Lake level variations from satellite radar altimetry with retracking of multi-leading edge

Transcription

1 Lake level variations from satellite radar altimetry with retracking of multi-leading edge Shirzad Roohi and Nico Sneeuw University of Stuttgart, Germany Institute of Geodesy Geodätische Woche, Essen, Germany 2013

2 Why waveform retracking? Improve the quality of water level measurements Increase the number of reliable observations particularly in the shoreline and shallow water 38.4 Sub satellite points Water level time series and fitting the trend to the all values Ascending tracks Ascending tracks tracks 178 Latitude [deg] In situ Gauge Descending tracks Residual = 42 cm Descending tracks tracks Longitude [deg] Residual = 83 cm Lake level variations from satellite radar altimetry with retracking of multi-leading edge 1

3 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 2 RADAR principle

4 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 3 How can we have more precise water level measurements? Increasing precision of range measurements Use more precise range correction, e.g. corrections included in GDRs waveform retracking, i.e. calculate another range correction from SGDRs R retracking = (G r G 0 ) c 2 τ G r : retracked gate, G 0 : nominal retracking gate, c: light velocity, τ: pulse duration

5 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 4 Waveform retracking techniques Conventional retrackers Onboard retracker (Ice-1/2 and Sea-ice) Offset Center Of Gravity (OCOG) Threshold β- parameters Unconventional retrackers Multi-leading edge Modified waveform

6 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 5 Data and area of study RA2 Geophysical and Sensor Data Records, i.e. RA2 GDRs and RA2 SGDRs of Envisat satellite altimetry from cycle 6 to cycle 113 Envisat satellite ground tracks from cycle 92

7 Conventional retrackers Onboard retrackers: Water level from RA2 GDRs data using median values of water level in each satellite over pass in Ice-1 retracker algorithm Water level from median values of all satellite tracks and fitting a trend Residual = 27 cm ) ) h(t i ) = a + bt i + ct 2 i + dsin ( 2π T t i + ecos( 2π T t i a, b, c, d and e are unknown parameters to be estimated. T is the annual period and h is the observed water height. Lake level variations from satellite radar altimetry with retracking of multi-leading edge 6

8 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 7 Conventional retrackers OCOG Threshold Water level time series from combined ascending and descending tracks 1275 Water level time series from combined ascending and descending tracks Residual = 27 cm.5 Residual = 15 cm

9 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 8 Unconventional retrackers Multi-leading edge Power Gate

10 Unconventional retrackers Multi-leading edge Water level time series from combined ascending and descending tracks Residual = 14 cm Lake level variations from satellite radar altimetry with retracking of multi-leading edge 9

11 Comparing different retrackers Onboard retracker Other retrackers Water level time series and fitting the trend to the all values Water level time series based on Threshold 10 % retracker Ascending tracks Ascending tracks Ascending track Ascending track Residual = 42 cm Residual = 59 cm Descending tracks Descending tracks Descending track Dscending track Residual = 83 cm Residual = 74 cm Lake level variations from satellite radar altimetry with retracking of multi-leading edge 10

12 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 11 Comparing different retrackers Water level standard deviation from different retrackers retracker standard deviation (cm) improvement Ice-1 27 OCOG 27 0 % Threshold % Threshold % Threshold % Multi-leading edge % Improvement = σ Ice 1 σ Ret σ Ice %

13 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 12 Along track waveform variations First ascending pass-jun 2002 Last ascending pass- Sep 2010 x Gate Gate Latitude [deg] Latitude [deg] 0

14 Validation OCOG Threshold Water level anomaly from satellite and in situ gauge measurements Satellite In situ gauge Water level anomaly from satellite and in situ gauge measurements Satellite In situ gauge Water level anomaly [m] Water level anomaly [m] RMS = 41 cm RMS = 23 cm Lake level variations from satellite radar altimetry with retracking of multi-leading edge 13

15 Validation Multi-leading edge Water level anomaly from satellite and in situ gauge measurements Satellite In situ gauge 0.2 Water level anomaly [m] RMS = 26 cm Lake level variations from satellite radar altimetry with retracking of multi-leading edge 14

16 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 15 Conclusion Obviously waveform retracking techniques can improve the quality of altimetry data. Due to the land and environmental effects on the return echoes to the altimeter particularly in the shoreline the waveform retracking is necessary. The quality of water level is dependent on the waveform retracking techniques. According to the result of data processing using both RA2 GDR and RA2 MWS (SGDRs) of Envisat, multi-leading edge and threshold 20 % retrackers outperform the other retackers to determine water level variations of Urmia lake.

17 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 16 Works under way Continuing waveform retracking using: β parameter Modified waveform

18 Thank you for your attention Lake level variations from satellite radar altimetry with retracking of multi-leading edge 17

19 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 18 References F. Frappart, S. Calmant, M. Cauhopé, F. Seyler and A. Cazenave, 2006, Preliminary results of Envisat RA-2 derived water levels validation over the Amazon basin. Remote sensing of environment 100, 2, G. J. Yun, C. Xiaotao, G. Y. Gang, S.Jialong and H. C. Way, 2009, Lake level variations monitored with satellite altimetry waveform retracking, Ieee journal of selected topics in applied earth observations and remote sensing, 2, 2, G. J. Yun, G. Y. Gang, H. C. Way, and S. J. Long, 2009, A multi-subwaveform parametric retracker of the radar satellite altimetric waveform and recovery of gravity anomalies over coastal oceans, Science China, Earth Sciences, 53, 4, G. J. Yun, H. C. Way, C. Xiaotao and L. Yuting, 2006, Improved threshold retracker for satellite altimeter waveform retracking over coastal sea, Progress in natural science, 16, 7.

20 Lake level variations from satellite radar altimetry with retracking of multi-leading edge 19 References H. Lee, C.K. Shum, K. H. Tseng, J. Y. Guo and C. Y. Kuo, 2010, Present-day lake level variation from Envisat altimetry over the northeastern Qinghai-Tibetan plateau: links with precipitation and temperature, Terr. Atmos. Ocean. Sci 22, 2, J. F. Crétaux and C. Birkett, 2006, Lake study from satellite radar altimetry, International Geophysics (Applied Geophysics) 338, 14, J. S. Silva, S. Calmant, F. Seyler, O. Corrêa, R. Filho, G. Cochonneau and W. J. Mansur, 2010, Water levels in the Amazon basin derived from the ERS 2 and Envisat radar altimetry missions, Remote sensing of environment 114, 10, Y. Yuchan, A. V. Kouraev, C.K. Shum, V. S. Vuglinsky, J. F. Crétaux and S. Calmanti, 2012, The performance of altimetry retrackers at lake Baikal, Terr. Atmos. Ocean. Sci 24, 4.