A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests
Author(s) -
Mildrexler David J.,
Zhao Maosheng,
Running Steven W.
Publication year - 2011
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2010jg001486
Subject(s) - environmental science , atmospheric sciences , surface air temperature , surface (topology) , meteorology , remote sensing , urban heat island , climatology , geology , precipitation , geography , geometry , mathematics
Most global temperature analyses are based on station air temperatures. This study presents a global analysis of the relationship between remotely sensed annual maximum LST ( LST max ) from the Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and the corresponding site‐based maximum air temperature ( T a max ) for every World Meteorological Organization station on Earth. The relationship is analyzed for different land cover types. We observed a strong positive correlation between LST max and T a max . As temperature increases, LST max increases faster than T a max and captures additional information on the concentration of thermal energy at the Earth's surface, and biophysical controls on surface temperature, such as surface roughness and transpirational cooling. For hot conditions and in nonforested cover types, LST is more closely coupled to the radiative and thermodynamic characteristics of the Earth than the air temperature ( T air ). Barren areas, shrublands, grasslands, savannas, and croplands have LST max values between 10°C and 20°C hotter than the corresponding T a max at higher temperatures. Forest cover types are the exception with a near 1:1 relationship between LST max and T a max across the temperature range and 38°C as the approximate upper limit of LST max with the exception of subtropical deciduous forest types where LST max occurs after canopy senescence. The study shows a complex interaction between land cover and surface energy balances. This global, semiautomated annual analysis could provide a new, unique, monitoring metric for integrating land cover change and energy balance changes.
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