The project starts today and is titled:
Understanding and Modeling the Role of Horizontal Heterogeneity on the Dynamics of the Nocturnal Boundary Layer Across Scales
We hope to use a suite of state-of-the-art simulations to improve our understanding of the physics in the near-surface atmosphere at night. Most models treat this environment as quasi-homogeneous. In reality, the nocturnal boundary layer can be rather inhomogeneous (i.e., temperature and roughness differences). By accounting for these inhomogeneities, we hope to improve the models that drive numerical weather and climate prediction.
The more specific project summary that we provided to the NSF is given below. If you are interested in the full proposal, shoot me an email.
The main goal of this project is to understand the role of surface heterogeneity in determination of average surface fluxes in the nocturnal boundary layer (NBL). This knowledge will be used to develop new physically-based models and parameterizations that can properly account for the interaction between natural land-surface heterogeneity and turbulence in the boundary layer. Our hypothesis is that under the stratified conditions characteristic of the NBL, surface heterogeneity will localize turbulent fluxes horizontally and vertically, and will enhance the flux contrast between regions with different surface states (e.g. temperature). The proposed research is unique because current surface flux parameterizations do not account for these consequential behaviors.
A series of numerical experiments will examine this hypothesis across a wide range of length and time scales. Direct numerical simulations of heterogeneous NBLs will be performed to examine small-scale turbulence physics. Simulation output will be combined with theory to construct new Large Eddy Simulation (LES) surface boundary conditions, which will be validated against field data. The LES data will inform new parameterizations for large-scale weather and climate models. The new models created during this project will form a new turbulent surface flux multi-scale framework valid for length scales from meters to tens of kilometers.
The project will improve the basic understanding of the NBL and how its dynamics are linked to natural land-surface characteristics. These dynamics will be studied using a variety of tools across length scales ranging from meters to kilometers. We will enhance the ability to predict the impacts of land cover and land-use change by advancing the understanding of how subgrid heterogeneity can be included in large-scale weather and climate models. This will directly improve weather forecasting by developing new models for surface processes that must be included as boundary conditions in all forecast models.
The new information and key data sets will be important components when seeking to enhance the accuracy of predictions of climate variability and change due to anthropogenic and naturally occurring alterations in land surface cover and usage. The generated models and knowledge will be especially important over the next decade, as climate models start to approach the resolution of regional weather forecasting models and weather forecasting approaches the resolution of LES.
Direct impacts include an archive server developed in coordination with the University of Utah (UofU) Center for High Performance Computing. Output products from the proposed simulations will be made available to the public through an application program interface.
Data generated from this project will also be incorporated into a newly-developed LES graduate course in the Department of Mechanical Engineering at the UofU. Finally, archival journal publications and presentations at national scientific conferences by project personnel will provide further dissemination of this innovative project.
Furthermore, we will collaborate with the UofU College of Engineering (CoE):
First, we will create a new learning module for the Hi-GEAR (Girls Engineering Abilities Realized) summer camp, which is designed to expose young women to STEM careers through projects led by female College of Engineering mentors. This module will teach students the basics of numerical weather prediction and how to produce the forecasts that they see on the TV/Internet.
Second, we will help develop new project motivated modules for the Discover Engineering program, which is an interactive traveling recruitment program that showcases each of the CoE majors to local high school students.