scholarly journals Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0)

2019 ◽  
Vol 12 (10) ◽  
pp. 4185-4219 ◽  
Author(s):  
Seppo Pulkkinen ◽  
Daniele Nerini ◽  
Andrés A. Pérez Hortal ◽  
Carlos Velasco-Forero ◽  
Alan Seed ◽  
...  
Keyword(s):  
Open Source ◽  
Early Warning Systems ◽  
The United States ◽  
Model Parameters ◽  
Warning Systems ◽  
File Formats ◽  
Time Simulation ◽  
Weather Forecasters ◽  
Scientific Experiments ◽  
Stochastic Space

Abstract. Pysteps is an open-source and community-driven Python library for probabilistic precipitation nowcasting, that is, very-short-range forecasting (0–6 h). The aim of pysteps is to serve two different needs. The first is to provide a modular and well-documented framework for researchers interested in developing new methods for nowcasting and stochastic space–time simulation of precipitation. The second aim is to offer a highly configurable and easily accessible platform for practitioners ranging from weather forecasters to hydrologists. In this sense, pysteps has the potential to become an important component for integrated early warning systems for severe weather. The pysteps library supports various input/output file formats and implements several optical flow methods as well as advanced stochastic generators to produce ensemble nowcasts. In addition, it includes tools for visualizing and post-processing the nowcasts and methods for deterministic, probabilistic and neighborhood forecast verification. The pysteps library is described and its potential is demonstrated using radar composite images from Finland, Switzerland, the United States and Australia. Finally, scientific experiments are carried out to help the reader to understand the pysteps framework and sensitivity to model parameters.

scholarly journals Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0)

2019 ◽  
Author(s):  
Seppo Pulkkinen ◽  
Daniele Nerini ◽  
Andrés A. Pérez Hortal ◽  
Carlos Velasco-Forero ◽  
Alan Seed ◽  
...  
Keyword(s):  
Open Source ◽  
Early Warning Systems ◽  
Model Parameters ◽  
Warning Systems ◽  
New Methods ◽  
File Formats ◽  
Time Simulation ◽  
Weather Forecasters ◽  
Scientific Experiments ◽  
Stochastic Space

Abstract. Pysteps is an open-source and community-driven Python library for probabilistic precipitation nowcasting – that is to say, very-short range forecasting (0–6 h). The aim of pysteps is to serve two different needs. The first is to provide a modular and well-documented framework for researchers interested in developing new methods for nowcasting and stochastic space-time simulation of precipitation. The second aim is to offer a highly configurable and easily accessible platform for practitioners ranging from weather forecasters to hydrologists. In this sense, pysteps has the potential to become an important component for integrated early warning systems for severe weather. The pysteps library supports standard input/output file formats and implements several optical flow methods as well as advanced stochastic generators to produce ensemble nowcasts. In addition, it includes tools for visualizing and post-processing the nowcasts and methods for deterministic, probabilistic, and neighbourhood forecast verification. The pysteps library is described and its potential is demonstrated using radar composite images from Finland, Switzerland, United States, and Australia. Finally, scientific experiments are carried out to help the reader to understand the pysteps framework and sensitivity to model parameters.

Disaster Scenarios

2030 ◽  
2010 ◽  
Author(s):  
Rutger van Santen ◽  
Djan Khoe ◽  
Bram Vermeer
Keyword(s):  
Volcanic Eruptions ◽  
Early Warning Systems ◽  
The United States ◽  
Warning Systems ◽  
University Campus ◽  
Human Beings ◽  
Tidal Waves ◽  
University Of Technology ◽  
Chinese Coast ◽  
The University

A hurricane striking the Chinese coast is ten times as lethal as one hitting the United States. The number of U.S. victims is limited because of better precautions, warning systems, and evacuation methods. More effective observation and communication can save lives. A century ago, hurricanes killed around 7,000 Americans every year, whereas nowadays there are only very few hurricanes of the lethality of Katrina. That progress has yet to reach every corner of Earth, says Guus Berkhout regretfully. This Dutch geophysicist has immersed himself in the mechanisms of disasters and disaster prevention since the beginning of his scientific career—first as professor of seismic imaging and later as professor of innovation at Delft University of Technology in the Netherlands. We talked to him at the university campus that lies 3 meters below sea level. At his laboratory, Berkhout analyzes the early warning systems and contingency plans that will be needed to protect both his lab and his compatriots. “We can’t stop earthquakes, volcanic eruptions, hurricanes, or tidal waves from happening,” he stresses. “And we may never be able to predict hurricanes or earthquakes with sufficient accuracy. Nor can we hope to prevent people from living in dangerous places. They are simply too attractive.” Human beings indeed seem addicted to living on the edge of catastrophe. The World Bank has calculated that a fifth of all countries are under permanent threat of natural disaster, with some 3.4 billion people—roughly half the world’s population—at heightened risk of being killed by one. Yet unsafe regions are often exceptionally popular places to live and work, one reason being that floodplains and the slopes of volcanoes are highly fertile. The climate is milder along the coast, the soil better, and transport more efficient than farther inland. Even the likelihood of earthquakes isn’t enough to persuade people to live elsewhere, as witnessed by some of the most densely populated areas of California and Japan. Current migration trends—moving to where the action is—suggest that the proportion of people living in unsafe areas will only increase.

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 Goes-13 IR Images for Rainfall Forecasting in Hurricane Storms

Forecasting ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 85-101
Author(s):  
Marilu Meza-Ruiz ◽  
Alfonso Gutierrez-Lopez
Keyword(s):  
Early Warning ◽  
Satellite Images ◽  
Early Warning Systems ◽  
The United States ◽  
Warning Systems ◽  
Rainfall Forecasting ◽  
Systematic Analysis ◽  
Tropical Regions ◽  
Surface Precipitation ◽  
Analysis Of The Images

Currently, it is possible to access a large amount of satellite weather information from monitoring and forecasting severe storms. However, there are no methods of employing satellite images that can improve real-time early warning systems in different regions of Mexico. The auto-estimator is the most commonly used technique that was developed for specific locations in the United States of America (32°–49° latitude) for the type of convective storms. However, the estimation of precipitation intensities for meteorological conditions in tropic latitudes, using the auto-estimator technique, needs to be re-adjusted and calibrated. It is necessary to improve this type of technique that allows decision-makers to have hydro-informatic tools capable of improving early warning systems in tropical regions (15°–25° Mexican tropic latitude). The main objective of the work is to estimate rainfall from satellite imagery in the infrared (IR) spectrum from the Geostationary Operational Environmental Satellite (GOES), validating these estimates with a network of surface rain gauges. Using the GOES-13 IR images every 15 min and using the auto-estimator, a downscaling of six hurricanes was performed from which surface precipitation events were measured. The two main difficulties were to match the satellite images taken every 15 min with the surface data measured every 10 min and to develop a program in C+ that would allow the systematic analysis of the images. The results of this work allow us to get a new adjustment of coefficients in a new equation of the auto-estimator, valid for rain produced by hurricanes, something that has not been done until now. Although no universal relationship has been found for hurricane rainfall, it is evident that the original formula of the auto-estimator technique needs to be modified according to geographical latitude.

scholarly journals Integrating local pore water pressure monitoring in territorial early warning systems for weather-induced landslides

Landslides ◽  
2021 ◽  
Author(s):  
Gaetano Pecoraro ◽  
Michele Calvello
Keyword(s):  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Model Performance ◽  
Early Warning Systems ◽  
Model Parameters ◽  
Pressure Measurements ◽  
Warning Systems ◽  
Warning Model ◽  
Statistical Indicators

AbstractA methodology designed to integrate widespread meteorological monitoring and pore water pressure measurements is proposed. The procedure is tested in 30 hydrological basins highly susceptible to weather-induced landslides in Norway. The following data are used: a catalog of 125 weather-induced landslides in soils registered between January 2013 and June 2017, widespread meteorological monitoring data employed in a territorial warning model, and pore water pressure measurements retrieved from boreholes installed for a variety of geotechnical projects. The territorial warning model is initially applied to identify the warning events and the correspondent warning level in the test areas over the analysis period. Afterwards, a method for assessing the territorial warning events by analyzing the trends of the monitored pore water pressures is proposed. Finally, an augmented territorial warning model is calibrated and validated using statistical indicators widely adopted in literature. The analysis of the results reveals a satisfactory correspondence between days with landslides and the warning levels provided by the augmented territorial warning model. A final comparison between the results of the model calibration and the model validation highlighted the consistency of the model performance, once the three model parameters are adequately set.

Smoke Detectors: Reducing Deaths and Injuries Due to Fire

PEDIATRICS ◽  
1980 ◽  
Vol 65 (4) ◽  
pp. 718-724
Author(s):  
Keith S. Reisinger
Keyword(s):  
Early Warning ◽  
Early Warning Systems ◽  
The United States ◽  
Warning Systems ◽  
Escape Route ◽  
Fire Hazards ◽  
Ambient Temperatures ◽  
The Past ◽  
Smoke Detectors ◽  
Heat Detectors

The United States leads all nations in the incidence of deaths due to fire. In the past two decades significant technologic advances have resulted in the development of inexpensive and reliable smoke detectors. These detectors can provide early warning to allow sleeping residents easy exit when a fire occurs in the home. Currently, there are three major types of early warning devices: heat detectors, photoelectric smoke detectors, and ionization smoke detectors. Heat detectors sound an alarm in response to rapid increases in temperature and/ or ambient temperatures above 135 F. Photoelectric smoke detectors are particularly effective for smoldering fires, because they are less influenced by the smaller particles of combustion emitted during household cooking or from automobile exhaust than are ionization smoke detectors. The ionization smoke detectors respond more quickly than photoelectric smoke detectors to fast burning fires and have been proved effective in sounding an early alarm in the vast majority of home fires. For best all-around fire protection, a home should have more than one type of detector. Detectors should be located on the ceiling or high on the ceiling of every level of the house close to each bedroom. Properly installed and maintained smoke detectors can reduce the tragic consequences of home fires, but even greater gains can be made by combining these early warning systems with a reduction in home fire hazards and in practicing a well planned fire escape route.

The United States Defence Areas in Greenland

1988 ◽  
Vol 23 (3) ◽  
pp. 123-144 ◽  
Author(s):  
Clive Archer
Keyword(s):  
United States ◽  
Early Warning Systems ◽  
The United States ◽  
Second World War ◽  
Warning Systems ◽  
Us Military ◽  
Military Presence ◽  
The Us ◽  
The Usa ◽  
Second World

Archer, C. The United States Defence Areas in Greenland. Cooperation and Conflict, XXIII, 1988, 123-144. An examination of the US military presence in Greenland shows how it has developed in tandem with wider US strategy. After the Second World War bases were used by Strategic Air Command and later for early warning systems. The US presence has had consequences for the host nations, Denmark and Greenland, in its effect on the local populations, in its intrusion into host state politics and by the association with the defence policies of the USA. The 1980s have brought a questioning of the US defence areas in Greenland by Greenlandic and Danish politicians.

r.massmov: an open-source landslide model for dynamic early warning systems

2013 ◽  
Vol 70 (2) ◽  
pp. 1153-1179 ◽  
Author(s):  
Monia Elisa Molinari ◽  
Massimiliano Cannata ◽  
Claudia Meisina
Keyword(s):  
Open Source ◽  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Landslide Model

scholarly journals Assessing the performance of regional landslide early warning models: the EDuMaP method

2016 ◽  
Vol 16 (1) ◽  
pp. 103-122 ◽  
Author(s):  
M. Calvello ◽  
L. Piciullo
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Model Performance ◽  
Warning System ◽  
Early Warning Systems ◽  
Communication Strategy ◽  
Performance Criteria ◽  
Model Parameters ◽  
Warning Systems ◽  
Warning Model

Abstract. A schematic of the components of regional early warning systems for rainfall-induced landslides is herein proposed, based on a clear distinction between warning models and warning systems. According to this framework an early warning system comprises a warning model as well as a monitoring and warning strategy, a communication strategy and an emergency plan. The paper proposes the evaluation of regional landslide warning models by means of an original approach, called the "event, duration matrix, performance" (EDuMaP) method, comprising three successive steps: identification and analysis of the events, i.e., landslide events and warning events derived from available landslides and warnings databases; definition and computation of a duration matrix, whose elements report the time associated with the occurrence of landslide events in relation to the occurrence of warning events, in their respective classes; evaluation of the early warning model performance by means of performance criteria and indicators applied to the duration matrix. During the first step the analyst identifies and classifies the landslide and warning events, according to their spatial and temporal characteristics, by means of a number of model parameters. In the second step, the analyst computes a time-based duration matrix with a number of rows and columns equal to the number of classes defined for the warning and landslide events, respectively. In the third step, the analyst computes a series of model performance indicators derived from a set of performance criteria, which need to be defined by considering, once again, the features of the warning model. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warning data from the municipal early warning system operating in Rio de Janeiro (Brazil).

scholarly journals Qualitative Study of Pediatric Early Warning Systems’ Impact on Interdisciplinary Communication in Two Pediatric Oncology Hospitals With Varying Resources

2020 ◽  
pp. 1079-1086
Author(s):  
Dylan Graetz ◽  
Erica C. Kaye ◽  
Marcela Garza ◽  
Gia Ferrara ◽  
Mario Rodriguez ◽  
...  
Keyword(s):  
United States ◽  
Intensive Care ◽  
Qualitative Study ◽  
Pediatric Oncology ◽  
Interdisciplinary Communication ◽  
Limited Resource ◽  
Early Warning Systems ◽  
The United States ◽  
Warning Systems ◽  
Care Providers

PURPOSE Hospitalized pediatric oncology patients are at high risk of deterioration and require frequent interdisciplinary communication to deliver high-quality care. Pediatric early warning systems (PEWS) are used by hospitals to reduce deterioration, but it is unknown how these systems affect communication about patient care in high- and limited-resource pediatric oncology settings. METHODS This qualitative study included semistructured interviews describing PEWS and subsequent team communication at 2 pediatric cancer centers, 1 in the United States and 1 in Guatemala. Participants included nurses, and frontline and intensive care providers who experienced recent deterioration events. Transcripts were coded and analyzed inductively using MAXQDA software. RESULTS The study included 41 providers in Guatemala and 42 providers in the United States (33 nurses, 30 ward providers, and 20 pediatric intensive care providers). Major themes identified include “hierarchy,” “empowerment,” “quality and method of communication,” and “trigger.” All providers described underlying medical hierarchies affecting the quality of communication regarding patient deterioration events and identified PEWS as empowering. Participants from the United States described the algorithmic approach to care and technology associated with PEWS contributing to impaired clinical judgement and a lack of communication. In both settings, PEWS sparked interdisciplinary communication and inspired action. CONCLUSION PEWS enhance interdisciplinary communication in high- and limited-resource study settings by empowering bedside providers. Traditional hierarchies contributed to negative communication and, in well-resourced settings, technology and automation resulted in lack of communication. Understanding contextual elements is integral to optimizing PEWS and improving pediatric oncology outcomes in hospitals of all resource levels.

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