Editorial for Special Issue: “Remotely Sensed Albedo”

Jean-Louis Roujean (1) , Shunlin Liang (2, 3) , Tao He (3)

1 CESBIO - Centre d'études spatiales de la biosphère
2 University of Maryland [College Park]
3 Wuhan University [China]

Land surface (bare soil, vegetation, and snow) albedo is an essential climate variable that affects the Earth's radiation budget, and therefore, is of vital interest for a broad number of applications: Thematic (urban, cryosphere, land cover, and bare soil), climate (Long Term Data Record), processing technics (gap filling, data merging), and products validation (cal/val). The temporal and spatial patterns of surface albedo variations can be retrieved from satellite observations after a series of processes, including atmospheric correction to surface spectral Bidirectional Reflectance Factor (BRF), and Bidirectional Reflectance Distribution Function (BRDF) modelling. The processing chain for deriving surface albedo introduces cumulative errors that can affect the accuracy of the retrieved satellite albedo products (MISR, MODIS, VEGETATION, and Proba-V). A new method is proposed to estimate Directional Hemispherical Reflectance (DHR) and Bi-Hemispherical Reflectance (BHR) from measured variables (downwelling, upwelling, and diffuse shortwave radiation) at 19 tower sites from the FLUXNET network, Surface Radiation Budget Network (SURFRAD), and Baseline Surface Radiation Network (BSRN) networks. The pixel-to-pixel comparison between DHR/BHR retrieved from coarse-resolution satellite observations and upscaled from tower sites from 2012 to 2016 emphasizes the parameters involved (land cover type, heterogeneity level, and instantaneous vs. time composite retrievals) [1]. Global warming effects pose a significant change in the albedo of the boreal forest areas as revealed by observed trends in AVHRR satellite albedo magnitude before and after the snow/ice melt season between 40 • N and 80 • N from 1982 to 2015. Absolute change is 4.4 albedo percentage units per 34 years. The largest changes in pre-melt-season albedo are concentrated in boreal forest, rather than tundra, and are consistent over large areas. The mean of absolute change of start date of the melt season is 11.2 days per 34 years, 10.6 days for end date of the melt season, and 14.8 days for length of the melt season. The albedo intensity preceding the start of the melt season correlates with climatic parameters (air temperature, precipitation, and wind speed) but is primarily affected by the changes in vegetation [2]. Still, at high latitudes, ice albedo feedback affects the global climate based on LTDR of MODIS and VIIRS product routinely disseminated by NOAA. An angular bin regression method acting as gap-filling supports the simulations of a physically-based sea-ice BRDF representing different types and mixing fractions (snow, ice, and seawater). A comparison of six years of ground measurements at 30 automatic weather stations gathered/derived from the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-NET) shows low bias (~0.03) and root mean squared error (RMSE) about 0.07) [3]. Long-term surface albedo datasets are essential for global climate analysis. A method originally developed for MODIS was applied to AVHRR LTDR reflectance to estimate daily surface albedo, which corrects for directional effects using the instantaneous Normalized Difference Vegetation Index (NDVI) and multiyear MODIS BRDF shapes. To reduce the high noise in the red band caused by atmospheric

Domaines: Planète et Univers [physics]; Interfaces continentales, environnement; Sciences de l'environnement

Jean-Louis Roujean, Shunlin Liang, Tao He. Editorial for Special Issue: “Remotely Sensed Albedo”. Remote Sensing, 2019, 11 (16), pp.1941. ⟨10.3390/rs11161941⟩. ⟨hal-02354398⟩