On the Improvements of Boundary-Layer Representation for High Resolution Weather Forecasting in Costal-Urban Environments

Author

David Melecio-Vazquez, CUNY City CollegeFollow

Date of Award

2021

Document Type

Dissertation

Department

Mechanical Engineering

First Advisor

Jorge E. Gonzalez-Cruz

Second Advisor

Robert D. Bornstein

Third Advisor

Joseph B. Olson

Keywords

urban boundary layer, ground-based remote sensing, turbulence, coastal meteorology, numerical weather prediction, weather forecasting

Abstract

As large urban centers around the world become more densely populated, the global conversion from natural to man-made land surfaces will only increase. These land-use changes affect the urban surface energy budget which in turn changes the structure of the planetary boundary layer (PBL) above. With current high-performance computing systems, meteorological and built environment information can be better utilized to quantify the anthropogenic effects of these modifications. Although these systems have improved forecasting near-surface weather conditions, a comprehensive approach to represent urban impacts on the PBL is still limited. Improved PBL representation can lead to better weather and climate forecasts, benefitting human health, risk reduction from extreme weather events, improved management of airport runways, and better planning for renewable energy resources.

In this dissertation, coastal-urban boundary-layers are investigated to provide: (1) a climatology of coastal-urban PBL thermal structure, (2) an evaluation of a PBL scheme newly coupled to a multilayer urban parameterization, and (3) insights for operational weather forecasting. Ground-based remote sensing is thus used to determine PBL structure over high-density New York City for a summer and winter season to provide insights for a modeling effort. The modeling focused on the evaluation of the performance of the Weather Research and Forecasting (WRF) model in the simulation of NYC impacts during a three-day regional heat wave and sea breeze event. The study proposes a new WRF configuration within the US National Weather Service (NWS)-National Ocean and Atmospheric Agency (NOAA) operational numerical weather prediction (NWP) forecast model. The goal is an improved PBL representation at a high resolution of 1-km grid over coastal cities by a coupling of the state-of-the-art multi-layer Building Environment Parameterization (BEP) and the Building Energy Model (BEM) schemes to three PBL options, including a first-time linkage with the operational Mellor-Yamada-Nakanishi-Niino (MYNN) Eddy Diffusivity and Mass Flux (EDMF) scheme.

Results showed that climatological clear-sky conditions produced a winter and summer shallow above-rooftop daytime superadiabatic layer that persisted into the night, unlike the traditional surface inversion found over non-coastal, non-urban surfaces. Above this shallow layer, a persistent elevated stable region was found. The heat event WRF simulations showed that MYNN-EDMF produces the best performance in comparisons to observed surface temperatures and sea-breeze front progression, with the BouLac PBL scheme best for surface wind speed. MYNN-EDMF also was the most accurate in reproducing the rural PBL case study observations, while its urban PBL structures were most like the climatological thermal structures.

Future efforts should utilize a TKE formulation that includes advection to better capture internal boundary layer effects and more precisely evaluate PBL heights. Future efforts should further refine the anthropogenic heat and building drag formulations, which will further reduce WRF urban temperature and wind speed biases, respectively. It is finally recommended that future NYC-area investigations include case-study and climatological observations at optimal locations for observing the interactions between the urban environment and sea-breeze systems.

Recommended Citation

Melecio-Vazquez, David, "On the Improvements of Boundary-Layer Representation for High Resolution Weather Forecasting in Costal-Urban Environments" (2021). CUNY Academic Works.
https://academicworks.cuny.edu/cc_etds_theses/965