A preliminary view of the CYGNSS soil moisture-vegetation activity linkage

Abstract

IntroductionSoil moisture (SM) is crucial for regulating vegetation productivity and sustaining plant growth. Understanding the linkage between SM and vegetation activity is paramount in eco-hydrology modeling and meteorological applications. CYGNSS, one of the most commonly spaceborne GNSS-R missions with publicly available data, has the advantage of retrieving SM with high accuracy and high temporal resolution.MethodsThis paper describes the linkage between the CYGNSS SM and vegetation activity. The CYGNSS SM from 2019.01 to 2022.12 with system error and land surface calibration is first retrieved. The linkages between the CYGNSS SM and two key vegetation activity indexes, i.e., NDVI and the start of the growing season (SOS), are then investigated.ResultsThe findings and conclusions mainly include: (1) The CYGNSS SM with system error and land surface error calibration shows a good correlation with the SMAP SM, i.e., R = 0.693 vs. ubRMSE = 0.054 m3m−3. Long time-series CYGNSS SM can be useful data for large-scale terrestrial ecosystems and global change studies. (2) The NDVI shows a negative correlation with SM in most pan-tropical areas, whereas a positive correlation with SM in Africa. The response of NDVI to SM is more significant in shrublands and grasslands. (3) The link between the CYGNSS SM and SOS displays strong annual variations, and the SM has generally experienced a significant negative effect on SOS. SM advances the vegetation green-up in arid and semi-arid areas.