Abstract
Land surface temperature (LST) plays a critical role in the water cycle and energy balance at global and regional scales. Large-scale LST estimates can be obtained from satellite observations and reanalysis data. In this study, we first investigate the long-term changes of LST during 2003–2017 on a per-pixel basis using three different datasets derived from (i) the Atmospheric Infrared Sounder (AIRS) onboard Aqua satellite, (ii) the Moderate Resolution Imaging Spectroradiometer (MODIS) also aboard Aqua, and (iii) the recently released ERA5-Land reanalysis data. It was found that the spatio-temporal patterns of these data agree very well. All three products globally showed an uptrend in the annual average LST during 2003–2017 but with considerable spatial variations. The strongest increase was found over the region north of 45° N, particularly over Asian Russia, whereas a slight decrease was observed over Australia. The regression analysis indicated that precipitation (P), incoming surface solar radiation (SW↓), and incoming surface longwave radiation (LW↓) can together explain the inter-annual LST variations over most regions, except over tropical forests, where the inter-annual LST variation is low. Spatially, the LST changes during 2003–2017 over the region north of 45° N were mainly influenced by LW↓, while P and SW↓ played a more important role over other regions. A detailed look at Asian Russia and the Amazon rainforest at a monthly time scale showed that warming in Asian Russia is dominated by LST increases in February–April, which are closely related with the simultaneously increasing LW↓ and clouds. Over the southern Amazon, the most apparent LST increase is found in the dry season (August–September), primarily affected by decreasing P. In addition, increasing SW↓ associated with decreasing atmospheric aerosols was another factor found to cause LST increases. This study shows a high level of consistency among LST trends derived from satellite and reanalysis products, thus providing more robust characteristics of the spatio-temporal LST changes during 2003–2017. Furthermore, the major climatic drivers of LST changes during 2003–2017 were identified over different regions, which might help us predict the LST in response to changing climate in the future.
Highlights
Introduction affiliationsLand surface temperature (LST) can be recognized as the heat emissions on the Earth’s surface and refers to the radiative skin temperature on the land surface [1]
Identification of the Spatio-Temporal Consistency of LST Trends Derived from Atmospheric Infrared Sounder (AIRS), Moderate Resolution Imaging Spectroradiometer (MODIS), and ERA5-Land
This study investigated the trends in annual average LST during 2003–2017 over each 1◦ grid cell at the global scale using two satellite products (AIRS and MODIS) and one reanalysis product (ERA5-Land)
Summary
Introduction affiliationsLand surface temperature (LST) can be recognized as the heat emissions on the Earth’s surface and refers to the radiative skin temperature on the land surface [1]. LST is a vital indicator for studying environmental changes, hydrological conditions, and the Earth’s energy balance [2,3,4]. LST measurements can be obtained from (i) the ground observations of in situ stations or networks [5], (ii) retrievals of remote sensing data [6], and (iii) reanalysis data based on surface energy balance model estimations [7]. In situ measurements have high accuracy and temporal resolution, their point-scale representativeness and the sparse distribution of meteorological stations are major limitations for both their research and applications at continental to global scales [8]. The accuracy of interpolated LST products is based on the density of ground observations.
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