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Atmosphere 2015, 6(8), 1032-1044; doi:10.3390/atmos6081032

Scaling Flux Tower Observations of Sensible Heat Flux Using Weighted Area-to-Area Regression Kriging

1
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China
3
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
Academic Editor: Daniele Contini
Received: 20 December 2014 / Revised: 4 July 2015 / Accepted: 20 July 2015 / Published: 24 July 2015
View Full-Text   |   Download PDF [904 KB, uploaded 24 July 2015]   |  

Abstract

Sensible heat flux (H) plays an important role in characterizations of land surface water and heat balance. There are various types of H measurement methods that depend on observation scale, from local-area-scale eddy covariance (EC) to regional-scale large aperture scintillometer (LAS) and remote sensing (RS) products. However, methods of converting one H scale to another to validate RS products are still open for question. A previous area-to-area regression kriging-based scaling method performed well in converting EC-scale H to LAS-scale H. However, the method does not consider the path-weighting function in the EC- to LAS-scale kriging with the regression residue, which inevitably brought about a bias estimation. In this study, a weighted area-to-area regression kriging (WATA RK) model is proposed to convert EC-scale H to LAS-scale H. It involves path-weighting functions of EC and LAS source areas in both regression and area kriging stages. Results show that WATA RK outperforms traditional methods in most cases, improving estimation accuracy. The method is considered to provide an efficient validation of RS H flux products. View Full-Text
Keywords: heat flux; EC; LAS; upscaling; downscaling; area-to-area regression kriging heat flux; EC; LAS; upscaling; downscaling; area-to-area regression kriging
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Hu, M.; Wang, J.; Ge, Y.; Liu, M.; Liu, S.; Xu, Z.; Xu, T. Scaling Flux Tower Observations of Sensible Heat Flux Using Weighted Area-to-Area Regression Kriging. Atmosphere 2015, 6, 1032-1044.

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