scholarly journals Tracking and short-term forecasting of mesoscale convective cloud clusters over southeast Brazil using satellite infrared imagery

2021 ◽  
Author(s):  
José Ricardo Siqueira ◽  
Valdo da Silva Marques
Keyword(s):  
Convective Cloud ◽  
Short Term ◽  
Infrared Imagery ◽  
Southeast Brazil ◽  
Cloud Clusters ◽  
Mesoscale Convective ◽  
Short Term Forecasting

Large-Scale Environmental Influences on Tropical Cyclone Formation Processes and Development Time

2020 ◽  
Vol 33 (22) ◽  
pp. 9763-9782
Author(s):  
Hsu-Feng Teng ◽  
James M. Done ◽  
Cheng-Shang Lee ◽  
Huang-Hsiung Hsu ◽  
Ying-Hwa Kuo
Keyword(s):  
Large Scale ◽  
Development Time ◽  
Analysis Method ◽  
Short Term ◽  
Convective Systems ◽  
Cloud Clusters ◽  
Mesoscale Convective ◽  
Environmental Transitions ◽  
Cluster Analysis Method ◽  
Low Levels

AbstractThe development of tropical cloud clusters (TCCs) to tropical cyclones (TCs) is the process of TC formation. This study identifies five main environmental transitions for the development of TCCs to TCs in the western North Pacific by using a cluster analysis method. Of these, three transitions indicate TCCs that develop in monsoon environments and two in easterly environments. Their numbers, distributions, and interannual variability differ. On average, the development time, defined as the period from the TCC forming to it developing into a TC, for TCCs that develop in easterly environments is shorter than that in monsoon environments. For the development of TCC to TC in easterly environments, TCCs have fewer embedded mesoscale convective systems (MCSs), which are located closer to the TCC center. Moreover, there is a stronger inward short-term (less than 10 days) angular momentum flux (AMF) at middle levels (800–500 hPa) before TCC formation. Conversely, in monsoon environments, TCCs have more MCSs, which are located farther from the TCC center. A stronger inward short-term AMF at low levels (1000–850 hPa) is observed before TCC formation and develops upward during the development of TCC to TC. The characteristics of MCS and AMF are significantly correlated with the development time of TCC to TC. In summary, large-scale easterly and monsoon environments cause TCCs to have different MCS and AMF characteristics, leading to higher efficiency for TCCs developing into TCs in easterly environments compared to monsoon environments.

A Wave-Relative Framework Analysis of AEW–MCS Interactions Leading to Tropical Cyclogenesis

2020 ◽  
Vol 148 (11) ◽  
pp. 4657-4671
Author(s):  
Kelly M. Núñez Ocasio ◽  
Jenni L. Evans ◽  
George S. Young
Keyword(s):  
West Africa ◽  
Thermodynamic Characteristics ◽  
Convective Cloud ◽  
Type Systems ◽  
Squall Line ◽  
Tropical Cyclogenesis ◽  
Framework Analysis ◽  
Convective Systems ◽  
Cloud Clusters ◽  
Mesoscale Convective

AbstractAn African easterly wave (AEW) and associated mesoscale convective systems (MCSs) dataset has been created and used to evaluate the propagation of MCSs, AEWs, and, especially, the propagation of MCSs relative to the AEW with which they are associated (i.e., wave-relative framework). The thermodynamic characteristics of AEW–MCS systems are also analyzed. The analysis is done for both AEW–MCS systems that develop into tropical cyclones and those that do not to quantify significant differences. It is shown that developing AEWs over West Africa are associated with a larger number of convective cloud clusters (CCCs; squall-line-type systems) than nondeveloping AEWs. The MCSs of developing AEWs propagate at the same speed of the AEW trough in addition to being in phase with the trough, whereas convection associated with nondeveloping AEWs over West Africa moves faster than the trough and is positioned south of it. These differences become important for the intensification of the AEW vortex as this slower-moving convection (i.e., moving at the same speed of the AEW trough) spends more time supplying moisture and latent heat to the AEW vortex, supporting its further intensification. An analysis of the rainfall rate (MCS intensity), MCS area, and latent heating rate contribution reveals that there are statistically significant differences between developing AEWs and nondeveloping AEWs, especially over West Africa where the fraction of extremely large MCS areas associated with developing AEWs is larger than for nondeveloping AEWs.

scholarly journals An explicit method of mesoscale convective storm prediction for the central region of Russia

2018 ◽  
Vol 15 ◽  
pp. 213-216
Author(s):  
Inna M. Gubenko ◽  
Maria M. Kurbatova ◽  
Konstantin G. Rubinstein
Keyword(s):  
Electric Field ◽  
Central Region ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Explicit Method ◽  
Convective Storm ◽  
Short Term ◽  
Mesoscale Convective ◽  
Short Term Forecasting ◽  
Cumulonimbus Cloud

Abstract. This work presents simulation results of the storm observed on the 13–14 July 2016 over the Central region of Russia. The Cumulonimbus cloud (Cb) electrification model coupled with the numerical weather prediction model WRF-ARW were used for this study. The prognostic values of the electric field magnitude were compared with observations. Forecast scores were obtained. The results show that the proposed approach of explicit modelling of the electric field is applicable to short-term forecasting of intense convection and passage tracking of storms. Obtaining varying values of the electric field could help to identify the diversity of hazardous weather phenomena associated with convection.

The causes of poverty in Russia

2020 ◽  
Vol 13 (1) ◽  
pp. 21-36
Author(s):  
I.S. Ivanchenko
Keyword(s):  
Regression Analysis ◽  
Regional Development ◽  
Financial Market ◽  
Russian Federation ◽  
Short Term ◽  
Financial Situation ◽  
Macroeconomic Variables ◽  
Development Plans ◽  
The Russian Federation ◽  
Short Term Forecasting

Subject. This article analyzes the changes in poverty of the population of the Russian Federation. Objectives. The article aims to identify macroeconomic variables that will have the most effective impact on reducing poverty in Russia. Methods. For the study, I used the methods of logical, comparative, and statistical analyses. Results. The article presents a list of macroeconomic variables that, according to Western scholars, can influence the incomes of the poorest stratum of society and the number of unemployed in the country. The regression analysis based on the selected variables reveals those ones that have a statistically significant impact on the financial situation of the Russian poor. Relevance. The results obtained can be used by the financial market mega-regulator to make anti-poverty decisions. In addition, the models built can be useful to the executive authorities at various levels for short-term forecasting of the number of unemployed and their income in drawing up regional development plans for the areas.

Very short-term forecasting of wind power generation using hybrid deep learning model

2021 ◽  
Vol 296 ◽  
pp. 126564
Author(s):  
Md Alamgir Hossain ◽  
Ripon K. Chakrabortty ◽  
Sondoss Elsawah ◽  
Michael J. Ryan
Keyword(s):  
Power Generation ◽  
Deep Learning ◽  
Wind Power ◽  
Learning Model ◽  
Wind Power Generation ◽  
Short Term ◽  
Short Term Forecasting ◽  
Deep Learning Model
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