1. Accuracy Assessment of the MODIS 16-day Snow Albedo: Comparisons with Greenland in situ Measurements
J. C. Stroeve, J. Box, F. Gao, S. Liang, A. Nolin, and C. Schaaf
All Stations
Introduction
Results
Legend
BSA “good”
WSA “good”
BSA “poor”
WSA “poor”
Estimates of snow albedo are available from the MODIS 16-day (MOD43) albedo product but the product has yet to be evaluated over “pure” snow pixels. This study makes use of the reprocessed version 4 MOD43 products. This version of the data set includes new shortwave and near infrared (NIR) narrow-to-broadband (NTB) conversion factors for “pure” snow pixels. To access how well the improved algorithm performs, intercomparisons between the MODIS 16-day albedo product and in situ measured albedo from several automatic weather (AWS) stations over the Greenland ice sheet from 2000 to 2003 are presented.
FIGURES: Comparison between in situ clear sky and MODIS BSA and WSA albedo using data from at 18 Greenland AWS locations. Open symbols represent observations that are labeled as “poor” quality. The QA flags describe the quality of input samples in terms of atmospheric correction, number of observations and the angular distribution of samples and indicate whether a high quality full inversion was made with the primary algorithm or a low quality magnitude inversion with the backup algorithm was performed. Even though a retrieval is labeled as "poor" quality, the backup algorithm may perform quite well.
MODIS Snow Albedo Product
The operationally archived MODIS products include:
1) BRDF model parameters associated with the first seven spectral bands of MODIS (see Table and three additional broadbands (0.3 – 0.7m, 0.7-5m, 0.3-5m).
Completely diffuse bihemispherical (or white-sky) albedo - derived through integration of the BRDF for the entire solar and viewing hemisphere
Direct beam directional hemispherical (or black-sky) albedo - calculated through integration of the BRDF for a particular illumination geometry.
Actual albedos under particular atmospheric and illumination conditions can be estimated as a function of the diffuse skylight and a proportion between the black-sky and white-sky albedos.
White sky (WSA) and black sky (BSA) albedo at local solar noon for the same 7 spectral bands and the 3 broadbands.
Nadir BRDF-Adjusted Reflectances (NBAR), for the 7 spectral bands at the solar zenith angle of the mean overpass time (MOD43B4), is also archived every 16 days.
Table 1. MODIS spectral channels used in the albedo product.
Band
Bandwidth (nanometers) 1
620 – 670 2
841 – 876 3
459 – 479 4
545 – 565 5
1230 – 1250 6
1628 – 1652 7
Table: Summary of albedo differences.
Station R F-Test P-value rmse Mean Diff Std. Dev.
1. Swiss Camp
Clear Sky/BSA
Clear Sky/WSA
2. Crawford Point
Clear Sky/BSA
Clear Sky/WSA
3. NASA-U
Clear Sky/BSA
Clear Sky/WSA
5. Humboldt
Clear Sky/BSA
Clear Sky/WSA
6. Summit
Clear Sky/BSA
Clear Sky/WSA
7. TUNU-N
Clear Sky/BSA
Clear Sky/WSA
8. DYE-2
Clear Sky/BSA
Clear Sky/WSA
9. JAR1
Clear Sky/BSA
Clear Sky/WSA
10. Saddle
Clear Sky/BSA
Clear Sky/WSA
12. NASA-E
Clear Sky/BSA
Clear Sky/WSA
13. CP2
Clear Sky/BSA
Clear Sky/WSA
14. NGRIP
Clear Sky/BSA
Clear Sky/WSA
15. NASA-SE
Clear Sky/BSA
Clear Sky/WSA
16. KAR
Clear Sky/BSA
Clear Sky/WSA
17. JAR2
Clear Sky/BSA
Clear Sky/WSA
19. JAR3
Clear Sky/BSA
Clear Sky/WSA
20. All Stations
Clear Sky/BSA
Clear Sky/WSA
MODIS Albedo Algorithm Description
Conclusions
Results are often similar for BSA and WSA retrievals. Most exceptions occur when the sun is low in the sky (and the retrievals are flagged as “poor”). Thus, the difference between BSA and WSA has more to do with “poor” versus “good” retrievals than with BSA versus WSA.
More frequent retrievals in time would better capture changes in snow conditions (e.g. melt, wind erosion, etc.).
Measuring albedo at high latitudes is difficult not only for field measurements but also for satellite observations. The reflectance at extreme low solar zenith angles poses difficulties in calibration and atmospheric correction and thus has lower quality.
Overall mean differences are within 5%.
Kernel-driven, linear BRDF model that relies on the weighted sum of an isotropic parameter and two functions (or kernels) of viewing and illumination geometry [Roujean et al., 1992].
One kernel is derived from radiative transfer models [Ross, 1981], the other is based on surface scattering and geometric shadow casting theory [Li and Strahler, 1992].
All cloud-clear, atmospherically corrected surface reflectances over a 16-day period are considered.
After determining whether the majority of the clear observations available represent a snow-covered or snow-free situation, the kernel weights that best fit the majority situation are selected [Lucht et al., 2000; Schaaf et al., 2002].
Backup algorithm is used when a full BRDF model can not be confidently retrieved due to poor or insufficient input observations - method relies on a global database of archetypal BRDF model based on a land cover classification and high quality full BRDF retrievals from the previous year.
Once an appropriate BRDF model has been retrieved, integration over all view angles results in a directional-hemispherical (black sky ) albedo at any desired solar angle and a further integration over all illumination angles results in a bihemispherical (white sky) albedo. These albedo quantities are intrinsic to a specific location and are governed by the character and structure of its land cover. They can be combined with appropriate optical depth information to produce an actual (blue-sky) albedo for a specific time.