Date of Award
Spring 5-6-2021
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Geography
First Advisor
Haydee Salmun
Second Advisor
Shipeng Sun
Academic Program Adviser
Sean Ahearn
Abstract
Two methods for estimating the planetary boundary layer, an algorithm to identify a maximum in the backscatter and a covariance wavelet transform method, are explored and applied to global radar wind profiler network data and ceilometer data respectively. The objective of the study is to establish that the data sources and algorithms can be used to estimate planetary boundary layer heights so that global studies can make use of these estimates. Data from the global network of wind profilers required significant restructuring and quality control in order to be used for the present study. The maximum backscatter identification algorithm was slightly modified from a previous study, and requires further fine-tuning for future use in estimating planetary boundary layer heights and drawing conclusions from those estimates. Linear interpolation of the radar wind profiler data in conjunction with the estimates obtained from the maximum backscatter identification algorithm were used to develop an experimental high order smoothing method for estimating diurnal cycles of the planetary boundary layer height. Applying both the maximum backscatter identification algorithm and covariance wavelet transform algorithm to data from radar wind profilers and ceilometers, respectively, resulted in similar estimates.
Recommended Citation
Josephs, Holly, "Estimation of the Planetary Boundary Layer Height: Part 1: Global Radar Wind Profiler Network Data; Part 2: A Comparison to Ceilometer Data" (2021). CUNY Academic Works.
https://academicworks.cuny.edu/hc_sas_etds/738
Included in
Atmospheric Sciences Commons, Data Science Commons, Other Oceanography and Atmospheric Sciences and Meteorology Commons