Short-term forecast of the auroral oval position on the basis of the ``virtual globe'' technology

2020 ◽  
Vol 20 (6) ◽  
pp. 1-9
Author(s):  
A. V. Vorobev ◽  
V. A. Pilipenko ◽  
R. I. Krasnoperov ◽  
G. R. Vorobeva ◽  
D. A. Lorentzen
2012 ◽  
Vol 2012 ◽  
pp. 1-7
Author(s):  
T. Egorova ◽  
E. Rozanov ◽  
A. V. Shapiro ◽  
W. Schmutz

We have applied chemistry-climate model (CCM) SOCOL to simulate the distribution of the temperature and gas species in the upper stratosphere and mesosphere. As an input for the simulation, we employ daily spectral solar UV irradiance measured by SUSIM instrument onboard UARS satellite in January 1992. We have carried out an ensemble of nine 1-month long simulations using slightly different initial states of the atmosphere. We have compared the obtained time evolution of the simulated species and temperature with available satellite measurements. The obtained results allowed us to define the areas where the nowcast and short-term forecast of the atmospheric species with CCM SOCOL could be successful.


2021 ◽  
Vol 4 ◽  
pp. 104-109
Author(s):  
S. S. Grozin ◽  
◽  
ZH.V. Ostrovskikh ◽  

The article deals with the problem of the emergence and functioning of financial pyramids based on the use of digital assets, using the example of the «Finico» project. The main performance indicators are analyzed, as well as the reasons that influenced the success of this project, its scale and duration of existence are characterized. Particular attention is paid to the ways of organizing and carrying out illegal financial activities with signs of financial pyramids, and some measures are proposed to counter it. A short-term forecast of an increase in the number of crimes committed using information, telecommunications and digital technologies in this area is given.


2019 ◽  
Vol 147 (11) ◽  
pp. 4045-4069 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Yunheng Wang ◽  
Jidong Gao ◽  
Edward R. Mansell

Abstract The assimilation of water vapor mass mixing ratio derived from total lightning data from the Geostationary Lightning Mapper (GLM) within a three-dimensional variational (3DVAR) system is evaluated for the analysis and short-term forecast (≤6 h) of a high-impact convective event over the northern Great Plains in the United States. Building on recent work, the lightning data assimilation (LDA) method adjusts water vapor mass mixing ratio within a fixed layer depth above the lifted condensation level by assuming nearly water-saturated conditions at observed lightning locations. In this algorithm, the total water vapor mass added by the LDA is balanced by an equal removal outside observed lightning locations. Additional refinements were also devised to partially alleviate the seasonal and geographical dependence of the original scheme. To gauge the added value of lightning, radar data (radial velocity and reflectivity) were also assimilated with or without lightning. Although the method was evaluated in quasi–real time for several high-impact weather events throughout 2018, this work will focus on one specific, illustrative severe weather case wherein the control simulation—which did not assimilate any data—was eventually able to initiate and forecast the majority of the observed storms. Given a relatively reasonable forecast in the control experiment, the GLM and radar assimilation experiments were still able to improve the short-term forecast of accumulated rainfall and composite radar reflectivity further, as measured by neighborhood-based metrics. These results held whether the simulations made use of one single 3DVAR analysis or high-frequency (10 min) successive cycling over a 1-h period.


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