Detect Water Storage by Swarm: Comparison
Please note this is a comparison between Version 1 by Kunjun Tian and Version 2 by Amina Yu.

The Gravity Recovery and Climate Experiment (GRACE) satellite provides time-varying gravity field models that can detect total water storage change (TWSC) from April 2002 to June 2017, and its second-generation satellite, GRACE Follow-On (GRACE-FO), provides models from June 2018, so there is a one year gap. Swarm satellites are equipped with Global Positioning System (GPS) receivers, which can be used to recover the Earth’s time-varying gravitational field. Swarm’s time-varying gravitational field models (from December 2013 to June 2018) were solved by the International Combination Service for Time-variable Gravity Field Solutions (COST-G) and the Astronomical Institute of the Czech Academy of Sciences (ASI). On a timely scale, Swarm has the potential to fill the gap between the two generations of GRACE satellites. 

  • Swarm
  • GRACE follow on
  • gap
  • TWSC
  • global basins

1. Introduction

The Gravity Recovery and Climate Experiment (GRACE) satellite is the first satellite mission dedicated to Earth gravity sounding, launched by the National Aeronautics and Space Administration (NASA) and the German Aerospace Center (DLR). In the decade since its launch in March 2002, GRACE has been widely used to detect Earth-mass transport, including total water storage change (TWSC) [1][2][1,2], changes in the Antarctic and Greenland ice caps [3][4][3,4], and global sea-level changes [5][6][5,6], making important contributions to Earth science-related research and functioning as an important tool for estimating changes in terrestrial water reserves. However, in September 2017, one of the batteries in the GRACE-2 satellite failed, and its mission was successfully ended in mid-October 2017 [7][8][7,8]. Now, the GRACE time-varying gravity field model provided by the three major international centers, the Jet Propulsion Laboratory (JPL), the University of Texas Space Research Institute (CSR), and the German Geosciences Research Center (GFZ), is currently up to date only as of June 2017. The successor to the GRACE mission, GRACE Follow-On (GRACE-FO), was successfully launched on 22 May 2018 in California, USA, and its measurement principle is similar to that of GRACE, so its model can be used to continue the study of TWSC. However, the GRACE-FO time-varying gravity field model data are now published from June 2018, which means that there is a one-year gap between GRACE and GRACE-FO, so, valid and reliable data need to be found to fill this gap and ensure the consistency of the time-varying gravity field information time series.
On 22 November 2013, the European Space Agency (ESA) successfully launched an Earth observation satellite constellation, Swarm, consisting of three satellites, similar to the Challenging Mini-satellite Payload (CHAMP) mission. Although its mission is mainly to monitor the Earth’s magnetic field variations, it can also be applied to study the time-varying gravity field because it carries high-precision Global Navigation Satellite System (GNSS) receivers and other key gravity detection equipment, thus filling the observation gap between GRACE and GRACE-FO [9]. The published Swarm time-varying gravity field models are the model from December 2013 to June 2019, solved by COST-G, and the model from December 2013 to October 2018, solved by ASI. The Swarm of both institutions allows the continuity of GRACE and GRACE-FO observations on a time scale, so it is particularly important to determine the feasibility and effectiveness of the Swarm-based model to recover changes in terrestrial water storage. In recent years, several scholars have used the Swarm time-varying gravity field model to detect water storage changes in basins. Lück et al. (2018) studied the possibility of Swarm bridging GRACE and GRACE-FO, and the possibility of using Swarm time-varying gravity field with significantly lower resolution to replace GRACE time-varying gravity field in missing months [10]. Meyer et al. (2019) provided a long-term time series of monthly gravity field solutions by combining laser satellite data, GPS and K/Ka band observations of GRACE mission and GPS observations of three Swarm satellites. In their study, the lunar gravity field from Swarm was used to fill the gap between GRACE and GRACE-FO tasks [11]. Li et al. (2019) used the Swarm time-varying gravity field to estimate terrestrial water storage changes in the Amazon Basin and the water storage deficit caused by the 2015/2016 drought event. Comparing GRACE data, hydrological models, and hydrological station data, they found that the Swarm results were in good agreement with GRACE, hydrological models, and virtual hydrological station estimates, providing a new and effective way to detect terrestrial water storage changes and drought events. It also has the potential to replace the GRACE satellite to detect extreme droughts and floods in the Amazon basin [12]. Cui et al. (2020) compared Swarm with the GRACE/GRACE-FO models in terms of model accuracy, observation noise, and inverted TWSC and the results verified that Swarm time-variable gravity field has the potential to extract TWSC signals in the Amazon River Basin and can serve as a complement to GRACE/GRACE-FO data for detecting TWSC in local areas [13]. Forootan et al. (2020) applied time-variable gravity fields (2013 onward) from the Swarm Earth explorer mission with a low spatial resolution of ∼1500 km. A novel iterative reconstruction approach was formulated based on independent component analysis (ICA) combining GRACE and Swarm fields. The reconstructed TWSC fields of 2003–2018 were compared with a commonly applied reconstruction technique and GRACE-FO TWSC fields, and the results indicated considerable noise reduction and improved long-term consistency of the iterative ICA reconstruction technique. These models were applied to evaluate trends and seasonal mass changes (for 2003–2018) within the world’s 33 largest river basins [14]. However, all the research does not define the best Swarm data processing and does not estimate the potential of Swarm worldly. Therefore, how to preserve the original Swarm signal as much as possible and how to better detect water storage changes in more basins will be the focus of ongoing Swarm-based research.
This paper targets 26 regions worldwide (see Figure 1 and Table 1) and explores regional water storage change time series between December 2013 and June 2017 from two institutions (ASI and COST-G) under different treatment strategies by computing the results of GRACE (GRACE-TWSC) and comparing them with the limits of Swarm in water storage detection and the optimal processing strategy. Finally, the TWSC of the Amazon, Volga, and Zambezi Basins is constructed to demonstrate the potential of Swarm to fill the gap between the two generations of GRACE missions.
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