428 research outputs found
The Sleeping Giant: Measuring Ocean-Ice Interactions in Antarctica
Global sea level rise threatens to be one of the most costly consequences of human-caused climate change. And yet, projections of sea level rise remain poorly understood and highly uncertain. The largest potential contribution to global sea level rise involves the loss of ice covering all or even a
portion of Antarctica. As global atmospheric and ocean temperatures rise, physical processes related to the ocean’s circulation: (i) carry this additional heat into the deep ocean, (ii) transport it poleward via the overturning circulation and (iii) ultimately deliver the heat to the underside of floating Antarctic ice shelves. Enhanced melting that occurs due to warm ocean waters plays an
important role in the loss of ice from the continent. Our understanding of the first two steps that bring heat towards Antarctica has increased substantially over the past two decades through improved measurements of air-sea interactions and interior ocean properties (e.g., Argo). Yet, the constraints on the oceanic delivery of heat to Antarctic ice shelves and its impact on melt rates remains critically under-studied. Our inability to constrain the rate of retreat of Antarctic
glaciers and how the Antarctic Ice Sheet will behave in a warming climate remains the single most significant reason for the large uncertainty in sea level projections over the 21st century. This problem is the focus of the KISS study, "The Sleeping Giant: Measuring Ocean Ice Interactions in Antarctica," and stands as one of the grand challenges of climate science today
BOSS-LDG: A Novel Computational Framework that Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery
We present a novel computational framework that connects Blue Waters, the
NSF-supported, leadership-class supercomputer operated by NCSA, to the Laser
Interferometer Gravitational-Wave Observatory (LIGO) Data Grid via Open Science
Grid technology. To enable this computational infrastructure, we configured,
for the first time, a LIGO Data Grid Tier-1 Center that can submit
heterogeneous LIGO workflows using Open Science Grid facilities. In order to
enable a seamless connection between the LIGO Data Grid and Blue Waters via
Open Science Grid, we utilize Shifter to containerize LIGO's workflow software.
This work represents the first time Open Science Grid, Shifter, and Blue Waters
are unified to tackle a scientific problem and, in particular, it is the first
time a framework of this nature is used in the context of large scale
gravitational wave data analysis. This new framework has been used in the last
several weeks of LIGO's second discovery campaign to run the most
computationally demanding gravitational wave search workflows on Blue Waters,
and accelerate discovery in the emergent field of gravitational wave
astrophysics. We discuss the implications of this novel framework for a wider
ecosystem of Higher Performance Computing users.Comment: 10 pages, 10 figures. Accepted as a Full Research Paper to the 13th
IEEE International Conference on eScienc
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FROM THE GUEST EDITORS. Introduction to the Special Issue on Ocean-Ice Interaction
The end of 2016 is an uneasy moment for climate science in the United States. With a new Administration and a new Congress arriving in January 2017, future support for climate science and observing systems is uncertain. Against this backdrop, this special issue of Oceanographyon ocean-ice interaction is timely. Although it was not our intent to highlight climate change, the fragile nature of Earth’s cryosphere and how it is responding to a warming world are essential parts of each article. Many aspects of the shrinking cryosphere are not yet understood, but the research described in these pages points to larger-than-anticipated—and alarming—changes to the planet’s large ice sheets, with associated future increases in global sea levels. Importantly, the articles in this special issue demonstrate the value to society of continuing vigorous scientific research that will enable us to better understand our planet’s rapidly changing polar environments
Changing expendable bathythermograph fall rates and their impact on estimates of thermosteric sea level rise
A time-varying warm bias in the global XBT data archive is demonstrated to be largely due to changes in the fall rate of XBT probes likely associated with small manufacturing changes at the factory. Deep-reaching XBTs have a different fall rate history than shallow XBTs. Fall rates were fastest in the early 1970s, reached a minimum between 1975 and 1985, reached another maximum in the late 1980s and early 1990s, and have been declining since. Field XBT/CTD intercomparisons and a pseudoprofile technique based on satellite altimetry largely confirm this time history. A global correction is presented and applied to estimates of the thermosteric component of sea level rise. The XBT fall rate minimum from 1975 to 1985 appears as a 10-yr “warm period” in the global ocean in thermosteric sea level and heat content estimates using uncorrected data. Upon correction, the thermosteric sea level curve has reduced decadal variability and a larger, steadier long-term trend
Bathymetry of Southeast Greenland From Oceans Melting Greenland (OMG) Data
Southeast Greenland has been a major participant in the ice sheet mass loss over the last several decades. Interpreting the evolution of glacier fronts requires information about their depth below sea level and ocean thermal forcing, which are incompletely known in the region. Here, we combine airborne gravity and multibeam echo sounding data from the National Aeronautics and Space Administration's Oceans Melting Greenland (OMG) mission with ocean probe and fishing boat depth data to reconstruct the bathymetry extending from the glacier margins to the edges of the continental shelf. We perform a three‐dimensional inversion of the gravity data over water and merge the solution with a mass conservation reconstruction of bed topography over land. In contrast with other parts of Greenland, we find few deep troughs connecting the glaciers to the sources of warm Atlantic Water, amidst a relatively uniform, shallow (350 m) continental shelf. The deep channels include the Kangerlugssuaq, Sermilik, Gyldenløve, and Tingmiarmiut Troughs
Swift: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications
Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and algorithms is thus crucial. In this paper, we introduce the fully open-source highly-parallel, versatile, and modular coupled hydrodynamics, gravity, cosmology, and galaxy-formation code Swift. The software package exploits hybrid shared- and distributed-memory task-based parallelism, asynchronous communications, and domain-decomposition algorithms based on balancing the workload, rather than the data, to efficiently exploit modern high-performance computing cluster architectures. Gravity is solved for using a fast-multipole-method, optionally coupled to a particle mesh solver in Fourier space to handle periodic volumes. For gas evolution, multiple modern flavours of Smoothed Particle Hydrodynamics are implemented. Swiftalso evolves neutrinos using a state-of-the-art particle-based method. Two complementary networks of sub-grid models for galaxy formation as well as extensions to simulate planetary physics are also released as part of the code. An extensive set of output options, including snapshots, light-cones, power spectra, and a coupling to structure finders are also included. We describe the overall code architecture, summarise the consistency and accuracy tests that were performed, and demonstrate the excellent weak-scaling performance of the code using a representative cosmological hydrodynamical problem with ≈300 billion particles. The code is released to the community alongside extensive documentation for both users and developers, a large selection of example test problems, and a suite of tools to aid in the analysis of large simulations run with Swift
Swift: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications
Numerical simulations have become one of the key tools used by theorists in
all the fields of astrophysics and cosmology. The development of modern tools
that target the largest existing computing systems and exploit state-of-the-art
numerical methods and algorithms is thus crucial. In this paper, we introduce
the fully open-source highly-parallel, versatile, and modular coupled
hydrodynamics, gravity, cosmology, and galaxy-formation code Swift. The
software package exploits hybrid task-based parallelism, asynchronous
communications, and domain-decomposition algorithms based on balancing the
workload, rather than the data, to efficiently exploit modern high-performance
computing cluster architectures. Gravity is solved for using a
fast-multipole-method, optionally coupled to a particle mesh solver in Fourier
space to handle periodic volumes. For gas evolution, multiple modern flavours
of Smoothed Particle Hydrodynamics are implemented. Swift also evolves
neutrinos using a state-of-the-art particle-based method. Two complementary
networks of sub-grid models for galaxy formation as well as extensions to
simulate planetary physics are also released as part of the code. An extensive
set of output options, including snapshots, light-cones, power spectra, and a
coupling to structure finders are also included. We describe the overall code
architecture, summarize the consistency and accuracy tests that were performed,
and demonstrate the excellent weak-scaling performance of the code using a
representative cosmological hydrodynamical problem with billion
particles. The code is released to the community alongside extensive
documentation for both users and developers, a large selection of example test
problems, and a suite of tools to aid in the analysis of large simulations run
with Swift.Comment: 39 pages, 18 figures, submitted to MNRAS. Code, documentation, and
examples available at www.swiftsim.co
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