Estimating sensible heat flux from remotely sensed moderate resolution imaging spectroradiometer (MODIS) data

Abstract

Sensible heat flux (H) has a high impact on energy exchange between the surface and atmosphere, climate change and climatic and hydrological modeling. In the past, remote sensing of H has become a major area of interest and as a result, various methods have been established for its retrieval. However, large discrepancies between measured and simulated values of H have been observed over land surfaces because of various assumptions and simplifications. This study presents a generalized algorithm for estimation of sensible heat flux that is suitable for a wide range of atmospheric and terrestrial conditions from Moderate Resolution Imaging Spectroradiometer (MODIS) data. MODIS is an adequate sensor to perform regional assessments by means of its high temporal and spatial coverage. Standard built-in atmospheric profiles in Fast Atmospheric Signature Code (F ASCODE) together with atmospheric conditions obtained by periodic radiosounding, once a week, performed at Broglio Space Center (BSC) in Malindi, Kenya were used in simulating MODIS data at 11.03 urn and 12.02 urn wavelengths using PcLnWin software. The General Split Window Technique (GSWT) earlier proposed by Mito er aI., 2006 was modified by removing some of the assumptions it was originally based on, for example air temperature (Ta) being approximately equal to surface temperature (Ts)' and used to retrieve surface temperature taking into account surface and air temperature difference effects, atmospheric water vapour and non- unitary surface emissivity. Formulation of sensible heat flux starting from the improved GSWT, bulk aerodynamic equation and the resulting aerodynamic resistance equation results in a general algorithm which relates sensible heat flux to the surface emittance effect, canopy properties, air temperature and different atmospheric stabilities.Unlike other conventional methods earlier developed for determination of sensible heat flux, a prior knowledge of the surface temperature as an auxiliary input is not necessary in this new algorithm. The estimates of sensible heat flux derived from MODIS using the proposed algorithm compared well with in situ measurements, obtained from Ebro River basin, Spain (41 °18'04"N, 0°'21 '51 "W, elevation 150 m), giving a good correlation coefficient of r = 0.9.