Application of Forecast Verification Science to Operational River Forecasting in the U.S. National Weather Service

2009 ◽  
Vol 90 (6) ◽  
pp. 779-784 ◽  
Author(s):  
Julie Demargne ◽  
Mary Mullusky ◽  
Kevin Werner ◽  
Thomas Adams ◽  
Scott Lindsey ◽  
...  
2021 ◽  
Author(s):  
Mike Farrar

<p>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 (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, "Environmental Security: weather, water and climate for a more secure world", which will explore the national and human security impacts from extreme weather and climate events and intersections with health, energy, food, and water security.</p>


Author(s):  
Yumin Yan ◽  
Brooke Fisher Liu ◽  
Anita Atwell Seate ◽  
Samantha Joan Stanley ◽  
Allison Patrice Chatham

2012 ◽  
Vol 27 (6) ◽  
pp. 1568-1579 ◽  
Author(s):  
Valliappa Lakshmanan ◽  
John Crockett ◽  
Kenneth Sperow ◽  
Mamoudou Ba ◽  
Lingyan Xin

Abstract AutoNowcaster (ANC) is an automated system that nowcasts thunderstorms, including thunderstorm initiation. However, its parameters have to be tuned to regional environments, a process that is time consuming, labor intensive, and quite subjective. When the National Weather Service decided to explore using ANC in forecast operations, a faster, less labor-intensive, and objective mechanism to tune the parameters for all the forecast offices was sought. In this paper, a genetic algorithm approach to tuning ANC is described. The process consisted of choosing datasets, employing an objective forecast verification technique, and devising a fitness function. ANC was modified to create nowcasts offline using weights iteratively generated by the genetic algorithm. The weights were generated by probabilistically combining weights with good fitness, leading to better and better weights as the tuning process proceeded.The nowcasts created by ANC using the automatically determined weights are compared with the nowcasts created by ANC using weights that were the result of manual tuning. It is shown that nowcasts created using the automatically tuned weights are as skilled as the ones created through manual tuning. In addition, automated tuning can be done in a fraction of the time that it takes experts to analyze the data and tune the weights.


2015 ◽  
Vol 143 (5) ◽  
pp. 1687-1702 ◽  
Author(s):  
Jose-Henrique G. M. Alves ◽  
Scott Stripling ◽  
Arun Chawla ◽  
Hendrik Tolman ◽  
Andre van der Westhuysen

Abstract Waves generated during Hurricane Sandy (October 2012) contributed significantly to life and property losses along the eastern U.S. seaboard. Extreme waves generated by Sandy propagated inland riding high water levels, causing direct destruction of property and infrastructure. High waves also contributed to the observed record-breaking storm surges. Operational wave-model guidance provided by the U.S. National Weather Service, via numerical model predictions made at NOAA’s National Centers for Environmental Prediction (NCEP), gave decision makers accurate information that helped mitigate the severity of this historical event. The present study provides a comprehensive performance assessment of operational models used by NCEP during Hurricane Sandy, and makes a brief review of reports issued by government agencies, private industry, and universities, indicating the importance of the interplay of waves and surges during the hurricane. Performance of wave models is assessed through validation made relative to western Atlantic NOAA/NDBC buoys that recorded significant wave heights exceeding 6 m (19.7 ft). Bulk validation statistics indicate a high skill of operational wave forecasts up to and beyond the 3-day range. Event-based validation reveals a remarkably high skill of NCEP’s wave ensemble system, with significant added value in its data for longer forecasts beyond the 72-h range. The study concludes with considerations about the extent of severe sea-state footprints during Sandy, the dissemination of real-time wave forecasts, and its impacts to emergency management response, as well as recent upgrades and future developments at NCEP that will improve the skill of its current wave forecasting systems, resulting in more reliable wave forecasts during life-threatening severe storm events in the future.


2015 ◽  
Vol 49 (2) ◽  
pp. 37-48
Author(s):  
Richard May ◽  
David Soroka ◽  
Wayne Presnell ◽  
Brian Garcia

AbstractAccording to National Oceanic and Atmospheric Administration's (NOAA's) official economic statistics, over half of the U.S. population lives within 50 miles of the coast. At sea, maritime commerce has tripled since about 1960‐2010. The National Weather Service (NWS) Marine Program has a mission to provide marine forecasts and warnings for the U.S. coastal waters and Great Lakes, offshore and high seas portions of the Pacific and Atlantic Oceans, Gulf of Mexico, Caribbean, and for a portion of the Arctic Ocean (north of Alaska). This information helps protect people and their property while on our nation's waters. Weather and ocean data are critical to the mariner. This is due to a combination of hazards—such as strong wind and large waves—and the fact that the mariner is often isolated. When in peril, rescue of these vessels may be hours or days in coming. Not having accurate and timely weather information and the knowledge to properly apply it increases risk to mariners and their vessels. In coastal areas, NWS provides vital services and products to inform and protect residents, businesses, tourists, and others from hazardous weather and surf conditions. Typically in the coastal community, rip currents and inundation caused by storms and unusually high tides are the primary focus. Techniques of marine forecasting have come a long way, bringing us into the modern era of marine observations via satellite, radar, and buoys and forecasting using sophisticated computer programs. The role of marine weather forecasters worldwide is a complex one and will continue to change in response to evolving technology and user requirements.


Author(s):  
Evan S. Bentley ◽  
Richard L. Thompson ◽  
Barry R. Bowers ◽  
Justin G. Gibbs ◽  
Steven E. Nelson

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.


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