Can a Persistence‐Based Prediction of GRACE Gravity Field Coefficients Reduce Uncertainties at Finer Temporal Scales?

Abstract

Enhancing the applicability of Gravity Recovery and Climate Experiment (GRACE) products poses challenges due to the trade‐off between the temporal and the spatial resolution within limits posed by the mission design. If a Kalman filter framework was adopted to characterize the relationship between monthly and finer temporal scales, it could facilitate the prediction of uncertainty associated with rapid mass changes at the higher temporal resolution. This study investigates the following key questions: (a) whether a persistence‐based prediction of gravity coefficients effectively reduces the uncertainties of finer temporal scale‐gravity coefficients to levels comparable with the known uncertainties of monthly gravity coefficients; and (b) the spectral degrees at which this consistency is most pronounced. The application of the resulting predictive approach to GRACE level‐2 data demonstrates its effectiveness in reducing uncertainty at high spherical harmonic degrees. The prediction approach allows for the estimation of sub‐monthly and weekly gravity coefficients with uncertainties that are comparable to the monthly resolution‐uncertainties for specific ranges of degrees. This is validated by the degree variance of the finer resolution‐estimates which largely align with those of the monthly raw gravity coefficients across the higher spherical harmonic degrees for sub‐monthly and weekly data. Further, this predictive framework, on a univariate basis, demonstrates its potential to mitigate the correlated errors to a useful extent as observed in the spectral and spatial domains. Reducing uncertainties at finer temporal scales for higher spherical harmonic degrees to levels comparable with monthly data enhances the assessment of rapid mass changes in localized hydrological studies.