scholarly journals New Flood Model Offers National Streamflow Coverage

Eos ◽  
2016 ◽  
Vol 97 ◽  
Author(s):  
JoAnna Wendel
Keyword(s):  
Flood Forecasting ◽  
National Weather Service ◽  
Flood Model ◽  
Neighborhood Level ◽  
Weather Service

The model, released by the National Weather Service, will provide neighborhood-level flood forecasting.

The United States National Weather Service Real-Time Flood Forecasting

2017 ◽  
Author(s):  
Pedro J. Restrepo
Keyword(s):  
Real Time ◽  
Snow Water Equivalent ◽  
Weather Forecast ◽  
The United States ◽  
Flood Forecasting ◽  
Federal State ◽  
National Weather Service ◽  
Precipitation Temperature ◽  
Snow Water ◽  
Weather Service

The U.S. National Weather Service (NWS) is the agency responsible for flood forecasting. Operational flow forecasting at the NWS is carried out at the 13 river forecasting centers for main river flows. Flash floods, which occur in small localized areas, are forecast at the 122 weather forecast offices. Real-time flood forecasting is a complex process that requires the acquisition and quality control of remotely sensed and ground-based observations, weather and climate forecasts, and operation of reservoirs, water diversions, and returns. Currently used remote-sense observations for operational hydrologic forecasts include satellite observations of precipitation, temperature, snow cover, radar observations of precipitation, and airborne observations of snow water equivalent. Ground-based observations include point precipitation, temperature, snow water equivalent, soil moisture and temperature, river stages, and discharge. Observations are collected by a number of federal, state, municipal, tribal and private entities, and transmitted to the NWS on a daily basis. Once the observations have been checked for quality, a hydrologic forecaster uses the Community Hydrologic Prediction System (CHPS), which takes care of managing the sequence of models and their corresponding data needs along river reaches. Current operational forecasting requires an interaction between the forecaster and the models, in order to adjust differences between the model predictions and the observations, thus improving the forecasts. The final step in the forecast process is the publication of forecasts.

An Analysis of 2016-2018 Tornadoes and National Weather Service Tornado Warnings across the contiguous United States

2021 ◽  
Author(s):  
Evan S. Bentley ◽  
Richard L. Thompson ◽  
Barry R. Bowers ◽  
Justin G. Gibbs ◽  
Steven E. Nelson
Keyword(s):  
United States ◽  
Rotational Velocity ◽  
Radar Data ◽  
Probability Of Detection ◽  
False Alarms ◽  
National Weather Service ◽  
Low Level ◽  
Tornado Warnings ◽  
Tornado Warning ◽  
Weather Service

AbstractPrevious work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–2018) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance.Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (<30 kt), broad (>1nm) circulations in a poor (STP=0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.

scholarly journals Long-Term Performance Metrics for National Weather Service Tornado Warnings

2018 ◽  
Vol 33 (6) ◽  
pp. 1501-1511 ◽  
Author(s):  
Harold E. Brooks ◽  
James Correia
Keyword(s):  
False Alarm ◽  
Lead Time ◽  
Performance Metrics ◽  
Warning System ◽  
Probability Of Detection ◽  
False Alarms ◽  
National Weather Service ◽  
False Alarm Ratio ◽  
Tornado Warnings ◽  
Weather Service

Abstract Tornado warnings are one of the flagship products of the National Weather Service. We update the time series of various metrics of performance in order to provide baselines over the 1986–2016 period for lead time, probability of detection, false alarm ratio, and warning duration. We have used metrics (mean lead time for tornadoes warned in advance, fraction of tornadoes warned in advance) that work in a consistent way across the official changes in policy for warning issuance, as well as across points in time when unofficial changes took place. The mean lead time for tornadoes warned in advance was relatively constant from 1986 to 2011, while the fraction of tornadoes warned in advance increased through about 2006, and the false alarm ratio slowly decreased. The largest changes in performance take place in 2012 when the default warning duration decreased, and there is an apparent increased emphasis on reducing false alarms. As a result, the lead time, probability of detection, and false alarm ratio all decrease in 2012. Our analysis is based, in large part, on signal detection theory, which separates the quality of the warning system from the threshold for issuing warnings. Threshold changes lead to trade-offs between false alarms and missed detections. Such changes provide further evidence for changes in what the warning system as a whole considers important, as well as highlighting the limitations of measuring performance by looking at metrics independently.

Teaching Mesoscale Meteorology in the Age of the Modernized National Weather Service: A Report on the Unidata/COMET Workshop

1995 ◽  
Vol 76 (12) ◽  
pp. 2463-2473 ◽  
Author(s):  
Mohan K. Ramamurthy ◽  
Charles Murphy ◽  
James Moore ◽  
Melanie Wetzel ◽  
David Knight ◽  
...  
Keyword(s):  
National Weather Service ◽  
Mesoscale Meteorology ◽  
Weather Service

scholarly journals The state of weather, water and climate services in the U.S. and strategic challenges for the next decade: the perspective from the American Meteorological Society and U.S. National Weather Service

2021 ◽  
Author(s):  
Mike Farrar
Keyword(s):  
Water Security ◽  
National Weather Service ◽  
Climate Services ◽  
Future Evolution ◽  
Keynote Presentation ◽  
Future Goals ◽  
American Meteorological Society ◽  
Environmental Prediction ◽  
The U.S ◽  
Weather Service

&lt;p&gt;This keynote presentation will discuss several key applications and operational systems in the U.S. National Weather Service (NWS) and how they fit in with the broader mission of providing science-based weather, water and climate services to the nation. In addition, the future evolution of the National Centers for Environmental Prediction&amp;#160;(NCEP) and NWS will be discussed as it relates to future goals and priorities related to people, science, technology, operational concepts and practices, and partnerships between government/public sector, the private sector, and academia. Also, in his role as the current President of the American Meteorological Society (AMS), Dr. Farrar will address the theme for the 2022 AMS annual meeting, &quot;Environmental Security: weather, water and climate for a more secure world&quot;, which will explore the national and human security impacts from extreme weather and climate events and intersections with health, energy, food, and water security.&lt;/p&gt;

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