Lecture: Inland Altimetry I

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1 Lecture: Inland Altimetry I Denise Dettmering (with contributions from W.Bosch, C.Schwatke, and E. Börgens) 1 Deutsches Geodätisches Forschungsinstitut (DGFI) München, Germany dettmering@dgfi.badw.de Summer School GRACE/GRACE-FO applications for the terrestrial water cycle September 2014 Mayschoss

2 Contents 1) Introduction to Satellite Altimetry Basis Principle of conventional radar altimetry Corrections Missions Groundtracks New and upcoming sensors 2 2) Inland Altimetry Waveforms Retracking Hooking Effect Accuracy 3) Data Bases for Altimetry Products for Inland Altimetry Products 4) Examples large lakes small lakes rivers

3 3 INTRODUCTION TO SATELLITE ALTIMETRY

4 Measurement principle of radar altimetry Fundamentals: Carrier frequency 13.5 GHz pulse width 12.5 ns pulse time delay 5 ms pulse repetition rate ~2000 Hz Averaging 0,05 s 4 Orbit height footprint velocity km 2-11 km ~ 6,7km/s

leading edge) 5 Energy (normalized) Radar echo (idealized) antenna damping Significant wave

5 Radar echo and analysis Altimeter Footprint (temporal evolution) Derived information: Distance to sea level / altimeter range from signal travel time (half-power point of leading edge) 5 Energy (normalized) Radar echo (idealized) antenna damping Significant wave height from slope of leading edge Waveform Backscatter coefficient Wind speed from total energy Time (ns)

6 Sea surface height Sea surface height = satellite height (corrected) range SSH = h sat r alt (- Σcorrections) 6 orbit r alt h sat SSH sea surface Ellipsoid

$observations doppler shift Error Atmospheric refraction (signal delay) due to Ionosphere [~3-5cm] Troposphere, dry component [~2.$

7 Corrections / error sources Orbit errors (radial component) [< 1 dm] Instrumental effects electronic time delay clock (oscillator) drift offset antenna phase center center of gravity time tagging of observations doppler shift Error Atmospheric refraction (signal delay) due to Ionosphere [~3-5cm] Troposphere, dry component [~2.3m ] Troposphere, wet component [~3-45cm] Target (ocean surface) ocean tides [m], loading [~10%] Earth tides [~3dm], pole tide [~1cm] electromagnetic bias (sea state, SSB) [~5% SWH] inverted barometer effect (IB) [up to 3 dm] 7

8 Altimeter mission overview 8 former missions: ERS-1, ERS-2, Envisat, TOPEX, Jason-1, GFO, ICESat active missions: Jason-2, Cryosat-2, HY-2A, SARAL

9 Altimetry Missions Main Characteristics Geosat 1) ERS-1 TOPEX 2) Poseidon Opearted by NOAA ESA CNES NASA Pulsewidth-limited altimeter systems New technologies ERS-2 GFO Jason-1 Envisat Jason-2 3) HY-2A ICESat Cryosat 4) Saral ESA US- Navy CNES NASA ESA CNES NASA NOOA EUMETSAT NSOAS NASA ESA ISRO CNES Launch 03/85 07/91 09/92 04/95 02/98 01/02 03/02 06/08 08/11 01/03 04/10 02/13 Acquisition until Mean height [km] 09/89 03/96 01/06 09/11 11/08 06/13 04/12 ongoing ongoing 10/09 ongoing ongoing Inclination [ ] Latitude coverage [ ] ± 72.0 ± 81.5 ± 66.0 ± ± 72.0 ± 66.0 ± ± 66.0 ± 80.7 ± 86.0 ± 88.0 ± Repeat cycle [days] Frequencies [GHz] wavelength /35/ & & & & 5.3 Laser: 1064 & 532nm Radiometer no Yes/2 Yes/2 Yes/3 Yes/2 Yes/3 Yes/2 Yes/3 Yes no no Yes/2 1) Geosat had two different mission phases: in addition to the characteristics given in the table, a geodetic mission (GM) with a non-repeat, drifting orbit 2) After the tandem configuration with Jason-1 (up to 08/02) the TOPEX orbit was shifted by the half track separation to double the spatial resolution of both missions. 3) After the tandem configuration with Jason-2 (up to 01/09) Jason-1 was shifted to double the spatial resolution of both missions. Since 05/12 Jason-1 was flying a geodetic orbit with a repeat cycle of 406 days. 4) Three different measurement modes: Pulsewidth limited, delay Doppler, and interferometric SAR

10 Orbits - Groundtracks Inclination => no measurements in polar regions Repeat cycle => same groundtrack after 10/35/ days (compromise between good spatial and temporal resolution) 11 Ground track of TOPEX / Jason-1 / Jason-2 10 day repeat cycle Track distance at equator: approx. 315 km Inclination: 66

spatial and temporal resolution) 12 Ground track of

11 Orbits - Groundtracks Inclination => no measurements in polar regions Repeat cycle => same groundtrack after 10/35/ days (compromise between good spatial and temporal resolution) 12 Ground track of ERS-1/ERS-2/ENVISAT/SARAL 35 day repeat cycle Track distance at equator: approx. 80 km Inclination: 98.55

12 Orbits - Groundtracks Inclination => no measurements in polar regions Repeat cycle => same groundtrack after 10/35/ days (compromise between good spatial and temporal resolution) 13 TOPEX / Jason-1 / Jason-2 10days ERS-1/ERS-2/ENVISAT/SARAL 35days

13 Orbits - Groundtracks 14 TOPEX / Jason-1 / Jason-2: 10 day repeat (315 km) ERS-1 / ERS-2 / Envisat / SARAL: 35 day repeat (80 km) Cryosat-2: 369 day repeat (8 km)

14 Multi-mission altimetry Combination of various altimeter missions in order to derive consistent and long-term (more than 20 years) time series Optimal temporal and spatial resolution Necessary processing steps: homogenization (e.g. consistent ocean tide corrections, ) actualization (latest and best orbits, reprocessed data sets, ) relative calibration of all missions by multi-mission cross-calibration (MMXO) Range bias with respect to TOPEX 15

New and upcoming sensors Conventional: nadir pointing, pulse-limited radar (Ku-band): GEOS-3 (1975-1979) to HY-2A (2011-?) Nadir pointing, pulse-limited radar (Ka-band): Saral/AltiKa (2013-?

15 New and upcoming sensors Conventional: nadir pointing, pulse-limited radar (Ku-band): GEOS-3 ( ) to HY-2A (2011-?) Nadir pointing, pulse-limited radar (Ka-band): Saral/AltiKa (2013-?) Laser altimeter: ICESat ( ), nadir-pointing (controllable) IceSAT-2 (planned for 2016), multi-beam approach Delay Doppler principle / SAR Cryosat-2 (2010-?), 3 different measurement modes (LRM, SAR, insar) Sentinel-3 (planned for 2015), SAR Wide-swath technology SWOT (planned for 2020) 16

SARAL/AltiKa Launch on 25/02/2013 Altitude ~800 km Inclination 98.55 Repetitivity 35 days Agency ISRO/CNES 17 only one frequency: Ka-band: 0.

16 SARAL/AltiKa Launch on 25/02/2013 Altitude ~800 km Inclination Repetitivity 35 days Agency ISRO/CNES 17 only one frequency: Ka-band: 0.84 cm (Ku-band: 2.2 cm) 40 Hz data Smaller ionospheric influence Larger influence by rain Smaller footprint CNES Relevance for inland altimetry: smaller footprint higher PRF

IceSAT ICESat (2003-2009) Ice, Cloud,and land Elevation Satellite Geoscience Laser Altimeter System (GLAS) Nadir-pointed laser altimeter; spacecraft enables off-nadir pointing capability Laser pulses

17 IceSAT ICESat ( ) Ice, Cloud,and land Elevation Satellite Geoscience Laser Altimeter System (GLAS) Nadir-pointed laser altimeter; spacecraft enables off-nadir pointing capability Laser pulses at 1064 and 532 nm wavelengths (40Hz) Backscattered light in the green (532 nanometers) is used for measurement of aerosols and other atmospheric characteristics. 3 lasers but only one operates at any given time provided multi-year elevation data (normally 3 times per year for about 1 month) NASA Relevance for inland altimetry: Very small footprint (~70m) Along-track resolution: ~170m Not continuously 18

IceSAT-2 Advanced Topographic Laser Altimeter System (ATLAS) visible, green laser pulses at a wavelength of 532 nm Laser is split into 6 beams, arranged in 3 pairs, with 3.

18 IceSAT-2 Advanced Topographic Laser Altimeter System (ATLAS) visible, green laser pulses at a wavelength of 532 nm Laser is split into 6 beams, arranged in 3 pairs, with 3.3 km between the pairs Fire at a rate of 10 khz - 10,000 times per second Launch scheduled for Differences to ICESat ( ): micro-pulse, multi-beam approach provides dense cross-track sampling Determination of surface's slope possible NASA

Cryosat-2 Mission dedicated to ice applications; but also fine for ocean and inland waters Three different measurement modes: 1) LRM Low Resolution

19 Cryosat-2 Mission dedicated to ice applications; but also fine for ocean and inland waters Three different measurement modes: 1) LRM Low Resolution Mode; conventional pulse-limited approach 2) SAR Synthetic Aperture Radar; Delay Doppler approach 3) insar interferometric SAR Geographical Mode Mask: 20 ESA

SAR - Synthetic Aperture Radar Burst of pulses will be send: Interval between transmitted pulses reduced from 500 μs (conventional radar altimeter) to 50 μs returning echoes are correlated treating

20 SAR - Synthetic Aperture Radar Burst of pulses will be send: Interval between transmitted pulses reduced from 500 μs (conventional radar altimeter) to 50 μs returning echoes are correlated treating the whole burst at once slight frequency shifts in the forward- and aft-looking parts of the beam (Doppler effect) separate the echo into strips arranged across the track Strip width: about 250 m 21

21 SAR mode 22 From: Credits: R.K. Raney, Johns Hopkins (University Applied Physics Laboratory)

22 insar interferometric SAR Cryosat-2 has two antennae: Detect echos coming from points not directly beneath the satellite Difference in the path-length of the radar wave will be measured Arrival angle can be computed 23

23 Sentinel-3 Mission Payload: Ku-/C-band Synthetic Aperture Radar Altimeter (SRAL) MicroWave Radiometer (Bifrequency) GNSS Receiver DORIS Laser Retro-Reflector 24 planned for 2015 SAR mode for all areas! ESA

SWOT (planned for 2020) Payload: KaRIn, altimeterinterferometer (large-swath) in Ka-Band Measurements over a 120 km wide swath with a +/- 10 km gap at the nadir track Cover at least 90 percent of the

24 SWOT (planned for 2020) Payload: KaRIn, altimeterinterferometer (large-swath) in Ka-Band Measurements over a 120 km wide swath with a +/- 10 km gap at the nadir track Cover at least 90 percent of the globe. Gaps are not to exceed 10 percent of Earth's surface. 25 Will be able to resolve 100 meter wide rivers and lakes of 250 m² in size. water level elevations with an expected accuracy of 10 cm and a slope accuracy of 1 cm/1 km

25 26 INLAND ALTIMETRY

26 Inland Altimetry special requirements Small targets => dense groundtrack pattern necessary => high-frequent data (18Hz, 20Hz, 40Hz) instead of 1Hz data => waveform classification as some/all waveforms may be contaminated by land => special retracking (land contamination) 27 Special care with some of the altimeter corrections => wet troposphere: radiometer rarely usable (land contamination) => dry troposphere: surface height not negligible => DAC/IB not necessary => ocean tides not necessary => SSB not applicable

27 Inland Altimetry special requirements Altimeter corrections for inland applications Ionospheric correction Wet troposphere correction Dry troposphere correction Earth tides Pol tides o no DAC/IB correction o no ocean tides o no SSB 28 All corrections are included in the altimeter data sets! Sometimes different solutions (e.g. from model and from measurements) are provided

28 Wet radiometer correction not usable for small inland bodies! Recent altimeter missions use a microwave radiometer to measure the radiation temperature and determine the water vapor (empirically) Problem: Radiometer footprint approx. 50 km Altimeter footprint about 2-10 km Near the coast (about 50 km) the radiometer measurement is disturbed due to the different radiation from land and water Wet tropospheric correction derived from radiometer is not usable near or at land ([cm] to [dm] error) 29 Solution: Use model correction for inland water applications

29 Dry radiometer correction attention when using former missions! Dry tropospheric correction strongly depends on the pressure, which is correlated to station height. Problem: In some older data sets the dry troposphere correction refers to the geoid This is no problem for ocean applications but may lead to strong errors on land (and inland waters) 30 Solution: Check for older mission data! Use external corrections for inland water applications

30 Waveform Analysis 31

31 Track direction island Waveform Analysis island 32 Brown linear - Ocean Brown exponential Coastal zone Brown peak Coastal zone Single peak - Land

32 Jason-2 Waveforms on Amazon river 33

33 Ocean versus non-ocean return Ocean like return Clear leading slope Slow decay of returns Tracking by half-power point of leading edge 34 Non-ocean radar echos Specular returns Often multiple returns Tracking e.g. by center of gravity A.Cazenave

34 Waveform Classification 35 Springer from: Gommenginger et al (2011)

35 Retracking of altimeter waveforms Retracking algorithms analyze waveforms to estimate parameters such as altimeter range, significant wave height, etc. Inland altimetry: focus on position of the leading edge (range); normally no interest in SWH or backscatter Retracking algorithms are optimized for different tasks e.g. MLE3 or Beta5 retracker work only on ocean-like waveforms => very accurate ranges e.g. OCOG or Improved Threshold retracker work on all waveforms => applicable to coastal zones and inland waters => noisy ranges Mixing of retracking algorithms lead to systematic offsets between retracked ranges No universal retracking algorithm available! 36

36 Beta5 Retracker Fit function to a single-ramped waveform with linear trailing edge (Zwally and Brenner, 2001) 37 b1:thermal noise level b2: return signal amplitude b3:midpoint onthe leading edge b4 : waveformrise time b5 : slope of trailing edge Springer from: Gommenginger et al (2011)

Beta5 Retracker - Examples measured waveform fitted function estimated epoch at mid-height 38 gives the time delay of the expected return of the radar

37 Beta5 Retracker - Examples measured waveform fitted function estimated epoch at mid-height 38 gives the time delay of the expected return of the radar pulse (estimated by the tracker algorithm) and thus the time the radar pulse took to travel the satellite-surface distance (or 'range') and back again

38 Offset Center of Gravity (OCOG) Retracker Find the center of gravity (COG); no function fitting 39 LEP: Leading Edge Position COG: Center of Gravity Springer from: Gommenginger et al (2011) P i : waveform power (i-the bin) N: total number of samples n1,n2: number of bins affected by aliasing at beginning/end of waveform (e.g. n1=4; n2=4)

39 OCOG Retracker - Examples 40

amplitude above the pre-leading edge thermal noise (DC) level 41 Davis (1997) suggests:

40 Threshold Retracker Find the leading edge by locating the first range bin to exceed a percentage of the maximum waveform amplitude.! Important: use max. amplitude above the pre-leading edge thermal noise (DC) level 41 Davis (1997) suggests: 50% threshold for surface-scattering dominated waveforms 10% or 20% threshold for volume-scattering surfaces

41 Range Estimation from Retrackers Main information from every retracking algorithm: leading edge position (LEP) What else has to be known: reference bin refbin (fixed) raw range (variable) binsize (fixed; normally about 3 ns) 42 retracked range = raw range + ((LEP refbin) * binsize * c / 2) ENVISAT Ku Jason-2 Ku Number of bins Reference bin Bin size ns ns

42 On-board retracker Today, most mission data sets contain more than one retracker working in parallel over all areas. This allows the user to choose the best-qualified range depending on the reflecting surface. On-board retrackers of Envisat RA2: 1) Ocean retracker: optimized for ocean surfaces; based on a modification of the Hayne model [Hayne, 1980] 2) Ice1 retracker: optimized for continental ice; OCOG retracker 3) Ice2 retracker: for ocean-like echos from continental ice sheets; fits a Brown-like model to the altimeter waveform 4) Sea-ice retracker: threshold retracker intended for use with data from sea ice, i.e. very specular or narrow-peaked echoes 43 In the practical you will have the chance to compare the performance of the different retrackers

measurement measured altimeter ranges are too long not only in flight

43 Hooking effect = off-nadir effect at land/water transitions main reflection coming from water which is not directly beneath the satellite off-nadir measurement measured altimeter ranges are too long not only in flight direction but also from cross-track targets 44 Elsevier from: Da Silva et al (2010)

44 Hooking effect Example of uncorrected off-nadir effect over Lake Malawi Jason-1 (radar) in blue and Icesat (laser) in red 45

(green) and Envisat (blue) for pass 0968 and 0650, respectively.

45 Hooking effect Example of uncorrected off-nadir effect over Lake Superior, US at the land water transition for all cycles of SARAL (green) and Envisat (blue) for pass 0968 and 0650, respectively. 46 land water from: Schwatke et al, 2014 (submitted to Marine Geodesy)

46 Land Contamination of Waveforms Amazon Basin, Rio Negro, near Manaus river width ~5 km Envisat pass 564 Waveforms 47 derived water heights Retracking may correct land influence visible in on-board ranges Land contamination Hooking effect

47 Accuracy of inland water level products Generally much lower than for sea level Strongly depends on the size of water target and on the measurement system (mainly on the footprint size) Normally data reprocessing is necessary in order to get reliable results 48 Accuracy is difficult to estimate as no truth is available for comparisons Measurement precision can be estimated from along track scatter In-situ measurements of gauges may be used for validation - but these are sparse

48 Comparison ENVISAT - Saral Both follow the same orbit and have the same ground track Saral has a smaller footprint (approx. 8km instead of 9-15 km) Saral has a higher data rate (40Hz/175m instead of 20 Hz / 375m) Example of uncorrected off-nadir effect over Lake Superior, US at the land water transition for one cycle of SARAL (green) and Envisat (blue) of pass 0968 and 0650, respectively (optimal case) 49 Land contamination Hooking effect land water from: Schwatke et al, 2014 (submitted to Marine Geodesy)

49 Accuracy of inland water level products Example: Great Lakes (US) RMS with respect to in-situ measurements from tide gauge 50 => a few centimeters! from: Schwatke et al, 2014 (submitted to Marine Geodesy)

50 Accuracy of inland water level products Example: Amazon basin 51 => dm to m accuracy! from: Schwatke et al, 2014 (submitted to Marine Geodesy)

51 52 DATA BASES

52 Data bases original data sets No single point of contact and various data formats! NOAA (GFO) ESA (ESA missions: ERS, Envisat, Cryosat) NSIDC (IceSat) AVISO (various missions) PODAAC (various missions) RADS (various missions) OpenADB (various missions) 53 Different Data Types (for most missions): GDR: Geophysical Data Record IGDR: Interim GDR => available after some days (preliminary orbit and corrections) OGDR: operational GDR => near real-time (on-board orbit and corrections) SGDR: Sensor GDR => include additional information, e.g. waveforms

53 Data bases original data sets - Mission information Mission information (non-exclusive list): CryoSat: Envisat: ERS-1/2: GFO: IceSAT: HY-2A: Jason-1: Jason-2 (OSTM): Saral: TOPEX/Poseidon: 54

54 Providers of value-added altimeter data (non-exclusive list!) AVISO Archiving, Validation and Interpretation of Satellite Oceanographic data Provides access to GDR and IGDR mission data of Topex/Poseidon, Jason-1, Jason-2, and Saral Sea surface height products (global and regional) from mono-mission and multi-mission data sets; gridded as well as along-track products Special products such as mean sea surface models (MSS) of (absolute) dynamic ocean topography (ADT or DOT), Ocean tide models (e.g. FES2012) Wind & wave data (wind speed and significant wave height) Auxiliary data and much more 55 Access free but subscription required

55 Providers of value-added altimeter data (non-exclusive list!) PO.DACC Physical Oceanography DAAC, JPL Provides access to TOPEX/Poseidon and Jason-1 mission data: GDR, IGDR, OGDR (binary coded; on behalf of NASA) Derived (gridded) ocean products based on various missions (sea surface topography, ocean circulation Historical data sets from GEOS-3 and Geosat 56

56 Providers of value-added altimeter data (non-exclusive list!) RADS Radar Altimeter Data Base System, DEOS An altimeter data base establishing harmonized, validated and crosscalibrated sea level data, developed and maintained by DEOS (Earth Oriented Space Research of the Delft Technical University) For GEOSAT, ERS-1, TOPEX, Poseidon, ERS-2, GFO, Jason-1, ENVISAT, Jason- 2, Cryosat, and Saral Most recent orbits, geophysical corrections and models are applied User can extract data with user defined options 57

57 Providers of value-added altimeter data (non-exclusive list!) Basic Radar Altimeter Toolbox (BRAT), ESA/CNES Software Toolbox (v3.1.0, March, 2020) read all altimetry mission data for ERS-1/2, Topex/Poseidon, GFO, Jason-1, Envisat, Jason-2 and Cryosat, (from SGDR to gridded merged data) do some processing and computations visualize the results 58 Includes A tutorial on altimetry and a mission overview Description of applications

58 Providers of value-added altimeter data (non-exclusive list!) Open Altimeter Data Base (OpenADB), DGFI Provides access to: Along track sea surface heights (SSH) and sea level anomalies (SLA) Mean sea level trend estimates Instantaneous Dynamic Ocean Topography Profiles (idot) Empirical Ocean Tide Model (EOT) Along track Vertical Total Electron Content (VTEC) DAHITI: Database for Hydrological Time Series of Inland Waters Additional information, such as mission overview, pass locator, 59

59 Data bases inland water products Different groups maintain data bases providing water level time series over river, lakes and wetlands using satellite altimetry Hydroweb Laboratoire d`etudes en Géophysique et Océanographie Spatiales (LEGOS) River and Lakes European Space Agency (ESA) Global Reservoir and Lake Monitor (GRLM) United States Department of Agriculture (USDA) Database for Hydrological Timeseries of Inland Waters (DAHITI) Deutsches Geodätisches Forschungsinstitut (DGFI) 60

Hydroweb (LEGOS) Products water levels, water storages Available time series about 100 over lakes about 250 over rivers Data Topex/Poseidon, ERS1/2, Envisat,

60 Hydroweb (LEGOS) Products water levels, water storages Available time series about 100 over lakes about 250 over rivers Data Topex/Poseidon, ERS1/2, Envisat, Jason-1, GFO Method Physical heights are estimated track-wise and corrected by the slope of the geoid Final time series are computed by merging altimeter data 61

River & Lakes (ESA) Products water levels Available time series 1227 over rivers/lakes Data Envisat Jason-2 (NRT) [ERS-2] Method Time series are estimated pass-wise

61 River & Lakes (ESA) Products water levels Available time series 1227 over rivers/lakes Data Envisat Jason-2 (NRT) [ERS-2] Method Time series are estimated pass-wise for each altimeter track crossing the lake or river. An expert system based on neural networks (including retracking) is used for processing water level time series. 62

Global Reservoir and Lake Monitor (GRLM) Products water levels Available time series 232 over lakes/reservoirs Data Topex, Jason-1, Jason-2, Envisat Method Time series of

62 Global Reservoir and Lake Monitor (GRLM) Products water levels Available time series 232 over lakes/reservoirs Data Topex, Jason-1, Jason-2, Envisat Method Time series of lakes and reservoirs are estimated by using parts of one single altimeter crossing per target Multi-mission altimeter data is used to extend the water level time series 63

DAHITI (DGFI) Products water levels Available time series 175 over lakes/rivers +142 (no public access) Data Envisat, Jason-1/2, Topex/Poseidon, Saral/Altika, Cryosat-2, GFO,

63 DAHITI (DGFI) Products water levels Available time series 175 over lakes/rivers +142 (no public access) Data Envisat, Jason-1/2, Topex/Poseidon, Saral/Altika, Cryosat-2, GFO, IceSAT, (HY-2A, ERS-1, ERS-2) Method Kalman-filter approach with classification and retracking of altimeter data Using multi-mission data of all available passes over the target 64

64 DAHITI (DGFI) DAHITI processing is based on: Using multi-mission altimeter data whenever available Provide absolute heights based on EIGEN 6C2 geoid (physical heights: where water will flow) Waveform classification by Support Vector Machine (SVM) Retracking of altimeter waveforms if necessary Outlier rejection by Support Vector Regression (SVR) Building a smooth space-time series by a Kalman Filter approach => Increasing temporal resolution of time series => Handling of data gaps with Laplace condition => Areal water level height estimation (not only along track) Minimization of errors due to geoid model and altimeter measurements 65

65 66 EXAMPLES

Lake Michigan (58,016 km²) Example I: Lake Michigan Mission Passes Jason-1 (1Hz) 041, 076, 219, 254 Jason-2 (1Hz) 041, 076, 219, 254 Topex (1Hz) 041, 076, 219, 254 Envisat (1Hz)

66 Lake Michigan (58,016 km²) Example I: Lake Michigan Mission Passes Jason-1 (1Hz) 041, 076, 219, 254 Jason-2 (1Hz) 041, 076, 219, 254 Topex (1Hz) 041, 076, 219, 254 Envisat (1Hz) 7, 338, 465, 551, 882, 923 Topex-EM (1Hz) 041, 076, 054 Jason1-EM (1Hz) 041, 076, 054 Comparison with gauge: Correlation: RMS: 6.2 cm altimetry gauge

Improvements of time series after retracking Jason-1 and Jason-2

67 Example II: Lake Chad Lake Chad (1,500 km²) Mission Passes Jason-1 (20Hz) 248 Jason-2 (20Hz) 248 Topex (10Hz) Improvements of time series after retracking Jason-1 and Jason-2 Mission Passes Jason-1 (20Hz)* 248 Jason-2 (20Hz)* 248 Topex (10Hz) 248 *retracked

68 Example III: Large Lakes in Africa 69

69 Example IV: Lake Sarygamysh Lake Sarygamysh East of Caspian Sea TOPEX/Jason, Envisat, GFO Long time series Only small seasonal variations Long-term trend visible m in 20 years

70 Example V: Aral Sea The water level of Aral Sea has dropped dramatically since the 1960s due to excessive water usage. 71 However, the effect is different for the three parts of the lake.

Example VI: Lake Kara-Bogaz-Gol Lake Kara-Bogaz-Gol Lagoon east of Caspian Sea TOPEX/Jason Long time series 1992-2014

71 Example VI: Lake Kara-Bogaz-Gol Lake Kara-Bogaz-Gol Lagoon east of Caspian Sea TOPEX/Jason Long time series separated from the Caspian Sea by a narrow, rocky ridge Water level rise since 1992 due to dam opening 72 5 m in 3 years

72 Example VII: Lake Huron Area/Volume estimations Intersection between water level heights and bathymetry model 73 NOAA

10 day repeat cycle Many invalid measurements due to

73 Example VIII: Amazon River (Manaus) TOPEX/Jason1/Jason2 Pass Long time series day repeat cycle Many invalid measurements due to small river width (few kilometers) 74 Seasonal variations about 10m!

74 Estimation of River Runoff 75 is also possible based on altimetry data! This will be presented by N. Sneeuw in Inland Altimetry II => Tomorrow, 9 a.m.

P. Cipollini, H. Snaith - A short course on Altimetry. Altimetry 2 - Data processing (from satellite height to sea surface height)

P. Cipollini, H. Snaith - A short course on Altimetry Altimetry 2 - Data processing (from satellite height to sea surface height) 1 2 Satellite height to sea surface height The altimeter measures the altitude