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David J. Stensrud, Michael H. Jain, Kenneth W. Howard, and Robert A. Maddox

Abstract

A brief field project was conducted during July 1988 to assess the potential for Next Generation Weather Radar (NEXRAD), 404-MHz radar wind profilers, and digital sounding systems to monitor the low-level wind field during clear-air conditions. The low-level jet was chosen as the phenomenon of interest because it is neither well sampled nor resolved by the current upper-air network, yet it is a common feature of mesoscale convective system and severe thunderstorm environments. Data were collected under quiescent synoptic conditions during several low-level jet events using a 10-cm NEXRAD-like Doppler radar and a digital sounding system colocated in Norman, Oklahoma. These data suggest that the areal-averaged horizontal winds calculated from the Doppler radar data using the Velocity Azimuth Display (VAD) technique are comparable with the winds observed using a digital sounding system, except under weak wind conditions. However, the vertical spacing of 304 m (1000 ft) between levels of horizontal VAD calculated winds, as currently proposed for NEXRAD, may not be of sufficient resolution to document the detailed wind structure of these events. The height of the maximum wind speed of the low-level jet on all days studied was below the planned lowest observation range gate of the 404-MHz radar wind profiler, indicating that a combination of NEXRAD and profiler data might be needed to sample the important wind field structure of the lower atmosphere. Lastly, the National Weather Service rawinsonde data processing software affects the vertical resolution of the low-level wind field in operational, and therefore archived, upper-air soundings. The procedure used to calculate NWS 1000 ft winds actually damps the wind speed profile and artificially increases the height of the level of maximum wind speed associated with the low-level jet. The appropriateness of these highly smoothed 1000 ft winds for input into sophisticated mesoscale weather prediction models should be considered.

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Katherine M. Willingham, Elizabeth J. Thompson, Kenneth W. Howard, and Charles L. Dempsey

Abstract

During the 2008 North American monsoon season, 140 microburst events were identified in Phoenix, Arizona, and the surrounding Sonoran Desert. The Sonoran microbursts were studied and examined for their frequency and characteristics, as observed from data collected from three Doppler radars and electrical power infrastructure damage reports. Sonoran microburst events were wet microbursts and occurred most frequently in the evening hours (1900–2100 local time). Stronger maximum differential velocities (20–25 m s−1) were observed more frequently in Sonoran microbursts than in many previously documented microbursts. Alignment of Doppler radar data to reports of wind-related damage to electrical power infrastructure in Phoenix allowed a comparison of microburst wind damage versus gust-front wind damage. For these damage reports, microburst winds caused more significant damage than gust-front winds.

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Steven M. Martinaitis, Stephen B. Cocks, Andrew P. Osborne, Micheal J. Simpson, Lin Tang, Jian Zhang, and Kenneth W. Howard

Abstract

Hurricane Harvey in 2017 generated one of the most catastrophic rainfall events in United States history. Numerous gauge observations in Texas exceeded 1200 mm, and the record accumulations resulted in 65 direct fatalities from rainfall-induced flooding. This was followed by Hurricane Florence in 2018, where multiple regions in North Carolina received over 750 mm of rainfall. The Multi-Radar Multi-Sensor (MRMS) system provides the unique perspective of applying fully automated seamless radar mosaics and locally gauge-corrected products for these two historical tropical cyclone rainfall events. This study investigates the performance of various MRMS quantitative precipitation estimation (QPE) products as it pertains to rare extreme tropical cyclone rainfall events. Various biases were identified in the radar-only approaches, which were mitigated in a new dual-polarimetric synthetic radar QPE approach. A local gauge correction of radar-derived QPE provided statistical improvements over the radar-only products but introduced consistent underestimation biases attributed to undercatch from tropical cyclone winds. This study then introduces a conceptual methodology to bulk correct for gauge wind undercatch across the numerous gauge networks ingested by the MRMS system. Adjusting the hourly gauge observations for wind undercatch resulted in increased storm-total accumulations for both tropical cyclones that better matched independent gauge observations, yet its application across large network collections highlighted the challenges of applying a singular wind undercatch correction scheme for significant wind events (e.g., tropical cyclones) while recognizing the need for increased metadata on gauge characteristics.

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Steven M. Martinaitis, Andrew P. Osborne, Micheal J. Simpson, Jian Zhang, Kenneth W. Howard, Stephen B. Cocks, Ami Arthur, Carrie Langston, and Brian T. Kaney

Abstract

Weather radars and gauge observations are the primary observations to determine the coverage and magnitude of precipitation; however, radar and gauge networks have significant coverage gaps, which can underrepresent or even miss the occurrence of precipitation. This is especially noticeable in mountainous regions and in shallow precipitation regimes. The following study presents a methodology to improve spatial representations of precipitation by seamlessly blending multiple precipitation sources within the Multi-Radar Multi-Sensor (MRMS) system. A high spatiotemporal resolution multisensor merged quantitative precipitation estimation (QPE) product (MSQPE) is generated by using gauge-corrected radar QPE as a primary precipitation source with a combination of hourly gauge observations, monthly precipitation climatologies, numerical weather prediction short-term precipitation forecasts, and satellite observations to use in areas of insufficient radar coverage. The merging of the precipitation sources is dependent upon radar coverage based on an updated MRMS radar quality index, surface and atmospheric conditions, topography, gauge locations, and precipitation values. Evaluations of the MSQPE product over the western United States resulted in improved statistical measures over its individual input precipitation sources, particularly the locally gauge-corrected radar QPE. The MSQPE scheme demonstrated its ability to sufficiently fill in areas where radar alone failed to detect precipitation due to significant beam blockage or poor coverage while minimizing the generation of false precipitation and underestimation biases that resulted from radar overshooting precipitation.

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Phillip B. Chilson, Winifred F. Frick, Jeffrey F. Kelly, Kenneth W. Howard, Ronald P. Larkin, Robert H. Diehl, John K. Westbrook, T. Adam Kelly, and Thomas H. Kunz

Aeroecology is an emerging scientific discipline that integrates atmospheric science, Earth science, geography, ecology, computer science, computational biology, and engineering to further the understanding of biological patterns and processes. The unifying concept underlying this new transdisciplinary field of study is a focus on the planetary boundary layer and lower free atmosphere (i.e., the aerosphere), and the diversity of airborne organisms that inhabit and depend on the aerosphere for their existence. Here, we focus on the role of radars and radar networks in aeroecological studies. Radar systems scanning the atmosphere are primarily used to monitor weather conditions and track the location and movements of aircraft. However, radar echoes regularly contain signals from other sources, such as airborne birds, bats, and arthropods. We briefly discuss how radar observations can be and have been used to study a variety of airborne organisms and examine some of the many potential benefits likely to arise from radar aeroecology for meteorological and biological research over a wide range of spatial and temporal scales. Radar systems are becoming increasingly sophisticated with the advent of innovative signal processing and dual-polarimetric capabilities. These capabilities should be better harnessed to promote both meteorological and aeroecological research and to explore the interface between these two broad disciplines. We strongly encourage close collaboration among meteorologists, radar scientists, biologists, and others toward developing radar products that will contribute to a better understanding of airborne fauna.

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Fred V. Brock, Kenneth C. Crawford, Ronald L. Elliott, Gerrit W. Cuperus, Steven J. Stadler, Howard L. Johnson, and Michael D. Eilts

Abstract

The Oklahoma mesonet is a joint project of Oklahoma State University and the University of Oklahoma. It is an automated network of 108 stations covering the state of Oklahoma. Each station measures air temperature, humidity, barometric pressure, wind speed and direction, rainfall, solar radiation, and soil temperatures. Each station transmits a data message every 15 min via a radio link to the nearest terminal of the Oklahoma Law Enforcement Telecommunications System that relays it to a central site in Norman, Oklahoma. The data message comprises three 5-min averages of most data (and one 15-min average of soil temperatures). The central site ingests the data, runs some quality assurance tests, archives the data, and disseminates it in real time to a broad community of users, primarily through a computerized bulletin board system. This manuscript provides a technical description of the Oklahoma mesonet including a complete description of the instrumentation. Sensor inaccuracy, resolution, height with respect to ground level, and method of exposure are discussed.

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Steven M. Martinaitis, Stephen B. Cocks, Micheal J. Simpson, Andrew P. Osborne, Sebastian S. Harkema, Heather M. Grams, Jian Zhang, and Kenneth W. Howard

Abstract

This study describes recent advancements in the Multi-Radar Multi-Sensor (MRMS) automated gauge ingest and quality control (QC) processes. A data latency analysis for the combined multiple gauge collection platforms provided guidance for a multiple-pass generation and delivery of gauge-based precipitation products. Various advancements to the gauge QC logic were evaluated over a 21-month period, resulting in an average of 86% of hourly gauge observations per hour being classified as useful. The fully automated QC logic was compared to manual human QC for a limited domain, which showed a >95% agreement in their QC reasoning categories. This study also includes an extensive evaluation of various characteristics related to the gauge observations ingested into the MRMS system. Duplicate observations between gauge collection platforms highlighted differences in site coordinates; moreover, errors in Automated Surface Observing System (ASOS) station site coordinates resulted in >79% of sites being located in a different MRMS 1-km grid cell. The ASOS coordinate analysis combined with examinations of other limitations regarding gauge observations highlight the need for robust and accurate metadata to further enhance the quality control of gauge data.

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Jonathan J. Gourley, Zachary L. Flamig, Humberto Vergara, Pierre-Emmanuel Kirstetter, Robert A. Clark III, Elizabeth Argyle, Ami Arthur, Steven Martinaitis, Galateia Terti, Jessica M. Erlingis, Yang Hong, and Kenneth W. Howard

Abstract

This study introduces the Flooded Locations and Simulated Hydrographs (FLASH) project. FLASH is the first system to generate a suite of hydrometeorological products at flash flood scale in real-time across the conterminous United States, including rainfall average recurrence intervals, ratios of rainfall to flash flood guidance, and distributed hydrologic model–based discharge forecasts. The key aspects of the system are 1) precipitation forcing from the National Severe Storms Laboratory (NSSL)’s Multi-Radar Multi-Sensor (MRMS) system, 2) a computationally efficient distributed hydrologic modeling framework with sufficient representation of physical processes for flood prediction, 3) capability to provide forecasts at all grid points covered by radars without the requirement of model calibration, and 4) an open-access development platform, product display, and verification system for testing new ideas in a real-time demonstration environment and for fostering collaborations.

This study assesses the FLASH system’s ability to accurately simulate unit peak discharges over a 7-yr period in 1,643 unregulated gauged basins. The evaluation indicates that FLASH’s unit peak discharges had a linear and rank correlation of 0.64 and 0.79, respectively, and that the timing of the peak discharges has errors less than 2 h. The critical success index with FLASH was 0.38 for flood events that exceeded action stage. FLASH performance is demonstrated and evaluated for case studies, including the 2013 deadly flash flood case in Oklahoma City, Oklahoma, and the 2015 event in Houston, Texas—both of which occurred on Memorial Day weekends.

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Steven V. Vasiloff, Dong-Jun Seo, Kenneth W. Howard, Jian Zhang, David H. Kitzmiller, Mary G. Mullusky, Witold F. Krajewski, Edward A. Brandes, Robert M. Rabin, Daniel S. Berkowitz, Harold E. Brooks, John A. McGinley, Robert J. Kuligowski, and Barbara G. Brown

Accurate quantitative precipitation estimates (QPE) and very short term quantitative precipitation forecasts (VSTQPF) are critical to accurate monitoring and prediction of water-related hazards and water resources. While tremendous progress has been made in the last quarter-century in many areas of QPE and VSTQPF, significant gaps continue to exist in both knowledge and capabilities that are necessary to produce accurate high-resolution precipitation estimates at the national scale for a wide spectrum of users. Toward this goal, a national next-generation QPE and VSTQPF (Q2) workshop was held in Norman, Oklahoma, on 28–30 June 2005. Scientists, operational forecasters, water managers, and stakeholders from public and private sectors, including academia, presented and discussed a broad range of precipitation and forecasting topics and issues, and developed a list of science focus areas. To meet the nation's needs for the precipitation information effectively, the authors herein propose a community-wide integrated approach for precipitation information that fully capitalizes on recent advances in science and technology, and leverages the wide range of expertise and experience that exists in the research and operational communities. The concepts and recommendations from the workshop form the Q2 science plan and a suggested path to operations. Implementation of these concepts is expected to improve river forecasts and flood and flash flood watches and warnings, and to enhance various hydrologic and hydrometeorological services for a wide range of users and customers. In support of this initiative, the National Mosaic and Q2 (NMQ) system is being developed at the National Severe Storms Laboratory to serve as a community test bed for QPE and VSTQPF research and to facilitate the transition to operations of research applications. The NMQ system provides a real-time, around-the-clock data infusion and applications development and evaluation environment, and thus offers a community-wide platform for development and testing of advances in the focus areas.

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Suzanne Van Cooten, Kevin E. Kelleher, Kenneth Howard, Jian Zhang, Jonathan J. Gourley, John S. Kain, Kodi Nemunaitis-Monroe, Zac Flamig, Heather Moser, Ami Arthur, Carrie Langston, Randall Kolar, Yang Hong, Kendra Dresback, Evan Tromble, Humberto Vergara, Richard A Luettich Jr., Brian Blanton, Howard Lander, Ken Galluppi, Jessica Proud Losego, Cheryl Ann Blain, Jack Thigpen, Katie Mosher, Darin Figurskey, Michael Moneypenny, Jonathan Blaes, Jeff Orrock, Rich Bandy, Carin Goodall, John G. W. Kelley, Jason Greenlaw, Micah Wengren, Dave Eslinger, Jeff Payne, Geno Olmi, John Feldt, John Schmidt, Todd Hamill, Robert Bacon, Robert Stickney, and Lundie Spence

The objective of the Coastal and Inland Flooding Observation and Warning (CI-FLOW) project is to prototype new hydrometeorologic techniques to address a critical NOAA service gap: routine total water level predictions for tidally influenced watersheds. Since February 2000, the project has focused on developing a coupled modeling system to accurately account for water at all locations in a coastal watershed by exchanging data between atmospheric, hydrologic, and hydrodynamic models. These simulations account for the quantity of water associated with waves, tides, storm surge, rivers, and rainfall, including interactions at the tidal/surge interface.

Within this project, CI-FLOW addresses the following goals: i) apply advanced weather and oceanographic monitoring and prediction techniques to the coastal environment; ii) prototype an automated hydrometeorologic data collection and prediction system; iii) facilitate interdisciplinary and multiorganizational collaborations; and iv) enhance techniques and technologies that improve actionable hydrologic/hydrodynamic information to reduce the impacts of coastal flooding. Results are presented for Hurricane Isabel (2003), Hurricane Earl (2010), and Tropical Storm Nicole (2010) for the Tar–Pamlico and Neuse River basins of North Carolina. This area was chosen, in part, because of the tremendous damage inflicted by Hurricanes Dennis and Floyd (1999). The vision is to transition CI-FLOW research findings and technologies to other U.S. coastal watersheds.

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