In:
Earth System Science Data, Copernicus GmbH, Vol. 14, No. 7 ( 2022-07-08), p. 3091-3113
Abstract:
Abstract. Daily mean land surface temperatures (LSTs) acquired from
polar orbiters are crucial for various applications such as global and
regional climate change analysis. However, thermal sensors from
polar orbiters can only sample the surface effectively with very limited
times per day under cloud-free conditions. These limitations have produced a
systematic sampling bias (ΔTsb) on the daily mean LST
(Tdm) estimated with the traditional method, which uses the averages of
clear-sky LST observations directly as the Tdm. Several methods have
been proposed for the estimation of the Tdm, yet they are becoming less
capable of generating spatiotemporally seamless Tdm across the globe.
Based on MODIS and reanalysis data, here we propose an improved annual and
diurnal temperature cycle-based framework (termed the IADTC framework) to
generate global spatiotemporally seamless Tdm products ranging from 2003
to 2019 (named the GADTC products). The validations show that the IADTC
framework reduces the systematic ΔTsb significantly. When
validated only with in situ data, the assessments show that the mean absolute
errors (MAEs) of the IADTC framework are 1.4 and 1.1 K for SURFRAD and
FLUXNET data, respectively, and the mean biases are both close to zero.
Direct comparisons between the GADTC products and in situ measurements indicate
that the MAEs are 2.2 and 3.1 K for the SURFRAD and FLUXNET datasets,
respectively, and the mean biases are −1.6 and −1.5 K for these two
datasets, respectively. By taking the GADTC products as references, further
analysis reveals that the Tdm estimated with the traditional averaging
method yields a positive systematic ΔTsb of greater than 2.0 K
in low-latitude and midlatitude regions while of a relatively small value in
high-latitude regions. Although the global-mean LST trend (2003 to 2019)
calculated with the traditional method and the IADTC framework is relatively
close (both between 0.025 to 0.029 K yr−1), regional discrepancies in LST
trend do occur – the pixel-based MAE in LST trend between these two
methods reaches 0.012 K yr−1. We consider the IADTC framework can guide the
further optimization of Tdm estimation across the globe, and the
generated GADTC products should be valuable in various applications such as
global and regional warming analysis. The GADTC products are freely
available at https://doi.org/10.5281/zenodo.6287052 (Hong et
al., 2022).
Type of Medium:
Online Resource
ISSN:
1866-3516
DOI:
10.5194/essd-14-3091-2022
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2022
detail.hit.zdb_id:
2475469-9
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