Abstract
The ambient air temperature (Ta) is an important environmental parameter which can be estimated from satellite observations of the land surface temperature (LST) using a linear regression model. This paper attempts to answer the question of whether the series of a single pixel or a spatially averaged series over several pixels should be used for modelling Ta from remotely sensed LST data. Sensitivity of LST-Ta relationship to the moderate resolution imaging spectroradiometer (MODIS) window size, which determines the number of pixels contributed in the correlations, over a number of test sites in New Zealand was analysed. LST series of a single pixel over a period of 10 years gave a correlation coefficient \(r\geqslant \) 0.80 with Ta measurements. Bootstrapping by random resampling from seasonal subsets of both time-series was applied to determine seasonal and inter-annual variability of LST-Ta relationship. A fast Fourier filtering was applied for noise reduction and detection of dominant spectra in LST series. Spatially averaged time-series from larger windows, which included more pixels, showed slightly higher agreement with Ta measurements. We considered the effects of wind speed (WS) and wind direction (WD) on the LST-Ta relationship. Highest correlation between Ta and LST time-series was achieved using a 25 × 25 window at 2 ≤ WS < 8 ms−1. No significant effect due to WD was found in the results. MODIS-Terra nighttime (∼10:30 PM) observations showed the highestwhile MODIS-Aqua nighttime (∼1:30 AM) observations showed the lowest agreement with Ta measurements. These results indicate that the best approach for modelling Ta based on LST observations from MODIS in the long-term is to use a spatially averaged LST series over a window of 5 × 5 to 25 × 25 pixels, with a consideration of WS effects and observation times.
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Notes
A detailed discussion about the importance of areally integrated remotely sensed data over point measurements is outlined in Owe et al. (1988).
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Acknowledgments
We acknowledge access to New Zealand’s National Climate Database (Cliflo), provided by the National Institute of Water & Atmospheric Research (NIWA), via an online web-based system which we used to download Ta and other climate parameters. Access to the MODIS LST product via Reverb tool and the MODIS near real-time data from the US National Aeronautics and Space Administration (NASA) is appreciated. Language editions and proof reading of the paper was done by Caroline Cameron-Blackgrove. We also express cordial thanks to the anonymous reviewers and the managing editor of the journal of Theorectical and Applied Climatology, Prof. Dr. Hartmut Grassl, for their invaluable comments which greatly improved the quality of this paper.
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Sohrabinia, M., Zawar-Reza, P. & Rack, W. Spatio-temporal analysis of the relationship between LST from MODIS and air temperature in New Zealand. Theor Appl Climatol 119, 567–583 (2015). https://doi.org/10.1007/s00704-014-1106-2
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DOI: https://doi.org/10.1007/s00704-014-1106-2