scholarly journals A Review Of The Research On Emergency Logistics Of Tropical Cyclone Disasters In Guangxi

2020 ◽  
Vol 11 (1) ◽  
pp. 47-47
Author(s):  
Guoyou Yue ◽  
Boonsub Panichakarn
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Economic Losses ◽  
Beibu Gulf ◽  
Super Typhoon ◽  
Emergency Logistics ◽  
Yulin City ◽  
Direct Economic Losses

It is found that Guangxi is affected by many tropical cyclones (generally referred to as typhoons in China) every year. According to the statistics of typhoons that entered the inland of Guangxi from 1970 to 2013, 89 typhoons entered Guangxi in 44 years, with an average of 2 typhoons per year (Jing Li, Liyan Qi, 2015). And these tropical cyclone disasters have caused a large number of casualties and economic losses in Guangxi. Typhoon No. 0606 "Prapiroon" entered Guangxi from Yulin city, causing 74 counties (cities and districts) in Guangxi to suffer disasters, affecting 5.76 million people, killing 34 people and causing direct economic losses of 7 billion yuan (Jing Li, et al., 2007). In addition, according to the report of Guangxi Civil Affairs Department, super typhoon No. 1409 "Rammasun" landed in Fangchenggang area of Beibu Gulf, causing 4.3211 million people in 11 cities and 57 counties (cities and districts) including Beihai and Fangchenggang to suffer disaster, affecting 1.456 million hectares of crops, 8,527 farmhouses collapsed, and the direct economic losses reached 13.84 billion yuan. Moreover, the number and intensity of tropical cyclone that caused serious damage to Guangxi increased gradually. Keywords: Emergency Logistics, Tropical Cyclone Disasters, Emergency Supplies Requirements, Emergency Supplies Dispatching, Guangxi

Building an Awareness Model of Emergency Supplies Dispatching for Tropical Cyclone Disasters in Guangxi

2020 ◽  
Vol 11 (1) ◽  
pp. 171-171
Author(s):  
Guoyou Yue ◽  
Boonsub Panichakarn
Keyword(s):  
Tropical Cyclone ◽  
Disaster Relief ◽  
Minimum Cost ◽  
Economic Losses ◽  
Beibu Gulf ◽  
Distribution Centers ◽  
Emergency Logistics ◽  
Displaced People ◽  
Direct Economic Losses ◽  
The Impact

It is found that Guangxi is affected by many tropical cyclones (generally referred to as typhoons in China) every year. According to the statistics of typhoons that entered the inland of Guangxi from 1970 to 2013, 89 typhoons entered Guangxi in 44 years, with an average of 2 typhoons per year (Jing Li, Liyan Qi, 2015). And these tropical cyclone disasters have caused a large number of casualties and economic losses in Guangxi. Typhoon No. 0606 "Prapiroon" entered Guangxi from Yulin city, causing 74 counties (cities and districts) in Guangxi to suffer disasters, affecting 5.76 million people, killing 34 people and causing direct economic losses of 7 billion yuan (Jing Li, et al., 2007). In addition, according to the report of Guangxi Civil Affairs Department, super typhoon No. 1409 "Rammasun" landed in Fangchenggang area of Beibu Gulf, causing 4.3211 million people in 11 cities and 57 counties (cities and districts) including Beihai and Fangchenggang to suffer disaster, affecting 1.456 million hectares of crops, 8,527 farmhouses collapsed, and the direct economic losses reached 13.84 billion yuan. Moreover, the number and intensity of tropical cyclone that caused serious damage to Guangxi increased gradually. The damage caused by tropical cyclone is very huge, the disaster area is widely distributed, and the loss of many people is also very large. How to deliver the emergency supplies to the victims timely at minimum cost becomes the key to disaster relief. But the emergency supplies dispatching involves many problems. Because the displaced people are distributed in different settlements. The extent of the impact varies from place to place and the type and amount of emergency supplies needed. The distance between settlements and distribution centers varies from place to place, as does the connectivity of roads. Therefore, it is necessary to establish an awareness model for emergency supplies dispatching to solve these problems, so that emergency agencies of governments at all levels can make emergency supplies dispatching scheme faster and improve disaster relief effects. Keywords: Emergency Logistics, Tropical Cyclone Disasters, Emergency Supplies Dispatching, Transshipment Problem, Guangxi

Supervised Machine Learning Techniques to Assess Tropical Cyclones in Bay of Bengal and Bangladesh

2021 ◽  
Author(s):  
Mariam Hussain ◽  
Seon Ki Park
Keyword(s):  
Machine Learning ◽  
Tropical Cyclone ◽  
Linear Regression ◽  
Tropical Cyclones ◽  
Bay Of Bengal ◽  
Early Warning Systems ◽  
Supervised Machine Learning ◽  
Extreme Weather Events ◽  
Economic Losses ◽  
Coastal Regions

<p>Bangladesh experiences extreme weather events such as heavy rainfall due to monsoon, tropical cyclones, and thunderstorms resulting in floods every year. Regular flood events significantly affect in agricultural industries and human lives for economic losses. One of the reasons for these weather phenomena to sustain is latent heat release from Bay of Bengal (BoB) and Southeast Tropical Indian Ocean (SETIO). As the country has limited observations from stations and oceans, modeling for numerical weather prediction (NWP) are challenging for local operations. For operational NWP, computational resources and time are also concerns for a developing country like Bangladesh. Besides, recent machine learning (ML) techniques are widely applied to study various meteorological events with efficient results. Therefore, this research aims to estimate predictability and accuracy of supervised ML for tropical cyclones by assessing air temperature at 2 meter (AT) and sea surface temperature (SST). For AT and SST, the study utilizes monthly data at 0.25 × 0.25<sup>o</sup> horizontal resolution provided by the ECMWF reanalysis (ERA5). The gridded data is downscaled to area of interests such as coastal regions, BoB and SEITO with a study period of 40 years from 1979 to 2018. Furthermore, Bangladesh Meteorological Department (BMD) provides AT for 36 years from 1979 to 2015. The experiments segregate into two sections: (1) data normalizations via linear regression (LR) and multi-linear regression (MLR) and (2) supervised ML techniques applications in Matlab 2018b. The pre-processed data for LR show that AT from coastal regions such as Chittagong (CG), Barishal (BR), and Khulna (KL) divisions have stronger correlations (R) to SST in BOB with R = 0.910, 0.850, and 0.846 respectively than SEITO (R = 0.698, 0.675 and 0.678 respectively). Moreover, for these three regions, the correlation of MLR is 0.916 and 0.745 for BoB and SEITO with residual standard error (RSE) 1.312 and 1.218 respectively. For supervised ML applications, coarse decision tree (CDT) predict SST based on AT with train (80%) and test (20%) of the ERA5 data. Finally, the results from CDT model indicate that SST predictions are possible with 98.5% accuracy based on coastal stations. The trained CDT also validated model prediction utilizing observed AT (BMD observations) to forecast monthly SST and found 85% accuracy for monthly time series. In conclusions, CDT can predict SST from station data and assess if there is any possibility for tropical cyclone formation. The future works include further assessment for various categories of tropical cyclone and predict their intensity based on SSTs. This research aims to contribute in disaster mitigation by improving early warning systems. The possibility of cyclone formations will help for preparedness in saving property damages in Bangladesh.</p>

Beyond Hurricane Sandy: What Might the Future Hold for Tropical Cyclones in the North Atlantic?

2014 ◽  
Vol 01 (01) ◽  
pp. 1450007 ◽  
Author(s):  
Radley M. Horton ◽  
Jiping Liu
Keyword(s):  
Tropical Cyclone ◽  
Sea Level Rise ◽  
Sea Level ◽  
Tropical Cyclones ◽  
North Atlantic ◽  
Hurricane Sandy ◽  
Economic Losses ◽  
The North ◽  
The Future ◽  
The North Atlantic

Coastal communities are beginning to understand that sea level rise is projected to dramatically increase the frequency of coastal flooding. However, deep uncertainty remains about how tropical cyclones may change in the future. The North Atlantic has historically been responsible for the majority of global tropical cyclone economic losses, with Hurricane Sandy's approximately USD$70 billion price tag providing a recent example. The North Atlantic has experienced an upward trend in both total tropical cyclones (maximum sustained winds > 18 m/s) and major hurricanes (maximum sustained winds > 50 m/s) in recent decades. While it remains unclear how much of this trend is related to anthropogenic warming, and how tropical cyclone risk may change in the future, the balance of evidence suggests that the strongest hurricanes may become more frequent and intense in the future, and that rainfall associated with tropical cyclones may increase as well. These projections, along with sea level rise and demographic trends, suggest vulnerability to tropical cyclones will increase in the future, thus requiring major coastal adaptation initiatives.

scholarly journals APPLICATION OF GROUND-BASED GPS WATER VAPOR DATA IN THE ANALYSIS OF TROPICAL CYCLONE SON-TINH HITTING HAINAN ISLAND

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 1049-1052
Author(s):  
S. T. Wang ◽  
Y. X. Lin ◽  
W. J. Wang ◽  
B. Y. Zhang ◽  
D. H. Zhang
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Atmospheric Pressure ◽  
Hainan Island ◽  
Satellite Observation ◽  
Economic Losses ◽  
Observation Data ◽  
Reference Information ◽  
Before And After ◽  
Meteorological Elements

Abstract. Tropical cyclone as a disaster. In addition to bringing abundant precipitation to the island, the huge wind will affect the public facilities in the island. In serious cases, it directly endangers people's lives and property. Every year, the disastrous damage caused by tropical cyclone causes direct or indirect economic losses to Hainan Island.This paper studies this problem. Based on the tropical cyclone data provided by China Typhoon Network and the information provided by GPS satellite observation data and 16 meteorological observatories in Hainan Island, this paper takes the monitoring of tropical cyclone Son-Tinh No. 9 in 2018 as an example to analyze the changes of meteorological elements and precipitation during the influence period of tropical cyclone. The results show that: The changes of atmospheric pressure, temperature and relative humidity at the stations are very obvious for the transit of tropical cyclones. When the island is affected by tropical cyclones, these parameters will change significantly. Among them, the abnormal changes of atmospheric pressure and temperature can effectively express the time and extent of the influence of tropical cyclone. It can be used as one of the important indicators to judge tropical cyclone before and after landfall. Based on these obvious changes, the influence of the parameters of tropical cyclone Son-Tinh before and after landing on Hainan Island is analyzed. It can effectively analyze the disasters caused by tropical cyclones and provide some reference information.

scholarly journals Tropical cyclone simulations over Bangladesh at convection permitting 4.4 km & 1.5 km resolution

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hamish Steptoe ◽  
Nicholas Henry Savage ◽  
Saeed Sadri ◽  
Kate Salmon ◽  
Zubair Maalick ◽  
...  
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Sea Level ◽  
Tropical Cyclones ◽  
Weather Forecasting ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Level Pressure ◽  
Medium Range ◽  
Gust Speed

AbstractHigh resolution simulations at 4.4 km and 1.5 km resolution have been performed for 12 historical tropical cyclones impacting Bangladesh. We use the European Centre for Medium-Range Weather Forecasting 5th generation Re-Analysis (ERA5) to provide a 9-member ensemble of initial and boundary conditions for the regional configuration of the Met Office Unified Model. The simulations are compared to the original ERA5 data and the International Best Track Archive for Climate Stewardship (IBTrACS) tropical cyclone database for wind speed, gust speed and mean sea-level pressure. The 4.4 km simulations show a typical increase in peak gust speed of 41 to 118 knots relative to ERA5, and a deepening of minimum mean sea-level pressure of up to −27 hPa, relative to ERA5 and IBTrACS data. The downscaled simulations compare more favourably with IBTrACS data than the ERA5 data suggesting tropical cyclone hazards in the ERA5 deterministic output may be underestimated. The dataset is freely available from 10.5281/zenodo.3600201.

scholarly journals Analysis of Atmospheric and Ionospheric Variations Due to Impacts of Super Typhoon Mangkhut (1822) in the Northwest Pacific Ocean

2021 ◽  
Vol 13 (4) ◽  
pp. 661
Author(s):  
Mohamed Freeshah ◽  
Xiaohong Zhang ◽  
Erman Şentürk ◽  
Muhammad Arqim Adil ◽  
B. G. Mousa ◽  
...  
Keyword(s):  
Wind Speed ◽  
Pacific Ocean ◽  
Tropical Cyclone ◽  
Sea Level ◽  
Northwest Pacific ◽  
Northwest Pacific Ocean ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Super Typhoon ◽  
The Northwest Pacific Ocean

The Northwest Pacific Ocean (NWP) is one of the most vulnerable regions that has been hit by typhoons. In September 2018, Mangkhut was the 22nd Tropical Cyclone (TC) over the NWP regions (so, the event was numbered as 1822). In this paper, we investigated the highest amplitude ionospheric variations, along with the atmospheric anomalies, such as the sea-level pressure, Mangkhut’s cloud system, and the meridional and zonal wind during the typhoon. Regional Ionosphere Maps (RIMs) were created through the Hong Kong Continuously Operating Reference Stations (HKCORS) and International GNSS Service (IGS) data around the area of Mangkhut typhoon. RIMs were utilized to analyze the ionospheric Total Electron Content (TEC) response over the maximum wind speed points (maximum spots) under the meticulous observations of the solar-terrestrial environment and geomagnetic storm indices. Ionospheric vertical TEC (VTEC) time sequences over the maximum spots are detected by three methods: interquartile range method (IQR), enhanced average difference (EAD), and range of ten days (RTD) during the super typhoon Mangkhut. The research findings indicated significant ionospheric variations over the maximum spots during this powerful tropical cyclone within a few hours before the extreme wind speed. Moreover, the ionosphere showed a positive response where the maximum VTEC amplitude variations coincided with the cyclone rainbands or typhoon edges rather than the center of the storm. The sea-level pressure tends to decrease around the typhoon periphery, and the highest ionospheric VTEC amplitude was observed when the low-pressure cell covers the largest area. The possible mechanism of the ionospheric response is based on strong convective cells that create the gravity waves over tropical cyclones. Moreover, the critical change state in the meridional wind happened on the same day of maximum ionospheric variations on the 256th day of the year (DOY 256). This comprehensive analysis suggests that the meridional winds and their resulting waves may contribute in one way or another to upper atmosphere-ionosphere coupling.

scholarly journals Are Special Processes at Work in the Rapid Intensification of Tropical Cyclones?

2015 ◽  
Vol 143 (3) ◽  
pp. 878-882 ◽  
Author(s):  
Roman Kowch ◽  
Kerry Emanuel
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Internal Variability ◽  
Open Ocean ◽  
Rapid Intensification ◽  
Exponential Distributions ◽  
Frequency Distributions ◽  
Fat Tail ◽  
Dissipation Rates ◽  
Special Factors

Abstract Probably not. Frequency distributions of intensification and dissipation developed from synthetic open-ocean tropical cyclone data show no evidence of significant departures from exponential distributions, though there is some evidence for a fat tail of dissipation rates. This suggests that no special factors govern high intensification rates and that tropical cyclone intensification and dissipation are controlled by statistically random environmental and internal variability.

Extended Prediction of North Indian Ocean Tropical Cyclones

2012 ◽  
Vol 27 (3) ◽  
pp. 757-769 ◽  
Author(s):  
James I. Belanger ◽  
Peter J. Webster ◽  
Judith A. Curry ◽  
Mark T. Jelinek
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Tropical Cyclones ◽  
North Indian Ocean ◽  
Ensemble Prediction ◽  
Tropical Cyclone Genesis ◽  
Lead Times ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
The North

Abstract This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.

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