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  • Author or Editor: A. JAMES WAGNER x
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A. James Wagner

The frequency of occurrence of frozen precipitation forms relative to the frequency of occurrence of non-frozen forms is determined as a function of geographical location and of the mean temperature (or thickness) of the layer from 1000 mb to 500 mb. The results are derived from the data for a large number of stations in the United States during two winter seasons. A map of the thickness values for equal probability of occurrence of frozen and non-frozen forms illustrates the effects of altitude and continentality.

It is found that the form of the precipitation can be specified with a confidence of 75 percent or more when the thickness value at a station is 100 feet or more from its “equal probability” value. Some refinements of the technique are discussed.

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Anthony G. Barnston
,
Ants Leetmaa
,
Vernon E. Kousky
,
Robert E. Livezey
,
Edward A. O'Lenic
,
Huug Van den Dool
,
A. James Wagner
, and
David A. Unger

The strong El Niño of 1997–98 provided a unique opportunity for National Weather Service, National Centers for Environmental Prediction, Climate Prediction Center (CPC) forecasters to apply several years of accumulated new knowledge of the U.S. impacts of El Niño to their long-lead seasonal forecasts with more clarity and confidence than ever previously. This paper examines the performance of CPC's official forecasts, and its individual component forecast tools, during this event. Heavy winter precipitation across California and the southern plains–Gulf coast region was accurately forecast with at least six months of lead time. Dryness was also correctly forecast in Montana and in the southwestern Ohio Valley. The warmth across the northern half of the country was correctly forecast, but extended farther south and east than predicted. As the winter approached, forecaster confidence in the forecast pattern increased, and the probability anomalies that were assigned reached unprecedented levels in the months immediately preceding the winter. Verification scores for winter 1997/98 forecasts set a new record at CPC for precipitation.

Forecasts for the autumn preceding the El Niño winter were less skillful than those of winter, but skill for temperature was still higher than the average expected for autumn. The precipitation forecasts for autumn showed little skill. Forecasts for the spring following the El Niño were poor, as an unexpected circulation pattern emerged, giving the southern and southeastern United States a significant drought. This pattern, which differed from the historical El Niño pattern for spring, may have been related to a large pool of anomalously warm water that remained in the far eastern tropical Pacific through summer 1998 while the waters in the central Pacific cooled as the El Niño was replaced by a La Niña by the first week of June.

It is suggested that in addition to the obvious effects of the 1997–98 El Niño on 3-month mean climate in the United States, the El Niño (indeed, any strong El Niño or La Niña) may have provided a positive influence on the skill of medium-range forecasts of 5-day mean climate anomalies. This would reflect first the connection between the mean seasonal conditions and the individual contributing synoptic events, but also the possibly unexpected effect of the tropical boundary forcing unique to a given synoptic event. Circumstantial evidence suggests that the skill of medium-range forecasts is increased during lead times (and averaging periods) long enough that the boundary conditions have a noticeable effect, but not so long that the skill associated with the initial conditions disappears. Firmer evidence of a beneficial influence of ENSO on subclimate-scale forecast skill is needed, as the higher skill may be associated just with the higher amplitude of the forecasts, regardless of the reason for that amplitude.

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Charles O. Stanier
,
R. Bradley Pierce
,
Maryam Abdi-Oskouei
,
Zachariah E. Adelman
,
Jay Al-Saadi
,
Hariprasad D. Alwe
,
Timothy H. Bertram
,
Gregory R. Carmichael
,
Megan B. Christiansen
,
Patricia A. Cleary
,
Alan C. Czarnetzki
,
Angela F. Dickens
,
Marta A. Fuoco
,
Dagen D. Hughes
,
Joseph P. Hupy
,
Scott J. Janz
,
Laura M. Judd
,
Donna Kenski
,
Matthew G. Kowalewski
,
Russell W. Long
,
Dylan B. Millet
,
Gordon Novak
,
Behrooz Roozitalab
,
Stephanie L. Shaw
,
Elizabeth A. Stone
,
James Szykman
,
Lukas Valin
,
Michael Vermeuel
,
Timothy J. Wagner
,
Andrew R. Whitehill
, and
David J. Williams

Abstract

The Lake Michigan Ozone Study 2017 (LMOS 2017) was a collaborative multiagency field study targeting ozone chemistry, meteorology, and air quality observations in the southern Lake Michigan area. The primary objective of LMOS 2017 was to provide measurements to improve air quality modeling of the complex meteorological and chemical environment in the region. LMOS 2017 science questions included spatiotemporal assessment of nitrogen oxides (NO x = NO + NO2) and volatile organic compounds (VOC) emission sources and their influence on ozone episodes; the role of lake breezes; contribution of new remote sensing tools such as GeoTASO, Pandora, and TEMPO to air quality management; and evaluation of photochemical grid models. The observing strategy included GeoTASO on board the NASA UC-12 aircraft capturing NO2 and formaldehyde columns, an in situ profiling aircraft, two ground-based coastal enhanced monitoring locations, continuous NO2 columns from coastal Pandora instruments, and an instrumented research vessel. Local photochemical ozone production was observed on 2 June, 9–12 June, and 14–16 June, providing insights on the processes relevant to state and federal air quality management. The LMOS 2017 aircraft mapped significant spatial and temporal variation of NO2 emissions as well as polluted layers with rapid ozone formation occurring in a shallow layer near the Lake Michigan surface. Meteorological characteristics of the lake breeze were observed in detail and measurements of ozone, NOx, nitric acid, hydrogen peroxide, VOC, oxygenated VOC (OVOC), and fine particulate matter (PM2.5) composition were conducted. This article summarizes the study design, directs readers to the campaign data repository, and presents a summary of findings.

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Karen A. Kosiba
,
Anthony W. Lyza
,
Robert J. Trapp
,
Erik N. Rasmussen
,
Matthew Parker
,
Michael I. Biggerstaff
,
Stephen W. Nesbitt
,
Christopher C. Weiss
,
Joshua Wurman
,
Kevin R. Knupp
,
Brice Coffer
,
Vanna C. Chmielewski
,
Daniel T. Dawson
,
Eric Bruning
,
Tyler M. Bell
,
Michael C. Coniglio
,
Todd A. Murphy
,
Michael French
,
Leanne Blind-Doskocil
,
Anthony E. Reinhart
,
Edward Wolff
,
Morgan E. Schneider
,
Miranda Silcott
,
Elizabeth Smith
,
Joshua Aikins
,
Melissa Wagner
,
Paul Robinson
,
James M. Wilczak
,
Trevor White
,
David Bodine
,
Matthew R. Kumjian
,
Sean M. Waugh
,
A. Addison Alford
,
Kim Elmore
,
Pavlos Kollias
, and
David D. Turner

Abstract

Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the U.S., but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear System (PERiLS) project was the first observational study of tornadoes associated with QLCSs ever undertaken. Participants were drawn from more than 10 universities, laboratories, and institutes, with over 100 students participating in field activities. The PERiLS field phases spanned two years, late winters and early springs of 2022 and 2023, to increase the probability of intercepting significant tornadic QLCS events in a range of large-scale and local environments. The field phases of PERiLS collected data in nine tornadic and nontornadic QLCSs with unprecedented detail and diversity of measurements. The design and execution of the PERiLS field phase and preliminary data and ongoing analyses are shown.

Open access
Brian J. Butterworth
,
Ankur R. Desai
,
Stefan Metzger
,
Philip A. Townsend
,
Mark D. Schwartz
,
Grant W. Petty
,
Matthias Mauder
,
Hannes Vogelmann
,
Christian G. Andresen
,
Travis J. Augustine
,
Timothy H. Bertram
,
William O.J. Brown
,
Michael Buban
,
Patricia Cleary
,
David J. Durden
,
Christopher R. Florian
,
Trevor J. Iglinski
,
Eric L. Kruger
,
Kathleen Lantz
,
Temple R. Lee
,
Tilden P. Meyers
,
James K. Mineau
,
Erik R. Olson
,
Steven P. Oncley
,
Sreenath Paleri
,
Rosalyn A. Pertzborn
,
Claire Pettersen
,
David M. Plummer
,
Laura D. Riihimaki
,
Eliceo Ruiz Guzman
,
Joseph Sedlar
,
Elizabeth N. Smith
,
Johannes Speidel
,
Paul C. Stoy
,
Matthias Sühring
,
Jonathan E. Thom
,
David D. Turner
,
Michael P. Vermeuel
,
Timothy J. Wagner
,
Zhien Wang
,
Luise Wanner
,
Loren D. White
,
James M. Wilczak
,
Daniel B. Wright
, and
Ting Zheng
Full access
Brian J. Butterworth
,
Ankur R. Desai
,
Philip A. Townsend
,
Grant W. Petty
,
Christian G. Andresen
,
Timothy H. Bertram
,
Eric L. Kruger
,
James K. Mineau
,
Erik R. Olson
,
Sreenath Paleri
,
Rosalyn A. Pertzborn
,
Claire Pettersen
,
Paul C. Stoy
,
Jonathan E. Thom
,
Michael P. Vermeuel
,
Timothy J. Wagner
,
Daniel B. Wright
,
Ting Zheng
,
Stefan Metzger
,
Mark D. Schwartz
,
Trevor J. Iglinski
,
Matthias Mauder
,
Johannes Speidel
,
Hannes Vogelmann
,
Luise Wanner
,
Travis J. Augustine
,
William O. J. Brown
,
Steven P. Oncley
,
Michael Buban
,
Temple R. Lee
,
Patricia Cleary
,
David J. Durden
,
Christopher R. Florian
,
Kathleen Lantz
,
Laura D. Riihimaki
,
Joseph Sedlar
,
Tilden P. Meyers
,
David M. Plummer
,
Eliceo Ruiz Guzman
,
Elizabeth N. Smith
,
Matthias Sühring
,
David D. Turner
,
Zhien Wang
,
Loren D. White
, and
James M. Wilczak

Abstract

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.

Open access
David C. Fritts
,
Ronald B. Smith
,
Michael J. Taylor
,
James D. Doyle
,
Stephen D. Eckermann
,
Andreas Dörnbrack
,
Markus Rapp
,
Bifford P. Williams
,
P.-Dominique Pautet
,
Katrina Bossert
,
Neal R. Criddle
,
Carolyn A. Reynolds
,
P. Alex Reinecke
,
Michael Uddstrom
,
Michael J. Revell
,
Richard Turner
,
Bernd Kaifler
,
Johannes S. Wagner
,
Tyler Mixa
,
Christopher G. Kruse
,
Alison D. Nugent
,
Campbell D. Watson
,
Sonja Gisinger
,
Steven M. Smith
,
Ruth S. Lieberman
,
Brian Laughman
,
James J. Moore
,
William O. Brown
,
Julie A. Haggerty
,
Alison Rockwell
,
Gregory J. Stossmeister
,
Steven F. Williams
,
Gonzalo Hernandez
,
Damian J. Murphy
,
Andrew R. Klekociuk
,
Iain M. Reid
, and
Jun Ma

Abstract

The Deep Propagating Gravity Wave Experiment (DEEPWAVE) was designed to quantify gravity wave (GW) dynamics and effects from orographic and other sources to regions of dissipation at high altitudes. The core DEEPWAVE field phase took place from May through July 2014 using a comprehensive suite of airborne and ground-based instruments providing measurements from Earth’s surface to ∼100 km. Austral winter was chosen to observe deep GW propagation to high altitudes. DEEPWAVE was based on South Island, New Zealand, to provide access to the New Zealand and Tasmanian “hotspots” of GW activity and additional GW sources over the Southern Ocean and Tasman Sea. To observe GWs up to ∼100 km, DEEPWAVE utilized three new instruments built specifically for the National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV): a Rayleigh lidar, a sodium resonance lidar, and an advanced mesosphere temperature mapper. These measurements were supplemented by in situ probes, dropsondes, and a microwave temperature profiler on the GV and by in situ probes and a Doppler lidar aboard the German DLR Falcon. Extensive ground-based instrumentation and radiosondes were deployed on South Island, Tasmania, and Southern Ocean islands. Deep orographic GWs were a primary target but multiple flights also observed deep GWs arising from deep convection, jet streams, and frontal systems. Highlights include the following: 1) strong orographic GW forcing accompanying strong cross-mountain flows, 2) strong high-altitude responses even when orographic forcing was weak, 3) large-scale GWs at high altitudes arising from jet stream sources, and 4) significant flight-level energy fluxes and often very large momentum fluxes at high altitudes.

Full access
Chelsea R. Thompson
,
Steven C. Wofsy
,
Michael J. Prather
,
Paul A. Newman
,
Thomas F. Hanisco
,
Thomas B. Ryerson
,
David W. Fahey
,
Eric C. Apel
,
Charles A. Brock
,
William H. Brune
,
Karl Froyd
,
Joseph M. Katich
,
Julie M. Nicely
,
Jeff Peischl
,
Eric Ray
,
Patrick R. Veres
,
Siyuan Wang
,
Hannah M. Allen
,
Elizabeth Asher
,
Huisheng Bian
,
Donald Blake
,
Ilann Bourgeois
,
John Budney
,
T. Paul Bui
,
Amy Butler
,
Pedro Campuzano-Jost
,
Cecilia Chang
,
Mian Chin
,
Róisín Commane
,
Gus Correa
,
John D. Crounse
,
Bruce Daube
,
Jack E. Dibb
,
Joshua P. DiGangi
,
Glenn S. Diskin
,
Maximilian Dollner
,
James W. Elkins
,
Arlene M. Fiore
,
Clare M. Flynn
,
Hao Guo
,
Samuel R. Hall
,
Reem A. Hannun
,
Alan Hills
,
Eric J. Hintsa
,
Alma Hodzic
,
Rebecca S. Hornbrook
,
L. Greg Huey
,
Jose L. Jimenez
,
Ralph F. Keeling
,
Michelle J. Kim
,
Agnieszka Kupc
,
Forrest Lacey
,
Leslie R. Lait
,
Jean-Francois Lamarque
,
Junhua Liu
,
Kathryn McKain
,
Simone Meinardi
,
David O. Miller
,
Stephen A. Montzka
,
Fred L. Moore
,
Eric J. Morgan
,
Daniel M. Murphy
,
Lee T. Murray
,
Benjamin A. Nault
,
J. Andrew Neuman
,
Louis Nguyen
,
Yenny Gonzalez
,
Andrew Rollins
,
Karen Rosenlof
,
Maryann Sargent
,
Gregory Schill
,
Joshua P. Schwarz
,
Jason M. St. Clair
,
Stephen D. Steenrod
,
Britton B. Stephens
,
Susan E. Strahan
,
Sarah A. Strode
,
Colm Sweeney
,
Alexander B. Thames
,
Kirk Ullmann
,
Nicholas Wagner
,
Rodney Weber
,
Bernadett Weinzierl
,
Paul O. Wennberg
,
Christina J. Williamson
,
Glenn M. Wolfe
, and
Linghan Zeng

Abstract

This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.

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