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The Use of Linear Regression Relations Derived from Model and Experimental Data for Retrieval of the Water Content of Clouds from Ground-Based Microwave Measurements

  • REMOTE SENSING OF ATMOSPHERE, HYDROSPHERE, AND UNDERLYING SURFACE
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Abstract

Estimates of the error in determining the cloud liquid water path by the multiple linear regression (MLR) technique using different regression relations obtained both by model calculations and by experimental data (for reference, results of the method based on the inversion of the radiative transfer equation were taken) are presented. It is shown that if the MLR method is trained by experimental data and measurements in seven spectral channels of the radiometer, the random component of the liquid water path error in the cloud is 0.015–0.017 kg/m2, which is half that obtained when trained by the results of model calculations. The cloud liquid water path bias does not exceed 0.005 kg/m2. The MLR results allow one to reliably identify periods of clear sky by the criterion of the minimum variance of the water content.

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Funding

This work was supported by the Russian Foundation for Basic Research (project no. 19-05-00372).

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Authors and Affiliations

  1. St. Petersburg University, 198504, St. Petersburg, Russia

    E. Yu. Biryukov & V. S. Kostsov

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  1. E. Yu. Biryukov
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  2. V. S. Kostsov
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Correspondence to E. Yu. Biryukov or V. S. Kostsov.

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The authors declare that they have no conflicts of interest.

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Translated by A. Nikol’skii

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Biryukov, E.Y., Kostsov, V.S. The Use of Linear Regression Relations Derived from Model and Experimental Data for Retrieval of the Water Content of Clouds from Ground-Based Microwave Measurements. Atmos Ocean Opt 32, 569–577 (2019). https://doi.org/10.1134/S1024856019050051

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