Masters Theses

Keywords and Phrases

HRRR; PWV; RAiDER; RH; SVP; ZTD

Abstract

Interferometric Synthetic Aperture Radar (InSAR) is a vital technique for monitoring ground surface deformation across large spatial scales. However, variability in atmospheric water vapor, pressure, and temperature introduces tropospheric delays that can significantly affect measurement accuracy. These delays are often corrected using outputs from numerical weather prediction (NWP) models. RAiDER, an open-source Python package, facilitates this by estimating tropospheric delays using models such as the High-Resolution Rapid Refresh (HRRR). Previous studies have shown that weather model–based corrections can substantially reduce atmospheric noise in InSAR data but also highlight persistent residual errors, especially at spatial scales smaller than the model grid resolution. This study aims to quantify the magnitude of residual tropospheric delay that persists after HRRR-based correction, using GNSS-derived Zenith Total Delay (ZTD) as ground truth. Specifically, we assess the accuracy of NWP-derived delays at spatial scales smaller than a single model grid cell. The analysis is conducted across three GNSS-dense regions in the United States: Rolla, Missouri (June 2024–March 2025); Salt Lake City, Utah (January–February 2020), and Mineral, California (January–October 2020). Standard deviations of the ZTD residuals are 3.53 cm in Rolla, 2.08 cm in Salt Lake City, and 2.72 cm in Mineral, highlighting spatial variability in model performance due to local atmospheric conditions. These residuals are used to develop a statistical model that estimates the uncertainty in InSAR-derived velocities.

Advisor(s)

Maurer, Jeremy

Committee Member(s)

Liu, Kelly H.
Gao, Stephen S.

Department(s)

Geosciences and Geological and Petroleum Engineering

Degree Name

M.S. in Geology and Geophysics

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2025

Pagination

xi, 95 pages

Note about bibliography

Includes_bibliographical_references_(pages 88-94)

Rights

© 2026 Adeyinka Olaoluwa Olaseinde , All Rights Reserved

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 12574

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