The Use of Artificial Neuron Networks for Retrieval Temperature and Humidity Sounding of the Atmosphere According to the Data of the MTVZA-GY Microwave Radiometer Installed on the Meteor-M No. 2-2 Satellite.
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| Title: | The Use of Artificial Neuron Networks for Retrieval Temperature and Humidity Sounding of the Atmosphere According to the Data of the MTVZA-GY Microwave Radiometer Installed on the Meteor-M No. 2-2 Satellite. |
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| Authors: | Filei, A. A.1 (AUTHOR) andreyvm-61@mail.ru, Andreev, A. I.1 (AUTHOR), Uspensky, A. B.2 (AUTHOR) |
| Source: | Izvestiya, Atmospheric & Oceanic Physics. Dec2021, Vol. 57 Issue 12, p1515-1526. 12p. |
| Subject Terms: | *Microwave radiometers, *Numerical weather forecasting, *Artificial neural networks, *Atmosphere, *Atmospheric layers, *Humidity |
| Abstract: | We consider the application of artificial neural networks for remote temperature and humidity profiles sounding of the atmosphere according to the data of the MTVZA-GY microwave radiometer installed on the Meteor-M No. 2-2 satellite. The satellite estimates of temperature and humidity profiles were compared with radiosonde data and with the products of numerical weather prediction models. In comparison with radiosonde data, the root-mean-square error of the temperature profile estimates does not exceed 3.0 K in the near-surface layer and is within 2 K in the rest of the atmospheric layer of 1000–10 hPa. The maximum root-mean-square error in the estimation of relative humidity profiles when compared with radiosonde data is 37% in the tropopause area, and when compared with the numerical weather predictive model data, does not exceed 20% in the entire atmospheric column. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Header | DbId: enr DbLabel: Energy & Power Source An: 156022975 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The Use of Artificial Neuron Networks for Retrieval Temperature and Humidity Sounding of the Atmosphere According to the Data of the MTVZA-GY Microwave Radiometer Installed on the Meteor-M No. 2-2 Satellite. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Filei%2C+A%2E+A%2E%22">Filei, A. A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> andreyvm-61@mail.ru</i><br /><searchLink fieldCode="AR" term="%22Andreev%2C+A%2E+I%2E%22">Andreev, A. I.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Uspensky%2C+A%2E+B%2E%22">Uspensky, A. B.</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Izvestiya%2C+Atmospheric+%26+Oceanic+Physics%22">Izvestiya, Atmospheric & Oceanic Physics</searchLink>. Dec2021, Vol. 57 Issue 12, p1515-1526. 12p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Microwave+radiometers%22">Microwave radiometers</searchLink><br />*<searchLink fieldCode="DE" term="%22Numerical+weather+forecasting%22">Numerical weather forecasting</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br />*<searchLink fieldCode="DE" term="%22Atmosphere%22">Atmosphere</searchLink><br />*<searchLink fieldCode="DE" term="%22Atmospheric+layers%22">Atmospheric layers</searchLink><br />*<searchLink fieldCode="DE" term="%22Humidity%22">Humidity</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We consider the application of artificial neural networks for remote temperature and humidity profiles sounding of the atmosphere according to the data of the MTVZA-GY microwave radiometer installed on the Meteor-M No. 2-2 satellite. The satellite estimates of temperature and humidity profiles were compared with radiosonde data and with the products of numerical weather prediction models. In comparison with radiosonde data, the root-mean-square error of the temperature profile estimates does not exceed 3.0 K in the near-surface layer and is within 2 K in the rest of the atmospheric layer of 1000–10 hPa. The maximum root-mean-square error in the estimation of relative humidity profiles when compared with radiosonde data is 37% in the tropopause area, and when compared with the numerical weather predictive model data, does not exceed 20% in the entire atmospheric column. [ABSTRACT FROM AUTHOR] |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1134/S0001433821120070 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1515 Subjects: – SubjectFull: Microwave radiometers Type: general – SubjectFull: Numerical weather forecasting Type: general – SubjectFull: Artificial neural networks Type: general – SubjectFull: Atmosphere Type: general – SubjectFull: Atmospheric layers Type: general – SubjectFull: Humidity Type: general Titles: – TitleFull: The Use of Artificial Neuron Networks for Retrieval Temperature and Humidity Sounding of the Atmosphere According to the Data of the MTVZA-GY Microwave Radiometer Installed on the Meteor-M No. 2-2 Satellite. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Filei, A. A. – PersonEntity: Name: NameFull: Andreev, A. I. – PersonEntity: Name: NameFull: Uspensky, A. B. IsPartOfRelationships: – BibEntity: Dates: – D: 30 M: 12 Text: Dec2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 00014338 Numbering: – Type: volume Value: 57 – Type: issue Value: 12 Titles: – TitleFull: Izvestiya, Atmospheric & Oceanic Physics Type: main |
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