Multitemporal mass change analysis of Greenland Ice Sheet using variational mode decomposition

Abstract

Summary The Greenland Ice Sheet (GrIS) is the largest ice body in the northern hemisphere. Quantifying the spatiotemporal characteristics of its mass change is crucial for understanding global climate change. Many studies have been focused on the long-term ice mass change and acceleration, but a more detailed analysis of multitemporal signals, including annual, interannual, and transient variations, is still imperative to study the periodic ice mass change. Here, we comprehensively characterize the multitemporal mass changes of the entire GrIS and subregions using a variational mode decomposition (VMD) method, applied to Gravity Recovery and Climate Experiment (GRACE) satellite data, surface mass balance model output, climate parameters, and GPS observations. We found both the interannual and transient mass variations of the southern subregions have larger amplitudes associated with pronounced precipitations, indicating that the southern mass change patterns are more vulnerable to short-term climate variability. We also found that the reported rapid mass loss in 2010, 2012, 2016, and 2019 should be attributed to the interannual signals, which result from low precipitations, significant runoff, and evapotranspiration. The largest interannual mass variation was discovered in 2019 (−235 Gt), but due to the combined effect of interannual loss (−147 Gt) and transient attenuation (−380 Gt), the greatest mass loss (−527 Gt) was observed at the end of 2012. Our study emphasizes the importance of multitemporal signals in characterizing the spatiotemporal GrIS mass change and exploring the coupling effect between ice mass change and climate conditions.

Greenland Interannual Ice Mass Variations Detected by GRACE Time‐Variable Gravity

“…Wu et al. (2022) further found mass variations of southern Greenland subregions mainly affected by pronounced precipitation. As temperature and precipitation patterns generally reflect large‐scale atmospheric circulations, B. Zhang et al.…”