# Presentation: 479292

## MERIS land surface albedo: Production and Validation

***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***

## Overview

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

## 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:](http://iceds.ge.ucl.ac.uk/)**__**[//iceds](http://iceds.ge.ucl.ac.uk/)**__**[.](http://iceds.ge.ucl.ac.uk/)**__**[ge](http://iceds.ge.ucl.ac.uk/)**__**[.](http://iceds.ge.ucl.ac.uk/)**__**[ucl](http://iceds.ge.ucl.ac.uk/)**__**[.ac.](http://iceds.ge.ucl.ac.uk/)**__**[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**

## BRDF/albedo approach

**Novel algorithms developed at Freie Universit****ät ****by **
**Thomas Schr****öder for aerosol correction**** **
**R****éné 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**

## Albedo retrieval scheme

-       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 <MERIS> NBAR OVER MODIS 16 DAY PERIOD

- CALCULATE <MERIS> 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

## 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) **

## Global mean annual probability = 0.636 (1 0.26) 

- 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

## 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 

- 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

## Global mean annual probability = 0.895 (1 0.14) 

- 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

## Global analysis of the availability of >=7 non-cloudy 

- D. Roy UMD

- Global analysis of the availability of >=7 non-cloudy
- MODIS Terra observations
- 32-day window moved in daily steps through 366 days of 2004

## 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**

## Validation issue: finding temporal coincidences (MOD43)

## 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)**

## 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**

**Albedo**

## 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****.****μ****m****-1**

## Current ICEDS portal test area