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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.
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Submitted on : Monday, November 14, 2022 - 3:53:15 PM
Last modification on : Tuesday, November 15, 2022 - 3:55:48 AM

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Earth and Space Science - 2022...
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E. J. Good, F. M. Aldred, D. J. Ghent, K. L. Veal, C. Jimenez. An Analysis of the Stability and Trends in the LST_cci Land Surface Temperature Datasets Over Europe. Earth and Space Science, 2022, 9, ⟨10.1029/2022EA002317⟩. ⟨insu-03851607⟩

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