English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper, we robustly analyze the noise reduction methods for processing spherical harmonic (SH) coefficient data products collected by the Gravity Recovery and Climate Experiment (GRACE) satellite mission and devise a comprehensive GRACE Matlab Toolbox (GRAMAT) to estimate spatio-temporal mass variations over land and oceans. Functions in GRAMAT contain: (1) destriping of SH coefficients to remove “north-to-south” stripes, or geographically correlated high-frequency errors, and Gaussian smoothing, (2) spherical harmonic analysis and synthesis, (3) assessment and reduction of the leakage effect in GRACE-derived mass variations, and (4) harmonic analysis of regional time series of the mass variations and assessment of the uncertainty of the GRACE estimates. As a case study, we analyze the terrestrial water storage (TWS) variations in the Amazon River basin using the functions in GRAMAT. In addition to obvious seasonal TWS variations in the Amazon River basin, significant interannual TWS variations are detected by GRACE using the GRAMAT, which are consistent with precipitation anomalies in the region. We conclude that using GRAMAT and processing the GRACE level-2 data products, the global spatio-temporal mass variations can be efficiently and robustly estimated, which indicates the potential wide range of GRAMAT’s applications in hydrology, oceanography, cryosphere, solid Earth and geophysical disciplines to interpret large-scale mass redistribution and transport in the Earth system. We postulate that GRAMAT will also be an effective tool for the analysis of data from the upcoming GRACE-Follow-On mission.

GRAMAT: a comprehensive Matlab toolbox for estimating global mass variations from GRACE satellite data