Abstract
Within the EGSIEM (European Gravity Service for Improved Emergency Management) project, a demonstrator
for a near real-time (NRT) gravity field service which provides daily GRACE gravity field solutions will be
established. Compared to the official GRACE gravity products, these NRT solutions will increase the temporal
resolution from one month to one day and reduce the latency from currently two months to five days. This fast
availability allows the monitoring of total water storage variations and of hydrological extreme events as they
occur, in contrast to a ‘confirmation after occurrence’ as is the situation today. The service will be jointly run by
GFZ (German Research Centre for Geosciences) and Graz University of Technology, with each analysis center
providing an independent solution. A Kalman filter framework, in which GRACE data is combined with prior
information, serves as basis for the gravity field recovery in order to increase the redundancy of the gravity
field estimates. The on-line nature of the NRT service necessitates a tailored smoothing algorithm as opposed to
post-processing applications, where forward-backward smoothing can be applied.
This contribution gives an overview on the near real-time processing chain and highlights differences between
the computed NRT solutions and the standard GRACE products. We discuss the special characteristics of the
Kalman filtered gravity field models as well as derived products and give an estimate of the expected error
levels. Additionally, we show the added value of the NRT solutions through comparison of the first results of the
pre-operational phase with in-situ data and monthly GRACE gravity field models.
for a near real-time (NRT) gravity field service which provides daily GRACE gravity field solutions will be
established. Compared to the official GRACE gravity products, these NRT solutions will increase the temporal
resolution from one month to one day and reduce the latency from currently two months to five days. This fast
availability allows the monitoring of total water storage variations and of hydrological extreme events as they
occur, in contrast to a ‘confirmation after occurrence’ as is the situation today. The service will be jointly run by
GFZ (German Research Centre for Geosciences) and Graz University of Technology, with each analysis center
providing an independent solution. A Kalman filter framework, in which GRACE data is combined with prior
information, serves as basis for the gravity field recovery in order to increase the redundancy of the gravity
field estimates. The on-line nature of the NRT service necessitates a tailored smoothing algorithm as opposed to
post-processing applications, where forward-backward smoothing can be applied.
This contribution gives an overview on the near real-time processing chain and highlights differences between
the computed NRT solutions and the standard GRACE products. We discuss the special characteristics of the
Kalman filtered gravity field models as well as derived products and give an estimate of the expected error
levels. Additionally, we show the added value of the NRT solutions through comparison of the first results of the
pre-operational phase with in-situ data and monthly GRACE gravity field models.
| Original language | English |
|---|---|
| Publication status | Published - 18 Apr 2016 |
| Event | European Geosciences Union General Assembly 2016: EGU 2016 - Wien, Austria Duration: 17 Apr 2016 → 22 Apr 2016 http://meetingorganizer.copernicus.org/EGU2016/EGU2016-13356-1.pdf http://meetingorganizer.copernicus.org/EGU2016/orals/20327 |
Conference
| Conference | European Geosciences Union General Assembly 2016 |
|---|---|
| Country/Territory | Austria |
| City | Wien |
| Period | 17/04/16 → 22/04/16 |
| Internet address |
Keywords
- GRACE
- near real-time
- time variable gravity field
Fields of Expertise
- Sustainable Systems