We combine the publicly available GRACE monthly gravity field time series to produce gravity fields with reduced systematic errors. We first compare the monthly gravity fields in the spatial domain in terms of signal and noise. Then, we combine the individual gravity fields with comparable signal content, but diverse noise characteristics. We test five different weighting schemes: equal weights, non-iterative coefficient-wise, order-wise, or field-wise weights, and iterative field-wise weights applying variance component estimation (VCE). The combined solutions are evaluated in terms of signal and noise in the spectral and spatial domains. Compared to the individual contributions, they in general show lower noise. In case the noise characte...
We present a new stochastic filter technique for statistically rigorous separation of gravity signal...
The Gravity Recovery and Climate Experiment (GRACE) mission can significantly improve our knowledge ...
AbstractThe Gravity Recovery and Climate Experiment (GRACE) mission can significantly improve our kn...
A large number of time-series of monthly gravity fields derived from GRACE data provide users with a...
In the frame of the European Gravity Service for Improved Emergency Management (EGSIEM), a prototype...
The Gravity Recovery And Climate Experiment (GRACE) mission has achieved a quantum leap in knowledge...
In this contribution we present gravity field monthly solutions from GRACE Follow-On (GRACE-FO) Leve...
Time-variable gravity field models derived from observations of the Gravity Recovery and Climate Exp...
The satellite missions GRACE and GRACE-FO, dedicated to the observation of the time-variable Earth g...
The Swarm satellite constellation?s GPS receivers provide valuable gravimetric data, with which it ...
Time-variable gravity field models derived from observations of the Gravity Recovery and Climate Exp...
With the release of the combined GRACE monthly gravity field time-series COST-G RL01 the Combination...
COST-G is the new combination service for time-variable gravity field solutions of the International...
Although the knowledge of the gravity of the Earth has improved considerably with CHAMP, GRACE, and ...
The new release AIUB-RL02 of monthly gravity models from GRACE GPS and K-Band range-rate data is bas...
We present a new stochastic filter technique for statistically rigorous separation of gravity signal...
The Gravity Recovery and Climate Experiment (GRACE) mission can significantly improve our knowledge ...
AbstractThe Gravity Recovery and Climate Experiment (GRACE) mission can significantly improve our kn...
A large number of time-series of monthly gravity fields derived from GRACE data provide users with a...
In the frame of the European Gravity Service for Improved Emergency Management (EGSIEM), a prototype...
The Gravity Recovery And Climate Experiment (GRACE) mission has achieved a quantum leap in knowledge...
In this contribution we present gravity field monthly solutions from GRACE Follow-On (GRACE-FO) Leve...
Time-variable gravity field models derived from observations of the Gravity Recovery and Climate Exp...
The satellite missions GRACE and GRACE-FO, dedicated to the observation of the time-variable Earth g...
The Swarm satellite constellation?s GPS receivers provide valuable gravimetric data, with which it ...
Time-variable gravity field models derived from observations of the Gravity Recovery and Climate Exp...
With the release of the combined GRACE monthly gravity field time-series COST-G RL01 the Combination...
COST-G is the new combination service for time-variable gravity field solutions of the International...
Although the knowledge of the gravity of the Earth has improved considerably with CHAMP, GRACE, and ...
The new release AIUB-RL02 of monthly gravity models from GRACE GPS and K-Band range-rate data is bas...
We present a new stochastic filter technique for statistically rigorous separation of gravity signal...
The Gravity Recovery and Climate Experiment (GRACE) mission can significantly improve our knowledge ...
AbstractThe Gravity Recovery and Climate Experiment (GRACE) mission can significantly improve our kn...