Improved sea-ice monitoring for the Baltic Sea Project summary

Transcription

1 Improved sea-ice monitoring for the Baltic Sea Project summary Leif E.B. Eriksson (1), Karin Borenäs (2), Wolfgang Dierking (3), Anders Berg (1) and Per Pemberton (2) (1) Chalmers University of Technology, Göteborg, Sweden (2) Swedish Meteorological and Hydrological Institute (3) Alfred Wegener Institute for Polar and Marine Research, Germany

2 Outline Introduction Field campaigns Satellite data Results Conclusions and discussion

3 Improved sea-ice monitoring for the Baltic sea Area: Gulf of Bothnia Cooperation: Swedish Meteorological and Hydrological Inst. (SMHI), Swedish Maritime Administration (SMA, Sjöfartsverket) and Alfred Wegener Institute (AWI), Germany Funding: Initial project Extended project 2008 and Swedish National Space Board, SMA and SMHI Data: TerraSAR-X through DLR AO ALOS PALSAR and Envisat ASAR through ADEN AO Radarsat-2 through SOAR program COSMO-SkyMed proposal approved too late

4 Objectives Improve determination of ice concentration detection of ice ridges discrimination of ice types Compare characteristics at different frequencies and polarisations Evaluate possibilities to incorporate new findings in operational services

5 Field campaigns

6 Bothnia Ice SAR experiment Three field campaigns : BothnIS 2007 Feb. to April 2007 BothnIS 2008 March 2008 BothnIS 2009 Feb. to April 2009

7 Test region Luleå Umeå

8 Helicopter flights Total Helicopter flights Helicopter landings on the ice for in situ measurements

9 Satellite data

10 SAR data for BothnIS Satellit ALOS PALSAR Envisat ASAR TerraSAR-X Radarsat-2 Mode FBS PLR WB AP WS SM SC FQ SCN SCW Pol. HH HH+HV+VV HH HH+VV or HH+HV HH HH+HV HH HH+HV+VV HH+HV or HH HH+HV or HH NA NA NA NA NA NA NA NA (+25) 8 11 (+42) FBS = Fine Beam Single pol.; PLR = polarimetric (quad pol.); WB = wide beam AP = Alternating Polarization; WS = Wide Swath SM = Strip Map; SC = ScanSAR FQ = Fine beam Quad pol.; SCN = ScanSAR Narrow; SCW = ScanSAR Wide NA = not available

11 Results Use of dual pol to get better separation between ice types and water

12 Chalmers University of Technology ALOS PALSAR PLR21.5 HV HH JAXA/METI 2007 VV JAXA/METI 2007 JAXA/METI rd ALOS Joint PI Symposium Kona, Hawaii,

13 ALOS PALSAR PLR21.5 HH HV R:HV G&B:HH JAXA/METI

14 Chalmers University of Technology TerraSAR-X HH 3rd ALOS Joint PI Symposium DLR HV DLR 2008 Kona, Hawaii,

15 TerraSAR-X R:HV G:HH B:HH DLR 2008 DLR 2008 R:HV G:HH B:HH

16 Results Identification of ice ridges

17 Chalmers University of Technology Comparison between airborne optical and IR photos BothnIS :12:45 3rd ALOS Joint PI Symposium Kona, Hawaii,

18 Ice ridge measurements

19 TerraSAR-X DLR 2008 DLR 2008 HH HV

20 ALOS PALSAR WB1

21 Results ALOS PALSAR WB1 for operational use in Europe

22 Comparison L-band and C-band JAXA/METI 2007 ESA 2007 ALOS WB ENVISAT WSM

23 ALOS PALSAR WB1 The banding effects that were previously seen in PALSAR WB1 data have not been observed in data from

24 Remaining problems ALOS PALSAR WB

25 Acquisition to delivery time 30 Acquisition to delivery time 800 ALOS - Acquisition to delivery time # acquisitions Hours Hours 0 17/01 27/01 06/02 16/02 26/02 08/03 18/03 28/03 Date ALOS ScanSAR acquisitions over the Gulf of Bothnia January to March 2009

26 Acquisition to delivery time 12 Acquisition to delivery time # acquisitions < 6 hours : 35% < 12 hours : 53% < 24 hours : 59% < 48 hours : 82% Hours ALOS ScanSAR acquisitions over the Baltic Sea during Jan. to March Only acquisitions to delivery time below 96 hours considered.

27 Remaining project tasks Tests with ScanSAR data from ALOS PALSAR and Radarsat-2 HH/HV at the Swedish ice service Tests of ice concentration algorithms with ALOS PALSAR and Radarsat-2 HH/HV Final report to Swedish National Space Board Publication of results in scientific journals

28 Ice concentration JAXA/METI 2009 Work in progress ALOS PALSAR WB1 HH Based on algorithm developed for C-band by Sverre Dokken Currently underestimates ice concentration

29 Conclusions Cross pol. make discrimination between open water and seaice easier in all three frequency bands, with the exception for smooth ice types. L-band cross pol. give better contrast between land and seaice. L-band data from ALOS PALSAR show deformed ice better than C-band data. L-band data from ALOS PALSAR seems to give better contrast between ice types during warm/wet conditions. For operational production of ice maps, ALOS PALSAR WB1 will be a useful complement to data from Radarsat-2 and ENVISAT ASAR.

30 PALSAR for Operational Ice Monitoring National ice services now consider PALSAR imagery a strong complementary dataset for operational ice monitoring North American Ice Service (Canada+U.S.) is using PALSAR daily with C-band SAR via ASF node European Ice Services will be using PALSAR very soon RADARSAT-1 HH Jan 13/08 PALSAR HH Jan 13/08 Winter -- Beaufort Sea

31 Thank you for your attention!