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Frank M. Monaldo
,
Xiaofeng Li
,
William G. Pichel
, and
Christopher R. Jackson

Spaceborne synthetic aperture radar (SAR) imagery can make high-resolution (≤500 m) ocean wind speed measurements. The authors anticipate reprocessing the full decade and a half of Radarsat-1 SAR imagery and generating a SAR wind speed archive. These data will be of use for studies of coastal atmospheric phenomena and assessment of offshore wind power potential. To illustrate the potential of this latter application, they review the ability of SARs to measure wind speed, discuss an approach for using SARs to create wind speed climatologies useful for wind power resource assessments, and consider issues concerning the applicably of such data for these assessments.

Full access
Philip J. Klotzbach
,
Johnny C. L. Chan
,
Patrick J. Fitzpatrick
,
William M. Frank
,
Christopher W. Landsea
, and
John L. McBride

Abstract

Advances in knowledge in tropical meteorological research are discussed in the context of contributions made by Professor William M. Gray. Gray pioneered the compositing approach to observational tropical meteorology through assembling of global radiosonde datasets and tropical cyclone research flight data. In the 1970s, he made fundamental contributions to knowledge of convective–larger-scale interactions. Throughout his career, he wrote seminal papers on tropical cyclone structure, cyclogenesis, motion, and seasonal forecasts. His conceptual development of a seasonal genesis parameter also laid an important framework for both seasonal forecasting as well as climate change studies on tropical cyclones. His work was a blend of both observationally based studies and the development of theoretical concepts. This paper reviews the progress in knowledge in the areas where Dr. Gray provided his largest contributions and describes the scientific legacy of Gray’s contributions to tropical meteorology.

Open access
Jennifer A. MacKinnon
,
Zhongxiang Zhao
,
Caitlin B. Whalen
,
Amy F. Waterhouse
,
David S. Trossman
,
Oliver M. Sun
,
Louis C. St. Laurent
,
Harper L. Simmons
,
Kurt Polzin
,
Robert Pinkel
,
Andrew Pickering
,
Nancy J. Norton
,
Jonathan D. Nash
,
Ruth Musgrave
,
Lynne M. Merchant
,
Angelique V. Melet
,
Benjamin Mater
,
Sonya Legg
,
William G. Large
,
Eric Kunze
,
Jody M. Klymak
,
Markus Jochum
,
Steven R. Jayne
,
Robert W. Hallberg
,
Stephen M. Griffies
,
Steve Diggs
,
Gokhan Danabasoglu
,
Eric P. Chassignet
,
Maarten C. Buijsman
,
Frank O. Bryan
,
Bruce P. Briegleb
,
Andrew Barna
,
Brian K. Arbic
,
Joseph K. Ansong
, and
Matthew H. Alford

Abstract

Diapycnal mixing plays a primary role in the thermodynamic balance of the ocean and, consequently, in oceanic heat and carbon uptake and storage. Though observed mixing rates are on average consistent with values required by inverse models, recent attention has focused on the dramatic spatial variability, spanning several orders of magnitude, of mixing rates in both the upper and deep ocean. Away from ocean boundaries, the spatiotemporal patterns of mixing are largely driven by the geography of generation, propagation, and dissipation of internal waves, which supply much of the power for turbulent mixing. Over the last 5 years and under the auspices of U.S. Climate Variability and Predictability Program (CLIVAR), a National Science Foundation (NSF)- and National Oceanic and Atmospheric Administration (NOAA)-supported Climate Process Team has been engaged in developing, implementing, and testing dynamics-based parameterizations for internal wave–driven turbulent mixing in global ocean models. The work has primarily focused on turbulence 1) near sites of internal tide generation, 2) in the upper ocean related to wind-generated near inertial motions, 3) due to internal lee waves generated by low-frequency mesoscale flows over topography, and 4) at ocean margins. Here, we review recent progress, describe the tools developed, and discuss future directions.

Open access
Svetla M. Hristova-Veleva
,
P. Peggy Li
,
Brian Knosp
,
Quoc Vu
,
F. Joseph Turk
,
William L. Poulsen
,
Ziad Haddad
,
Bjorn Lambrigtsen
,
Bryan W. Stiles
,
Tsae-Pyng Shen
,
Noppasin Niamsuwan
,
Simone Tanelli
,
Ousmane Sy
,
Eun-Kyoung Seo
,
Hui Su
,
Deborah G. Vane
,
Yi Chao
,
Philip S. Callahan
,
R. Scott Dunbar
,
Michael Montgomery
,
Mark Boothe
,
Vijay Tallapragada
,
Samuel Trahan
,
Anthony J. Wimmers
,
Robert Holz
,
Jeffrey S. Reid
,
Frank Marks
,
Tomislava Vukicevic
,
Saiprasanth Bhalachandran
,
Hua Leighton
,
Sundararaman Gopalakrishnan
,
Andres Navarro
, and
Francisco J. Tapiador

Abstract

Tropical cyclones (TCs) are among the most destructive natural phenomena with huge societal and economic impact. They form and evolve as the result of complex multiscale processes and nonlinear interactions. Even today the understanding and modeling of these processes is still lacking. A major goal of NASA is to bring the wealth of satellite and airborne observations to bear on addressing the unresolved scientific questions and improving our forecast models. Despite their significant amount, these observations are still underutilized in hurricane research and operations due to the complexity associated with finding and bringing together semicoincident and semicontemporaneous multiparameter data that are needed to describe the multiscale TC processes. Such data are traditionally archived in different formats, with different spatiotemporal resolution, across multiple databases, and hosted by various agencies. To address this shortcoming, NASA supported the development of the Jet Propulsion Laboratory (JPL) Tropical Cyclone Information System (TCIS)—a data analytic framework that integrates model forecasts with multiparameter satellite and airborne observations, providing interactive visualization and online analysis tools. TCIS supports interrogation of a large number of atmospheric and ocean variables, allowing for quick investigation of the structure of the tropical storms and their environments. This paper provides an overview of the TCIS’s components and features. It also summarizes recent pilot studies, providing examples of how the TCIS has inspired new research, helping to increase our understanding of TCs. The goal is to encourage more users to take full advantage of the novel capabilities. TCIS allows atmospheric scientists to focus on new ideas and concepts rather than painstakingly gathering data scattered over several agencies.

Free access
Svetla M. Hristova-Veleva
,
P. Peggy Li
,
Brian Knosp
,
Quoc Vu
,
F. Joseph Turk
,
William L. Poulsen
,
Ziad Haddad
,
Bjorn Lambrigtsen
,
Bryan W. Stiles
,
Tsae-Pyng Shen
,
Noppasin Niamsuwan
,
Simone Tanelli
,
Ousmane Sy
,
Eun-Kyoung Seo
,
Hui Su
,
Deborah G. Vane
,
Yi Chao
,
Philip S. Callahan
,
R. Scott Dunbar
,
Michael Montgomery
,
Mark Boothe
,
Vijay Tallapragada
,
Samuel Trahan
,
Anthony J. Wimmers
,
Robert Holz
,
Jeffrey S. Reid
,
Frank Marks
,
Tomislava Vukicevic
,
Saiprasanth Bhalachandran
,
Hua Leighton
,
Sundararaman Gopalakrishnan
,
Andres Navarro
, and
Francisco J. Tapiador
Full access
Molly Baringer
,
Mariana B. Bif
,
Tim Boyer
,
Seth M. Bushinsky
,
Brendan R. Carter
,
Ivona Cetinić
,
Don P. Chambers
,
Lijing Cheng
,
Sanai Chiba
,
Minhan Dai
,
Catia M. Domingues
,
Shenfu Dong
,
Andrea J. Fassbender
,
Richard A. Feely
,
Eleanor Frajka-Williams
,
Bryan A. Franz
,
John Gilson
,
Gustavo Goni
,
Benjamin D. Hamlington
,
Zeng-Zhen Hu
,
Boyin Huang
,
Masayoshi Ishii
,
Svetlana Jevrejeva
,
William E. Johns
,
Gregory C. Johnson
,
Kenneth S. Johnson
,
John Kennedy
,
Marion Kersalé
,
Rachel E. Killick
,
Peter Landschützer
,
Matthias Lankhorst
,
Tong Lee
,
Eric Leuliette
,
Feili Li
,
Eric Lindstrom
,
Ricardo Locarnini
,
Susan Lozier
,
John M. Lyman
,
John J. Marra
,
Christopher S. Meinen
,
Mark A. Merrifield
,
Gary T. Mitchum
,
Ben Moat
,
Didier Monselesan
,
R. Steven Nerem
,
Renellys C. Perez
,
Sarah G. Purkey
,
Darren Rayner
,
James Reagan
,
Nicholas Rome
,
Alejandra Sanchez-Franks
,
Claudia Schmid
,
Joel P. Scott
,
Uwe Send
,
David A. Siegel
,
David A. Smeed
,
Sabrina Speich
,
Paul W. Stackhouse Jr.
,
William Sweet
,
Yuichiro Takeshita
,
Philip R. Thompson
,
Joaquin A. Triñanes
,
Martin Visbeck
,
Denis L. Volkov
,
Rik Wanninkhof
,
Robert A. Weller
,
Toby K. Westberry
,
Matthew J. Widlansky
,
Susan E. Wijffels
,
Anne C. Wilber
,
Lisan Yu
,
Weidong Yu
, and
Huai-Min Zhang
Free 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
,
Matthias Lankhorst
,
Eric Leuliette
,
Ricardo Locarnini
,
John M. Lyman
,
John J. Marra
,
Christopher S. Meinen
,
Mark A. Merrifield
,
Gary T. Mitchum
,
Ben I. Moat
,
R. Steven Nerem
,
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