Land surface temperature from Ka band (37 GHz) passive microwave observations

Abstract

[1] An alternative to thermal infrared satellite sensors for measuring land surface temperature (T s ) is presented. The 37 GHz vertical polarized brightness temperature is used to derive T s because it is considered the most appropriate microwave frequency for temperature retrieval. This channel balances a reduced sensitivity to soil surface characteristics with a relatively high atmospheric transmissivity. It is shown that with a simple linear relationship, accurate values for T s can be obtained from this frequency, with a theoretical bias of within 1 K for 70% of vegetated land areas of the globe. Barren, sparsely vegetated, and open shrublands cannot be accurately described with this single channel approach because variable surface conditions become important. The precision of the retrieved land surface temperature is expected to be better than 2.5 K for forests and 3.5 K for low vegetation. This method can be used to complement existing infrared derived temperature products, especially during clouded conditions. With several microwave radiometers currently in orbit, this method can be used to observe the diurnal temperature cycles with surprising accuracy.

Comparison of Microwave and Infrared Land Surface Temperature Products Over the NAFE'06 Research Sites

“…For four different sensors, the Ka-band data are extracted with the center of pixel nearest to the ground stations. The specifications of the MW sensors are listed in Table II. The brightness temperatures are converted into T s (T S,MW ) according to Holmes et al [10], [11] T S,MW = 1.11T B,Ka − 15.20 for T B > 259.8 K…”

“…This Ka-band temperature retrieval is recently expanded with the help of a global ground truth network and more strictly related to the skin temperature [10], [11], instead of to the 1-cm 1545-598X/$25.00 © 2008 IEEE [12] were compared to satellite-derived MW T s observations. The NAFE'06 campaign was located in the western part of the Murrumbidgee catchment, Australia.…”

Estimation of Land Surface Temperature through Blending MODIS and AMSR-E Data with the Bayesian Maximum Entropy Method

“…The first is based on thermal infrared (TIR) remotely sensed data, such as single channel algorithms, temperature and emissivity separation algorithms, and split-window algorithms, which have been used for sensors with one, two or multiple TIR channels, respectively [16][17][18][19][20]. The other is based on passive microwave (PMW) remotely sensed data, including the empirical and statistical, semi-empirical and physical methods, in which the lower-frequency (ď37 GHz) brightness temperatures (TB) and surface emissivities from passive microwave radiometry are usually used [21][22][23][24][25][26][27][28]. For the former method, the retrieved LSTs are mostly within a relatively fine spatial scale; for example, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Aqua satellite platforms provide daily, eight-day, and monthly LST products at 1 km (near) and 6 km (near) resolution.…”

Atmospheric Effect Analysis and Correction of the Microwave Vegetation Index

“…For the land surface parameters, the accuracy of surface temperature and surface elevation will also have an influence on the atmospheric-corrected MVI_B. According to the validation in the paper [23], the accuracy of land surface temperature estimated using Equation (9) is about 4.5 K. Surface elevation used in this study was a combination of SRTM DEM and DEM from MYD03. The accuracy of SRTM DEM is less than 10 m [25], and the DEM from MYD03 is expected to have, at worst, 100 m uncertainty in the vertical direction [26].…”

“…In clear sky conditions, T s was directly derived from the MODIS land surface temperature product [22]. Under cloudy sky conditions, T s was estimated based on the vertical polarized brightness temperature at 36.5 GHz of AMSR-E [23]. The formula is shown in Equation (9):…”