Abstract
In many disciplines, knowledge on the accuracy of Land Surface Temperature (LST) as an input is of great importance. One of the most efficient methods in LST evaluation is cross validation. Well-documented and validated polar satellites with a high spatial resolution can be used as references for validating geostationary LST products. This study attempted to investigate the discrepancies between a Moderate Resolution Imaging Spectro-radiometer (MODIS) and Indian National Satellite (INSAT-3D) LSTs for high temperatures, focusing on six deserts with sand dune land cover in the Middle East from 3 March 2015 to 24 August 2016. Firstly, the variability of LSTs in the deserts of the study area was analyzed by comparing the mean, Standard Deviation (STD), skewness, minimum, and maximum criteria for each observation time. The mean value of the LST observations indicated that the MYD-D observation times are closer to those of diurnal maximum and minimum LSTs. At all times, the LST observations exhibited a negative skewness and the STD indicated higher variability during times of MOD-D. The observed maximum LSTs from MODIS collection 6 showed higher values in comparison with the last versions of LSTs for hot spot regions around the world. After the temporal, spatial, and geometrical matching of LST products, the mean of the MODIS—INSAT LST differences was calculated for the study area. The results demonstrated that discrepancies increased with temperature up to +15.5 K. The slopes of the mean differences were relatively similar for all deserts except for An Nafud, suggesting an effect of View Zenith Angle (VZA). For modeling the discrepancies between two sensors in continuous space, the Diurnal Temperature Cycles (DTC) of both sensors were constructed and compared. The sample DTC models approved the results from discrete LST subtractions and proposed the uncertainties within MODIS DTCs. The authors proposed that the observed LST discrepancies in high temperatures could be the result of inherent differences in LST retrieval algorithms.
Highlights
Land Surface Temperature (LST) is a key variable in the study of the surface energy budget and land surface modeling
LST comparisons of both sensors in high temperatures were conducted by the following steps: (1) Analysis of temporal variability of MOD11A1 LST products over the study area; (2) data preparation; (3) investigation of variability of LSTs in sand dune deserts; (4) spatial, angular, and temporal matching; (5) LST difference calculation for four observation times of Moderate Resolution Imaging Spectro-radiometer (MODIS) during one day and interpolated
The results of this study showed considerable discrepancies between INSAT and daily MODIS
Summary
Land Surface Temperature (LST) is a key variable in the study of the surface energy budget and land surface modeling. LST is an indicator of long wave, sensible, and latent heat flux, and is used to study land surface processes and the lower boundary condition from local to global scales [1,2]. LST is critical for accurately retrieving important climatic variables, such as relative humidity [8], soil moisture [9,10], canopy evapotranspiration [11], and surface heat and water fluxes [12]. 2017, 9, 347 and climatological modeling, some studies have analyzed it as a standalone product for monitoring temperature changes, causes, and consequences. Other researchers have used it as an indicator of other parameter changes in many disciplines [13,14,15,16,17,18,19,20]
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