Toward a typology of weak-signal early alert systems: functional early warning systems in the post-COVID age

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jan Černý ◽  
Martin Potančok ◽  
Elias Castro Hernandez
Keyword(s):  
Peer Review ◽  
Early Warning ◽  
Warning System ◽  
Early Warning Systems ◽  
Weak Signal ◽  
Warning Systems ◽  
Weak Signals ◽  
Content Type ◽  
Human In The Loop ◽  
Early Alert Systems

PurposeThe study aims to expand on the concept of an early warning system (EWS) by introducing weak-signal detection, human-in-the-loop (HIL) verification and response tuning as integral parts of an EWS's design.Design/methodology/approachThe authors bibliographically highlight the evolution of EWS over the last 30+ years, discuss instances of EWSs in various types of organizations and industries and highlight limitations of current systems.FindingsProposed system to be used in the transforming of weak signals to early warnings and associated weak/strong responses.Originality/valueThe authors contribute to existing literature by presenting (1) novel approaches to dealing with some of the well-known issues associated with contemporary EWS and (2) an event-agnostic heuristic for dealing with weak signals.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2020-0513.

The human dimension of early warning – a viewpoint

2019 ◽  
Vol 11 (2) ◽  
pp. 263-274
Author(s):  
Mo Hamza ◽  
Peter Månsson
Keyword(s):  
Early Warning ◽  
Warning System ◽  
Early Warning Systems ◽  
Human Dimension ◽  
Warning Systems ◽  
Theoretical Frameworks ◽  
Content Type ◽  
Starting Point ◽  
End To End ◽  
Early Warnings

Purpose The 2004 Boxing Day tsunami prompted global efforts to develop end-to-end multi-hazard warning systems. Taking this event as a starting point, and drawing on experiences from the following advancement of the Indonesian tsunami early warning system, this paper aims to highlight the importance of paying attention to human factors and the perceptions and behaviors of end recipients when trying to design efficient early warning systems. Design/methodology/approach The study is a viewpoint where theoretical frameworks for the design of efficient early warning systems are used as backdrop to an extensive review and analysis of secondary data, including scientific papers and newspaper articles. Findings The paper presents what an end-to-end warning system means, explores process problems related to perception and communication and concludes with views and recommendations toward more inclusive early warnings. Originality/value Research and practice related to early warning systems have traditionally had a strong focus on technological elements whilst the target groups of early warnings (i.e. communities) have received far less attention and resources. This paper focuses on the human dimension of warning systems and uses a real case to exemplify how efficient warning systems not only require a sound scientific and technological basis, but also depend on the awareness, trust and will of the people they aim to protect.

scholarly journals Brief communication "Landslide Early Warning System: toolbox and general concepts"

2013 ◽  
Vol 13 (1) ◽  
pp. 85-90 ◽  
Author(s):  
E. Intrieri ◽  
G. Gigli ◽  
N. Casagli ◽  
F. Nadim
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
End Users ◽  
Flow Chart ◽  
Warning Systems ◽  
Limited Experience ◽  
Practical Guidelines ◽  
Landslide Early Warning

Abstract. We define landslide Early Warning Systems and present practical guidelines to assist end-users with limited experience in the design of landslide Early Warning Systems (EWSs). In particular, two flow chart-based tools coming from the results of the SafeLand project (7th Framework Program) have been created to make them as simple and general as possible and in compliance with a variety of landslide types and settings at single slope scale. We point out that it is not possible to cover all the real landslide early warning situations that might occur, therefore it will be necessary for end-users to adapt the procedure to local peculiarities of the locations where the landslide EWS will be operated.

scholarly journals Communication architecture of an early warning system

2010 ◽  
Vol 10 (11) ◽  
pp. 2215-2228 ◽  
Author(s):  
M. Angermann ◽  
M. Guenther ◽  
K. Wendlandt
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Satellite Communication ◽  
Warning System ◽  
Early Warning Systems ◽  
Lessons Learned ◽  
Warning Systems ◽  
Communication Architecture ◽  
Design And Implementation ◽  
Communication Links

Abstract. This article discusses aspects of communication architecture for early warning systems (EWS) in general and gives details of the specific communication architecture of an early warning system against tsunamis. While its sensors are the "eyes and ears" of a warning system and enable the system to sense physical effects, its communication links and terminals are its "nerves and mouth" which transport measurements and estimates within the system and eventually warnings towards the affected population. Designing the communication architecture of an EWS against tsunamis is particularly challenging. Its sensors are typically very heterogeneous and spread several thousand kilometers apart. They are often located in remote areas and belong to different organizations. Similarly, the geographic spread of the potentially affected population is wide. Moreover, a failure to deliver a warning has fatal consequences. Yet, the communication infrastructure is likely to be affected by the disaster itself. Based on an analysis of the criticality, vulnerability and availability of communication means, we describe the design and implementation of a communication system that employs both terrestrial and satellite communication links. We believe that many of the issues we encountered during our work in the GITEWS project (German Indonesian Tsunami Early Warning System, Rudloff et al., 2009) on the design and implementation communication architecture are also relevant for other types of warning systems. With this article, we intend to share our insights and lessons learned.

Torrent Monitoring and Early Warning Systems Development

2022 ◽  
pp. 195-216
Author(s):  
Dejan Vasović ◽  
Ratko Ristić ◽  
Muhamed Bajrić
Keyword(s):  
Emergency Management ◽  
Early Warning ◽  
Early Warning System ◽  
Catchment Area ◽  
Warning System ◽  
Modern Society ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Small Catchment ◽  
National Emergency

The level of sustainability of a modern society is associated with the ability to manage unwanted stressors from the environment, regardless of origin. Torrential floods represent a hydrological hazard whose frequency and intensity have increased in recent years, mainly due to climate changes. In order to effectively manage the risks of torrents, it is necessary to apply early warning systems, since torrential floods are formed very quickly, especially on the watercourses of a small catchment area. The early warning system is part of a comprehensive torrential flood risk management system, seen as a technical entity for the collection, transformation, and rapid distribution of data. Modern early warning systems are the successors of rudimentary methods used in the past, and they are based on ICT and mobile applications developed in relation to the requirements of end users. The chapter presents an analysis of characteristic examples of the use. The main conclusion of the chapter indicates the need to implement early warning systems in national emergency management structures.

KLR Approach as an Early Warning Indicator of Turkish Currency and Banking Crisis in 2000 and 2001

2016 ◽  
pp. 222-239
Author(s):  
Filiz Eryılmaz
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Financial Stability ◽  
Banking Crisis ◽  
Warning System ◽  
Early Warning Systems ◽  
Lessons Learned ◽  
Warning Systems ◽  
Window Approach ◽  
Global Growth

International organizations as private sector institutions started to develop Early Warning System [EWS] models aiming to anticipate whether and when individual countries can collide with a financial crisis. EWS models can be made most useful to help sustain global growth and maintain financial stability, especially in light of the lessons learned from the current and past crises. This paper proposes Early Warning Systems (EWS) for Turkish Currency and Banking Crisis in 2000 and 2001. To that end “KLR model” or “signaling window” approach developed by Kaminski, Lorezondo and Reinhart (1998) is testified in the empirical part of this research and applied to a sample of Turkey macroeconomic data for the 1998-2003 monthly periods.

scholarly journals Recognizing the Famine Early Warning Systems Network: Over 30 Years of Drought Early Warning Science Advances and Partnerships Promoting Global Food Security

2019 ◽  
Vol 100 (6) ◽  
pp. 1011-1027 ◽  
Author(s):  
Chris Funk ◽  
Shraddhanand Shukla ◽  
Wassila Mamadou Thiaw ◽  
James Rowland ◽  
Andrew Hoell ◽  
...  
Keyword(s):  
Food Security ◽  
Early Warning ◽  
Warning System ◽  
Climate Extremes ◽  
Early Warning Systems ◽  
Food Prices ◽  
Humanitarian Assistance ◽  
Warning Systems ◽  
Recent Climate ◽  
Drought Early Warning

AbstractOn a planet with a population of more than 7 billion, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow-onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017. Since 1985, the U.S. Agency for International Development’s Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model, and predict food insecurity. Here we provide an overview of FEWS NET’s DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET’s monitoring system, it draws from many disciplines—remote sensing, climate prediction, agroclimatic monitoring, and hydrologic modeling. Here we describe FEWS NET’s multiagency multidisciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Midseason droughts are monitored using multiple cutting-edge Earth-observing systems. Crop and hydrologic models can translate these observations into impacts. The resulting information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.

scholarly journals Rainfall Threshold Estimation and Landslide Forecasting for Kalimpong, India Using SIGMA Model

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1195 ◽  
Author(s):  
Minu Treesa Abraham ◽  
Neelima Satyam ◽  
Sai Kushal ◽  
Ascanio Rosi ◽  
Biswajeet Pradhan ◽  
...  
Keyword(s):  
Early Warning ◽  
Sigma Model ◽  
Warning System ◽  
Daily Rainfall ◽  
Early Warning Systems ◽  
Rainfall Threshold ◽  
Integrated System ◽  
Warning Systems ◽  
Rainfall Forecasting ◽  
Rainfall Thresholds

Rainfall-induced landslides are among the most devastating natural disasters in hilly terrains and the reduction of the related risk has become paramount for public authorities. Between the several possible approaches, one of the most used is the development of early warning systems, so as the population can be rapidly warned, and the loss related to landslide can be reduced. Early warning systems which can forecast such disasters must hence be developed for zones which are susceptible to landslides, and have to be based on reliable scientific bases such as the SIGMA (sistema integrato gestione monitoraggio allerta—integrated system for management, monitoring and alerting) model, which is used in the regional landslide warning system developed for Emilia Romagna in Italy. The model uses statistical distribution of cumulative rainfall values as input and rainfall thresholds are defined as multiples of standard deviation. In this paper, the SIGMA model has been applied to the Kalimpong town in the Darjeeling Himalayas, which is among the regions most affected by landslides. The objectives of the study is twofold: (i) the definition of local rainfall thresholds for landslide occurrences in the Kalimpong region; (ii) testing the applicability of the SIGMA model in a physical setting completely different from one of the areas where it was first conceived and developed. To achieve these purposes, a calibration dataset of daily rainfall and landslides from 2010 to 2015 has been used; the results have then been validated using 2016 and 2017 data, which represent an independent dataset from the calibration one. The validation showed that the model correctly predicted all the reported landslide events in the region. Statistically, the SIGMA model for Kalimpong town is found to have 92% efficiency with a likelihood ratio of 11.28. This performance was deemed satisfactory, thus SIGMA can be integrated with rainfall forecasting and can be used to develop a landslide early warning system.

scholarly journals Communication Structures and Decision Making Cues and Criteria to Support Effective Drought Warning in Central Malawi

2020 ◽  
Vol 2 ◽  
Author(s):  
Alexia Calvel ◽  
Micha Werner ◽  
Marc van den Homberg ◽  
Andrés Cabrera Flamini ◽  
Ileen Streefkerk ◽  
...  
Keyword(s):  
Decision Making ◽  
Early Warning ◽  
Warning System ◽  
Agricultural Practices ◽  
Early Warning Systems ◽  
Sudden Onset ◽  
Small Scale ◽  
Warning Systems ◽  
Structured Interviews ◽  
Early Action

Early warning systems trigger early action and enable better disaster preparedness. People-centered dissemination and communication are pivotal for the effective uptake of early warnings. Current research predominantly focuses on sudden-onset hazards, such as floods, ignoring considerable differences with slow-onset hazards, such as droughts. We identify the essential factors contributing to effective drought dissemination and communication using the people-centered approach advocated in the WMOs Multi-Hazard Early Warning System Framework (MHEWS). We use semi-structured interviews with key stakeholders and focus group discussions with small-scale farmers in the Mangochi and Salima Districts of Malawi. We show that the timely release of seasonal forecast, the tailoring of the drought warning content (and its timing) to agricultural decision making, and the provision of several dissemination channels enhance trust and improve uptake of drought warning information by farmers. Our analysis demonstrates that farmers seek, prepare, and respond to drought warning information when it is provided as advice on agricultural practices, rather than as weather-related information. The information was found to be useful where it offers advice on the criteria and environmental cues that farmers can use to inform their decisions in a timely manner. Based on our findings, we propose that by focusing on enhancing trust, improving information uptake and financial sustainability as key metrics, the MHEWS can be adapted for use in monitoring the effectiveness of early warning systems.

scholarly journals Verification of Red Flag Warnings across the Northwestern U.S. as Forecasts of Large Fire Occurrence

Fire ◽  
2020 ◽  
Vol 3 (4) ◽  
pp. 60
Author(s):  
Joshua Clark ◽  
John T. Abatzoglou ◽  
Nicholas J. Nauslar ◽  
Alistair M.S. Smith
Keyword(s):  
Early Warning ◽  
Warning System ◽  
Early Warning Systems ◽  
The United States ◽  
Fire Occurrence ◽  
Warning Systems ◽  
Large Fire ◽  
Fire Activity ◽  
Large Fires ◽  
Red Flag

Red Flag Warnings (RFWs) issued by the National Weather Service in the United States (U.S.) are an important early warning system for fire potential based on forecasts of critical fire weather that promote increased fire activity, including the occurrence of large fires. However, verification of RFWs as they relate to fire activity is lacking, thereby limiting means to improve forecasts as well as increase value for end users. We evaluated the efficacy of RFWs as forecasts of large fire occurrence for the Northwestern U.S.—RFWs were shown to have widespread significant skill and yielded an overall 124% relative improvement in forecasting large fire occurrences than a reference forecast. We further demonstrate that the skill of RFWs is significantly higher for lightning-ignited large fires than for human-ignited fires and for forecasts issued during periods of high fuel dryness than those issued in the absence of high fuel dryness. The results of this first verification study of RFWs related to actualized fire activity lay the groundwork for future efforts towards improving the relevance and usefulness of RFWs and other fire early warning systems to better serve the fire community and public.

scholarly journals Using learning analytics to develop early-warning system for at-risk students

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Gökhan Akçapınar ◽  
Arif Altun ◽  
Petek Aşkar
Keyword(s):  
Online Learning ◽  
Academic Performance ◽  
Early Warning ◽  
At Risk Students ◽  
Warning System ◽  
Early Warning Systems ◽  
Computer Hardware ◽  
Warning Systems ◽  
Processing Techniques

Abstract In the current study interaction data of students in an online learning setting was used to research whether the academic performance of students at the end of term could be predicted in the earlier weeks. The study was carried out with 76 second-year university students registered in a Computer Hardware course. The study aimed to answer two principle questions: which algorithms and features best predict the end of term academic performance of students by comparing different classification algorithms and pre-processing techniques and whether or not academic performance can be predicted in the earlier weeks using these features and the selected algorithm. The results of the study indicated that the kNN algorithm accurately predicted unsuccessful students at the end of term with a rate of 89%. When findings were examined regarding the analysis of data obtained in weeks 3, 6, 9, 12, and 14 to predict whether the end-of-term academic performance of students could be predicted in the earlier weeks, it was observed that students who were unsuccessful at the end of term could be predicted with a rate of 74% in as short as 3 weeks’ time. The findings obtained from this study are important for the determination of features for early warning systems that can be developed for online learning systems and as indicators of student success. At the same time, it will aid researchers in the selection of algorithms and pre-processing techniques in the analysis of educational data.

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