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aft_4_Luojus_GlobSnow_IGARSS_2011_final.ppt

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  • 1. ESA DUE GLOBSNOW Investigating Hemispherical Trends in Snow Accumulation Using GlobSnow Snow Water Equivalent Data Kari Luojus ( Finnish Meteorological Institute) J. Pulliainen, M. Takala, J. Lemmetyinen (FMI) C. Derksen, L. Wang (EC) S. Metsämäki (SYKE), B. Bojkov (ESA) GlobSnow project consortium: FMI, NR, ENVEO, GAMMA, SYKE, EC, Norut
  • 2. ESA-funded GlobSnow project: Production of hemispherical scale snow extent (SE) and snow water equivalent (SWE) climate data records; along with a demonstration of a near real time processing and data dissemination chain for the products. Consortium; Finnish Meteorological Institute (FMI) with ENVEO IT GmbH (Austria), GAMMA Remote Sensing (Switzerland), Norwegian Computing Center, Finnish Environment Institute (SYKE), and Environment Canada (EC). Products and project details: www.globsnow.info Near-real-time snow map production on-going since: 1 October 2010 ESA GlobSnow
  • 3. GlobSnow: Long term snow products
    • SWE (30 years) and SE product (15 years) + NRT demonstration
      • Primary products:
        • Daily SWE / Daily fractional SE
      • Secondary products:
        • Weekly SWE / SE (mean and maximum)
          • Sliding average: data from current day + previous 6 days
          • 1 file for every day
        • Monthly SWE / SE(mean and maximum)
          • 12 files per year: January, February, March…
      • Spatial coverage: Northern Hemisphere (both SE & SWE)
  • 4. GlobSnow – SWE ECV
    • A new State-of-the-Art Snow Water Equivalent (SWE) climate data record
    • Work initiated at HUT/LST during 1990’s by Profs Pulliainen and Hallikainen
    • SWE Methodology (main body of work) published 2006 in RSE by Pulliainen
    • Past 5 years the work has been carried at FMI Arctic research centre
    • Shifted in high gear for ESA DUE GlobSnow (T.O. ESA/ESRIN: B.Bojkov)
    • -> Past 3 years of work by an experienced team (key people originally HUT/LST + team at Environment Canada) have resulted in a new SWE climate record (daily, 1979 – 2010, hemispherical SWE record)
    • Validation, spanning NH, indicates a new level of accuracy for SWE retrieval
    • Production of 30+ years SWE data on a (FMI Cray 5 XTm) super computer
    • Results presented in earlier conferences & a journal article in press (and a project document library for GlobSnow users)
  • 5. SWE product (development by FMI & EC)
    • SWE climate record for 1979 - 2010 (+ NRT demonstration)
      • Spaceborne microwave radiometer data
        • AMSR-E data (2003 – present)
        • SSM/I data (1987 – 2002)
        • SMMR data (1979 – 1987)
        • + Global weather station data from WMO stations
    • Produced in EASE-grid projection ~ 25km resolution
    • Product includes error estimates for each SWE value
  • 6. Overview for the SWE product
    • Daily maps of hemispherical snow cover:
      • SWE for the permanent seasonal snow area
      • Total snow area (Snow Extent)
    • Regions with high topograpical variability are masked out
      • Alpine regions
      • Glaciers
      • Greenland
    • NRT production of SWE demonstrated in 2010-2011
    • NRT to be transferred to EUMETSAT H-SAF late 2011
    • Data format HDF4 & NetCDF CF
    • Data access through FTP & WWW
  • 7. Daily SWE product: 15 February 2008 Northern Hemisphere
  • 8. SWE algorithm selection & retrieval validation
    • Daily SWE estimates acquired with 5 algorithms evaluated for Eurasia (1994-1997)
    • FMI Assimilation algorithm (Pulliainen 2006)
    • EC SWE suite (Goodison, Walker, Goita, Derksen et al. 1993-2009)
    • Chang et al. 1987 (original channel difference algorithm)
    • SPD-algorithm (Asbacher 1989)
    • Armstrong and Brodzik 2001-algorithm (Improved channel difference)
    • SWE estimates computed between 09/1994 and 12/1997 (SSM/I data)
    • Chang, SPD and Armstrong –algorithms were evaluated for both asc & desc nodes; FMI uses desc node data complemented with asc node data
    • Evaluations for North America and Finland were carried out in addition to the analyses for Eurasia
  • 9. Validation data – INTAS SSCONE data
    • INTAS SSCONE data (from the former USSR and Russia)
      • There are 1294 snow path stations with data from the USSR
        • Manual ground-based measurements on snow depth
        • Used as the validation data for the GlobSnow evaluations
        • There were 450 path stations with data for 1994-1997
  • 10. Overall performance for SWE algorithms Eurasia 09/1994 – 12/1997 Evaluation with 450 INTAS snow courses 29559 29451 65.9 mm 63.9 mm 0.052 0.121 -12.7 mm -3.1 mm 67.1 mm 63.9 mm SPD algorithm (asc node) SPD algorithm (desc node) 26726 27521 71.1 mm 70.8 mm 0.011 0.029 -8.4 mm 1.6 mm 71.6 mm 70.7 mm Chang et al. 1987 (asc node) Chang et al. 1987 (desc node) 21796 24791 57.3 mm 59.9 mm 0.044 0.029 -44.1 mm -42.9 mm 72.3 mm 73.7 mm Armstrong et al. 2001 (asc node) Armstrong et al. 2001 (desc node) 18109 61.5 mm 0.210 -28.2 mm 67.6 mm EC algorithm 26063 43.1 mm 0.611 -3.1 mm 43.2 mm FMI algorithm - (selected for GlobSnow) Samples Unbiased RMSE Corr.coeff bias RMSE Name
  • 11. Consistency of GlobSnow SWE retrieval 1980 - 2009 SWE<150 mm All SWE
    • RMS error and retrieval bias calculated independently for each year
    • Consistent inter-annual characteristics & minimal difference between sensors
    AMSR-E F 13 SSM/I F 11 SSM/I F 8 SSM/I SMMR AMSR-E F 13 SSM/I F 11 SSM/I F 8 SSM/I SMMR AMSR-E F 13 SSM/I F 11 SSM/I F 8 SSM/I SMMR AMSR-E F 13 SSM/I F 11 SSM/I F 8 SSM/I SMMR
  • 12. AMSR-E vs. SSM/I evaluations (2003 - 2010)
    • GlobSnow SWE PMW sensor changes from SSM/I to AMSR-E at the beginning of 2003
      • FPS v1.0 (current sensor set)
        • SMMR 1979 – 1987
        • SSM/I 1987 – 2002
        • AMSR-E 2003 – 2010
      • Possible alternative sensor set (e.g. NSIDC sea ice)
        • SMMR 1979 – 1987
        • SSM/I 1987 - 2010
    • Comparisons between for SSM/I and AMSR-E derived SWE datasets (2003-2010) conducted
  • 13.
    • Change of bias: DMSP-F13 results in higher snow mass (SWE) than AMSR-E, but DMSP-F17 gives a lower snow mass after summer 2009
    2009-2010 DMSP-F17 2003 – 2008 DMSP-F13 AMSR-E vs. SSM/I evaluations (2003 - 2010)
  • 14. AMSR-E vs. SSM/I trend (1980 - 2010)
  • 15. SSMI, -8,2% trend for 30 years AMSR-E, -9.6% trend for 30 years AMSR-E vs. SSM/I trend (1980 - 2010)
  • 16. Summary on SWE product
    • Current long term datasets on Global scale: Monthly from 1978, daily from 2002
      • GlobSnow: Daily 30+ years ( … from launch of SMMR 1978)
    • Thematic accuracy
      • Current alternative algorithms
        • Global scale 40mm – 200mm
        • Regional scale 20mm – 50mm (methods typically regionally adjusted)
      • GlobSnow algorithm (Global scale):
    • RMSE of 43.2 mm for Eurasia (diagnostic dataset; > 26 000 samples)
    • RMSE of 33.5 mm for Eurasia (for SWE < 150mm; >23 000 samples)
    • Error estimates (error bars)
      • Current methods do not provide information on estimation error
      • GlobSnow SWE algorithm: Error estimates for each SWE estimate
  • 17. GlobSnow Snow Extent Dataset 28.07.11 Finnish Meteorological Institute
    • SE retrieval using ERS-2 ATSR-2 and Envisat AATSR data
    • - Finnish Environment Institute’s SCAmod algorithm.
    • - Norwegian Linear Reflectance’ (NLR) fractional snow cover (FSC) algorithm;
    • - 15 years SE data record has been produced using optical imagery from ATSR-2 (1995-) and AATSR (2002-) on a hemispherical scale.
    yellow – clouds green – bare ground white – snow cover
  • 18. Daily, weekly and monthly products April 2003 19 April 2003 10 April 2003 Optical data ~ 1km spatial resolution
  • 19. Examples of monthly products, 2003 April 2003 May 2003 June 2003
  • 20. 28.07.11 Finnish Meteorological Institute
    • 30+ year daily Snow Water Equivalent climate record (25 km resolution)
    • 30+ year daily Snow Extent (PMW) climate record (25 km resolution)
    • 15+ year daily Snow Extent (optical) climate record (1km resolution)
      • Version 1.0 of low resolution SWE/SE (30 years) and high resolution SE (15 years) are available now
      • The extensive validation effort indicates a new level of accuracy for hemispherical scale SWE retrieval for the 30+ year evaluation
      • Long term trends indicate a clear decline in hemispherical snow mass
    • The near-real-time GlobSnow processing system is on-going an operational demonstration phase (ESA GlobSnow -> Eumetsat H-SAF)
    • Products (freely available) and additional details: www.globsnow.info
    GlobSnow - Summary
  • 21. SWE algorithm evaluations: Eurasia 1994-1997
    • Detailed analyses reported within GlobSnow project documentation
      • - Accessible through the GlobSnow User www-pages
  • 22. SWE product & trend analyses Average SWE for March 1997 Mean snow mass for March (30 year trend)
  • 23. SWE product & mountain hydrology
    • Baseline SWE dataset does not include estimates for mountains
      • Coarse resolution radiometer data not well suited for highly varied topography
    • An on-going development effort to map mountains with GlobSnow SWE algorithm
    • 1st “Prototype” mountain SWE dataset for 2008-2010 released:
    • www.globsnow.info/swe /
    • A more advanced version to be released by the end of summer 2011