Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors
Description: The living biosphere interacts with atmospheric processes at a multitude of scales. Understanding these processes requires integration of multiple observations for comparison to theories embedded in atmospheric models. But, all observations mismatch the scale of all models. Therefore, spatial and temporal scaling of surface fluxes is fundamental to how we evaluate theories on what happens within the sub-grid of atmospheric models and how those feed back onto larger scale dynamics. The Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors (CHEESEHEAD) is an intensive field-campaign designed specifically to address long-standing puzzles regarding the role of atmospheric boundary-layer responses to scales of spatial heterogeneity in surface-atmosphere heat and water exchanges.
Intellectual Merit:
The high-density observing network is coupled to large eddy simulation (LES) and machine-learning scaling-experiments to better understand sub-mesoscale responses and improve numerical weather and climate prediction formulations of sub-grid processes. This project will advance spatiotemporal scaling methods for heterogeneous land surface properties and fluxes and theories on the scales at which the lower atmosphere responds to surface heterogeneity. CHEESEHEAD aims to provide a level of observation density and instrumentation reliability never previously achieved to test and develop hypotheses on spatial heterogeneity and atmosphere feedbacks.
Broader Impacts:
The experiment generates knowledge that advances the science of surface flux measurement and modeling, relevant to many scientific applications such as numerical weather prediction, climate change, energy resources, and computational fluid dynamics. The research will train next generation land-atmosphere graduate and undergraduate students. Field support outreach and teacher training is included via middle, high school, and undergraduate student involvement at nearby schools and colleges in coordination with UCAR's (University Corporation for Atmospheric Research) GLOBE program, Northland College, and local school districts. The database of observations and models will be made immediately available to the community and public for general use for further scientific advancement.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Funder: National Science Foundation
Amount: $1,610,000
Funding type: grant
Funder scheme: Continuing Grant
Start date: 2018-08-01
End date: 2024-01-31
Investigator: Ankur Desai
Institution: University of Wisconsin-Madison
Funded outputs count: 49
Funder award ID: 1822420
OpenAlex ID: G761808994