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How Satellite Remote Sensing of The Ice Sheets Can Contribute to Studies of Sea Level Changes Wolfgang Dierking Alfred Wegener Ins2tute, Helmholtz Center for Polar and Marine Research Bremerhaven, Germany

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Page 1: How$Satellite$Remote$Sensing$of$The$Ice ... › 36408 › 1 › REKLIM_2014_Dierking.pdf · How$Satellite$Remote$Sensing$of$The$Ice$ SheetsCanContributetoStudiesofSea LevelChanges

How  Satellite  Remote  Sensing  of  The  Ice  Sheets  Can  Contribute  to  Studies  of  Sea  

Level  Changes  

Wolfgang  Dierking  Alfred  Wegener  Ins2tute,    

Helmholtz  Center  for  Polar  and  Marine  Research  Bremerhaven,  Germany  

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Sea  Level  -­‐>  Ice  Sheet  Mass  Balance  

Contribu2on  of  the  ice  sheets  to  sea  level  changes  via  mass  gain  or  mass  loss  over  2me.      

Remy  and  Parouty,  Remote  Sensing  2009  

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Mass  Balance  of  Ice  Sheets:    Measurement  Principles  

•  (changes  of  gravity  field:  Ingo  Sasgen)  

•  temporal  changes  of  eleva2on    •  mass  budget  method  o snow  accumula2on  o  ice  discharge,  mel2ng  

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Mass  Balance  of  Ice  Sheets:  Methods  

elevaCon  changes  per  year  

•  height  -­‐>  volume                (per  unit  area,  on  a  grid)  

•  density  (known?)  

 •  ice  sheet  margin:                discharge?                extension?            

t=t0  h=h0  

t=t1  h=h1  

!V (i, j) = !h(i, j)!x!y

!M (i, j) = !(i, j)!V (i, j)

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roughness

Problems:    

•  op2mal  pulse  travel              2me  determina2on?    

•  accuracy  of  reference              (geoid)?    

•  atmospheric  influence              on  pulse  travel  2me?    

•  return  ambigui2es              (terrain  slope)?  

CryoSat

SIRALca. 580 kg

ca. 4 m

ElevaCon:  Laser  or  Radar  AlCmetry  Cryosat-2

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Results:  ElevaCon  Change  

Eleva2on  change  of  Antarc2ca  and  Greenland  between    January  2011  and  January  2014,  derived  from  Cryosat  data  (Helm  et  al.,  The  Cryosphere  8,  2014)  

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Height  Retrieval:  Tricky!  AlCmeter  -­‐  effects  to  be  considered:    

•     Seasonal  density  varia2ons            change  volume  but  not                            necessarily  mass.    •     Where  does  the  radar                          al2meter  signal  come                from?  Posi2on  of  reflector              stable  over  the  years??  

•     Ver2cal  mo2on  of  the                bedrock  (glacial  rebound)?              (Antarc2c:  0.5  mm/yr)  

Surface  eleva2on  2me  series  (Ligtenberg  et  al.,    GRL  39,  2012)  

Height  differences  between  two  radar    frequencies  -­‐>  effect  of  different  penetra2on  depths  (Remy  and  Parouty,    Remote  Sensing  2009)      Meters

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mass  budget  method      o     snow  accumula2on  -­‐>Stefanie  Linow  

o     ice  discharge    

o     mel2ng  

t=t0  

Mgain (i, j)!/!t= !snow (i, j)!h(i, j)!x!y!/!t t=t1  

Δh ΔH

ΔW

Mice ! loss !/!t =!vref!ice!H!W

vref

Mmelt !/!t = !waterVwater !/!t

!M /!t = (Mgain "Mice ! loss "Mmelt ) /!t

Mass  Balance  of  Ice  Sheets:  Methods  

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Mass  Budget:  Imaging  Sensors  on  Satellites  

Sensors  differing  by:    

•  spectral  range  (frequency)  •  polariza2on  •  spa2al  coverage  •  spa2al  resolu2on  •  temporal  gaps  between              image  acquisi2ons    

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Ice  Flux:  Reference  =  Grounding  Line  

2

1100m 1

1300m

grounded ice

floating ice

-0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0 5 10 15 20 25 30 35

distance (km)

diff.

ver

tical

dis

plac

emen

t (m

)

1

-0.50

-0.40

-0.30

-0.20

-0.10

0.00

0.10

0 5 10 15 20 25 30 35

distance (km)

diff.

ver

tical

dis

plac

emen

t (m

)2 Using  radar  images  for  calcula2ng    

ver2cal    displacements  

flux  gate  

2dal  movement  

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Ice  Flux:  Velocity  Fields  

Using  radar  images  for  calcula2ng    ice  veloci2es  

Mohr  et  al.,  Nature  391,  1998

Flow  vectors  and  eleva2on  of    Storstrømmen  Glacier,  Greenland,    derived  from  satellite  radar  images  

Different  methods  can  be  applied,  dependent  on    glacier  velocity:  •  feature  tracking  •  speckle  tracking  •  differen;al  INSAR  

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Results:  Grounding  Lines  And  Velocity  Fields  

Rignot  et  al.,  GRL  38,  2011

Grounding  lines,  colors  indicate  results  from  different  satellite  radars  and  an    op2cal  sensor  (also  possible  with  laser)    

Rignot  et  al.,  Science  333,  2011

Antarc2c  ice  velocity  derived  using    images  from  different  satellite  radars  

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Results:  Grounding  Lines  And  Velocity  Fields  

Rignot  et  al.,  GRL  38,  2011

Grounding  lines,  colors  indicate  results  from  different  satellite  radars  and  an    op2cal  sensor  (also  possible  with  laser)    

Rignot  et  al.,  Science  333,  2011

Antarc2c  ice  velocity  derived  using    Images  from  different  satellite  radars  

     Results  shown:  Composites  of  regional  analyses!    

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Ice  Flux:  Dimension  of  Flux  Gate  Ice  Penetra2ng  Radar  (IPR)  (airborne  measurements):    ice  shelf  thickness    

Imaging  sensors:  width  (grounding  line)  

Ice thickness

By  courtesy  of  W.  Rack,  AWI  

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Mass  Loss:  Ice  Sheet  Summer  Melt  

2000 2003

0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

2001 2002

Number  of  melt  days  (from  scaferometer  data)  -­‐>  extent,  dura2on,  but  no  informa2on  about  volume  (Steffen  et  al.,  GRL  31,  2004)  

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Rignot  et  al.    Nature  Geoscience  Vol.  1,  Jan.  2008  

AntarcCc  Ice  Sheet  Mass  Balance  Required  Data    

ice  velocity:    •     speckle  tracking  -­‐>              Radarsat-­‐1,  ALOS              PALSAR,  ERS-­‐1  •     INSAR  -­‐>              ERS1/2  tandem    flux  gate  height:  •     from  surface  eleva2on    grounding  line  posi2on  •     from  dif.  INSAR    snow  accumula2on:  •     from  a  regional        climate  model  

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The  Message?  

•  Many  different  satellite  sensor  types  are  available  for  observa2ons  of  the  ice  sheets!  

•  Mass  balance  studies  require  to  combine  satellite  observa2ons,  in-­‐situ  data,  and  modeling  (e.  g.  precipita2on,  

         firn  densifica2on…).    

•  Satellite  remote  sensing  helps  to  fill  gaps  between  ground                measurements  and  to  validate  models  for  simula2ons  of              sea  ice  dynamics.    •  Many  satellite  sensors  are  operated  at  spa2al  resolu2ons            op2mal  for  regional  studies  (e.  g.  imaging  radar  -­‐>  ice              shelves)  

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Benefits  for  the  End  User?  

•  Data  sets  on                ice  shelf  thickness,  grounding  line,  ice  velocity,  DEM,…            are  available  via                Pangea,  NSIDC,  NASA,…    •  Discussion  between  the  cryosphere  community  and              space  agencies  about  needs  of  the  former  are  ongoing.              Examples:                    ESA  -­‐>  WSs  on  new  mission  concepts;  cryosphere  science                        conferences,  Earth  Explorer  Missions;                      DLR-­‐>  SIGNAL  mission  proposal  dedicated  to  ice  sheet                    observa2ons;