A multisensory algorithm of satellite radiothermovision


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Resumo

A multisensory algorithm of satellite radiothermovision has been proposed that makes it possible to combine the data of satellite radiothermal monitoring of the Earth from different sources within a single method of spatiotemporal interpolation taking into account the differences in time of measurements and in the spatial resolution of different instruments. The new algorithm was tested in a series of measurements with SSMIS instruments onboard F16, F17 satellites of DMSP and AMSR-2 instruments onboard the GCOMW1 satellite in November 2013, as well as a series of measurements with the same instruments in August 2012 supplemented with data from WindSat. The parameters of the spatiotemporal interpolation of total precipitable water fields are improved nearly twofold (with a time step of 1.5 h on a regular grid with 0.125° sampling) compared with the method that previously used only SSM/I data. The achieved spatial sampling exceeds known world analogues while maintaining a high accuracy of interpolation. In addition, the problem of the transition from the fields at a fixed local time to the fields at a fixed universal time is briefly considered. It has been shown that this transition is mainly relevant in the study of the fast atmospheric processes on a global scale with high temporal resolution.

Sobre autores

D. Ermakov

Kotel’nikov Institute of Radio-Engineering and Electronics (IRE) of Russian Academy of Sciences; Space Research Institute of the Russian Academy of Sciences

Email: e.sharkov@mail.ru
Rússia, Fryazino, Moscow oblast, 141120; Moscow, 117997

E. Sharkov

Space Research Institute of the Russian Academy of Sciences

Autor responsável pela correspondência
Email: e.sharkov@mail.ru
Rússia, Moscow, 117997

A. Chernushich

Kotel’nikov Institute of Radio-Engineering and Electronics (IRE) of Russian Academy of Sciences

Email: e.sharkov@mail.ru
Rússia, Fryazino, Moscow oblast, 141120


Declaração de direitos autorais © Pleiades Publishing, Ltd., 2016

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