As part of a collaborative NSF-funded Navigating the New Arctic (NNA) effort, the Greenland Hazards Project has installed two new Global Navigation Satellite Systems (GNSS) in Nuuk and Uummannaq in Western Greenland. The primary objective of these systems is to provide researchers with high rate (1 second) water level measurements using all available GNSS constellations and frequencies. Previous studies have shown that GNSS-IR can be successfully implemented to study tides (Ansari et al., 2020; Tabibi et al., 2020) and other ocean signals such as significant wave heights (Larson et al., 2013, 2017; Roesler, et al., 2018; Sepulveda et al., 2023). A crucial piece of the NNA project is to capture wave heights using GNSS-IR that originate from landslide-generated tsunamis. By combining machine learning and tsunami modeling with data GNSS-IR our project aims to develop a system that can accurately detect extreme waves. Data from the Uummannaq (UMNQ) site is of particular interest due to the potential for noise from the formation of sea ice, snow accumulation on the ice, and the presence of large icebergs. Earlier work has shown success measuring snow accumulation over sea ice thickness from GNSS-IR and the use of GNSS-IR to measure sea ice freeboard height (Dahl-Jensen, et al., 2022; Xie, 2022). Here we use GNSS-IR coupled with images produced and published by the Danish Meteorological Institute (DMI) which uses SMOS and Cryosat-2 data to determine sea ice properties over time. In contrast, the Nuuk (NKAR) site is not expected to encounter sea ice or many iceberg signals but is placed in an area with high amounts of boat traffic. During winter storms the Nuuk waterfront may experience storm waves and rough seas, creating the possibility for large wave heights. Finally, we present an analysis of the data including all available signals as inputs into machine learning algorithms in the future.