Transforming GRACE mascon TWS-L3 data into vertical displacements using a regression approach: a case study of the Türkiye region

The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On satellite missions have been monitoring hydrological events on Earth’s surface for nearly two decades. Monthly gravity solutions from these satellites are available as Level-2 (L2) spherical harmonic coefficients or as ready-to-use Level-3 (L3) data, typically representing Total Water Storage (TWS) variations. L3 data, such as Goddard Space Flight Center (GSFC) mascon data, include essential corrections like post-glacial rebound and signal-leakage, and precisely represent TWS variations for specific regions, such as river basins, without additional corrections. However, certain geopotential changes, such as groundwater-induced vertical displacements, gravity anomalies and geoid height changes cannot be directly obtained from these data. To evaluate these geopotential changes, L3 data needs to be transformed into harmonic coefficient solutions. While this method is more computationally demanding compared to adapting L2 data with necessary corrections, the question remains: How can L3 TWS data be directly transformed into other potential changes? In this study, we propose a regression approach for the Türkiye region, using approximately hundred GSFC-mascon blocks to convert TWS into groundwater-induced vertical displacements. Transformation parameters are estimated by considering outcomes from L2 data, specifically selecting DDK2- filtered data. The ratio between vertical displacement and TWS for each mascon is modeled by a quadratic function based on TWS magnitudes. Investigating residuals reveals a timedependent pattern, which requires a second regression to model this aspect. This two-step regression approach successfully transforms TWS into vertical displacements, with a rootmean- square error of about half a millimeter, providing satisfactory results for the region.