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Joseph Egger
and
H-D. Schilling

Abstract

Using geopotential height observations we analyze the fluctuations of the barotropic vorticity transfer from synoptic scale flow (zonal wavenumber m > 5) to planetary scales (m ≤ 5). We hypothesize that this transfer can be seen as a stochastic forcing of the planetary flow modes which is essentially independent of the state at planetary scales. The covariance of the transfer and the planetary flow is presented for selected planetary modes. In parallel, the linear barotropic vorticity equation is solved for these modes where the transfer is prescribed as stochastic forcing with the statistical characteristics of the observed transfer. The covariance of forcing and response is derived and compared to the observed covariance. It turns out that there is good agreement for retrograde and quasi-stationary modes. The agreement is less satisfactory for the largest atmospheric mode and for prograde modes with relatively large wavenumber. 11 is shown that the transfer cannot be seen as a diffusive process. We conclude that the transfer can be seen as stochastic forcing at least for the quasi-stationary modes. This has implications for the modeling of the long-term variability of the atmosphere which is dominated by these modes.

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D. Schüttemeyer
,
Ch Schillings
,
A. F. Moene
, and
H. A. R. de Bruin

Abstract

A simple satellite-based algorithm for estimating actual evaporation based on Makkink’s equation is applied to a seasonal cycle in 2002 at three test sites in Ghana, West Africa: at a location in the humid tropical southern region and two in the drier northern region. The required input for the algorithm is incoming solar radiation, air temperature at standard level, and the green-vegetation fraction. These data are obtained from Meteorological Satellite (Meteosat) and Moderate-Resolution Imaging Spectroradiometer (MODIS) images. The observation period includes the rapid wet-to-dry transition after the wet season. Incoming solar radiation and air temperature are validated against local measurements at the three sites. It is found that the incoming solar radiation obtained from Meteosat corresponds well with the measurements. For air temperature from Meteosat data, the diurnal cycle is realistically reproduced but is in need of a bias correction. The algorithm output is compared with the evapotranspiration data obtained from hourly large-aperture scintillometer observations and simultaneous “in situ” measurements of net radiation and soil heat flux. It is found that the actual evapotranspiration can be monitored using the modified Makkink method, with daily mean errors of between 5% and 35% of measured evapotranspiration and a seasonal error smaller than 5%. Furthermore, it appears that the algorithm realistically describes the daily cycle of evapotranspiration.

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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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