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Article

Assessment of MODIS and VIIRS Ice Surface Temperature Products over the Antarctic Ice Sheet

1
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China
2
Institute of Earth Surface System and Hazards, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China
3
Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
4
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, 3584 CS Utrecht, The Netherlands
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(6), 955; https://doi.org/10.3390/rs17060955
Submission received: 11 February 2025 / Revised: 28 February 2025 / Accepted: 5 March 2025 / Published: 7 March 2025

Abstract

The ice surface temperature (IST) derived from thermal infrared remote sensing is crucial for accurately monitoring ice or snow surface temperatures in the polar region. Generally, the remote sensing IST needs to be validated by the in situ IST to ensure its accuracy. However, due to the limited availability of in situ IST measurements, previous studies in the validation of remote sensing ISTs are scarce in the Antarctic ice sheet. This study utilizes ISTs from eight broadband radiation stations to assess the accuracy of the latest-released Moderate Resolution Imaging Spectroradiometer (MODIS) IST and Visible Infrared Imager Radiometer Suite (VIIRS) IST products, which were derived from two different algorithms, the Split-Window (SW-based) algorithm and the Temperature–Emissivity Separation (TES-based) algorithm, respectively. This study also explores the sources of uncertainty in the validation process. The results reveal prominent errors when directly validating remote sensing ISTs with the in situ ISTs, which can be attributed to incorrect cloud detection due to the similar spectral characteristics of cloud and snow. Hence, cloud pixels are misclassified as clear pixels in the satellite cloud mask during IST validation, which emphasizes the severe cloud contamination of remote sensing IST products. By using a cloud index (n) to remove the cloud contamination pixels in the remote sensing IST products, the overall uncertainties for the four products are about 2 to 3 K, with the maximum uncertainty (RMSE) reduced by 3.51 K and the bias decreased by 1.26 K. Furthermore, a progressive cold bias in the validation process was observed with decreasing temperature, likely due to atmospheric radiation between the radiometer and the snow surface being neglected in previous studies. Lastly, this study found that the cloud mask errors of satellites are more pronounced during the winter compared to that in summer, highlighting the need for caution when directly using remote sensing IST products, particularly during the polar night.
Keywords: Antarctic ice sheet; MODIS; VIIRS; ice surface temperature; validation; broadband radiation Antarctic ice sheet; MODIS; VIIRS; ice surface temperature; validation; broadband radiation

Share and Cite

MDPI and ACS Style

Shi, C.; Wang, N.; Wu, Y.; Zhang, Q.; Reijmer, C.H.; Smeets, P.C.J.P. Assessment of MODIS and VIIRS Ice Surface Temperature Products over the Antarctic Ice Sheet. Remote Sens. 2025, 17, 955. https://doi.org/10.3390/rs17060955

AMA Style

Shi C, Wang N, Wu Y, Zhang Q, Reijmer CH, Smeets PCJP. Assessment of MODIS and VIIRS Ice Surface Temperature Products over the Antarctic Ice Sheet. Remote Sensing. 2025; 17(6):955. https://doi.org/10.3390/rs17060955

Chicago/Turabian Style

Shi, Chenlie, Ninglian Wang, Yuwei Wu, Quan Zhang, Carleen H. Reijmer, and Paul C. J. P. Smeets. 2025. "Assessment of MODIS and VIIRS Ice Surface Temperature Products over the Antarctic Ice Sheet" Remote Sensing 17, no. 6: 955. https://doi.org/10.3390/rs17060955

APA Style

Shi, C., Wang, N., Wu, Y., Zhang, Q., Reijmer, C. H., & Smeets, P. C. J. P. (2025). Assessment of MODIS and VIIRS Ice Surface Temperature Products over the Antarctic Ice Sheet. Remote Sensing, 17(6), 955. https://doi.org/10.3390/rs17060955

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