Emergency flood bulletins for Cyclones Idai and Kenneth: A critical evaluation of the use of global flood forecasts for international humanitarian preparedness and response

Emerton, Rebecca; Cloke, Hannah; Ficchì, Andrea; Hawker, Laurence; Wit, Sara de; Speight, Linda; Prudhomme, Christel; Rundell, Philip; West, R.E.; Neal, Jeffrey; Cuna, Joaquim; Harrigan, Shaun; Titley, Helen; Magnusson, Linus; Pappenberger, Florian; Klingaman, Nicholas P.; Stephens, Elisabeth

doi:10.1016/j.ijdrr.2020.101811

Cited by 61 publications

(46 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Heavy rains associated with TC DINEO (2017) have caused 700,000 refugees and tens of millions of USD of damage in Mozambique, while the overall cost of TCs ENAWO (2017) and AVA (2018), which affected nearly one million people in Madagascar, was estimated to be more than USD 600 million (about 7% of Madagascar's average annual gross domestic product). These heavy tolls are, however, out of all proportion to those of TCs IDAÏ (considered by the United Nations as the worst natural disaster ever in the MC) and KENNETH (the most intense TC ever reported in the MC [20]), which both made landfall in Mozambique in 2019 [21]. According to the latest economic reports, these two storms have affected a total of nearly 1.7 million people and caused damage and losses estimated at ~USD three billion-plus a further recovery cost estimated at USD 3.4 billion-by the World Bank and Mozambican officials [22].…”

Section: Introductionmentioning

confidence: 99%

Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 1: Overview and Observing Component of the Research Project RENOVRISK-CYCLONE

et al. 2021

View full text Add to dashboard Cite

The international research program “ReNovRisk-CYCLONE” (RNR-CYC, 2017–2021) directly involves 20 partners from 5 countries of the south-west Indian-Ocean. It aims at improving the observation and modelling of tropical cyclones in the south-west Indian Ocean, as well as to foster regional cooperation and improve public policies adapted to present and future tropical cyclones risk in this cyclonic basin. This paper describes the structure and main objectives of this ambitious research project, with emphasis on its observing components, which allowed integrating numbers of innovative atmospheric and oceanic observations (sea-turtle borne and seismic data, unmanned airborne system, ocean gliders), as well as combining standard and original methods (radiosoundings and global navigation satellite system (GNSS) atmospheric soundings, seismic and in-situ swell sampling, drone and satellite imaging) to support research on tropical cyclones from the local to the basin-scale.

show abstract

Section: Introductionmentioning

confidence: 99%

Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 1: Overview and Observing Component of the Research Project RENOVRISK-CYCLONE

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Extreme weather phenomena such as tropical cyclones (TCs), that are relatively short-lived (average life span of 7-10 days), destructive events, have a significant impact on life and property (Emerton et al 2020). Spatio-temporal patterns of heavy rainfall related to tropical cyclones have been investigated using climate network approaches (Traxl et al 2016;Ozturk et al 2018Ozturk et al , 2019.…”

Section: Introductionmentioning

confidence: 99%

Complex network approach for detecting tropical cyclones

et al. 2021

Self Cite

View full text Add to dashboard Cite

Tropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the interactions among climate variables at different locations on the Earth’s surface, and in particular, time-evolving climate networks have been successfully applied to study different climate phenomena at comparably long time scales, such as the El Niño Southern Oscillation, different monsoon systems, or the climatic impacts of volcanic eruptions. Here, we develop and apply a complex network approach suitable for the investigation of the relatively short-lived TCs. We show that our proposed methodology has the potential to identify TCs and their tracks from mean sea level pressure (MSLP) data. We use the ERA5 reanalysis MSLP data to construct successive networks of overlapping, short-length time windows for the regions under consideration, where we focus on the north Indian Ocean and the tropical north Atlantic Ocean. We compare the spatial features of various topological properties of the network, and the spatial scales involved, in the absence and presence of a cyclone. We find that network measures such as degree and clustering exhibit significant signatures of TCs and have striking similarities with their tracks. The study of the network topology over time scales relevant to TCs allows us to obtain crucial insights into the effects of TCs on the spatial connectivity structure of sea-level pressure fields.

show abstract

“…Extreme weather phenomena such as tropical cyclones (TCs), that are relatively short-lived, destructive events, have a significant impact on life and property (Emerton et al, 2020). Spatio-temporal patterns of heavy rainfall related to tropical cyclones have been investigated using climate network approaches (Traxl et al, 2016;Ozturk et al, 2018Ozturk et al, , 2019.…”

Section: Introductionmentioning

confidence: 99%

Complex Network Approach for Detecting Tropical Cyclones

Gupta

Boers

Pappenberger

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

Tropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society around the globe, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the interactions among climate variables at different locations on the Earth's surface, and in particular, time-evolving climate networks have been successfully applied to study different climate phenomena at comparably long time scales, such as the El Ni~no Southern Oscillation, different monsoon systems, or the climatic impacts of volcanic eruptions. Here, we develop and apply a complex network approach suitable for the investigation of the relatively short-lived TCs. We show that our proposed methodology has the potential to identify TCs and their tracks from mean sea level pressure (MSLP) data. We use the ERA5 reanalysis MSLP data to construct successive networks 20 of overlapping, short-length time windows for the regions under consideration, where we focus on the north Indian Ocean and the tropical north Atlantic Ocean. We compare the spatial features of various topological properties of the network, and the spatial scales involved, in the absence and presence of a cyclone. We find that network measures such as degree and clustering exhibit significant signatures of TCs and have striking similarities with their tracks. The study of network topology over time scales relevant to TCs allows us to obtain useful insights into the individual local signature of changes in the flow structure of the regional climate system.

show abstract

Emergency flood bulletins for Cyclones Idai and Kenneth: A critical evaluation of the use of global flood forecasts for international humanitarian preparedness and response

Cited by 61 publications

References 48 publications

Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 1: Overview and Observing Component of the Research Project RENOVRISK-CYCLONE

Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 1: Overview and Observing Component of the Research Project RENOVRISK-CYCLONE

Complex network approach for detecting tropical cyclones

Complex Network Approach for Detecting Tropical Cyclones

Contact Info

Product

Resources

About