Optimal estimation of areal values of near-land-surface temperatures for testing global and local spatio-temporal trends

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dc.contributor.author Wang, Hong
dc.contributor.author Pardo Iguzquiza, Eulogio
dc.contributor.author Dowd, Peter A.
dc.contributor.author Yang, Yongguo
dc.date.accessioned 2021-02-18T10:59:48Z
dc.date.available 2021-02-18T10:59:48Z
dc.date.issued 2017-09
dc.identifier.citation Computers and Geosciences, vol.106, 109-117 es_ES
dc.identifier.issn 0098-3004
dc.identifier.uri http://hdl.handle.net/20.500.12468/841
dc.description.abstract This paper provides a solution to the problem of estimating the mean value of near-land-surface temperature over a relatively large area (here, by way of example, applied to mainland Spain covering an area of around half a million square kilometres) from a limited number of weather stations covering a non-representative (biased) range of altitudes. As evidence mounts for altitude-dependent global warming, this bias is a significant problem when temperatures at high altitudes are under-represented. We correct this bias by using altitude as a secondary variable and using a novel clustering method for identifying geographical regions (clusters) that maximize the correlation between altitude and mean temperature. In addition, the paper provides an improved regression kriging estimator, which is optimally determined by the cluster analysis. The optimal areal values of near-land-surface temperature are used to generate time series of areal temperature averages in order to assess regional changes in temperature trends. The methodology is applied to records of annual mean temperatures over the period 1950–2011 across mainland Spain. The robust non-parametric Theil-Sen method is used to test for temperature trends in the regional temperature time series. Our analysis shows that, over the 62-year period of the study, 78% of mainland Spain has had a statistically significant increase in annual mean temperature. es_ES
dc.description.sponsorship School of Resources and Geosciences, China University of Mining and Technology, China es_ES
dc.description.sponsorship Instituto Geológico y Minero de España, España es_ES
dc.description.sponsorship University of Adelaide, Australia es_ES
dc.description.sponsorship Australian Research Council, Australia es_ES
dc.language.iso en es_ES
dc.publisher Elsevier es_ES
dc.relation NSFC41672324 es_ES
dc.relation NSFC41430317 es_ES
dc.relation CGL2015-71510-R es_ES
dc.relation DP110104766 es_ES
dc.rights Acceso abierto es_ES
dc.subject Constrained spatial clustering es_ES
dc.subject Temperature-altitude correlation es_ES
dc.subject Regression kriging es_ES
dc.subject Time series es_ES
dc.subject Temperature trend detection es_ES
dc.subject Global warming es_ES
dc.title Optimal estimation of areal values of near-land-surface temperatures for testing global and local spatio-temporal trends es_ES
dc.type Postprint es_ES
dc.relation.publisherversion https://www.sciencedirect.com/science/article/pii/S0098300417301310?via%3Dihub es_ES
dc.description.funder Ministry of Science and Technology, China es_ES
dc.description.funder China Scholarship Council, China es_ES
dc.description.funder Ministerio de Economía, Industria y Competitividad, España es_ES
dc.identifier.doi https://doi.org/10.1016/j.cageo.2017.06.002 es_ES
dc.coverage.spatialStudy España es_ES


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