Multiscale and multisource data fusion for full-coverage PM2.5 concentration mapping: Can spatial pattern recognition come with modeling accuracy?

2022 ◽  
Vol 184 ◽  
pp. 31-44
Author(s):  
Kaixu Bai ◽  
Ke Li ◽  
Jianping Guo ◽  
Ni-Bin Chang
2004 ◽  
Vol 14 (9) ◽  
pp. 818-823 ◽  
Author(s):  
Christian Graff ◽  
Gwenaël Kaminski ◽  
Michael Gresty ◽  
Théophile Ohlmann

2007 ◽  
Vol 22 (2) ◽  
pp. 204-217 ◽  
Author(s):  
P. S. Lucio ◽  
F. C. Conde ◽  
A. M. Ramos

This article attempts to quantify the spatial uncertainties associated with extreme temperature’s response, by assessing data derived from climate model. This is undertaken by a comparison of the spatial pattern of a long-term time-series aggregation (1960/61-1989/90) for extreme temperatures simulated by a particular GCM (the UK Met Office - Hadley Centre climate model, HadCM3) to that of the USA NCAR NCEP Reanalyses, which are considered as ‘truth’, over the MICE (Modelling the Impacts of Climate Extremes - EU Project) spatial domain. Since evaluation of models is crucial to assessing future scenarios, the aim of this study is to investigate whether the extreme values predicted by the HadCM3 climate model can simulate those produced by NCEP Reanalyses, assuming that the extremes of both models are realizations of the same spatial stochastic process. To get more useful information about the uncertainties surrounding spatial climate projection, one also has to analyze the pattern of temperature extremes in terms of their anomalies. A common technical issue in the assessment of numerical spatial models is based on the Principal Components Analysis and Bayesian Classification for spatial pattern recognition. These methodologies are very important and useful for guiding an evolutionary statistical model-building process. This study leads to the conclusion that the HadCM3 Simulations do not realistically reproduce the NCEP Reanalyses, despite the fact that the climatology of extremes has demonstrated very similar spatial patterns. It is likely therefore that such instability may persist in the future.


Author(s):  
Andreas Christian Braun ◽  
Carolina Rojas ◽  
Cristian Echeverri ◽  
Franz Rottensteiner ◽  
Hans-Peter Bahr ◽  
...  

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