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Peter R. Gent
,
Frank O. Bryan
,
Gokhan Danabasoglu
,
Scott C. Doney
,
William R. Holland
,
William G. Large
, and
James C. McWilliams

Abstract

This paper describes the global ocean component of the NCAR Climate System Model. New parameterizations of the effects of mesoscale eddies and of the upper-ocean boundary layer are included. Numerical improvements include a third-order upwind advection scheme and elimination of the artificial North Pole island in the original MOM 1.1 code. Updated forcing fields are used to drive the ocean-alone solution, which is integrated long enough so that it is in equilibrium. The ocean transports and potential temperature and salinity distributions are compared with observations. The solution sensitivity to the freshwater forcing distribution is highlighted, and the sensitivity to resolution is also briefly discussed.

Full access
Stuart P. Bishop
,
Peter R. Gent
,
Frank O. Bryan
,
Andrew F. Thompson
,
Matthew C. Long
, and
Ryan Abernathey

Abstract

The Southern Ocean’s Antarctic Circumpolar Current (ACC) and meridional overturning circulation (MOC) response to increasing zonal wind stress is, for the first time, analyzed in a high-resolution (0.1° ocean and 0.25° atmosphere), fully coupled global climate simulation using the Community Earth System Model. Results from a 20-yr wind perturbation experiment, where the Southern Hemisphere zonal wind stress is increased by 50% south of 30°S, show only marginal changes in the mean ACC transport through Drake Passage—an increase of 6% [136–144 Sverdrups (Sv; 1 Sv ≡ 106 m3 s−1)] in the perturbation experiment compared with the control. However, the upper and lower circulation cells of the MOC do change. The lower cell is more affected than the upper cell with a maximum increase of 64% versus 39%, respectively. Changes in the MOC are directly linked to changes in water mass transformation from shifting surface isopycnals and sea ice melt, giving rise to changes in surface buoyancy forcing. The increase in transport of the lower cell leads to upwelling of warm and salty Circumpolar Deep Water and subsequent melting of sea ice surrounding Antarctica. The MOC is commonly supposed to be the sum of two opposing components: a wind- and transient-eddy overturning cell. Here, the transient-eddy overturning is virtually unchanged and consistent with a large-scale cancellation of localized regions of both enhancement and suppression of eddy kinetic energy along the mean path of the ACC. However, decomposing the time-mean overturning into a time- and zonal-mean component and a standing-eddy component reveals partial compensation between wind-driven and standing-eddy components of the circulation.

Full access
Markus Jochum
,
Bruce P. Briegleb
,
Gokhan Danabasoglu
,
William G. Large
,
Nancy J. Norton
,
Steven R. Jayne
,
Matthew H. Alford
, and
Frank O. Bryan

Abstract

The Community Climate System Model, version 4 (CCSM4) is used to assess the climate impact of wind-generated near-inertial waves (NIWs). Even with high-frequency coupling, CCSM4 underestimates the strength of NIWs, so that a parameterization for NIWs is developed and included into CCSM4. Numerous assumptions enter this parameterization, the core of which is that the NIW velocity signal is detected during the model integration, and amplified in the shear computation of the ocean surface boundary layer module. It is found that NIWs deepen the ocean mixed layer by up to 30%, but they contribute little to the ventilation and mixing of the ocean below the thermocline. However, the deepening of the tropical mixed layer by NIWs leads to a change in tropical sea surface temperature and precipitation. Atmospheric teleconnections then change the global sea level pressure fields so that the midlatitude westerlies become weaker. Unfortunately, the magnitude of the real air-sea flux of NIW energy is poorly constrained by observations; this makes the quantitative assessment of their climate impact rather uncertain. Thus, a major result of the present study is that because of its importance for global climate the uncertainty in the observed tropical NIW energy has to be reduced.

Full access
Joseph J. Cione
,
George H. Bryan
,
Ronald Dobosy
,
Jun A. Zhang
,
Gijs de Boer
,
Altug Aksoy
,
Joshua B. Wadler
,
Evan A. Kalina
,
Brittany A. Dahl
,
Kelly Ryan
,
Jonathan Neuhaus
,
Ed Dumas
,
Frank D. Marks
,
Aaron M. Farber
,
Terry Hock
, and
Xiaomin Chen

Abstract

Unique data from seven flights of the Coyote small unmanned aircraft system (sUAS) were collected in Hurricanes Maria (2017) and Michael (2018). Using NOAA’s P-3 reconnaissance aircraft as a deployment vehicle, the sUAS collected high-frequency (>1 Hz) measurements in the turbulent boundary layer of hurricane eyewalls, including measurements of wind speed, wind direction, pressure, temperature, moisture, and sea surface temperature, which are valuable for advancing knowledge of hurricane structure and the process of hurricane intensification. This study presents an overview of the sUAS system and preliminary analyses that were enabled by these unique data. Among the most notable results are measurements of turbulence kinetic energy and momentum flux for the first time at low levels (<150 m) in a hurricane eyewall. At higher altitudes and lower wind speeds, where data were collected from previous flights of the NOAA P-3, the Coyote sUAS momentum flux values are encouragingly similar, thus demonstrating the ability of an sUAS to measure important turbulence properties in hurricane boundary layers. Analyses from a large-eddy simulation (LES) are used to place the Coyote measurements into context of the complicated high-wind eyewall region. Thermodynamic data are also used to evaluate the operational HWRF model, showing a cool, dry, and thermodynamically unstable bias near the surface. Preliminary data assimilation experiments also show how sUAS data can be used to improve analyses of storm structure. These results highlight the potential of sUAS operations in hurricanes and suggest opportunities for future work using these promising new observing platforms.

Free access
Joseph J. Cione
,
George H. Bryan
,
Ronald Dobosy
,
Jun A. Zhang
,
Gijs de Boer
,
Altug Aksoy
,
Joshua B. Wadler
,
Evan A. Kalina
,
Brittany A. Dahl
,
Kelly Ryan
,
Jonathan Neuhaus
,
Ed Dumas
,
Frank D. Marks
,
Aaron M. Farber
,
Terry Hock
, and
Xiaomin Chen
Full 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
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
Maurice Blackmon
,
Byron Boville
,
Frank Bryan
,
Robert Dickinson
,
Peter Gent
,
Jeffrey Kiehl
,
Richard Moritz
,
David Randall
,
Jagadish Shukla
,
Susan Solomon
,
Gordon Bonan
,
Scott Doney
,
Inez Fung
,
James Hack
,
Elizabeth Hunke
,
James Hurrell
,
John Kutzbach
,
Jerry Meehl
,
Bette Otto-Bliesner
,
R. Saravanan
,
Edwin K. Schneider
,
Lisa Sloan
,
Michael Spall
,
Karl Taylor
,
Joseph Tribbia
, and
Warren Washington

The Community Climate System Model (CCSM) has been created to represent the principal components of the climate system and their interactions. Development and applications of the model are carried out by the U.S. climate research community, thus taking advantage of both wide intellectual participation and computing capabilities beyond those available to most individual U.S. institutions. This article outlines the history of the CCSM, its current capabilities, and plans for its future development and applications, with the goal of providing a summary useful to present and future users.

The initial version of the CCSM included atmosphere and ocean general circulation models, a land surface model that was grafted onto the atmosphere model, a sea-ice model, and a “flux coupler” that facilitates information exchanges among the component models with their differing grids. This version of the model produced a successful 300-yr simulation of the current climate without artificial flux adjustments. The model was then used to perform a coupled simulation in which the atmospheric CO2 concentration increased by 1 % per year.

In this version of the coupled model, the ocean salinity and deep-ocean temperature slowly drifted away from observed values. A subsequent correction to the roughness length used for sea ice significantly reduced these errors. An updated version of the CCSM was used to perform three simulations of the twentieth century's climate, and several projections of the climate of the twenty-first century.

The CCSM's simulation of the tropical ocean circulation has been significantly improved by reducing the background vertical diffusivity and incorporating an anisotropic horizontal viscosity tensor. The meridional resolution of the ocean model was also refined near the equator. These changes have resulted in a greatly improved simulation of both the Pacific equatorial undercurrent and the surface countercurrents. The interannual variability of the sea surface temperature in the central and eastern tropical Pacific is also more realistic in simulations with the updated model.

Scientific challenges to be addressed with future versions of the CCSM include realistic simulation of the whole atmosphere, including the middle and upper atmosphere, as well as the troposphere; simulation of changes in the chemical composition of the atmosphere through the incorporation of an integrated chemistry model; inclusion of global, prognostic biogeochemical components for land, ocean, and atmosphere; simulations of past climates, including times of extensive continental glaciation as well as times with little or no ice; studies of natural climate variability on seasonal-to-centennial timescales; and investigations of anthropogenic climate change. In order to make such studies possible, work is under way to improve all components of the model. Plans call for a new version of the CCSM to be released in 2002. Planned studies with the CCSM will require much more computer power than is currently available.

Full 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