An Investigation of GNSS RO Data Pattern for Climate Change Monitoring and Analysis over Africa

Abstract

Climate change monitoring and analysis is a critical aspect that involves the consideration of both spatial and temporal dimensions. Improved spatial distribution of the Global Navigation Satellite System (GNSS) ground-based Continuous Operating Reference (COR) stations can lead to enhanced results when coupled with a continuous flow of data over time. In Africa, a significant number of COR stations do not operate continuously and lack collocation with meteorological sensors essential for climate studies. Consequently, Africa faces challenges related to inadequate spatial distribution and temporal data flow from GNSS ground-based stations, impacting climate change monitoring and analysis. This research delves into the pattern of GNSS Radio Occultation (RO) data across Africa, addressing the limitations of the GNSS ground-based data for climate change research. The spatial analysis employed Ripley's F, G, K, and L-functions, along with calculations of nearest neighbour and Kernel density. The analysis yielded a Moran's P-value of 0.001 and a Moran's I-value approaching 1.0. For temporal analysis, the study investigated the data availability period of selected GNSS RO missions. Additionally, it examined seasonal temperature variations from May 2001 to May 2023, showcasing alignment with findings from other researchers worldwide, Hence, this study suggests the utilization of GNSS RO missions/campaigns like METOP and COSMIC owing to their superior spatial and temporal resolution.