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Solar zenith angle-based calibration of Himawari-8 land surface temperature based on MODIS spatiotemporal characteristics
  • +4
  • Yi Yu,
  • Luigi J. Renzullo,
  • Tim R. McVicar,
  • Thomas G. Van Niel,
  • Dejun Cai,
  • Siyuan Tian,
  • Yichuan Ma
Yi Yu
Fenner School of Environment & Society, The Australian National University, Canberra, ACT 2601, Australia

Corresponding Author:[email protected]

Author Profile
Luigi J. Renzullo
Bureau of Meteorology, Canberra, ACT 2600, Australia
Tim R. McVicar
CSIRO Environment, Canberra, ACT 2601, Australia
Thomas G. Van Niel
CSIRO Environment, Wembley, WA 6913, Australia
Dejun Cai
CSIRO Environment, Canberra, ACT 2601, Australia
Siyuan Tian
Bureau of Meteorology, Canberra, ACT 2600, Australia
Yichuan Ma
Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China


The geostationary Himawari-8 satellite offers a unique opportunity to monitor sub-daily thermal dynamics over Asia and Oceania, and several operational land surface temperature (LST) retrieval algorithms have been developed for this purpose. However, studies have reported inconsistency between LST data obtained from geostationary and polar-orbiting platforms, particularly for daytime LST, which usually shows directional artefacts and can be strongly impacted by viewing and illumination geometries and shadowing effects. To overcome this challenge, Solar Zenith Angle (SZA) serves as an ideal physical variable to quantify systematic differences between platforms. Here we presented an SZA-based Calibration (SZAC) method to operationally calibrate the daytime component of a split-window retrieved Himawari-8 LST (referred to here as the baseline). SZAC describes the spatial heterogeneity and magnitude of diurnal LST discrepancies from different products. The SZAC coefficient was spatiotemporally optimised against highest-quality assured (error < 1 K) pixels from the MODerate-resolution Imaging Spectroradiometer (MODIS) daytime LST between 01/Jan/2016 and 31/Dec/2020. We evaluated the calibrated LST data, referred to as the Australian National University LST with SZAC (ANUSZAC), against MODIS LST and the Visible Infrared Imaging Radiometer Suite (VIIRS) LST, as well as in-situ LST from the OzFlux network. Two peer Himawari-8 LST products from Chiba University and the Copernicus Global Land Service were also collected for comparisons. The median daytime bias of ANUSZAC LST against Terra-MODIS LST, Aqua-MODIS LST and VIIRS LST was 1.52 K, 0.98 K and -0.63 K, respectively, which demonstrated improved performance compared to baseline (5.37 K, 4.85 K and 3.02 K, respectively) and Chiba LST (3.71 K, 2.90 K and 1.07 K, respectively). All four Himawari-8 LST products showed comparable performance of unbiased root mean squared error (ubRMSE), ranging from 2.47 to 3.07 K, compared to LST from polar-orbiting platforms. In the evaluation against in-situ LST, the overall mean values of bias (ubRMSE) of baseline, Chiba, Copernicus and ANUSZAC LST during daytime were 4.23 K (3.74 K), 2.16 K (3.62 K), 1.73 K (3.31 K) and 1.41 K (3.24 K), respectively, based on 171,289 hourly samples from 20 OzFlux sites across Australia between 01/Jan/2016 and 31/Dec/2020. In summary, the SZAC method offers a promising approach to enhance the reliability of geostationary LST retrievals by incorporating the spatiotemporal characteristics observed by accurate polar-orbiting LST data. Furthermore, it is possible to extend SZAC for LST estimation by using data acquired by geostationary satellites in other regions, e.g., Europe, Africa and Americas, as this could improve our understanding of the error characteristics of overlapped geostationary imageries, allowing for targeted refinements and calibrations to further enhance applicability.
Land surface temperature; Geostationary; Himawari-8; Diurnal temperature cycle; Calibration; Solar zenith angle; MODIS; VIIRS
23 Nov 2023Submitted to ESS Open Archive
27 Nov 2023Published in ESS Open Archive
Jul 2024Published in Remote Sensing of Environment volume 308 on pages 114176. 10.1016/j.rse.2024.114176