Global VLM and Relative Sea Level Acceleration Derived from Global GNSS Datasets

Description

We provide global Vertical Land Motion (VLM) and Relative Sea Level acceleration datasets based on global GNSS data from 1994 to 2023. Selected GNSS station information (rate and acceleration) is assigned to the global coastal segment from the Dynamic Interactive Vulnerability Assessment (DIVA) model (Nicholls et al., 2021), as well as global tide gauge stations. We project these changes to 2050. A comprehensive description of the method used to derive acceleration from global GNSS datasets can be found in Sherpa et al. (2023). The method is briefly summarized below. 

1. We perform step correction on the GNSS time series. 
2. Following (Sherpa et al., 2023), We apply Singular Spectrum Analysis (SSA) to the time series of continental GNSS stations with observation longer than 10 years to investigate VLM rate variations.
3. We use refined time series from SSA to obtain VLM rates, acceleration, and their uncertainties.
4. We  project VLM (relative sea level) to 2050, using the current rate of VLM and acceleration.
5. We provide this information at Global DIVA segments and Global tide gauge stations.

This dataset consists of,

1. Global GNSS Stations Velocity and Acceleration (Current): A CSV file containing derived VLM rates and their corresponding latitude and longitude.
2. Global DIVA Segment Velocity and Acceleration (Current) and 2050: A shapefile containing rates, accelerations based on GNSS, GNSS data begin date, GNSS data end date and GNSS data time duration at global DIVA segments in centimeters and time in days.
3. Global IPCC Tide Gauge Station 2050 Stations: A CSV file detailing for 2050 both from Sherpa and Shirzaei (2023) analysis and IPCC at global tide gauge.

For a more detailed description of these datasets see the README file. Anyone wishing to use this dataset should cite Sherpa et al. (2023) and contact Sonam Futi Sherpa at sonam_sherpa@brown.edu with any questions so that we may offer guidance regarding the optimal usage of our dataset. 

References:

Nicholls, R. J., Lincke, D., Hinkel, J., Brown, S., Vafeidis, A. T., Meyssignac, B., Hanson, S. E., Merkens, J.-L., & Fang, J. (2021). A global analysis of subsidence, relative sea-level change and coastal flood exposure. Nature Climate Change, 11(4), 338–342. https://doi.org/10.1038/s41558-021-00993-z

Sherpa, S. F., Shirzaei, M., & Ojha, C. (2023). Disruptive Role of Vertical Land Motion in Future Assessments of Climate Change-Driven Sea-Level Rise and Coastal Flooding Hazards in the Chesapeake Bay. Journal of Geophysical Research: Solid Earth, 128(4), e2022JB025993. https://doi.org/10.1029/2022JB025993