Good, E. J., Ghent, D. J., Bulgin, C. E.
ORCID: https://orcid.org/0000-0003-4368-7386 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
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.
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| Item Type | Article |
| URI | https://centaur.reading.ac.uk/id/eprint/71902 |
| Identification Number/DOI | 10.1002/2017JD026880 |
| Refereed | Yes |
| Divisions | Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology |
| Publisher | American Geophysical Union |
| Download/View statistics | View download statistics for this item |
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