Abstract
Global surface skin temperature has been retrieved from MetOp IASI ultraspectral infrared measurements over the past 13+ years. Monthly and spatially gridded surface skin temperature is produced to show some phenomena associated with its natural variability. This article has aimed to demonstrate that thermal infrared remote sensing data can be used for monitoring global surface environmental characteristics and associated change through the continuity observations of MetOp series. The time-series anomalies of surface skin temperature are used to estimate its associated trend. Error estimation and evaluation has been performed and discussed in order to understand the uncertainty and variability in the trends. The trends derived from IASI global surface skin temperatures are compared with those of the NASA GISS global surface air temperature. Despite the physical differences between surface skin and air temperatures, reasonable agreement is shown between these two datasets indicating consistency and global surface warming, achieving our core objective of investigating the surface skin temperature retrieved from MetOp satellites’ measurements and associated trends. The inferred trend of IASI global surface skin temperature illustrates an approximate 0.037±0.002 K/yr. global average increase has occurred during the September 2007—present (November 2020) time period; this warming trend is more pronounced in the northern hemisphere.
Highlights
G LOBAL or regional surface air temperature analyses are routinely performed to monitor global climate change by many groups such as the NOAA National Centers for Environmental Information, the Hadley Centre of the U.K
We have developed an inversion scheme, able to deal with cloudy as well as cloud-free radiances observed with ultraspectral thermal infrared (TIR) sounders, and applied it to Interferometer Atmospheric Sounding Instrument (IASI) data for retrieving atmospheric thermodynamic and surface or cloud microphysical parameters simultaneously [16]
Simultaneous retrieval of Earth’s surface skin temperature and emissivity from TIR spectra is critical to achieving highest retrieval accuracy, and a proper cloud detection within a retrieval scheme is essential to filter out the data influenced by cloud attenuation
Summary
G LOBAL or regional surface air temperature analyses are routinely performed to monitor global climate change by many groups such as the NOAA National Centers for Environmental Information, the Hadley Centre of the U.K. Global surface parameters like surface skin temperature (Tss) and emissivity (εν) are important parameters in physical processes of the Earth’s surface, such as energy fluxes between the surface and atmosphere, and water balance on regional or global scales [2], [6] These surface parameters provide information on the surface equilibrium state of temporal and spatial variability [6]. Satellite-measurement-derived Earth’s surface skin temperature and its anomaly trends is useful to monitor our global environment, even though many studies and trend analyses have been done with Earth’s Tsa. Tss and Tsa are physically different parameters and Tss is relatively unrepresented in previous work. IASI measurements are used to obtain Tss globally for analysis and assessment of trends from regional to global scales Such global Tss estimation can only be enabled by utilization of satellite remote sensing datasets.
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