An Analysis of the Stability and Trends in the LST_cci Land Surface Temperature Datasets Over Europe

Abstract

Long‐term satellite land surface temperature (LST) data are desirable to augment 2m air temperatures (T2m) measured in situ and as an independent measure of surface temperature change. However, previous studies show variable agreement between LST and T2m time series. The objective of this study is to assess the stability and trends in six new LST data sets from the European Space Agency's Climate Change Initiative for LST (LST_cci). LST anomalies are compared with homogenized station T2m anomalies over Europe, which verifies all six data sets are well coupled (LST vs T2m anomaly correlations and slopes: 0.6–0.9). The temporal stability of the LST_cci data is assessed through a comparison with the T2m anomaly time series. Only the LST_cci data sets for the MODerate resolution Imaging Spectroradiometer (MODIS) onboard Aqua and the Advanced Along‐Track Scanning Radiometer (AATSR) appear stable; the MODIS/Terra, ATSR‐2, and multisensor InfraRed and MicroWave data sets show non‐climatic discontinuities associated with changes in sensor and/or drift over time. For MODIS/Aqua (2002–2018), significant trends in LST of 0.64–0.66 K/decade compare well with the equivalent T2m trends of 0.52–0.59 K/decade. The LST and T2m trends for AATSR (2002–2012) are found to be statistically insignificant, likely due to the comparatively short study period and specific years available for analysis. No evidence is found to suggest that trends calculated using cloud‐free InfraRed observations are affected by clear‐sky bias. This study suggests that satellite LST data can be used to assess warming trends over land and for other climate applications if the required homogeneity is assured.

Satellite-Derived Land Surface Temperature Dynamics in the Context of Global Change—A Review

“…The comparison between the global MODIS LST trend and the trend of ERA 5 reanalysis LST showed good accordance in the magnitude as well as in the spatial distribution [10]. Another study by [175] compared daily LST anomalies derived from the CCI LST datasets with daily air temperature measurements and also observed good accordance. These kinds of studies show that remotely sensed LST is a reliable information source for climate change studies.…”

“…In addition to land cover changes, which lead to LST changes within a short time, longterm trends of LST can provide deep insights concerning the climate change of our planet. While the difference between instantaneous LST and air temperature can be high, there is a strong agreement in long-term trends between these two variables [155,175]. This, and the fact that thermal remote sensing data have been around for decades now, make LST a valuable resource for measuring global warming.…”

Spatiotemporal Analysis of Land Surface Temperature in Response to Land Use and Land Cover Changes: A Remote Sensing Approach

“…A combination of imagery from different Landsat sensors (5,7,8) was required to establish the long-term LST timeline of this study. However, this combination of sensors also poses specific issues that need to be considered during analysis.…”

“…E_m = E_s (1 − P_v) + E_v × P_v (5) where E_s and E_v are the emissivity of soil and vegetation. For this study, the emissivity of soil and vegetation were selected as 0.97 and 0.985 following a previous study [55].…”

“…Consequently, it is essential to note that LST differs from the air temperature typically featured in daily weather reports [2]. However, previous studies have demonstrated a strong correlation between LST and air temperature in urban areas [3][4][5]. Moreover, LST is an essential input for climatic, hydrological, ecological, and biogeochemical models [6].…”