The layer of the atmosphere closest to the surface is known as the planetary boundary layer. During the daytime, when the sun warms the surface and air rises and becomes turbulent, meteorologists refer to this layer as the convective boundary layer (CBL). The height above the ground of the top of the CBL is variable and has relevance to thunderstorm initiation, precipitation, and pollutant concentration. However, there is no simple way to provide continuous measurements of the height of the CBL over large areas. This project will further investigate a method to retrieve the CBL top height by using the operational National Weather Service radar network. These weather radars are sensitive enough to detect gradients in different airmasses, such as the more humid convective boundary layer and the drier air above that. The significance of the work is through the development of a dataset that can be used to assess the ability of numerical models to simulate the convective boundary layer, and therefore practical weather phenomena. The project also has a significant education and outreach component, with training for multiple graduate students, creation of features for a public television program, and implementation of a Research Experience for Teachers program.
The overarching goal of this project is to improve understanding of the evolution of the convective boundary layer top height (CBLH) using the clear-air remote sensing capabilities of the operational WSR-88D radar network. S-band weather radar, in non-precipitating situations, can differentiate between biological returns (e.g. insects) and Bragg scatter (refractive index gradients) by using differential reflectivity to define the CBLH. This technique would provide a significant increase in observations of CBLH due to the rapid updates and nationwide footprint of the WSR-88D network. Five main activities are: 1) Develop monthly mean values of observed hourly daytime CBLH from at least 50 radars across the US over two distinct years (2014 and 2022) to explore similarities and differences in CBLH evolution, 2) Develop monthly mean values of predicted hourly daytime CBLH from the operational Rapid Refresh (RAP) model, 3) Calculate the difference between the radar observed CBLH and the RAP predicted CBLH, and explore reasons for the differences using all available observations, 4) Explore the ability of the differential reflectivity observations to estimate entrainment zone depth by comparing them to new rawinsonde observations, and 5) Study the late afternoon inversion layer separation and CBL descent using the observations and modeling derived above.
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.
