NDLI: A new physically based method for Air temperature downscaling

Content Provider	IEEE Xplore Digital Library
Author	Yuan Rong Hongbo Su Renhua Zhang Jing Tian Shaohui Chen Yongmin Yang Bin Li
Copyright Year	2011
Description	Author affiliation: Key Laboratory of Water Cycle&Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101, China (Yuan Rong; Hongbo Su; Renhua Zhang; Jing Tian; Shaohui Chen; Yongmin Yang; Bin Li)
Abstract	An international widespread concern about scaling is how to choose appropriate scale or resolution, and how to evaluate the impact of them[1]. Air temperature is an important input variable to estimate terrestrial evapotranspiration based on satellite remote sensing. The air temperature obtained by the observations from surface meteorological stations is limited in their spatial and temporal representation, while the validated GDAS (Global Data Assimilation System) has many advantages, it can provide the simulated temperature data every 3 hours, and it has great value in downscaling analysis. There are three major driving factors of the near surface air temperature: the surface long-wave radiative balance, land-air turbulent heat exchange, and advection. The fluctuation of the Air temperature (2m height level above ground) mainly depends on underlying surface feedback. Northern China was chosen as the study area. Using air temperature data from the GDAS forcing dataset as a data source, we proposed a new method for downscaling air temperature based on land surface temperature. In order to evaluate the performance of our methods, bilinear interpolation, spline interpolation were used in the comparison. To assess the performance of the downscaling approaches, the ground measurements were used to compare with the downscaling results. Experiments show that the effect of static feedback interpolation is the best based on the surface temperature. What we have got are as follows. First, In most plain areas, the air temperature(2m height level above ground) mainly depends on the temperature of the surface temperature. Second, during the process of downscaling, pure mathematic methods appear to be not sufficient. It is necessary that the effects of physical basis be taken into consideration.
Starting Page	1814
Ending Page	1817
File Size	343518
Page Count	4
File Format	PDF
ISBN	9781457710032
ISSN	21537003
e-ISBN	9781457710056
DOI	10.1109/IGARSS.2011.6049474
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Land surface temperature Temperature distribution Ocean temperature Interpolation Spatial resolution Temperature sensors interpolation air temperature downscaling GDAS
Content Type	Text
Resource Type	Article

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