Su (2026) SWPU-PMA2025: a global surface mass redistribution dataset derived from GRACE L1B data and a modified point‒mass modeling approach

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-02-04
• Authors: Yong Su
• DOI: 10.17632/5v459zkn95.2

Research Groups

• Southwest Petroleum University

Short Summary

This study introduces a modified Point-Mass Modeling Approach (PMA) and an adaptive constraint matrix to process GRACE Level-1B data, generating a global surface mass redistribution dataset (SWPU-PMA2025) with improved spatial resolution and reduced noise/leakage.

Objective

• To develop and apply a modified Point-Mass Modeling Approach (PMA) and an adaptive constraint matrix to derive a global surface mass redistribution dataset from GRACE Level-1B data, aiming to enhance spatial and temporal resolution while mitigating striping noise and signal leakage issues.

Study Configuration

• Spatial Scale: Global, with a spatial resolution of 0.5° (approximately 55 km at the equator).
• Temporal Scale: Monthly, covering the period from 2002 to 2016.

Methodology and Data

• Models used: Modified Point-Mass Modeling Approach (PMA), adaptive constraint matrix construction method.
• Data sources: GRACE Level-1B satellite observations.

Main Results

• A global surface mass redistribution dataset, SWPU-PMA2025, was successfully generated from GRACE Level-1B data.
• The dataset has a spatial resolution of 0.5° and a temporal resolution of one month, covering the period from 2002 to 2016.
• The modified PMA and adaptive constraint matrix effectively established a direct mathematical relationship between satellite observations and surface mass blocks, demonstrating the approach's effectiveness in generating a time series.
• The adaptive constraint matrix operates independently of external geophysical inputs, maintains temporal adaptability, accounts for long-term ocean mass changes, and effectively mitigates land signal leakage.
• The dataset is provided in NetCDF (.nc) format and includes variables for longitude, latitude, time, and equivalent water height (lwe_thickness).

Contributions

• Introduction of a novel modified Point-Mass Modeling Approach (PMA) that directly links satellite observations to surface mass blocks, bypassing traditional intermediate gravity field models.
• Development of an adaptive constraint matrix that is independent of external geophysical inputs and maintains temporal adaptability, offering a robust solution for GRACE data processing.
• Effective mitigation of common challenges in GRACE data processing, such as striping noise, signal leakage, and limitations in spatial resolution, without compromising true geophysical signals.
• Generation of a new, high-resolution global surface mass redistribution dataset (SWPU-PMA2025) that accounts for long-term ocean mass changes and provides improved data quality for various geodetic and geophysical applications.

Funding

• National Natural Science Foundation of China (Grant ID: 42374004)

Citation

@article{Su2026SWPUPMA2025,
  author = {Su, Yong},
  title = {SWPU-PMA2025: a global surface mass redistribution dataset derived from GRACE L1B data and a modified point‒mass modeling approach},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/5v459zkn95.2},
  url = {https://doi.org/10.17632/5v459zkn95.2}
}