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  • Author or Editor: R. L. Thompson x
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D. S. Wratt
,
R. N. Ridley
,
M. R. Sinclair
,
H. Larsen
,
S. M. Thompson
,
R. Henderson
,
G. L. Austin
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S. G. Bradley
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A. Auer
,
A. P. Sturman
,
I. Owens
,
B. Fitzharris
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B. F. Ryan
, and
J.-F. Gayet

The Southern Alps Experiment is being mounted to study the influence of New Zealand's Southern Alps on local weather and climate. This paper describes these alpine influences and outlines proposed field and modeling experiments. Experiment goals include understanding and quantifying factors that govern the intensity and spatial distribution of heavy rainfall, the west to east distribution of precipitation across the mountains, and the intensity of lee wind storms and warming. Linked research will explore the use of deterministic rainfall models to predict river flows from mountain watersheds.

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Mark T. Stoelinga
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Peter V. Hobbs
,
Clifford F. Mass
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John D. Locatelli
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Brian A. Colle
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Robert A. Houze Jr.
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Arthur L. Rangno
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Nicholas A. Bond
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Bradley F. Smull
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Roy M. Rasmussen
,
Gregory Thompson
, and
Bradley R. Colman

Despite continual increases in numerical model resolution and significant improvements in the forecasting of many meteorological parameters, progress in quantitative precipitation forecasting (QPF) has been slow. This is attributable in part to deficiencies in the bulk microphysical parameterization (BMP) schemes used in mesoscale models to simulate cloud and precipitation processes. These deficiencies have become more apparent as model resolution has increased. To address these problems requires comprehensive data that can be used to isolate errors in QPF due to BMP schemes from those due to other sources. These same data can then be used to evaluate and improve the microphysical processes and hydrometeor fields simulated by BMP schemes. In response to the need for such data, a group of researchers is collaborating on a study titled the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE). IMPROVE has included two field campaigns carried out in the Pacific Northwest: an offshore frontal precipitation study off the Washington coast in January–February 2001, and an orographic precipitation study in the Oregon Cascade Mountains in November–December 2001. Twenty-eight intensive observation periods yielded a uniquely comprehensive dataset that includes in situ airborne observations of cloud and precipitation microphysical parameters; remotely sensed reflectivity, dual-Doppler, and polarimetric quantities; upper-air wind, temperature, and humidity data; and a wide variety of surface-based meteorological, precipitation, and microphysical data. These data are being used to test mesoscale model simulations of the observed storm systems and, in particular, to evaluate and improve the BMP schemes used in such models. These studies should lead to improved QPF in operational forecast models.

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D. W. Stahle
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R. D. D'Arrigo
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P. J. Krusic
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M. K. Cleaveland
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E. R. Cook
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R. J. Allan
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J. E. Cole
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R. B. Dunbar
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M. D. Therrell
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D. A. Gay
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M. D. Moore
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M. A. Stokes
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B. T. Burns
,
J. Villanueva-Diaz
, and
L. G. Thompson

Exactly dated tree-ring chronologies from ENSO-sensitive regions in subtropical North America and Indonesia together register the strongest ENSO signal yet detected in tree-ring data worldwide and have been used to reconstruct the winter Southern Oscillation index (SOI) from 1706 to 1977. This reconstruction explains 53% of the variance in the instrumental winter SOI during the boreal cool season (December–February) and was verified in the time, space, and frequency domains by comparisons with independent instrumental SOI and sea surface temperature (SST) data. The large-scale SST anomaly patterns associated with ENSO in the equatorial and North Pacific during the 1879–1977 calibration period are reproduced in detail by this reconstruction. Cross-spectral analyses indicate that the reconstruction reproduces over 70% of the instrumental winter SOI variance at periods between 3.5 and 5.6 yr, and over 88% in the 4-yr frequency band. Oscillatory modes of variance identified with singular spectrum analysis at ~3.5,4.0, and 5.8 yr in both the instrumental and reconstructed series exhibit regimelike behavior over the 272-yr reconstruction. The tree-ring estimates also suggest a statistically significant increase in the interannual variability of winter SOI, more frequent cold events, and a slightly stronger sea level pressure gradient across the equatorial Pacific from the mid–nineteenth to twentieth centuries. Some of the variability in this reconstruction must be associated with background climate influences affecting the ENSO teleconnection to subtropical North America and may not arise solely from equatorial ENSO forcing. However, there is some limited independent support for the nineteenth to twentieth century changes in tropical Pacific climate identified in this reconstruction and, if substantiated, it will have important implications to the low-frequency dynamics of ENSO.

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Kyle R. Clem
,
Marilyn N. Raphael
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Susheel Adusumilli
,
Rebecca Baiman
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Alison F. Banwell
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Sandra Barreira
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Rebecca L. Beadling
,
Steve Colwell
,
Lawrence Coy
,
Rajashree T. Datta
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Jos De Laat
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Devon Dunmire
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Ryan L. Fogt
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Natalie M. Freeman
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Helen Amanda Fricker
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Alex S. Gardner
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Bryan Johnson
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Linda M. Keller
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Natalya A. Kramarova
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Matthew A. Lazzara
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Jan L. Lieser
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Michael MacFerrin
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Graeme A. MacGilchrist
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Michelle L. MacLennan
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Robert A. Massom
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Matthew R. Mazloff
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Thomas L. Mote
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Eric R. Nash
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Paul A. Newman
,
Taylor Norton
,
Irina Petropavlovskikh
,
Michael Pitts
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Phillip Reid
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Michelle L. Santee
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Ted A. Scambos
,
Jia-Rui Shi
,
Sharon Stammerjohn
,
Susan E. Strahan
,
Andrew F. Thompson
,
Jonathan D. Wille
, and
Earle Wilson
Free access
R. A Anthes
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P. A Bernhardt
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Y. Chen
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L. Cucurull
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K. F. Dymond
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D. Ector
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S. B. Healy
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S.-P. Ho
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D. C Hunt
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Y.-H. Kuo
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H. Liu
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K. Manning
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C. McCormick
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T. K. Meehan
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W J. Randel
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C. Rocken
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W S. Schreiner
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S. V. Sokolovskiy
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S. Syndergaard
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D. C. Thompson
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K. E. Trenberth
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T.-K. Wee
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N. L. Yen
, and
Z Zeng

The radio occultation (RO) technique, which makes use of radio signals transmitted by the global positioning system (GPS) satellites, has emerged as a powerful and relatively inexpensive approach for sounding the global atmosphere with high precision, accuracy, and vertical resolution in all weather and over both land and ocean. On 15 April 2006, the joint Taiwan-U.S. Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC)/Formosa Satellite Mission 3 (COSMIC/FORMOSAT-3, hereafter COSMIC) mission, a constellation of six microsatellites, was launched into a 512-km orbit. After launch the satellites were gradually deployed to their final orbits at 800 km, a process that took about 17 months. During the early weeks of the deployment, the satellites were spaced closely, offering a unique opportunity to verify the high precision of RO measurements. As of September 2007, COSMIC is providing about 2000 RO soundings per day to support the research and operational communities. COSMIC RO data are of better quality than those from the previous missions and penetrate much farther down into the troposphere; 70%–90% of the soundings reach to within 1 km of the surface on a global basis. The data are having a positive impact on operational global weather forecast models.

With the ability to penetrate deep into the lower troposphere using an advanced open-loop tracking technique, the COSMIC RO instruments can observe the structure of the tropical atmospheric boundary layer. The value of RO for climate monitoring and research is demonstrated by the precise and consistent observations between different instruments, platforms, and missions. COSMIC observations are capable of intercalibrating microwave measurements from the Advanced Microwave Sounding Unit (AMSU) on different satellites. Finally, unique and useful observations of the ionosphere are being obtained using the RO receiver and two other instruments on the COSMIC satellites, the tiny ionosphere photometer (TIP) and the tri-band beacon.

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Adam J. Clark
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Israel L. Jirak
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Scott R. Dembek
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Gerry J. Creager
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Fanyou Kong
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Kevin W. Thomas
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Kent H. Knopfmeier
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Burkely T. Gallo
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Christopher J. Melick
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Ming Xue
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Keith A. Brewster
,
Youngsun Jung
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Aaron Kennedy
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Xiquan Dong
,
Joshua Markel
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Matthew Gilmore
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Glen S. Romine
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Kathryn R. Fossell
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Ryan A. Sobash
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Jacob R. Carley
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Brad S. Ferrier
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Matthew Pyle
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Curtis R. Alexander
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Steven J. Weiss
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John S. Kain
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Louis J. Wicker
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Gregory Thompson
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Rebecca D. Adams-Selin
, and
David A. Imy

Abstract

One primary goal of annual Spring Forecasting Experiments (SFEs), which are coorganized by NOAA’s National Severe Storms Laboratory and Storm Prediction Center and conducted in the National Oceanic and Atmospheric Administration’s (NOAA) Hazardous Weather Testbed, is documenting performance characteristics of experimental, convection-allowing modeling systems (CAMs). Since 2007, the number of CAMs (including CAM ensembles) examined in the SFEs has increased dramatically, peaking at six different CAM ensembles in 2015. Meanwhile, major advances have been made in creating, importing, processing, verifying, and developing tools for analyzing and visualizing these large and complex datasets. However, progress toward identifying optimal CAM ensemble configurations has been inhibited because the different CAM systems have been independently designed, making it difficult to attribute differences in performance characteristics. Thus, for the 2016 SFE, a much more coordinated effort among many collaborators was made by agreeing on a set of model specifications (e.g., model version, grid spacing, domain size, and physics) so that the simulations contributed by each collaborator could be combined to form one large, carefully designed ensemble known as the Community Leveraged Unified Ensemble (CLUE). The 2016 CLUE was composed of 65 members contributed by five research institutions and represents an unprecedented effort to enable an evidence-driven decision process to help guide NOAA’s operational modeling efforts. Eight unique experiments were designed within the CLUE framework to examine issues directly relevant to the design of NOAA’s future operational CAM-based ensembles. This article will highlight the CLUE design and present results from one of the experiments examining the impact of single versus multicore CAM ensemble configurations.

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Yolande L. Serra
,
Jennifer S. Haase
,
David K. Adams
,
Qiang Fu
,
Thomas P. Ackerman
,
M. Joan Alexander
,
Avelino Arellano
,
Larissa Back
,
Shu-Hua Chen
,
Kerry Emanuel
,
Zeljka Fuchs
,
Zhiming Kuang
,
Benjamin R Lintner
,
Brian Mapes
,
David Neelin
,
David Raymond
,
Adam H. Sobel
,
Paul W. Staten
,
Aneesh Subramanian
,
David W. J. Thompson
,
Gabriel Vecchi
,
Robert Wood
, and
Paquita Zuidema
Full access
Gregory C. Johnson
,
Rick Lumpkin
,
Simone R. Alin
,
Dillon J. Amaya
,
Molly O. Baringer
,
Tim Boyer
,
Peter Brandt
,
Brendan R. Carter
,
Ivona Cetinić
,
Don P. Chambers
,
Lijing Cheng
,
Andrew U. Collins
,
Cathy Cosca
,
Ricardo Domingues
,
Shenfu Dong
,
Richard A. Feely
,
Eleanor Frajka-Williams
,
Bryan A. Franz
,
John Gilson
,
Gustavo Goni
,
Benjamin D. Hamlington
,
Josefine Herrford
,
Zeng-Zhen Hu
,
Boyin Huang
,
Masayoshi Ishii
,
Svetlana Jevrejeva
,
John J. Kennedy
,
Marion Kersalé
,
Rachel E. Killick
,
Peter Landschützer
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Matthias Lankhorst
,
Eric Leuliette
,
Ricardo Locarnini
,
John M. Lyman
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John J. Marra
,
Christopher S. Meinen
,
Mark A. Merrifield
,
Gary T. Mitchum
,
Ben I. Moat
,
R. Steven Nerem
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Renellys C. Perez
,
Sarah G. Purkey
,
James Reagan
,
Alejandra Sanchez-Franks
,
Hillary A. Scannell
,
Claudia Schmid
,
Joel P. Scott
,
David A. Siegel
,
David A. Smeed
,
Paul W. Stackhouse
,
William Sweet
,
Philip R. Thompson
,
Joaquin A. Triñanes
,
Denis L. Volkov
,
Rik Wanninkhof
,
Robert A. Weller
,
Caihong Wen
,
Toby K. Westberry
,
Matthew J. Widlansky
,
Anne C. Wilber
,
Lisan Yu
, and
Huai-Min Zhang
Free access
Gregory C. Johnson
,
Rick Lumpkin
,
Tim Boyer
,
Francis Bringas
,
Ivona Cetinić
,
Don P. Chambers
,
Lijing Cheng
,
Shenfu Dong
,
Richard A. Feely
,
Baylor Fox-Kemper
,
Eleanor Frajka-Williams
,
Bryan A. Franz
,
Yao Fu
,
Meng Gao
,
Jay Garg
,
John Gilson
,
Gustavo Goni
,
Benjamin D. Hamlington
,
Helene T. Hewitt
,
William R. Hobbs
,
Zeng-Zhen Hu
,
Boyin Huang
,
Svetlana Jevrejeva
,
William E. Johns
,
Sato Katsunari
,
John J. Kennedy
,
Marion Kersalé
,
Rachel E. Killick
,
Eric Leuliette
,
Ricardo Locarnini
,
M. Susan Lozier
,
John M. Lyman
,
Mark A. Merrifield
,
Alexey Mishonov
,
Gary T. Mitchum
,
Ben I. Moat
,
R. Steven Nerem
,
Dirk Notz
,
Renellys C. Perez
,
Sarah G. Purkey
,
Darren Rayner
,
James Reagan
,
Claudia Schmid
,
David A. Siegel
,
David A. Smeed
,
Paul W. Stackhouse
,
William Sweet
,
Philip R. Thompson
,
Denis L. Volkov
,
Rik Wanninkhof
,
Robert A. Weller
,
Caihong Wen
,
Toby K. Westberry
,
Matthew J. Widlansky
,
Josh K. Willis
,
Lisan Yu
, and
Huai-Min Zhang
Free 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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