Publications

Cheng, Q; Hao, WF; Ma, C; Ye, F; Luo, J; Qu, Y (2023). Daily Arctic Sea-Ice Albedo Retrieval With a Multiband Reflectance Iteration Algorithm. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 61, 4302712.

Abstract
Arctic sea-ice albedo plays a crucial role in regional and global climate changes. A high-quality albedo product over Arctic sea-ice surfaces with fine spatial and temporal resolution is scarce and therefore greatly required. This study proposed a new and operational algorithm named multiband reflectance iteration (MBRI) to estimate broadband albedo of Arctic sea ice from Moderate Resolution Imaging Spectroradiometer (MODIS). This algorithm uses an iteration procedure with multiband spectral reflectance data to retrieve the sea-ice bidirectional reflectance distribution function (BRDF), which is built based on the combination of the asymptotic radiative transfer (ART) model and the three-component ocean water albedo (TCOWA) model. Then, the broadband albedo is calculated from single-angular/date observations of MODIS. A daily 500-m albedo product over Arctic sea-ice regions from 2000 to 2017 is generated. Validation with the in situ sea-ice measurements from Tara Arctic Ocean expedition shows that the MBRI retrieved albedo has a correlation coefficient ${R}$ of 0.79, a bias of 0.005, and an RMSE of 0.067. Moreover, compared with the automatic weather station (AWS) measurements from the Program for Monitoring of the Greenland Ice Sheet (PROMICE), the MBRI albedo achieves more satisfactory performance with an ${R}$ value of 0.92, a bias of 0.019, and an RMSE of 0.062. Finally, the MBRI albedo trend analysis reveals a decreasing trend for Arctic sea-ice albedo throughout the past two decades, with a significant trend slope of -0.21% per year in the September sea-ice zone.

DOI:
10.1109/TGRS.2023.3323506

ISSN:
1558-0644