Planeta Scientific Research Center for Space Hydrometeorology

Moscow, Russia

Planeta Scientific Research Center for Space Hydrometeorology

Moscow, Russia

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Rublev A.N.,Planeta Scientific Research Center for Space Hydrometeorology | Gorchakova I.A.,Russian Academy of Sciences | Udalova T.A.,RAS Research Center Kurchatov Institute
Izvestiya - Atmospheric and Ocean Physics | Year: 2011

Based on mathematical simulation, quantitative estimates of the effect that coarse dust particles have on the accuracy of retrieving the optical characteristics of aerosol have been obtained from the results of ground-based measurements of the spectral fluxes of both direct and scattered solar radiations. The results of verifying a retrieval algorithm (used at the AERONET ground-based network) based on special test models showed that the aerosol characteristics retrieved with this algorithm are unsuitable for calculating integral solar fluxes and for simulating space spectrometric IR measurements when the concentration of dust particles in the atmosphere exceeds their concentration in the well-known CONT model of continental aerosol by a factor of two or more. © 2011 Pleiades Publishing, Ltd.


Kramchaninova E.K.,Planeta Scientific Research Center for Space Hydrometeorology | Uspensky A.B.,Planeta Scientific Research Center for Space Hydrometeorology
Izvestiya - Atmospheric and Ocean Physics | Year: 2013

The possibility of remotely monitoring the total atmospheric ozone content (TAOC) using data from the multichannel geostationary scanning instrument (MGSI) aboard the Elektro-L no. 1 Russian meteorological satellite is explored. In addition to the MGSI measurements in three channels (8.2-9.2, 9.2-10.2, and 10.2-11.2 μm), data on the vertical temperature distributions in the ozone layer and the temperature and pressure at the underlying terrain level (satellite sensing results or forecast data) are used as additional predictors in the process of TAOC estimation. The TAOC estimates are constructed with the use of a regularized regression algorithm (ridge regression). The learning and check samples are formed using independent TAOC estimates based on the data gathered by the OMI instrument aboard the EOS Aura satellite. Numerical experiments in processing the actual MGSI data gathered over certain periods within the interval from November 2011 to August 2012 reveal the possibility of arranging regular monitoring of the TAOC fields with high spatial and temporal resolutions and an acceptable precision: the absolute value of relative mean deviations and the relative root-mean-square deviations of the estimates based on the MGSI data from the estimates based on the OMI data lie within intervals of 1-2% and 5-7%, respectively, depending on the underlying terrain type. © 2013 Pleiades Publishing, Ltd.

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