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A spatiotemporal analysis of the relationship between near-surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series

Good, E. J., Ghent, D. J., Bulgin, C. E. and Remedios, J. J. (2017) A spatiotemporal analysis of the relationship between near-surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series. Journal of Geophysical Research: Atmospheres, 122 (17). pp. 9185-9210. ISSN 2169-8996

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To link to this item DOI: 10.1002/2017JD026880

Abstract/Summary

The relationship between satellite land surface temperature (LST) and ground-based observations of 2m air temperature (T2m) is characterised in space and time using >17 years of data. The analysis uses a new monthly LST climate data record (CDR) based on the Along-Track Scanning Radiometer (ATSR) series, which has been produced within the European Space Agency GlobTemperature project (http://www.globtemperature.info/). Global LST-T2m differences are analysed with respect to location, land cover, vegetation fraction and elevation, all of which are found to be important influencing factors. LSTnight (~10 pm local solar time, clear-sky only) is found to be closely coupled with minimum T2m (Tmin, all-sky) and the two temperatures generally consistent to within ±5 °C (global median LSTnight- Tmin= 1.8 °C, interquartile range = 3.8 °C). The LSTday (~10 am local solar time, clear-sky only)-maximum T2m (Tmax, all-sky) variability is higher (global median LSTday- Tmax= -0.1°C, interquartile range = 8.1 °C) because LST is strongly influenced by insolation and surface regime. Correlations for both temperature pairs are typically >0.9 outside of the tropics. The monthly global and regional anomaly time series of LST and T2m – which are completely independent data sets - compare remarkably well. The correlation between the data sets is 0.9 for the globe with 90% of the CDR anomalies falling within the T2m 95% confidence limits. The results presented in this study present a justification for increasing use of satellite LST data in climate and weather science, both as an independent variable, and to augment T2m data acquired at meteorological stations.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:71902
Publisher:American Geophysical Union

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