Improving GLASS AVHRR-derived terrestrial shortwave blue-sky albedo using GLASS MODIS-derived albedo: a global long-term study

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Authors: Zi Yang, Hongjun Zhu, Jie Yuan, Rufat Guluzade, Xin Pan, Xu Ding, Suyi Liu, Congbao Zhu, Yuqian Li, Longlong Guo, Yi Yang
Cited by: 0
References: 38

Abstract

Land surface albedo is a key parameter in the Earth’s energy budget and plays a vital role in climate, ecological, and hydrological processes. A consistent, long-term global record of land surface blue-sky shortwave albedo (0.3–3.0 μm) is essential for understanding climate variability. However, existing long-term albedo products, such as the GLASS shortwave albedo derived from MODIS and AVHRR observations, exhibit notable discrepancies due to differences in sensor characteristics and processing methodologies. In particular, the GLASS AVHRR albedo product is generally of lower quality and accuracy than the MODIS-based GLASS product. In this study, we integrated GLASS blue-sky albedo data from both sensors and calibrated the AVHRR-derived albedo to match the MODIS-derived albedo, resulting in a harmonized 1982–2019 global land surface blue-sky shortwave albedo dataset. The calibration process addresses known issues, such as differences in temporal compositing windows and the reduced accuracy of AVHRR in high-altitude, high-latitude, and arid regions. Following spatiotemporal adjustment, discrepancies between AVHRR and MODIS albedo during 2001–2019 were substantially reduced (by approximately 0.05–0.10 in high-altitude (>5000 m), high-latitude (>60°), desert, and polar regions), thereby improving the overall accuracy and consistency of the AVHRR product. The calibrated AVHRR product achieved a higher consistency with site observations (R2 ≈0.73 at high-latitude sites, 0.53 at high-altitude sites, and 0.62 in arid regions) than the original AVHRR (0.71, 0.42, and 0.58, respectively). Analogous corrections were applied to the pre-2001 AVHRR record, yielding a consistent, nearly 40-year global blue-sky albedo dataset. This harmonized dataset provides a reliable baseline for climate, ecosystem phenology, and hydrology studies.

Fields of Study & Subjects

Remote Sensing in Agriculture Calibration and Measurement Techniques Atmospheric aerosols and clouds

Publication details

Journal / source
International Journal of Remote Sensing
Volume
47
Issue
7
Pages
3062–3086
Publication date
7 February 2026
Language
EN