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Ralph A. Kahn
,
Tim A. Berkoff
,
Charles Brock
,
Gao Chen
,
Richard A. Ferrare
,
Steven Ghan
,
Thomas F. Hansico
,
Dean A. Hegg
,
J. Vanderlei Martins
,
Cameron S. McNaughton
,
Daniel M. Murphy
,
John A. Ogren
,
Joyce E. Penner
,
Peter Pilewskie
,
John H. Seinfeld
, and
Douglas R. Worsnop

Abstract

A modest operational program of systematic aircraft measurements can resolve key satellite aerosol data record limitations. Satellite observations provide frequent global aerosol amount maps but offer only loose aerosol property constraints needed for climate and air quality applications. We define and illustrate the feasibility of flying an aircraft payload to measure key aerosol optical, microphysical, and chemical properties in situ. The flight program could characterize major aerosol airmass types statistically, at a level of detail unobtainable from space. It would 1) enhance satellite aerosol retrieval products with better climatology assumptions and 2) improve translation between satellite-retrieved optical properties and species-specific aerosol mass and size simulated in climate models to assess aerosol forcing, its anthropogenic components, and other environmental impacts. As such, Systematic Aircraft Measurements to Characterize Aerosol Air Masses (SAM-CAAM) could add value to data records representing several decades of aerosol observations from space; improve aerosol constraints on climate modeling; help interrelate remote sensing, in situ, and modeling aerosol-type definitions; and contribute to future satellite aerosol missions. Fifteen required variables are identified and four payload options of increasing ambition are defined to constrain these quantities. “Option C” could meet all the SAM-CAAM objectives with about 20 instruments, most of which have flown before, but never routinely several times per week, and never as a group. Aircraft integration and approaches to data handling, payload support, and logistical considerations for a long-term, operational mission are discussed. SAM-CAAM is feasible because, for most aerosol sources and specified seasons, particle properties tend to be repeatable, even if aerosol loading varies.

Open access
Katharine S. Law
,
Andreas Stohl
,
Patricia K. Quinn
,
Charles A. Brock
,
John F. Burkhart
,
Jean-Daniel Paris
,
Gerard Ancellet
,
Hanwant B. Singh
,
Anke Roiger
,
Hans Schlager
,
Jack Dibb
,
Daniel J. Jacob
,
Steve R. Arnold
,
Jacques Pelon
, and
Jennie L. Thomas

Given the rapid nature of climate change occurring in the Arctic and the difficulty climate models have in quantitatively reproducing observed changes such as sea ice loss, it is important to improve understanding of the processes leading to climate change in this region, including the role of short-lived climate pollutants such as aerosols and ozone. It has long been known that pollution produced from emissions at midlatitudes can be transported to the Arctic, resulting in a winter/spring aerosol maximum known as Arctic haze. However, many uncertainties remain about the composition and origin of Arctic pollution throughout the troposphere; for example, many climate–chemistry models fail to reproduce the strong seasonality of aerosol abundance observed at Arctic surface sites, the origin and deposition mechanisms of black carbon (soot) particles that darken the snow and ice surface in the Arctic is poorly understood, and chemical processes controlling the abundance of tropospheric ozone are not well quantified. The International Polar Year (IPY) Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, Climate, Chemistry, Aerosols and Transport (POLARCAT) core project had the goal to improve understanding about the origins of pollutants transported to the Arctic; to detail the chemical composition, optical properties, and climate forcing potential of Arctic aerosols; to evaluate the processes governing tropospheric ozone; and to quantify the role of boreal forest fires. This article provides a review of the many results now available based on analysis of data collected during the POLARCAT aircraft-, ship-, and ground-based field campaigns in spring and summer 2008. Major findings are highlighted and areas requiring further investigation are discussed.

Full access
Annmarie G. Carlton
,
Joost de Gouw
,
Jose L. Jimenez
,
Jesse L. Ambrose
,
Alexis R. Attwood
,
Steven Brown
,
Kirk R. Baker
,
Charles Brock
,
Ronald C. Cohen
,
Sylvia Edgerton
,
Caroline M. Farkas
,
Delphine Farmer
,
Allen H. Goldstein
,
Lynne Gratz
,
Alex Guenther
,
Sherri Hunt
,
Lyatt Jaeglé
,
Daniel A. Jaffe
,
John Mak
,
Crystal McClure
,
Athanasios Nenes
,
Thien Khoi Nguyen
,
Jeffrey R. Pierce
,
Suzane de Sa
,
Noelle E. Selin
,
Viral Shah
,
Stephanie Shaw
,
Paul B. Shepson
,
Shaojie Song
,
Jochen Stutz
,
Jason D. Surratt
,
Barbara J. Turpin
,
Carsten Warneke
,
Rebecca A. Washenfelder
,
Paul O. Wennberg
, and
Xianling Zhou

Abstract

The Southeast Atmosphere Studies (SAS), which included the Southern Oxidant and Aerosol Study (SOAS); the Southeast Nexus (SENEX) study; and the Nitrogen, Oxidants, Mercury and Aerosols: Distributions, Sources and Sinks (NOMADSS) study, was deployed in the field from 1 June to 15 July 2013 in the central and eastern United States, and it overlapped with and was complemented by the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. SAS investigated atmospheric chemistry and the associated air quality and climate-relevant particle properties. Coordinated measurements from six ground sites, four aircraft, tall towers, balloon-borne sondes, existing surface networks, and satellites provide in situ and remotely sensed data on trace-gas composition, aerosol physicochemical properties, and local and synoptic meteorology. Selected SAS findings indicate 1) dramatically reduced NOx concentrations have altered ozone production regimes; 2) indicators of “biogenic” secondary organic aerosol (SOA), once considered part of the natural background, were positively correlated with one or more indicators of anthropogenic pollution; and 3) liquid water dramatically impacted particle scattering while biogenic SOA did not. SAS findings suggest that atmosphere–biosphere interactions modulate ambient pollutant concentrations through complex mechanisms and feedbacks not yet adequately captured in atmospheric models. The SAS dataset, now publicly available, is a powerful constraint to develop predictive capability that enhances model representation of the response and subsequent impacts of changes in atmospheric composition to changes in emissions, chemistry, and meteorology.

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.

Full access