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Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C) Data

View Article: PubMed Central - PubMed

ABSTRACT

On the basis of the radiative transfer theory, this paper addressed the estimate of Land Surface Temperature (LST) from the Chinese first operational geostationary meteorological satellite-FengYun-2C (FY-2C) data in two thermal infrared channels (IR1, 10.3-11.3 μm and IR2, 11.5-12.5 μm), using the Generalized Split-Window (GSW) algorithm proposed by Wan and Dozier (1996). The coefficients in the GSW algorithm corresponding to a series of overlapping ranging of the mean emissivity, the atmospheric Water Vapor Content (WVC), and the LST were derived using a statistical regression method from the numerical values simulated with an accurate atmospheric radiative transfer model MODTRAN 4 over a wide range of atmospheric and surface conditions. The simulation analysis showed that the LST could be estimated by the GSW algorithm with the Root Mean Square Error (RMSE) less than 1 K for the sub-ranges with the Viewing Zenith Angle (VZA) less than 30° or for the sub-rangs with VZA less than 60° and the atmospheric WVC less than 3.5 g/cm2 provided that the Land Surface Emissivities (LSEs) are known. In order to determine the range for the optimum coefficients of the GSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according to the land surface classification or using the method proposed by Jiang et al. (2006); and the WVC could be obtained from MODIS total precipitable water product MOD05, or be retrieved using Li et al.' method (2003). The sensitivity and error analyses in term of the uncertainty of the LSE and WVC as well as the instrumental noise were performed. In addition, in order to compare the different formulations of the split-window algorithms, several recently proposed split-window algorithms were used to estimate the LST with the same simulated FY-2C data. The result of the intercomparsion showed that most of the algorithms give comparable results.

No MeSH data available.


Plot of the atmospheric water vapor content as function of atmospheric temperature T0 in the first boundary layer of the selected 1413 atmospheric profiles in TIGR2002.
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f1-sensors-08-00933: Plot of the atmospheric water vapor content as function of atmospheric temperature T0 in the first boundary layer of the selected 1413 atmospheric profiles in TIGR2002.

Mentions: Keeping in mind that a practical LST algorithm should accommodate atmospheric variations wide enough to cover all possible real situations, two radiosonde observation databases were taken into account in our simulation. One is the latest version of the Thermodynamic Initial Guess Retrieval (TIGR) database TIGR2002, which was constructed by the Laboratoire de Meteorologie Dynamique (LMD) and represents a worldwide set of atmospheric situations (2311 radisoundings) from polar to tropical atmosphere with varying water vapor amounts ranging from 0.1 to 8 g/cm2 (http://ara.lmd.polytechnique.fr/htdocs-public/products/TIGR/TIGR.html). The other is the six standard atmospheric profiles (tropical, mid-latitude summer, mid-latitude winter, sub-arctic summer, sub-arctic winter, and US76) stored in the MODTRAN 4. For LST retrieval, we only consider atmospheric variation in clear-sky conditions. Consequently, the profiles with relative humidity at one of levels greater than 90% in TIGR2002 were discarded as this seldom happens under clear-sky conditions. Therefore, 1413 representative atmospheric situations were extracted from TIGR2002. Figure 1 shows a plot of the atmospheric Water Vapor Content (WVC) as function of the atmospheric temperature T0 in the first boundary layer of these selected atmospheres. As shown in this figure, the T0 varies from 231 K to 315 K and the atmospheric WVC changes from 0.06 g/cm2 to 6.44 g/cm2.


Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C) Data
Plot of the atmospheric water vapor content as function of atmospheric temperature T0 in the first boundary layer of the selected 1413 atmospheric profiles in TIGR2002.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3927530&req=5

f1-sensors-08-00933: Plot of the atmospheric water vapor content as function of atmospheric temperature T0 in the first boundary layer of the selected 1413 atmospheric profiles in TIGR2002.
Mentions: Keeping in mind that a practical LST algorithm should accommodate atmospheric variations wide enough to cover all possible real situations, two radiosonde observation databases were taken into account in our simulation. One is the latest version of the Thermodynamic Initial Guess Retrieval (TIGR) database TIGR2002, which was constructed by the Laboratoire de Meteorologie Dynamique (LMD) and represents a worldwide set of atmospheric situations (2311 radisoundings) from polar to tropical atmosphere with varying water vapor amounts ranging from 0.1 to 8 g/cm2 (http://ara.lmd.polytechnique.fr/htdocs-public/products/TIGR/TIGR.html). The other is the six standard atmospheric profiles (tropical, mid-latitude summer, mid-latitude winter, sub-arctic summer, sub-arctic winter, and US76) stored in the MODTRAN 4. For LST retrieval, we only consider atmospheric variation in clear-sky conditions. Consequently, the profiles with relative humidity at one of levels greater than 90% in TIGR2002 were discarded as this seldom happens under clear-sky conditions. Therefore, 1413 representative atmospheric situations were extracted from TIGR2002. Figure 1 shows a plot of the atmospheric Water Vapor Content (WVC) as function of the atmospheric temperature T0 in the first boundary layer of these selected atmospheres. As shown in this figure, the T0 varies from 231 K to 315 K and the atmospheric WVC changes from 0.06 g/cm2 to 6.44 g/cm2.

View Article: PubMed Central - PubMed

ABSTRACT

On the basis of the radiative transfer theory, this paper addressed the estimate of Land Surface Temperature (LST) from the Chinese first operational geostationary meteorological satellite-FengYun-2C (FY-2C) data in two thermal infrared channels (IR1, 10.3-11.3 μm and IR2, 11.5-12.5 μm), using the Generalized Split-Window (GSW) algorithm proposed by Wan and Dozier (1996). The coefficients in the GSW algorithm corresponding to a series of overlapping ranging of the mean emissivity, the atmospheric Water Vapor Content (WVC), and the LST were derived using a statistical regression method from the numerical values simulated with an accurate atmospheric radiative transfer model MODTRAN 4 over a wide range of atmospheric and surface conditions. The simulation analysis showed that the LST could be estimated by the GSW algorithm with the Root Mean Square Error (RMSE) less than 1 K for the sub-ranges with the Viewing Zenith Angle (VZA) less than 30° or for the sub-rangs with VZA less than 60° and the atmospheric WVC less than 3.5 g/cm2 provided that the Land Surface Emissivities (LSEs) are known. In order to determine the range for the optimum coefficients of the GSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according to the land surface classification or using the method proposed by Jiang et al. (2006); and the WVC could be obtained from MODIS total precipitable water product MOD05, or be retrieved using Li et al.' method (2003). The sensitivity and error analyses in term of the uncertainty of the LSE and WVC as well as the instrumental noise were performed. In addition, in order to compare the different formulations of the split-window algorithms, several recently proposed split-window algorithms were used to estimate the LST with the same simulated FY-2C data. The result of the intercomparsion showed that most of the algorithms give comparable results.

No MeSH data available.