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Bore-ing into Nocturnal Convection

Kevin R. Haghi
,
Bart Geerts
,
Hristo G. Chipilski
,
Aaron Johnson
,
Samuel Degelia
,
David Imy
,
David B. Parsons
,
Rebecca D. Adams-Selin
,
David D. Turner
, and
Xuguang Wang

Abstract

There has been a recent wave of attention given to atmospheric bores in order to understand how they evolve and initiate and maintain convection during the night. This surge is attributable to data collected during the 2015 Plains Elevated Convection at Night (PECAN) field campaign. A salient aspect of the PECAN project is its focus on using multiple observational platforms to better understand convective outflow boundaries that intrude into the stable boundary layer and induce the development of atmospheric bores. The intent of this article is threefold: 1) to educate the reader on current and future foci of bore research, 2) to present how PECAN observations will facilitate aforementioned research, and 3) to stimulate multidisciplinary collaborative efforts across other closely related fields in an effort to push the limitations of prediction of nocturnal convection.

Full access
Adam J. Clark
,
John S. Kain
,
David J. Stensrud
,
Ming Xue
,
Fanyou Kong
,
Michael C. Coniglio
,
Kevin W. Thomas
,
Yunheng Wang
,
Keith Brewster
,
Jidong Gao
,
Xuguang Wang
,
Steven J. Weiss
, and
Jun Du

Abstract

Probabilistic quantitative precipitation forecasts (PQPFs) from the storm-scale ensemble forecast system run by the Center for Analysis and Prediction of Storms during the spring of 2009 are evaluated using area under the relative operating characteristic curve (ROC area). ROC area, which measures discriminating ability, is examined for ensemble size n from 1 to 17 members and for spatial scales ranging from 4 to 200 km.

Expectedly, incremental gains in skill decrease with increasing n. Significance tests comparing ROC areas for each n to those of the full 17-member ensemble revealed that more members are required to reach statistically indistinguishable PQPF skill relative to the full ensemble as forecast lead time increases and spatial scale decreases. These results appear to reflect the broadening of the forecast probability distribution function (PDF) of future atmospheric states associated with decreasing spatial scale and increasing forecast lead time. They also illustrate that efficient allocation of computing resources for convection-allowing ensembles requires careful consideration of spatial scale and forecast length desired.

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Corey K. Potvin
,
Jacob R. Carley
,
Adam J. Clark
,
Louis J. Wicker
,
Patrick S. Skinner
,
Anthony E. Reinhart
,
Burkely T. Gallo
,
John S. Kain
,
Glen S. Romine
,
Eric A. Aligo
,
Keith A. Brewster
,
David C. Dowell
,
Lucas M. Harris
,
Israel L. Jirak
,
Fanyou Kong
,
Timothy A. Supinie
,
Kevin W. Thomas
,
Xuguang Wang
,
Yongming Wang
, and
Ming Xue

Abstract

The 2016–18 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiments (SFE) featured the Community Leveraged Unified Ensemble (CLUE), a coordinated convection-allowing model (CAM) ensemble framework designed to provide empirical guidance for development of operational CAM systems. The 2017 CLUE included 81 members that all used 3-km horizontal grid spacing over the CONUS, enabling direct comparison of forecasts generated using different dynamical cores, physics schemes, and initialization procedures. This study uses forecasts from several of the 2017 CLUE members and one operational model to evaluate and compare CAM representation and next-day prediction of thunderstorms. The analysis utilizes existing techniques and novel, object-based techniques that distill important information about modeled and observed storms from many cases. The National Severe Storms Laboratory Multi-Radar Multi-Sensor product suite is used to verify model forecasts and climatologies of observed variables. Unobserved model fields are also examined to further illuminate important intermodel differences in storms and near-storm environments. No single model performed better than the others in all respects. However, there were many systematic intermodel and intercore differences in specific forecast metrics and model fields. Some of these differences can be confidently attributed to particular differences in model design. Model intercomparison studies similar to the one presented here are important to better understand the impacts of model and ensemble configurations on storm forecasts and to help optimize future operational CAM systems.

Full access
Bart Geerts
,
David Parsons
,
Conrad L. Ziegler
,
Tammy M. Weckwerth
,
Michael I. Biggerstaff
,
Richard D. Clark
,
Michael C. Coniglio
,
Belay B. Demoz
,
Richard A. Ferrare
,
William A. Gallus Jr.
,
Kevin Haghi
,
John M. Hanesiak
,
Petra M. Klein
,
Kevin R. Knupp
,
Karen Kosiba
,
Greg M. McFarquhar
,
James A. Moore
,
Amin R. Nehrir
,
Matthew D. Parker
,
James O. Pinto
,
Robert M. Rauber
,
Russ S. Schumacher
,
David D. Turner
,
Qing Wang
,
Xuguang Wang
,
Zhien Wang
, and
Joshua Wurman

Abstract

The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night.

To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings.

Full access
Pavlos Kollias
,
Robert Palmer
,
David Bodine
,
Toru Adachi
,
Howie Bluestein
,
John Y. N. Cho
,
Casey Griffin
,
Jana Houser
,
Pierre. E. Kirstetter
,
Matthew R. Kumjian
,
James M. Kurdzo
,
Wen Chau Lee
,
Edward P. Luke
,
Steve Nesbitt
,
Mariko Oue
,
Alan Shapiro
,
Angela Rowe
,
Jorge Salazar
,
Robin Tanamachi
,
Kristofer S. Tuftedal
,
Xuguang Wang
,
Dusan Zrnić
, and
Bernat Puigdomènech Treserras

Abstract

Phased array radars (PARs) are a promising observing technology, at the cusp of being available to the broader meteorological community. PARs offer near-instantaneous sampling of the atmosphere with flexible beam forming, multifunctionality, and low operational and maintenance costs and without mechanical inertia limitations. These PAR features are transformative compared to those offered by our current reflector-based meteorological radars. The integration of PARs into meteorological research has the potential to revolutionize the way we observe the atmosphere. The rate of adoption of PARs in research will depend on many factors, including (i) the need to continue educating the scientific community on the full technical capabilities and trade-offs of PARs through an engaging dialogue with the science and engineering communities and (ii) the need to communicate the breadth of scientific bottlenecks that PARs can overcome in atmospheric measurements and the new research avenues that are now possible using PARs in concert with other measurement systems. The former is the subject of a companion article that focuses on PAR technology while the latter is the objective here.

Full access
Robert Palmer
,
David Whelan
,
David Bodine
,
Pierre Kirstetter
,
Matthew Kumjian
,
Justin Metcalf
,
Mark Yeary
,
Tian-You Yu
,
Ramesh Rao
,
John Cho
,
David Draper
,
Stephen Durden
,
Stephen English
,
Pavlos Kollias
,
Karen Kosiba
,
Masakazu Wada
,
Joshua Wurman
,
William Blackwell
,
Howard Bluestein
,
Scott Collis
,
Jordan Gerth
,
Aaron Tuttle
,
Xuguang Wang
, and
Dusan Zrnić
Full access
Mark Weber
,
Kurt Hondl
,
Nusrat Yussouf
,
Youngsun Jung
,
Derek Stratman
,
Bryan Putnam
,
Xuguang Wang
,
Terry Schuur
,
Charles Kuster
,
Yixin Wen
,
Juanzhen Sun
,
Jeff Keeler
,
Zhuming Ying
,
John Cho
,
James Kurdzo
,
Sebastian Torres
,
Chris Curtis
,
David Schvartzman
,
Jami Boettcher
,
Feng Nai
,
Henry Thomas
,
Dusan Zrnić
,
Igor Ivić
,
Djordje Mirković
,
Caleb Fulton
,
Jorge Salazar
,
Guifu Zhang
,
Robert Palmer
,
Mark Yeary
,
Kevin Cooley
,
Michael Istok
, and
Mark Vincent

Abstract

This article summarizes research and risk reduction that will inform acquisition decisions regarding NOAA’s future national operational weather radar network. A key alternative being evaluated is polarimetric phased-array radar (PAR). Research indicates PAR can plausibly achieve fast, adaptive volumetric scanning, with associated benefits for severe-weather warning performance. We assess these benefits using storm observations and analyses, observing system simulation experiments, and real radar-data assimilation studies. Changes in the number and/or locations of radars in the future network could improve coverage at low altitude. Analysis of benefits that might be so realized indicates the possibility for additional improvement in severe-weather and flash-flood warning performance, with associated reduction in casualties. Simulations are used to evaluate techniques for rapid volumetric scanning and assess data quality characteristics of PAR. Finally, we describe progress in developing methods to compensate for polarimetric variable estimate biases introduced by electronic beam-steering. A research-to-operations (R2O) strategy for the PAR alternative for the WSR-88D replacement network is presented.

Full access
Adam J. Clark
,
Steven J. Weiss
,
John S. Kain
,
Israel L. Jirak
,
Michael Coniglio
,
Christopher J. Melick
,
Christopher Siewert
,
Ryan A. Sobash
,
Patrick T. Marsh
,
Andrew R. Dean
,
Ming Xue
,
Fanyou Kong
,
Kevin W. Thomas
,
Yunheng Wang
,
Keith Brewster
,
Jidong Gao
,
Xuguang Wang
,
Jun Du
,
David R. Novak
,
Faye E. Barthold
,
Michael J. Bodner
,
Jason J. Levit
,
C. Bruce Entwistle
,
Tara L. Jensen
, and
James Correia Jr.

The NOAA Hazardous Weather Testbed (HWT) conducts annual spring forecasting experiments organized by the Storm Prediction Center and National Severe Storms Laboratory to test and evaluate emerging scientific concepts and technologies for improved analysis and prediction of hazardous mesoscale weather. A primary goal is to accelerate the transfer of promising new scientific concepts and tools from research to operations through the use of intensive real-time experimental forecasting and evaluation activities conducted during the spring and early summer convective storm period. The 2010 NOAA/HWT Spring Forecasting Experiment (SE2010), conducted 17 May through 18 June, had a broad focus, with emphases on heavy rainfall and aviation weather, through collaboration with the Hydrometeorological Prediction Center (HPC) and the Aviation Weather Center (AWC), respectively. In addition, using the computing resources of the National Institute for Computational Sciences at the University of Tennessee, the Center for Analysis and Prediction of Storms at the University of Oklahoma provided unprecedented real-time conterminous United States (CONUS) forecasts from a multimodel Storm-Scale Ensemble Forecast (SSEF) system with 4-km grid spacing and 26 members and from a 1-km grid spacing configuration of the Weather Research and Forecasting model. Several other organizations provided additional experimental high-resolution model output. This article summarizes the activities, insights, and preliminary findings from SE2010, emphasizing the use of the SSEF system and the successful collaboration with the HPC and AWC.

A supplement to this article is available online (DOI:10.1175/BAMS-D-11-00040.2)

Full access
Greg M. McFarquhar
,
Elizabeth Smith
,
Elizabeth A. Pillar-Little
,
Keith Brewster
,
Phillip B. Chilson
,
Temple R. Lee
,
Sean Waugh
,
Nusrat Yussouf
,
Xuguang Wang
,
Ming Xue
,
Gijs de Boer
,
Jeremy A. Gibbs
,
Chris Fiebrich
,
Bruce Baker
,
Jerry Brotzge
,
Frederick Carr
,
Hui Christophersen
,
Martin Fengler
,
Philip Hall
,
Terry Hock
,
Adam Houston
,
Robert Huck
,
Jamey Jacob
,
Robert Palmer
,
Patricia K. Quinn
,
Melissa Wagner
,
Yan (Rockee) Zhang
, and
Darren Hawk
Free access
James D. Doyle
,
Jonathan R. Moskaitis
,
Joel W. Feldmeier
,
Ronald J. Ferek
,
Mark Beaubien
,
Michael M. Bell
,
Daniel L. Cecil
,
Robert L. Creasey
,
Patrick Duran
,
Russell L. Elsberry
,
William A. Komaromi
,
John Molinari
,
David R. Ryglicki
,
Daniel P. Stern
,
Christopher S. Velden
,
Xuguang Wang
,
Todd Allen
,
Bradford S. Barrett
,
Peter G. Black
,
Jason P. Dunion
,
Kerry A. Emanuel
,
Patrick A. Harr
,
Lee Harrison
,
Eric A. Hendricks
,
Derrick Herndon
,
William Q. Jeffries
,
Sharanya J. Majumdar
,
James A. Moore
,
Zhaoxia Pu
,
Robert F. Rogers
,
Elizabeth R. Sanabia
,
Gregory J. Tripoli
, and
Da-Lin Zhang

Abstract

Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes.

Open access