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Consistent combination of geodetic and geophysical Earth rotation information

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In current official low-latency Earth Rotation Parameter (ERP) products of the International Earth Rotation and Reference Systems Service (IERS), only geodetic data is used. For ERP predictions, deterministic signals and long-term trends of geodetic time series are combined with geophysical (Effective angular momentum; EAM) data. Consequently, the transition between the combined (geodetic) and predicted ERPs (prediction day zero) is connected to an abrupt change in input data yielding inconsistencies between the two parts of the time series. Most notably, the gradients of the predicted ERPs differ with respect to the geodetic ERPs.In our study, carried out within the framework of a DFG-funded project between DGFI-TUM, GFZ and TUM named PROGRESS (Pro- and Retrospective highly accurate and consistent Earth Orientation parameters for Geodetic Research within the Earth System Sciences), we developed an alternative approach that directly combines geodetic and geophysical ERP information to achieve a consistent and continuously differentiable time series. To achieve this goal, the last days of the ERP combination include EAM-based ERP information with increasing relative weight with respect to the geodetic ERP information (and vice-versa). To improve the information provided by space-geodetic techniques, systematic biases are studied in detail such as the impact of different satellite constellations and solar radiation pressure models on the determination of GNSS LOD biases.
Title: Consistent combination of geodetic and geophysical Earth rotation information
Description:
In current official low-latency Earth Rotation Parameter (ERP) products of the International Earth Rotation and Reference Systems Service (IERS), only geodetic data is used.
For ERP predictions, deterministic signals and long-term trends of geodetic time series are combined with geophysical (Effective angular momentum; EAM) data.
Consequently, the transition between the combined (geodetic) and predicted ERPs (prediction day zero) is connected to an abrupt change in input data yielding inconsistencies between the two parts of the time series.
Most notably, the gradients of the predicted ERPs differ with respect to the geodetic ERPs.
In our study, carried out within the framework of a DFG-funded project between DGFI-TUM, GFZ and TUM named PROGRESS (Pro- and Retrospective highly accurate and consistent Earth Orientation parameters for Geodetic Research within the Earth System Sciences), we developed an alternative approach that directly combines geodetic and geophysical ERP information to achieve a consistent and continuously differentiable time series.
To achieve this goal, the last days of the ERP combination include EAM-based ERP information with increasing relative weight with respect to the geodetic ERP information (and vice-versa).
To improve the information provided by space-geodetic techniques, systematic biases are studied in detail such as the impact of different satellite constellations and solar radiation pressure models on the determination of GNSS LOD biases.

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