scholarly journals Estimating Temperature Fields from MODIS Land Surface Temperature and Air Temperature Observations in a Sub-Arctic Alpine Environment

2014 ◽  
Vol 6 (2) ◽  
pp. 946-963 ◽  
Author(s):  
Scott Williamson ◽  
David Hik ◽  
John Gamon ◽  
Jeffrey Kavanaugh ◽  
Gwenn Flowers
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temperature Fields ◽  
Alpine Environment ◽  
Modis Land Surface Temperature ◽  
Temperature Observations

scholarly journals Estimation of Daily Air Temperature Based on MODIS Land Surface Temperature Products over the Corn Belt in the US

2015 ◽  
Vol 7 (1) ◽  
pp. 951-970 ◽  
Author(s):  
Linglin Zeng ◽  
Brian Wardlow ◽  
Tsegaye Tadesse ◽  
Jie Shan ◽  
Michael Hayes ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Corn Belt ◽  
Modis Land Surface Temperature ◽  
The Us

scholarly journals Improving the Performance of Temperature Index Snowmelt Model of SWAT by Using MODIS Land Surface Temperature Data

2014 ◽  
Vol 2014 ◽  
pp. 1-20 ◽  
Author(s):  
Yan Yang ◽  
Takeo Onishi ◽  
Ken Hiramatsu
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temperature Data ◽  
Temperature Index ◽  
Simulation Performance ◽  
Modis Land Surface Temperature ◽  
Snowmelt Model ◽  
Surface Temperature Data

Simulation results of the widely used temperature index snowmelt model are greatly influenced by input air temperature data. Spatially sparse air temperature data remain the main factor inducing uncertainties and errors in that model, which limits its applications. Thus, to solve this problem, we created new air temperature data using linear regression relationships that can be formulated based on MODIS land surface temperature data. The Soil Water Assessment Tool model, which includes an improved temperature index snowmelt module, was chosen to test the newly created data. By evaluating simulation performance for daily snowmelt in three test basins of the Amur River, performance of the newly created data was assessed. The coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) were used for evaluation. The results indicate that MODIS land surface temperature data can be used as a new source for air temperature data creation. This will improve snow simulation using the temperature index model in an area with sparse air temperature observations.

scholarly journals A statistical framework for estimating air temperature using MODIS land surface temperature data

2016 ◽  
Vol 37 (3) ◽  
pp. 1181-1194 ◽  
Author(s):  
Nasime Janatian ◽  
Morteza Sadeghi ◽  
Seyed Hossein Sanaeinejad ◽  
Elham Bakhshian ◽  
Ali Farid ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Temperature Data ◽  
Modis Land Surface Temperature ◽  
Statistical Framework ◽  
Surface Temperature Data
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