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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #312680
Title: Using microwave observations to estimate land surface temperature during cloudy conditions

Author
item HOLMES, T. - Science Systems, Inc
item Crow, Wade
item HAIN, C. - University Of Maryland
item Anderson, Martha

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 12/15/2014
Publication Date: 1/1/2015
Citation: Holmes, T., Crow, W.T., Hain, C., Anderson, M.C. 2015. Using microwave observations to estimate land surface temperature during cloudy conditions. American Geophysical Union Fall Meeting. Abstract No. GC51D-0451.

Interpretive Summary:

Technical Abstract: Land surface temperature (LST), a key ingredient for physically-based retrieval algorithms of hydrological states and fluxes, remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observations and passive microwave observations (MW). TIR is the most commonly used approach and the method of choice to provide standard LST products for various satellite missions. MW-based LST retrievals on the other hand are not as widely adopted for land applications; currently their principle use is in soil moisture retrieval algorithms. MW and TIR technologies present two highly complementary and independent means of measuring LST. MW observations have a high tolerance to clouds but a low spatial resolution, and TIR has a high spatial resolution with temporal sampling restricted to clear skies. The nature of the temperature at the very surface layer of the land makes it difficult to combine temperature estimates between different methods. The skin temperature is characterized by a strong diurnal cycle that is dependant in timing and amplitude on the exact sensing depth and thermal properties of the vegetation. This paper builds on recent progress in characterizing the main structural components of the DTC that explain differences in TIR and MW estimates of LST. Spatial patterns in DTC timing (phase lag with solar noon) and DTC amplitude have been calculated for TIR, MW and compared to weather prediction estimates. Based on these comparisons MW LST can be matched to the TIR record. This paper will compare in situ measurements of LST with satellite estimates from (downscaled) TIR and (reconciled) MW products. By contrasting the validation results of clear sky days with those of cloudy days the expected tolerance to clouds of the MW observations will be tested. The goal of this study is to determine the weather conditions in which MW can supplement the TIR LST record.