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  • Author or Editor: DAVID WILLIAMSON x
  • Bulletin of the American Meteorological Society x
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Thomas J. Phillips
,
Gerald L. Potter
,
David L. Williamson
,
Richard T. Cederwall
,
James S. Boyle
,
Michael Fiorino
,
Justin J. Hnilo
,
Jerry G. Olson
,
Shaocheng Xie
, and
J. John Yio

To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands that the GCM parameterizations of unresolved processes, in particular, should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a realistically initialized climate GCM, and the application of six hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be tested in the same framework.

To further this method for evaluating and analyzing parameterizations in climate GCMs, the U.S. Department of Energy is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM.

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