1985
DOI: 10.1175/1520-0450(1985)024<0128:tiiima>2.0.co;2
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The Improved Initialization Inversion Method: A High Resolution Physical Method for Temperature Retrievals from Satellites of the TIROS-N Series

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Cited by 364 publications
(175 citation statements)
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“…Here we provide some examples rather than a complete review. LST can be retrieved from a single infrared channel through an accurate radiative transfer model if surface emissivity is known and temperature/water vapor profile is given by either satellite soundings or conventional radiosonde data (Price, 1983;Susskind, Rosenfield, Reuter, & Chahine, 1984;Chedin, Scott, Wahiche, & Moulinier, 1985;Ottlé & Vidal-Madjar, 1992). Split-window LST methods require known surface emissivities to make corrections for the atmospheric and surface emissivity effects based on the differential atmospheric absorption in the 10-13 Am split window without knowledge of the atmospheric temperature/water vapor profile although column water vapor is used in some split-window LST algorithms to improve the accuracy of LST retrieval (Price, 1984;Becker, 1987;Wan & Dozier, 1989;Becker & Li, 1990;Sobrino, Coll, & Caselles, 1991;Vidal, 1991;Kerr, Lagouarde, & Imbernon, 1992;Ottlé & Stoll, 1993;Prata, 1994;Wan & Dozier, 1996).…”
Section: Heritage For Lst Remote Sensingmentioning
confidence: 99%
“…Here we provide some examples rather than a complete review. LST can be retrieved from a single infrared channel through an accurate radiative transfer model if surface emissivity is known and temperature/water vapor profile is given by either satellite soundings or conventional radiosonde data (Price, 1983;Susskind, Rosenfield, Reuter, & Chahine, 1984;Chedin, Scott, Wahiche, & Moulinier, 1985;Ottlé & Vidal-Madjar, 1992). Split-window LST methods require known surface emissivities to make corrections for the atmospheric and surface emissivity effects based on the differential atmospheric absorption in the 10-13 Am split window without knowledge of the atmospheric temperature/water vapor profile although column water vapor is used in some split-window LST algorithms to improve the accuracy of LST retrieval (Price, 1984;Becker, 1987;Wan & Dozier, 1989;Becker & Li, 1990;Sobrino, Coll, & Caselles, 1991;Vidal, 1991;Kerr, Lagouarde, & Imbernon, 1992;Ottlé & Stoll, 1993;Prata, 1994;Wan & Dozier, 1996).…”
Section: Heritage For Lst Remote Sensingmentioning
confidence: 99%
“…Section 2 describes the AIRS-LMD cloud property retrieval algorithm, which makes use of retrieved atmospheric temperature and water vapour profiles of the AIRS L2 data (Susskind et al, 2003(Susskind et al, , 2006 and of atmospheric spectral transmissivity profiles which have been simulated for atmospheric profiles of the Thermodynamic Initial Guess Retrieval (TIGR) data base (Chédin et al, 1985;Chevallier et al, 1998). AIRS data have been collocated with CALIPSO data and then with the Radar -Lidar GEOPROF data.…”
Section: Introductionmentioning
confidence: 99%
“…Entries to the model include AOD, height, surface pressure, surface temperature and emissivity, viewing angle, two refractive indices from Volz (1972Volz ( , 1973 and Balkanski et al (2007) and a set of 2311 atmospheric situations. These were selected using statistical methods from 80 000 radiosonde reports and stored in the Thermodynamic Initial Guess Retrieval (TIGR) climatological database (Chédin et al, 1985;Chevallier et al, 1998). The PSD is modelled by a monomodal log-normal distribution described by the effective radius (R eff ) and the standard deviation of the distribution σ g .…”
Section: Iasi Lmd Algorithmmentioning
confidence: 99%