MERIS land surface albedo: Production and Validation

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MERIS land surface albedo Production and
Validation
Jan-Peter Muller Professor of Image
Understanding and Remote Sensing MODIS MISR
Science Team Member (NASA EOS Project) HRSC
Science Team Member (ESA Mars Express
2003) Chair, CEOS-WGCV Terrain mapping sub-group
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Overview

• Objectives
• BRDF/Albedo retrieval approach
• Moving vs Static time window issue
• Validation approach
• Wish-list

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Objectives

• Derivation of a one-year land surface albedo from
  MERIS for
• 13 of the 15 MERIS wavelengths (2 inside O2
  absorption bands)
• 2 broadband albedos (0.4-0.7µm, 0.7-1.0µm)
• MONTHLY time step (see later) for 2003
• Input Level 2 RayleighO3 corrected
• 10km sinusoidal and 0.1º spatial resolutions
• Publication of MERIS albedo browse images (as Web
  Map Services layers) within CEOS-WGISS EO Data
  Portal (http//iceds.ge.ucl.ac.uk)
• Main driver is to improve the retrieval of
  atmospheric parameters from MERIS. Hence, we need
  spectral albedos at the MERIS wavelengths
• Extremely limited resources (JPM) for validation
  by inter-comparison with other EO sensors and
  BRSN data

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BRDF/albedo approach

• Novel algorithms developed at Freie Universität
  by
• Thomas Schröder for aerosol correction
• Réné Preusker for cloud masking/detection
• Brockmann Consult responsible for
• algorithm coding, implementation and test (both
  production system and subsets as part of a new
  release of BEAM)
• Production processing of MERIS level 2
• Previous experience in development of cal/val
  database for MERIS ocean products
• BRDF retrieval will NOT be performed as sampling
  of the bi-directional plane insufficient for most
  land surfaces given the narrower swath (1130km)
  and lower temporal sampling (every 3 days at the
  equator) of MERIS
• Instead BRDF will be taken from MOD43C2 (0.05º)
  and magnitude inversion employed for each
  cloud-free pixel directional spectral reflectance
  sample and average taken over appropriate monthly
  period. Would like to test use of Maignan et al
  (RSE04) for months when sufficient POLDER-2
  samples available
• Unresolved issues with high reflectance areas
  snow and desert

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Albedo retrieval scheme
MOD43C2 BRDF (0.05º) QA1 flags
BIN/AVERAGE MERIS SDRs (0.05º)
MOD43C3 NBAR (0.05º)
QA2 Nsamps, stddev
DAILY MAGNITUDE INVERSION with MOD43C2
CALCULATE ltMERISgt NBAR OVER MODIS 16 DAY PERIOD
INTERCOMPARE WITH MOD43C3
MERIS 0.05º 16- DAY NBAR
CALCULATE MERIS NBAR 0.05º DAILY
CALCULATE ltMERISgt ALBEDO OVER 6 DAY
DAILY MERIS ALBEDO CALC.
MERIS 0.05º 16- DAY ALBEDOS
DIFF STATS
INTERCOMP-ARE WITH MOD43C1
MONTHLY/ SEASONAL AVERAGE RE-PROJECT TO 10KM
QA3 Nsamps, std.dev.
MOD43C1 ALBEDO (0.05º)
N.B. Status ATBD completed, coding
underway, production due to start in June,
completed by MERIS user workshop in Sep05
INTERPOLATE ALBEDO VALUES AT 9 OTHER BANDS
INTEGRATE TO VIS AND NIR Broadband
MERIS 10KM 13- SPECTRAL 2 BROADBAND MONTHLY
SEASONAL ALBEDOS
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Moving vs Static window

• Dr David Roy (MODIS Land QA/LDOPE Facility) has
  analysed global cloud statistics from Terra and
  Aqua separately and TerraAqua for fixed 16-day
  window and Terra-only (equivalent to Terra) with
  a moving 32-day window
• Results indicate that a MOVING 32-day time-step
  with daily updated calculations will lead to MUCH
  higher retrievals of cloud-free pixels and many
  more FULL INVERSIONS of MOD43
• Schaaf et al (BU) have shown that TERRAAQUA will
  improve the number of FULL INVERSIONS of MOD43
• Analysis by Roy using TerraAqua (fixed 16-day vs
  moving window) show excellent improvements in
  cloud-free samples
• Plan to extend this to cloud statistics from
  MERIS to assess which approach will yield better
  statistics
• N.B. POLDER-2 uses a 30-day moving window
  approach, reported at an unequal time interval
  (5th, 15th and 25th of each month)

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Global 10 degree tile-level analysis of the mean
annual probability of obtaining gt7 non-cloudy
MODIS Terra observations in 16-day windows moved
in daily steps through 366 days of 2004
Global mean annual probability 0.636 (1s 0.26)
computed over the illustrated 143 non-polar
tiles containing gt25 land
droy_at_kratmos.gsfc.nasa.gov
mean annual probability of obtaining gt7
non-cloudy observations
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Global 10 degree tile-level analysis of the mean
annual probability of obtaining gt7 non-cloudy
MODIS Aqua observations in 16-day windows moved
in daily steps through 366 days of 2004
Global mean annual probability 0.595 (1s 0.26)
computed over the illustrated 143 non-polar
tiles containing gt25 land
droy_at_kratmos.gsfc.nasa.gov
mean annual probability of obtaining gt7
non-cloudy observations
D. Roy UMD
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Global 10 degree tile-level analysis of the mean
annual probability of obtaining gt7 non-cloudy
MODIS Terra and Aqua observations in 16-day
windows moved in daily steps through 366 days of
2004
Global mean annual probability 0.895 (1s 0.14)
computed over the illustrated 143 non-polar
tiles containing gt25 land
droy_at_kratmos.gsfc.nasa.gov
mean annual probability of obtaining gt7
non-cloudy observations
D. Roy UMD
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Global analysis of the availability of gt7
non-cloudy MODIS Terra observations 32-day
window moved in daily steps through 366 days of
2004
D. Roy UMD
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Validation approach(1)

• Difference statistics between MERIS-Albedo and
  MOD43C1 will be analysed
• Overlapping MERIS swath NBARs (Nadir-equivalent
  BRDF Adjsuted Reflectance) will be used to assess
  how accurate the BRDF correction has performed as
  well as detect poorly corrected aerosol
  correction and poorly masked clouds
• Inter-comparisons will be performed with
• MISR 0.5º true monthly level-3 product (2003)
• POLDER2 0.1º resampled 6km sinusoidal gridded
  30-day products reported on the 15th of each
  month (Apr03-to-Oct03
• MOD43C1 sampled for best albedo value of two
  16-day time periods within the months of Jan,
  Feb, Sep, Oct, Nov-03

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Validation issue finding temporal coincidences
(MOD43)
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Validation issues wish-list (if time available)

• Scaling issues for MERIS albedo validation using
  in situ (SURFRAD/BSRN)
• Assessing the impact of topography (elevation and
  slope) from SRTM (ICEDS)
• Assessing the impact of urban areas on visible
  albedo variations (ICEDS)

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Albedo over urban areasNile Delta (JD305
31.10.2000)

• Distinctly higher albedo over urban areas in the
  Nile Delta
• Can be hard to get full inversions over urban
  areas as they are frequently misidentified as
  cloudy

Albedo
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Night-time lights (1995-6)Cities around The
Great Lakes Senses light sources down to 10-9
W/cm2/sr/?m (Elvidge et al., 1999)
Radiance x 10-10 W.m-2.sr-1.µm-1
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Current ICEDS portal test area