Skill assessment of a real-time forecast system utilizing a coupled hydrologic and coastal hydrodynamic model during Hurricane Irene (2011)

2013 ◽  
Vol 71 ◽  
pp. 78-94 ◽  
Author(s):  
Kendra M. Dresback ◽  
Jason G. Fleming ◽  
Brian O. Blanton ◽  
Carola Kaiser ◽  
Jonathan J. Gourley ◽  
...  
Keyword(s):  
Real Time ◽  
Hydrodynamic Model ◽  
Skill Assessment ◽  
Forecast System ◽  
Hurricane Irene

The Debris Flow Disaster Faster-Than-Early Forecast System (DFS) with Multi-Sensors Integrated Wireless Sensor Networks

2013 ◽  
Vol 347-350 ◽  
pp. 975-979
Author(s):  
Rong Zhao ◽  
Cai Hong Li ◽  
Yun Jian Tan ◽  
Jun Shi ◽  
Fu Qiang Mu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Debris Flow ◽  
Real Time ◽  
Debris Flows ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Forecast System ◽  
Debris Flow Disaster

This paper presents a Debris Flow Disaster Faster-than-early Forecast System (DFS) with wireless sensor networks. Debris flows carrying saturated solid materials in water flowing downslope often cause severe damage to the lives and properties in their path. Faster-than-early or faster-than-real-time forecasts are imperative to save lives and reduce damage. This paper presents a novel multi-sensor networks for monitoring debris flows. The main idea is to let these sensors drift with the debris flow, to collect flow information as they move along, and to transmit the collected data to base stations in real time. The Raw data are sent to the cloud processing center from the base station. And the processed data and the video of the debris flow are display on the remote PC. The design of the system address many challenging issues, including cost, deployment efforts, and fast reaction.

scholarly journals An automatic lake-model application using near real-time data forcing: Development of an operational forecast model for Lake Erie

2021 ◽  
Author(s):  
Shuqi Lin ◽  
Leon Boegman ◽  
Shiliang Shan ◽  
Ryan Mulligan
Keyword(s):  
Open Access ◽  
Real Time ◽  
Public Safety ◽  
Lake Erie ◽  
Water Resource Management ◽  
Computational Models ◽  
Fishery Management ◽  
Water Levels ◽  
Time Data ◽  
Forecast System

Abstract. For enhanced public safety and water resource management, a three-dimensional operational lake hydrodynamic forecast system called COASTLINES (Canadian cOASTal and Lake forecastINg modEl System) was developed. The modelling system is built upon the Aquatic Ecosystem Model (AEM3D) model, with predictive simulation capabilities developed and tested for a large lake (i.e., Lake Erie). The open-access web-based platform derives model forcing, code execution, post-processing and visualization of the model outputs, including water level elevations and temperature, is in near real-time. COASTLINES currently generates 240-h predictions using atmospheric forcing from 15 km and 25 km horizontal-resolution operational meteorological products from the Environment Canada Global Deterministic Forecast System (GDPS). Simulated water levels were validated against observations from 6 gauge stations, with model error increasing for longer forecast times. Satellite images and lake buoys were applied to validate forecast lake surface temperature (LST) and the water column thermal stratification. The forecast LST is as accurate as hindcasts, with a root-mean-square-deviation < 2 ℃. COASTLINES predicts storm-surge events and up-/down-welling events that are important for flood water and drinking water/fishery management, respectively. Model forecasts are available in real-time at https://coastlines.engineering.queensu.ca/. This study provides an example of the successful development of an operational forecasting system, entirely driven by open-access data, that may be easily adapted to simulate aquatic systems or to drive other computational models, as required for management and public safety.

Basin Hydrometeorology Real-Time Forecast System

2012 ◽  
pp. 665-671
Author(s):  
Tao Peng ◽  
Cheng-zhi Wei ◽  
Jin-tao Ye ◽  
Jun-chao Wang ◽  
Zhi-yuan Yin
Keyword(s):  
Real Time ◽  
Forecast System

Can Proficiency Criteria Be Accurately Identified During Real-Time Fundamental Movement Skill Assessment?

2019 ◽  
Vol 91 (1) ◽  
pp. 64-72 ◽  
Author(s):  
Brodie Ward ◽  
Ashleigh Thornton ◽  
Brendan Lay ◽  
Nigel Chen ◽  
Michael Rosenberg
Keyword(s):  
Real Time ◽  
Skill Assessment ◽  
Fundamental Movement Skill ◽  
Movement Skill Assessment

Utilization of the Northern Gulf Operational Forecast System to Predict Trajectories of Surface Oil from a Persistent Source Offshore of the Mississippi River Delta

2014 ◽  
Vol 2014 (1) ◽  
pp. 531-543 ◽  
Author(s):  
Amy MacFadyen ◽  
Eugene Wei ◽  
Christopher Warren ◽  
Charlie Henry ◽  
Glen Watabayashi
Keyword(s):  
Mississippi River ◽  
Hydrodynamic Model ◽  
Unstructured Grid ◽  
River Delta ◽  
Grid Resolution ◽  
Mississippi River Delta ◽  
Forecast System ◽  
Structured Grid ◽  
Trajectory Models ◽  
One Year

ABSTRACT In this paper, we demonstrate the use of a new operational, unstructured-grid hydrodynamic model within the oil spill trajectory model GNOME (the General NOAA Operational Modeling Environment) to examine the transport of surface oil from a known source approximately 10 miles offshore of the Mississippi River Delta. At this location, a cluster of wells and/or contaminated sediments have been persistently leaking small amounts of oil since they were damaged in 2004. Slicks associated with this source are frequently detected in satellite imagery analysis, which indicates they are often oriented in the along isobath direction with typical dimensions of 0.5–2 km by 10–30 km varying with wind conditions. The Northern Gulf of Mexico Operation Forecast System (NGOFS) has recently been deployed by NOAA and includes this region. The underlying hydrodynamic model is an unstructured grid finite-volume model which allows variable grid resolution ranging from 10 km offshore to ~600 m near the coastline. Unstructured grid models are ideally suited for coastal areas as they allow flexible resolution to resolve complex bathymetry and coastlines. However, large model domains combined with high grid resolution can provide a challenge for operational trajectory models as sub-setting the model grid is not as straightforward as in the structured grid case. The utility of any hydrodynamic model for emergency response depends not only on its accuracy, but on the trajectory modeler's ability to access and use the information in a timely manner. As part of this study, we have developed tools to allow the NGOFS results (in addition to other unstructured grid models) to be readily available to GNOME users. Using output from the NGOFS in GNOME, a one year modeled simulation was run in which surface particles were released continuously from the location of the damaged wells. Predicted trajectories of modeled particles less than ~24-hours in age compare qualitatively well with the satellite observations.

Real-Time Performance of a Multi-Model Ensemble-Based Extended Range Forecast System in Predicting the 2014 Monsoon Season Based on NCEP-CFSv2

2015 ◽  
Vol 109 (10) ◽  
pp. 1802 ◽  
Author(s):  
A. K. Sahai ◽  
R. Chattopadhyay ◽  
S. Joseph ◽  
R. Mandal ◽  
A. Dey ◽  
...  
Keyword(s):  
Real Time ◽  
Monsoon Season ◽  
Model Ensemble ◽  
Forecast System ◽  
Time Performance ◽  
Extended Range

A Real-Time Tsunami Inundation Forecast System Using Vector Supercomputer SX-ACE

2018 ◽  
Vol 13 (2) ◽  
pp. 234-244 ◽  
Author(s):  
Akihiro Musa ◽  
Takashi Abe ◽  
Takuya Inoue ◽  
Hiroaki Hokari ◽  
Yoichi Murashima ◽  
...  
Keyword(s):  
Real Time ◽  
Local Governments ◽  
High Performance ◽  
Polygonal Domain ◽  
Computational Domain ◽  
Xeon Phi ◽  
Forecast System ◽  
Tsunami Inundation ◽  
City Regions ◽  
Efficient Vector

Tsunami disasters can cause serious casualties and damage to social infrastructures. An early understanding of disaster states is required in order to advise evacuations and plan rescues and recoveries. We have developed a real-time tsunami inundation forecast system using a vector supercomputer SX-ACE. The system can complete a tsunami inundation and damage estimation for coastal city regions at the resolution of a 10 m grid size in under 20 minutes, and distribute tsunami inundation and infrastructure damage information to local governments in Japan. We also develop a new configuration for the computational domain, which is changed from rectangles to polygons and called a polygonal domain, in order to effectively simulate in the entire coast of Japan. Meanwhile, new supercomputers have been developed, and their peak performances have increased year by year. In 2016, a new Xeon Phi processor calledKnights Landingwas released for high-performance computing. In this paper, we present an overview of our real-time tsunami inundation forecast system and the polygonal domain, which can decrease the amount of computation in a simulation, and then discuss its performance on a vector supercomputer SX-ACE and a supercomputer system based on Intel Xeon Phi. We also clarify that the real-time tsunami inundation forecast system requires the efficient vector processing of a supercomputer with high-performance cores.

scholarly journals A Dynamical Initialization Scheme for Real-Time Forecasts of Tropical Cyclones Using the WRF Model*

2013 ◽  
Vol 141 (3) ◽  
pp. 964-986 ◽  
Author(s):  
Dong-Hyun Cha ◽  
Yuqing Wang
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Initial Conditions ◽  
Wrf Model ◽  
Forecast Model ◽  
Initial Position ◽  
Northwest Pacific ◽  
Forecast System ◽  
Positive Effects ◽  
Forecast Models

Abstract To improve the initial conditions of tropical cyclone (TC) forecast models, a dynamical initialization (DI) scheme using cycle runs is developed and implemented into a real-time forecast system for northwest Pacific TCs based on the Weather Research and Forecasting (WRF) Model. In this scheme, cycle runs with a 6-h window before the initial forecast time are repeatedly conducted to spin up the axisymmetric component of the TC vortex until the model TC intensity is comparable to the observed. This is followed by a 72-h forecast using the Global Forecast System (GFS) prediction as lateral boundary conditions. In the DI scheme, the spectral nudging technique is employed during each cycle run to reduce bias in the large-scale environmental field, and the relocation method is applied after the last cycle run to reduce the initial position error. To demonstrate the effectiveness of the proposed DI scheme, 69 forecast experiments with and without the DI are conducted for 13 TCs over the northwest Pacific in 2010 and 2011. The DI shows positive effects on both track and intensity forecasts of TCs, although its overall skill depends strongly on the performance of the GFS forecasts. Compared to the forecasts without the DI, on average, forecasts with the DI reduce the position and intensity errors by 10% and 30%, respectively. The results demonstrate that the proposed DI scheme improves the initial TC vortex structure and intensity and provides warm physics spinup, producing initial states consistent with the forecast model, thus achieving improved track and intensity forecasts.

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