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  • Author or Editor: Ray D. Jackson x
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B. Soden
,
S. Tjemkes
,
J. Schmetz
,
R. Saunders
,
J. Bates
,
B. Ellingson
,
R. Engelen
,
L. Garand
,
D. Jackson
,
G. Jedlovec
,
T. Kleespies
,
D. Randel
,
P. Rayer
,
E. Salathe
,
D. Schwarzkopf
,
N. Scott
,
B. Sohn
,
S. de Souza-Machado
,
L. Strow
,
D. Tobin
,
D. Turner
,
P. van Delst
, and
T. Wehr

An intercomparison of radiation codes used in retrieving upper-tropospheric humidity (UTH) from observations in the ν2 (6.3 μm) water vapor absorption band was performed. This intercomparison is one part of a coordinated effort within the Global Energy and Water Cycle Experiment Water Vapor Project to assess our ability to monitor the distribution and variations of upper-tropospheric moisture from spaceborne sensors. A total of 23 different codes, ranging from detailed line-by-line (LBL) models, to coarser-resolution narrowband (NB) models, to highly parameterized single-band (SB) models participated in the study. Forward calculations were performed using a carefully selected set of temperature and moisture profiles chosen to be representative of a wide range of atmospheric conditions. The LBL model calculations exhibited the greatest consistency with each other, typically agreeing to within 0.5 K in terms of the equivalent blackbody brightness temperature (Tb ). The majority of NB and SB models agreed to within ±1 K of the LBL models, although a few older models exhibited systematic Tb biases in excess of 2 K. A discussion of the discrepancies between various models, their association with differences in model physics (e.g., continuum absorption), and their implications for UTH retrieval and radiance assimilation is presented.

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Randall M. Dole
,
J. Ryan Spackman
,
Matthew Newman
,
Gilbert P. Compo
,
Catherine A. Smith
,
Leslie M. Hartten
,
Joseph J. Barsugli
,
Robert S. Webb
,
Martin P. Hoerling
,
Robert Cifelli
,
Klaus Wolter
,
Christopher D. Barnet
,
Maria Gehne
,
Ronald Gelaro
,
George N. Kiladis
,
Scott Abbott
,
Elena Akish
,
John Albers
,
John M. Brown
,
Christopher J. Cox
,
Lisa Darby
,
Gijs de Boer
,
Barbara DeLuisi
,
Juliana Dias
,
Jason Dunion
,
Jon Eischeid
,
Christopher Fairall
,
Antonia Gambacorta
,
Brian K. Gorton
,
Andrew Hoell
,
Janet Intrieri
,
Darren Jackson
,
Paul E. Johnston
,
Richard Lataitis
,
Kelly M. Mahoney
,
Katherine McCaffrey
,
H. Alex McColl
,
Michael J. Mueller
,
Donald Murray
,
Paul J. Neiman
,
William Otto
,
Ola Persson
,
Xiao-Wei Quan
,
Imtiaz Rangwala
,
Andrea J. Ray
,
David Reynolds
,
Emily Riley Dellaripa
,
Karen Rosenlof
,
Naoko Sakaeda
,
Prashant D. Sardeshmukh
,
Laura C. Slivinski
,
Lesley Smith
,
Amy Solomon
,
Dustin Swales
,
Stefan Tulich
,
Allen White
,
Gary Wick
,
Matthew G. Winterkorn
,
Daniel E. Wolfe
, and
Robert Zamora

Abstract

Forecasts by mid-2015 for a strong El Niño during winter 2015/16 presented an exceptional scientific opportunity to accelerate advances in understanding and predictions of an extreme climate event and its impacts while the event was ongoing. Seizing this opportunity, the National Oceanic and Atmospheric Administration (NOAA) initiated an El Niño Rapid Response (ENRR), conducting the first field campaign to obtain intensive atmospheric observations over the tropical Pacific during El Niño.

The overarching ENRR goal was to determine the atmospheric response to El Niño and the implications for predicting extratropical storms and U.S. West Coast rainfall. The field campaign observations extended from the central tropical Pacific to the West Coast, with a primary focus on the initial tropical atmospheric response that links El Niño to its global impacts. NOAA deployed its Gulfstream-IV (G-IV) aircraft to obtain observations around organized tropical convection and poleward convective outflow near the heart of El Niño. Additional tropical Pacific observations were obtained by radiosondes launched from Kiritimati , Kiribati, and the NOAA ship Ronald H. Brown, and in the eastern North Pacific by the National Aeronautics and Space Administration (NASA) Global Hawk unmanned aerial system. These observations were all transmitted in real time for use in operational prediction models. An X-band radar installed in Santa Clara, California, helped characterize precipitation distributions. This suite supported an end-to-end capability extending from tropical Pacific processes to West Coast impacts. The ENRR observations were used during the event in operational predictions. They now provide an unprecedented dataset for further research to improve understanding and predictions of El Niño and its impacts.

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