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\begin{document}

\title{Himawari-ANU: A recalibrated geostationary land surface temperature
dataset based on MODIS spatiotemporal characteristics}



\author[1]{Yi Yu}%
\author[2]{Luigi J. Renzullo}%
\author[3]{Tim R. McVicar}%
\author[4]{Thomas G. Van Niel}%
\author[3]{Dejun Cai}%
\author[2]{Siyuan Tian}%
\affil[1]{Fenner School of Environment \& Society, The Australian National University, Canberra, ACT 2601, Australia}%
\affil[2]{Bureau of Meteorology, Canberra, ACT 2600, Australia}%
\affil[3]{CSIRO Environment, Canberra, ACT 2601, Australia}%
\affil[4]{CSIRO Environment, Wembley, WA 6913, Australia}%


\vspace{-1em}



  
  \date{June 06, 2024}


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\begin{abstract}
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 \textless{} 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 (ANU\textsubscript{SZAC}),
against MODIS LST and the Visible Infrared Imaging Radiometer Suite
(VIIRS) LST, as well as~\emph{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 ANU\textsubscript{SZAC}~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\emph{~in-situ}~LST,
the overall mean values of bias (ubRMSE) of baseline, Chiba, Copernicus
and ANU\textsubscript{SZAC}~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.%
\end{abstract}%



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