EGU22-111, updated on 25 Mar 2022
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Bridging GRACE and GRACE Follow-On TWS gap using forward-backward autoregressive model

Artur Lenczuk1, Anna Klos1, Matthias Weigelt2, Wieslaw Kosek3, Jan Mikocki1, and Janusz Bogusz1
Artur Lenczuk et al.
  • 1Faculty of Civil Engineering and Geodesy, Military University of Technology, Warsaw, Poland (
  • 2Faculty of Civil Engineering and Geodetic Science, Leibniz University Hannover, Hannover, Germany
  • 3Faculty of Production Engineering, University of Life Sciences in Lublin, Lublin, Poland

Nowadays, huge number of regions spread around the World are struggling with the problem of water availability. Hence, the quality and quantity of continental water resources must be regularly controlled. Currently, land water components are monitored, among others by measuring their weight, type and density or analyzing the level of water in the stilling wells. However, due to the time-consuming nature of such measurements, information on each components monitoring is lacking in many areas. For 15 years, the information about global hydrological changes has been regularly examined using monthly gravity fields provided by Gravity Recovery and Climate Experiment (GRACE) mission. GRACE mission ended in October 2017 and almost a year later, the GRACE Follow‐On (GRACE-FO) mission was launched in May 2018. Bridging the gap between both GRACE missions is currently a large challenge. In the following study, we propose a new bridging approach based on remove-restore technique combined with an autoregressive model (AR); the latter is utilized for residuals. The residuals are obtained as differences between GRACE/GRACE-FO data and climatology defined by Total Water Storage (TWS) parameter for Global Land Data Assimilation System (GLDAS) hydrological model. Residual annual sine-curve and its 3 overtones are then subtracted with the use of Least Squares Estimation (LSE) method. We predict missing TWS values using backward-forward AR approach. We conduct the TWS forecasting in two stages: (1) based only on the values before the gap (forward approach) and (2) the values available after the gap (backward approach). In our study, to test the adopted approach, we generate artificial 11 months gap. Comparing TWS values from our technique to values from original GRACE data in testing gap, we obtain differences within ±90 cm with median equal to -8 cm. The extreme values are observed in Amazon, Southern Asia or Alaska. The analysis of ratio between GRACE minus GLDAS and GRACE minus predicted values shows that our approach is better than the hydrological model standalone for more than 70% of continental areas. In the case of natural gap between both GRACE generation mission, the misclosures in backward-forward prediction calculated between TWS values predicted by forward and backward approach is 10 cm. This represents approximately 20% of total signal for observed TWS in 53% areas of the World. The presentation will include a discussion on regional analysis upon the areas characterized with extreme water changes occurred in natural observation gap. Analysis shows that presented method is able to capture the occurrence of droughts or floods, but does not reflect its magnitude. The obtained results indicate that presented remove-restore AR approach can be utilized to forecast geophysical changes much better for regions characterized with insignificant seasonal hydrological effect.

How to cite: Lenczuk, A., Klos, A., Weigelt, M., Kosek, W., Mikocki, J., and Bogusz, J.: Bridging GRACE and GRACE Follow-On TWS gap using forward-backward autoregressive model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-111,, 2022.