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Comparison of different techniques in atmospheric temperature-humidity sensing from space. / Polyakov, A.; Timofeyev, Y.M.; Virolainen, Y.

в: International Journal of Remote Sensing, Том 35, № 15, 2014, стр. 5899-5912.

Результаты исследований: Научные публикации в периодических изданияхстатья

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Polyakov, A. ; Timofeyev, Y.M. ; Virolainen, Y. / Comparison of different techniques in atmospheric temperature-humidity sensing from space. в: International Journal of Remote Sensing. 2014 ; Том 35, № 15. стр. 5899-5912.

BibTeX

@article{1a8adc3d7c7441d9828a0c96cf82f54a,
title = "Comparison of different techniques in atmospheric temperature-humidity sensing from space",
abstract = "Numerical closed-loop experiments on retrieving atmospheric temperature and humidity profiles by high-resolution measurements of the outgoing thermal infrared (IR) radiation using a Russian Fourier spectrometer (IRFS-2) were performed. Three techniques were used: multiple linear regression (MLR), the iterative physical-mathematical approach (IPMA), and artificial neural networks (ANNs). The MLR technique gives significant root mean square (RMS) errors in the retrieval of the temperature profile, especially in the troposphere region; these errors may be as great as 2–3 K. The ANN and IPMA techniques are considerably more accurate, giving approximately equal RMS errors of 1.0–1.5 K at altitudes of 2–30 km. For all interpretation techniques, a growth of errors of retrieval of temperature in the lower troposphere is observed and is especially substantial (up to 3 K for the near-surface temperature) in thermal sensing over land. The systematic errors of temperature retrieval for the ANN technique are practically z",
author = "A. Polyakov and Y.M. Timofeyev and Y. Virolainen",
year = "2014",
doi = "10.1080/01431161.2014.945004",
language = "English",
volume = "35",
pages = "5899--5912",
journal = "International Joural of Remote Sensing",
issn = "0143-1161",
publisher = "Taylor & Francis",
number = "15",

}

RIS

TY - JOUR

T1 - Comparison of different techniques in atmospheric temperature-humidity sensing from space

AU - Polyakov, A.

AU - Timofeyev, Y.M.

AU - Virolainen, Y.

PY - 2014

Y1 - 2014

N2 - Numerical closed-loop experiments on retrieving atmospheric temperature and humidity profiles by high-resolution measurements of the outgoing thermal infrared (IR) radiation using a Russian Fourier spectrometer (IRFS-2) were performed. Three techniques were used: multiple linear regression (MLR), the iterative physical-mathematical approach (IPMA), and artificial neural networks (ANNs). The MLR technique gives significant root mean square (RMS) errors in the retrieval of the temperature profile, especially in the troposphere region; these errors may be as great as 2–3 K. The ANN and IPMA techniques are considerably more accurate, giving approximately equal RMS errors of 1.0–1.5 K at altitudes of 2–30 km. For all interpretation techniques, a growth of errors of retrieval of temperature in the lower troposphere is observed and is especially substantial (up to 3 K for the near-surface temperature) in thermal sensing over land. The systematic errors of temperature retrieval for the ANN technique are practically z

AB - Numerical closed-loop experiments on retrieving atmospheric temperature and humidity profiles by high-resolution measurements of the outgoing thermal infrared (IR) radiation using a Russian Fourier spectrometer (IRFS-2) were performed. Three techniques were used: multiple linear regression (MLR), the iterative physical-mathematical approach (IPMA), and artificial neural networks (ANNs). The MLR technique gives significant root mean square (RMS) errors in the retrieval of the temperature profile, especially in the troposphere region; these errors may be as great as 2–3 K. The ANN and IPMA techniques are considerably more accurate, giving approximately equal RMS errors of 1.0–1.5 K at altitudes of 2–30 km. For all interpretation techniques, a growth of errors of retrieval of temperature in the lower troposphere is observed and is especially substantial (up to 3 K for the near-surface temperature) in thermal sensing over land. The systematic errors of temperature retrieval for the ANN technique are practically z

U2 - 10.1080/01431161.2014.945004

DO - 10.1080/01431161.2014.945004

M3 - Article

VL - 35

SP - 5899

EP - 5912

JO - International Joural of Remote Sensing

JF - International Joural of Remote Sensing

SN - 0143-1161

IS - 15

ER -

ID: 7009953