Assimilation of GBVTD-retrieved winds from single-Doppler radar for short-term forecasting of super typhoon Saomai (0608) at landfall

2011 ◽  
Vol 138 (665) ◽  
pp. 1055-1071 ◽  
Author(s):  
Kun Zhao ◽  
Ming Xue ◽  
Wen-Chau Lee
Keyword(s):  
Doppler Radar ◽  
Short Term ◽  
Super Typhoon ◽  
Short Term Forecasting ◽  
Typhoon Saomai

scholarly journals Radar Refractivity Retrieval: Validation and Application to Short-Term Forecasting

2005 ◽  
Vol 44 (3) ◽  
pp. 285-300 ◽  
Author(s):  
Tammy M. Weckwerth ◽  
Crystalyne R. Pettet ◽  
Frédéric Fabry ◽  
Shin Ju Park ◽  
Margaret A. LeMone ◽  
...  
Keyword(s):  
Great Plains ◽  
Doppler Radar ◽  
Doppler Velocity ◽  
Good Representation ◽  
Short Term ◽  
Near Surface ◽  
National Network ◽  
Low Level ◽  
Short Term Forecasting ◽  
Convection Initiation

Abstract This study will validate the S-band dual-polarization Doppler radar (S-Pol) radar refractivity retrieval using measurements from the International H2O Project conducted in the southern Great Plains in May–June 2002. The range of refractivity measurements during this project extended out to 40–60 km from the radar. Comparisons between the radar refractivity field and fixed and mobile mesonet refractivity values within the S-Pol refractivity domain show a strong correlation. Comparisons between the radar refractivity field and low-flying aircraft also show high correlations. Thus, the radar refractivity retrieval provides a good representation of low-level atmospheric refractivity. Numerous instruments that profile the temperature and moisture are also compared with the refractivity field. Radiosonde measurements, Atmospheric Emitted Radiance Interferometers, and a vertical-pointing Raman lidar show good agreement, especially at low levels. Under most daytime summertime conditions, radar refractivity measurements are representative of an ∼250-m-deep layer. Analyses are also performed on the utility of refractivity for short-term forecasting applications. It is found that the refractivity field may detect low-level boundaries prior to the more traditional radar reflectivity and Doppler velocity fields showing their existence. Data from two days on which convection initiated within S-Pol refractivity range suggest that the refractivity field may exhibit some potential utility in forecasting convection initiation. This study suggests that unprecedented advances in mapping near-surface water vapor and subsequent improvements in predicting convective storms could result from implementing the radar refractivity retrieval on the national network of operational radars.

scholarly journals Rain Forecasting for Ho Chi Minh City Using Doppler Weather Radar Dwsr-2500C

2016 ◽  
Vol 62 (1) ◽  
pp. 1-10
Author(s):  
Dang Quoc Dung ◽  
Nguyen The Hao ◽  
Nguyen Minh Giam
Keyword(s):  
Doppler Radar ◽  
Extreme Rainfall ◽  
Ho Chi Minh City ◽  
Short Term ◽  
Flood Prevention ◽  
Weather Radars ◽  
Monitoring And Forecasting ◽  
Extreme Rain ◽  
Short Term Forecasting ◽  
The City

Abstract Rainfall amounts vary randomly over time and space. Rainfall monitoring and forecasting is a difficult task, especially for a short-term period from 30 minutes to 3 hours. Recently Doppler weather radars have been used as one of the new solutions in the short-term forecasting of extreme rain or storm. This research presents some results of forecasting the wind direction, velocity, and rainfall of a typical rainy day, 14 September 2010, based on CAPPI images of a DWSR-2500C radar in the Nha Be district, Ho Chi Minh City (HCMC). The results showed that the Doppler radar, in a scanning radius of 30 km, is very effective in forecasting extreme rainfall for each region and district when reflected radar signals from clouds moving towards the city are detected. This research provides useful information in the forecast of extreme rainfall for flood prevention works in the HCM City.

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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