SMOSIce L-Band Radiometry for Sea Ice Applications

Transcription

1 Institute of Environmental Physics University of Bremen SMOSIce L-Band Radiometry for Sea Ice Applications Georg Heygster 1), Christian Haas 2), Lars Kaleschke 3), Helge Rebhan 5), Detlef Stammer 3), Rasmus Tonboe 4) 1) Institute of Environmental Physics, University of Bremen 2) Alfred-Wegener-Institute for Polar and Marine Research, Bremerhaven 3) Institute of Oceanography, University of Hamburg 5) ESA ESTEC, Nordwijk SMOS CAL VAL Workshop ESRIN, October 2007

2 Overview I. Heritages from SMOS proposal and workshops II. Study L-band Radiometry for sea ice applications III. Conclusions 2

3 I. Heritages SMOS Proposal 1998: Science team 7 subgroups: 6: Snow and Ice 7: Campaigns : SMOS science workshops 1999 Recommendations of the Cryosphere Group: Understanding of L-band emission from sea ice and snow under various weather and seasonal conditions, and factors influencing emissivity Characterize emissivity with theoretical and semiempirical models Campaigns for development and validation Develop algorithms to retrieve target characteristics 2001 Matzler: Applications of SMOS over terrestrial ice and snow Grain size <<! Ice absorption coeff small Snow penetration depth ~ 10x higher 6 GHz dry: >100m 5 % water: ~ 1m 3

4 Heritages Cryospheric part of the German SMOS proposal Submitted 2005 to ESA young ice types melt ponds signatures L-band signatures of sea ice Microwave emissivity model Weather induced changes of sea ice emissivity Signatures of land ice Nov. 2006: First German SMOS workshop Sea ice study suggested 4

5 II. ESA Study: SMOSIce L-band Radiometry for Sea Ice Applications 1. L-band emissivity model 2. Retrieval algorithms 3. External calibration: minimum signal

6 Low direct atmospheric influence in L Band More detailed: emissivity model II.1 Microwave Emissivity Models Normalized Radiometric Sensitivity Salinity SST Wind speed Cloud liquid Water vapor Frequency [GHz] (adapted from Vowinkel 1988) 6

7 II.1 Microwave Emissivity Models needed for understanding of SMOS signals developed for higher frequencies Candidates a) Three-layer dielectric slab (Vant et al., 1978) b) Strong Fluctuation Theory (Stogryn 1987) c) MELMS (Wiesmann and Matzler (1999) with ice variant MEMLSI (Tonboe et al., 2006) 7

8 a) Three-layer dielectric slab Based on salinity (Vant et al., 1978) Scattering ignored Thickness from UHF observations retrieved (Menashi et al. 1993) 8

9 Three-layer dielectric slab 1.4 GHz 19 GHz Vb = 0 (Lake Ice) Vb = 5 Vb = 15 (Young Sea Ice) Vb = 0 (Lake Ice) Vb = 5 Vb = 15 (Young Sea Ice) Thickness / m Thickness / m 9

10 b) Strong Fluctuation Theory (SFT) Directly from Maxwell s equations (Stogryn 1987, Grenfell 1992) Isothermal layers Each described by 10 parameters temperature density thickness Salinity SFT combined with atmospheric RT model MWMOD 1996 (Simmer 1994, Fuhrhop et al. 1998) 10

11 SFT examples Dark Nilas First-year Ice Frequency / GHz Frequency / GHz 11

12 SFT examples H-pol Emissivity Frequency / GHz Thickness / mm Thickness / mm 12

13 c) MEMLS Microwave Emission Model of Layered Snowpacks: Wiesmann and Matzler 1999 MEMLSI: extension with sea ice module: Tonboe et al Six-flux RT theory Multiple scattering by stratification and grains 13

14 MEMLS examples Simulated penetration depths of Nilas Fist-Year Ice Multiyear Ice 14

15 II.2 Retrieval Algorithms Goals: 1. discriminate sea ice vs. open water 2. determine ice concentration and ice thickness. Thickness of young ice from SMOS? Methods: 1. Signatures of ice types at SMOS observation modes and geometries 2. - Model-based forward calculations - Campaign data 15

16 Signature of sea ice Sea ice brightness temperatures and emissivity currently available only between 6 and 90 GHz. Determine for sea ice types occurring at sufficiently large scales (Arctic FY, MY; Antarctic A, B; Yong ) Tasks: Investigate brightness and emissivity of Arctic FYI, MYI and Antarctic ice types A, B under various weather and seasonal conditions as a function of Basic ice parameters (salinity, temperature, thickness, age) Sensor parameters (incidence angle, 4 polarizations) Emissivity determination requires knowledge of temperature profile in ice (Field work) Stokes components U, V depend on azimuth! 16

17 Campaign data SMOS Sea Ice campaign Kokkola, Finland, March 2007 add-on of the POL-ICE campaign preparing RADARSAT-2 EMIRAD: 4 Stokes 1.4 GHz Ice thickness by AWI s EM bird Meltpond 2000 campaign Baffin Bay, Canada, June 2000 NASA Aqua AMSR-E Validation program SLFMR: 1.4 GHz, 5 flights 17

18 Meltpond 2000 campaign Flight track P3 June 27 L-band TB vs. SSM/I ASI 85 GHz IC 18

19 Signature of sea ice Sea ice brightness temperatures and emissivity currently available only between 6 and 90 GHz. Determine for sea ice types occurring at sufficiently large scales (Arctic FY, MY, Antarctic A, B) Tasks: Investigate brightness and emissivity of Arctic FYI, MYI and Antarctic ice types A, B under various weather and seasonal conditions as a function of Basic ice parameters (salinity, temperature, thickness, age) Sensor parameters (incidence angle, polarization) Emissivity determination requires knowledge of temperature profile in ice (Field work) Stokes components U, V depend on azimuth! 19

20 II.3 External Calibration Lowest surface TBs: open water in high latitudes (Ruf 2000) Near ice edge S varies strongly Identify regions from combined satellite observations (left) and model runs (right) 20

21 III. Conclusions and Outlook Plans for analyses and understanding of cryospheric SMOS data currently underdeveloped 3 fields of activity suggested: 1. L-band emissivity model, candidates: Three-layer dielectric slab Strong Fluctuation Theory MELMSI 2. Retrieval algorithms Ice/water discrimination requires signatures of sea ice field campaigns needed for in situ microphysical data: SMOS Sea Ice Campaign, Kokkola, Finland, March 2007 Meltpond 2000 Campaign, Baffin Bay 3. External calibration: minimum signal 21

22 III. Conclusions and Outlook Outlook: Several Retrievals will need synergy with other sensors, e.g. AMSR, SSMIS, SAR, scatterometer,.. Melt ponds? 22

23 Backup Slides

24 b) SFT details Directly from Maxwell s equations (Stogryn 1987, Grenfell 1992) Isothermal layers Each described by 10 parameters temperature density layer thickness (layering) salinity snow grain size snow water content ice: air bubbles: size, density, shape, orientation SFT combined with atmospheric RT model MWMOD 1996 Coherent reflections at layer boundaries may cause instable signal Fortran 24

25 c) MEMLS details Microwave Emission Model of Layered Snowpacks: Wiesmann and Matzler 1999 MEMLSI: extension with sea ice module: Tonboe et al Six-flux RT theory Multiple scattering by stratification and grains Refraction and radiation trapping by internal reflection Combination of coherent and incoherent superposition Validated 5 to 100 GHz Primary limitation: empirical scattering description Matlab or Gnu 25

26 Example: AMSU emissivities 26

27 Example: Determination of AMSU emissivities penetration depth 37 GHz 90 GHz _Dry snow MY Ice 7 4 FY Ice

28 Examples: AMSU emissivities 28

29 Example: AMSU emissivities 29