator | James Madison University , Harrisonburg , USA |
Dan Li | Co-Investigator | Boston University , Boston , USA |
Angela Erb | Co-Investigator | University of Massachusetts Boston, Boston , USA |
Cenlin He | Co-Investigator | National Center for Atmospheric Research (NCAR) , Boulder , USA |
Crystal Schaaf | Collaborator | University of Massachusetts Boston, Dorchester , US |
With more than 50% of the global population living in cities and the continued urbanization trends, urban areas represent critical hotspots of water, energy, and health challenges facing humanity in the 21st century. A better understanding and prediction of urban microclimate and hydrology within the context of global environmental change plays a key role in tackling these challenges. Although correctly characterizing the albedo of building materials is identified as the most important factor to improve urban simulation results, most urban land surface models used in weather and climate models (e.g., the single-layer urban canopy model in the Weather Research and Forecasting or WRF model) still employ tabulated albedo values, which have extremely limited spatial variability. We propose to improve urban albedo characterization in weather models using remote sensing data. Specifically, we will (1) develop a new, high-resolution urban albedo dataset based on Landsat and Sentinel-2, (2) separate roof from impervious ground in the NLCD impervious surface dataset, (3) conduct and analyze WRF simulations with the new urban albedo dataset, and (4) implement the new albedo dataset into publicly released WRF versions. The proposed research will improve the characterization of the albedo parameters in WRF, improve the simulation of urban meteorological variables at the weather scale, and thus empower stakeholders and researchers to better navigate urban planning and policies in a changing climate.