A novel GRACE reconstructive filter to extract the mass changes in Madagascar

Abstract

SUMMARY The precise estimation of the mass changes in Madagascar is a challenge by using the Gravity Recovery and Climate Experiment (GRACE) mission Level-2 products since they are contaminated by noise. Although this issue can be alleviated by the empirical destriping method or spatial filtering, they result in potential signal distortion or signal leakage. To improve this, we propose a reconstructive filter, whose parameters are optimized by the signal-to-noise ratio. Subsequently, our optimal filter corresponding to the best signal-to-noise ratio (5.63) is used to estimate the mass changes (2002–2017) in Madagascar. Eventually, our results are compared with two reliable GRACE mascon products and other independent observations. Correspondingly, here are our major conclusions: (1) Compared with groundwater storage from the mascon products, our estimates have the highest Pearson correlation (0.5) with in situ observation and can detect the rapid increase of groundwater storage during the rainy season. (2) The Fourier spectrum analysis detects a ∼3.8-yr periodic signal in the terrestrial water storage changes in Madagascar, which is contributed from the interannual precipitation driven by climate factor (Indian Ocean Dipole) and the aliasing error for imperfect GRACE pre-process. Our work introduces an effective filter for processing GRACE Level-2 data and presents novel insights into mass changes in Madagascar.