Thu Aug 14, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Wu, Yi, Yang, Fan, Liu, Shuhao, and Forootan, Ehsan, 2025. PyHawk: An efficient gravity recovery solver for low–low satellite-to-satellite tracking gravity missions. Computers and Geosciences, 201:105934, doi:10.1016/j.cageo.2025.105934.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025CG....20105934W,
author = {{Wu}, Yi and {Yang}, Fan and {Liu}, Shuhao and {Forootan}, Ehsan},
title = "{PyHawk: An efficient gravity recovery solver for low{\textendash}low satellite-to-satellite tracking gravity missions}",
journal = {Computers and Geosciences},
keywords = {GRACE(-FO), Python toolbox, Gravity recovery, Orbit determination, Level-2 gravity solutions, Low{\textendash}low satellite-to-satellite tracking},
year = 2025,
month = jul,
volume = {201},
eid = {105934},
pages = {105934},
abstract = "{The low{\textendash}low satellite-to-satellite tracking (LL-SST) gravity
missions, such as the Gravity Recovery and Climate Experiment
(GRACE) and its Follow-On (GRACE-FO), provide an important
space-based Essential Climate Variable (ECV) to measure changes
in the Terrestrial Water Storage (TWS). Due to the high-
precision Global Navigation Satellite System (GNSS) receiver,
accelerometers, and inter-satellite ranging instrument, these
LL-SST missions are able to sense extremely tiny perturbations
on both the orbit and inter-satellite ranges, which can project
into the Earth's time-variable gravity fields. The measurement
systems of these LL-SST missions are highly complex; therefore,
a data processing chain is required to exploit the potential of
their high-precision measurements, which challenges both general
and expert users. In this study, we present an open-source,
user-friendly, cross-platform and integrated toolbox ``PyHawk'',
which is the first Python-based software in relevant field, to
address the complete data processing chain of LL-SST missions
including GRACE, GRACE-FO and probably the future gravity
missions. This toolbox provides non-expert users an easy access
to the payload data pre-processing, background force modeling,
orbit integration, ranging calibration, as well as the ability
for temporal gravity field recovery using LL-SST measurements.
In addition, a series of high-standard benchmark tests have been
provided to evaluate PyHawk, confirming its performance to be
comparable with those used to provide the official Level-2 time-
variable gravity field solutions of GRACE. Researchers working
with orbit determination and gravity field modeling can benefit
from this toolbox.}",
doi = {10.1016/j.cageo.2025.105934},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025CG....20105934W},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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