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Hydrological mass changes inferred from high-low satellite- to-satellite tracking data Tonie van Dam, Matthias Weigelt Mohammad J. Tourian Nico Sneeuw.

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Presentation on theme: "Hydrological mass changes inferred from high-low satellite- to-satellite tracking data Tonie van Dam, Matthias Weigelt Mohammad J. Tourian Nico Sneeuw."— Presentation transcript:

1 Hydrological mass changes inferred from high-low satellite- to-satellite tracking data Tonie van Dam, Matthias Weigelt Mohammad J. Tourian Nico Sneeuw Adrian Jäggi Lars Prange

2 GRACE und GRACE Follow-On (GFO) 2 Low-low © CSR Texas K-Band (Laser) GPS Accelerometer ~ 4-5 year data gap (?) year

3 Other gravity field missions 3 High-low GOCE © ESA © EADS Astrium SWARM year

4 CHAMP

5 CHAMP reprocessing Prange 2010 10 s sampling empirical absolute antenna phase center model GPS positions: Postprocessing with a Kalman filter: acceleration approach no accelerometer data used no regularization and no a priori model / information Approach: Kalman filtering (Davis et al. 2012) Prediction model Process noise Trend + mean annual signal Time series K lm Filtered time series

6 Filtered monthly gravity field solution

7 CHAMP vs. GRACE CHAMP: GRACE: 1400km

8 CHAMP vs. GRACE CHAMP: GRACE: 1400km CHAMP: GRACE: 1000km

9 CHAMP vs. GRACE CHAMP: GRACE: 1400km CHAMP: GRACE: 1000km CHAMP: GRACE: 750km

10 CHAMP vs. GRACE CHAMP: GRACE: 1400km CHAMP: GRACE: 1000km CHAMP: GRACE: 750km CHAMP: GRACE: 500km

11 CHAMP vs. GRACE CHAMP: GRACE: 1400km CHAMP: GRACE: 1000km CHAMP: GRACE: 750km CHAMP: GRACE: 500km CHAMP: GRACE: 750km

12 CHAMP vs. GRACE CHAMP: GRACE: 1400km CHAMP: GRACE: 1000km CHAMP: GRACE: 750km CHAMP: GRACE: 500km CHAMP: GRACE: 750km CHAMP: GRACE: 750km

13 EVALUATION WITH HYDRO- METEOROLOGY

14 Mass change as a hydrological observable 14 Balance P=precipitation ET a =evapo- transpiration R=runoff = divergence of vertically integrated moisture flux CHAMP GRACE

15 Mass estimate & correlation – 750km

16 Mass estimate & correlation – 450km

17 “Optimal” filter radius is catchment and signal dependent (see Tourian 2013)

18 EVALUATION WITH GPS

19 Loading analysis - Amazon 750 km CHAMP GRACE 450 km

20 Loading analysis - Amazon 750 km CHAMP GRACE 450 km GPS GRACE CHAMP [mm] year Surface displacement - 450 km

21 Loading analysis – South Africa 750 km CHAMP GRACE 450 km

22 Loading analysis – South Africa 750 km CHAMP GRACE 450 km GPS CHAMP GRACE Surface displacement - 450 km [mm] year

23 Loading analysis – East Asia CHAMP GRACE 750 km 450 km

24 Loading analysis – East Asia CHAMP GRACE 750 km 450 km Surface displacement - 450 km [mm] year GRACE CHAMP GPS

25 SUMMARY

26 Summary Time variable gravity field from high-low SST Long wavelength features Refinement in the processing possible/necessary –Spatial error pattern needs to be understood Filter dependency on catchment and application –Processing might include a beneficial smoothing! Remarkable agreement with hydro-meteorology and GPS SWARM? GOCE?

27 SUMMARY

28 BACKUP

29 Filter size for Amazon basin

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