1. DEPARTMENT OF GEOMATIC ENGINEERING 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

2. DEPARTMENT OF GEOMATIC ENGINEERING Overview Objectives BRDF/Albedo retrieval approach Moving vs Static time window issue Validation approach Wish-list

3. DEPARTMENT OF GEOMATIC ENGINEERING 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 Rayleigh+O3 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)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

4. DEPARTMENT OF GEOMATIC ENGINEERING BRDF/albedo approach Novel algorithms developed at Freie Universit ä t by –Thomas Schr ö der for aerosol correction –R é n é 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

5. Albedo retrieval scheme Meris L2 SDRs MOD43C2 BRDF (0.05º) + QA#1 flags BIN/AVERAGE MERIS SDRs (0.05º) DAILY MAGNITUDE INVERSION with MOD43C2 DAILY MERIS ALBEDO CALC. MONTHLY/ SEASONAL AVERAGE RE- PROJECT TO 10KM QA#2 Nsamps, ± stddev CALCULATE MERIS NBAR 0.05º DAILY CALCULATE NBAR OVER MODIS 16 DAY PERIOD CALCULATE ALBEDO OVER 6 DAY QA3 Nsamps, ± std.dev. MERIS 0.05º 16- DAY NBAR INTERCOMPARE WITH MOD43C3 DIFF STATS MOD43C3 NBAR (0.05º) MERIS 0.05º 16- DAY ALBEDOS INTERCOMP-ARE WITH MOD43C1 MOD43C1 ALBEDO (0.05º) INTERPOLATE ALBEDO VALUES AT 9 OTHER BANDS + INTEGRATE TO VIS AND NIR Broadband MERIS 10KM 13- SPECTRAL +2 BROADBAND MONTHLY+ SEASONAL ALBEDOS N.B. Status: ATBD completed, coding underway, production due to start in June, completed by MERIS user workshop in Sep05

6. DEPARTMENT OF GEOMATIC ENGINEERING Moving vs Static window Dr David Roy (MODIS Land QA/LDOPE Facility) has analysed global cloud statistics from Terra and Aqua separately and Terra+Aqua 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 TERRA+AQUA will improve the number of FULL INVERSIONS of MOD43 Analysis by Roy using Terra+Aqua (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)

7. Global mean annual probability = 0.636 (1  0.26) [computed over the illustrated 143 non-polar tiles containing >25% land] Global 10 degree tile-level analysis of the mean annual probability of obtaining >=7 non-cloudy MODIS Terra observations in 16-day windows moved in daily steps through 366 days of 2004 mean annual probability of obtaining >=7 non-cloudy observations droy@kratmos.gsfc.nasa.gov

8. Global 10 degree tile-level analysis of the mean annual probability of obtaining >=7 non-cloudy MODIS Aqua observations in 16-day windows moved in daily steps through 366 days of 2004 mean annual probability of obtaining >=7 non-cloudy observations Global mean annual probability = 0.595 (1  0.26) [computed over the illustrated 143 non-polar tiles containing >25% land] droy@kratmos.gsfc.nasa.gov D. Roy UMD

9. Global mean annual probability = 0.895 (1  0.14) [computed over the illustrated 143 non-polar tiles containing >25% land] Global 10 degree tile-level analysis of the mean annual probability of obtaining >=7 non-cloudy MODIS Terra and Aqua observations in 16-day windows moved in daily steps through 366 days of 2004 mean annual probability of obtaining >=7 non-cloudy observations droy@kratmos.gsfc.nasa.gov D. Roy UMD

10. Global analysis of the availability of >=7 non-cloudy MODIS Terra observations 32-day window moved in daily steps through 366 days of 2004 Percentage of windows over the year where the probability of obtaining >=7 non-cloudy observations is > 0.9

11. DEPARTMENT OF GEOMATIC ENGINEERING 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

12. DEPARTMENT OF GEOMATIC ENGINEERING Validation issue: finding temporal coincidences (MOD43)

13. DEPARTMENT OF GEOMATIC ENGINEERING 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)

14. DEPARTMENT OF GEOMATIC ENGINEERING Albedo over urban areas Nile 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 -0.25 -0.20 -0.15 -0.10 -0.05 -0 Albedo

15. DEPARTMENT OF GEOMATIC ENGINEERING Night-time lights (1995-6): Cities around The Great Lakes Senses light sources down to 10 -9 W/cm 2 /sr/  m (Elvidge et al., 1999) Radiance: x 10 -10 W.m -2.sr -1. μ m -1

16. DEPARTMENT OF GEOMATIC ENGINEERING Current ICEDS portal test area