Spectra of Atmospheric Variables as Deduced from Ground-Based Radiometry

Ciotti, P.; Solimini, D.; Basili, P.

doi:10.1109/tge.1979.294615

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…In meteorology, satellite-based infrared and microwave sensors measure atmospheric variables on a global scale [i], while ground-based radiometers have proven their capability in continuously profiling the troposphere [2]. The dramatic increase of retrieval accuracy attainable by the contemporary use of satellite and ground-based data [3] and the sensitivity of radiometric instruments to clear-air turbulence and to internal waves [4,5] appear to be of considerable practical importance. The electromagnetic remote sensing of the earth surface (land or sea) by infrared and microwave sensors points out new ramified directions of beneficial applications [6].…”

Section: Em Remote Sensing and In Verse Problemsmentioning

confidence: 99%

“…The dramatic increase of retrieval accuracy attainable by the contemporary use of satellite and ground-based data [3] and the sensitivity of radiometric instruments to clear-air turbulence and to internal waves [4,5] appear to be of considerable practical importance. The electromagnetic remote sensing of the earth surface (land or sea) by infrared and microwave sensors points out new ramified directions of beneficial applications [6].…”

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confidence: 99%

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Aspects of digital signal processing in radiometric remote sensing of geophysical variables

Ciotti¹,

Solimini²

ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing

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When geophysical variables are estimated from remotely sensed electromagnetic data, severe difficulties are often encountered because of the ill-posed nature of the problem, so that the use of effective processing becomes essential. The inversion of radiometric data in the retrieval of atmospheric temperature profiles is considered and the use of the Kalman filter algorithm is analyzer to assess its performance from the point of view of accuracy of estimates and spatial resolution. The sensitivity to experimental errors is pointed out and the use of adaptive filtering to reduce the inaccuracy of data 0' examined. With regard to spectra of radiometric flucturtions, the performance of recently proposed spectr2l estimation techniques, amenable to the originally proposed maximum entropy method, are considered. The estimate of line parameters to identify and follow th temporal evolution of atmospheric internal oscillations is discussed, as well as the accuracy of retrieval of the slopes of radiometric turbulent spectra. E.M. REMOTE SENSING AND IN VERSE PROBLEMS A large variety of relevant and beneficial applications is drawing interest onto passive electromagnetic sensing techniques. In meteorology, satellite-based infrared and microwave sensors measure atmospheric variables on a global scale [i], while ground-based radiometers have proven their capability in continuously profiling the troposphere [2]. The dramatic increase of retrieval accuracy attainable by the contemporary use of satellite and ground-based data [3] and the sensitivity of radiometric instruments to clear-air turbulence and to internal waves [4,5] appear to be of considerable practical importance. The electromagnetic remote sensing of the earth surface (land or sea) by infrared and microwave sensors points out new ramified directions of beneficial applications [6]. Microwave thermography is now enriching the medical instrumentation and efforts are being made towards quantitative determination of subcutaneous temperature distribution as an effective tool in diagnosis and curative treatment [7].Full exploitation of the many potentialities of passive electromagnetic nsing techniques is subject to the feasibility of an adequate information retrieval from radiometric data, that is from the electromagnetic power 1874 impinging on the instrument antenno. As a result of the radiative transfer theory [8], the power reaching the radiometer is in general a weighted integral of the electromagnetic power emitted and scattered inside the medium under observation. Once the space-time distribution of intensity of emission and/or scattering is determined, the properties of the medium to be sensed can be retrieved through convenient modelling of the electromagnetic interaction mechanisms. The sensing process, therefore, requires different radiometric measurements and the subsequent inversion of the corresponding set of data.In the significant case of temperature profile retrieval, a Fredhoim integral equation of the first kind V (Y) = ( W (Y, z) B (z) dz Jo (1) relate...

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Section: Em Remote Sensing and In Verse Problemsmentioning

confidence: 99%

mentioning

confidence: 99%

Aspects of digital signal processing in radiometric remote sensing of geophysical variables

Ciotti¹,

Solimini²

ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing

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Inversion of ground‐based radiometric data by Kalman filtering

Basili¹,

Ciotti²,

Solimini³

1981

Radio Science

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Retrieval of atmospheric vertical temperature profiles from ground‐based radiometric observations requires shrewdness and judicious choice of parameters to surmount the noxious effects of the ill‐posed nature of the inversion. Kalman linear estimation, already successfully used in satellite microwave sounding of atmospheric temperature, can be also applied to infer the thermal state of the lower troposphere from ground‐based infrared measurements. After a short survey of the relevant formalism the implementation of the Kalman filter is discussed with regard to the transition operator and to the error covariances. In particular, the measurement errors are considered in some detail, and their dependence on the atmospheric dynamics is pointed out. The attainable spatial resolution is compared with that of another commonly used inversion technique, and, finally, a set of temperature profiles estimated by the Kalman algorithm from a sequence of successive radiometric measurements is reported.

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Remote sensing of atmospheric waves in O₂ and H₂O microwave emissions

El-Raey¹

1982

Radio Science

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Atmospheric microwave emissions from oxygen near 58.0, 54.0, and 51.0 GHz and water vapor at 22.235 GHz are monitored simultaneously at a time interval of 10 s. Power spectral analysis of radiometer output indicated frequent occurrence of enhanced emissions at periods between 3 and 13 min. These are attributed to local buoyancy Brunt‐Väisälä oscillations in the earth's atmosphere. Inversion of integrated brightness temperatures makes it possible to remote sense temperature profiles and natural waves simultaneously. It is suggested that spectral analysis of microwave and/or infrared emissions, as monitored by a geostationary satellite‐borne radiometer, may reveal important characteristics and relationships between temperature profiles and natural oscillations in the earth's atmosphere over a wide height range.

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Spectra of Atmospheric Variables as Deduced from Ground-Based Radiometry

Cited by 7 publications

References 8 publications

Aspects of digital signal processing in radiometric remote sensing of geophysical variables

Aspects of digital signal processing in radiometric remote sensing of geophysical variables

Inversion of ground‐based radiometric data by Kalman filtering

Remote sensing of atmospheric waves in O₂ and H₂O microwave emissions

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Spectra of Atmospheric Variables as Deduced from Ground-Based Radiometry

Cited by 7 publications

References 8 publications

Aspects of digital signal processing in radiometric remote sensing of geophysical variables

Aspects of digital signal processing in radiometric remote sensing of geophysical variables

Inversion of ground‐based radiometric data by Kalman filtering

Remote sensing of atmospheric waves in O2 and H2O microwave emissions

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Product

Resources

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Remote sensing of atmospheric waves in O₂ and H₂O microwave emissions