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2. Climate Impacts from Large Volcanic Eruptions in a High-resolution Climate Model: the Importance of Forcing Structure
- Author(s):
- Yang, Wenchang; Vecchi, Gabriel; Fueglistaler, Stephan; Horowitz, Larry; Luet, David; Muñoz, Ángel; Paynter, David; Underwood, Seth
- Abstract:
- Explosive volcanic eruptions have large climate impacts, and can serve as observable tests of the climatic response to radiative forcing. Using a high resolution climate model, we contrast the climate responses to Pinatubo, with symmetric forcing, and those to Santa Maria and Agung, which had meridionally asymmetric forcing. Although Pinatubo had larger global-mean forcing, asymmetric forcing strongly shifts the latitude of tropical rainfall features, leading to larger local precipitation/TC changes. For example, North Atlantic TC activity over is enhanced/reduced by SH-forcing (Agung)/NH-forcing (Santa Maria), but changes little in response to the Pinatubo forcing. Moreover, the transient climate sensitivity estimated from the response to Santa Maria is 20% larger than that from Pinatubo or Agung. This spread in climatic impacts of volcanoes needs to be considered when evaluating the role of volcanoes in global and regional climate, and serves to contextualize the well-observed response to Pinatubo.
- Type:
- Dataset
- Issue Date:
- 2019
3. Sound velocities in shock-synthesized stishovite to 72 GPa
- Author(s):
- Berryman, Eleanor J.; Winey, J. M.; Gupta, Yogendra M.; Duffy, Thomas S.
- Abstract:
- Stishovite (rutile-type SiO2) is the archetype of dense silicates and may occur in post-garnet eclogitic rocks at lower-mantle conditions. Sound velocities in stishovite are fundamental to understanding its mechanical and thermodynamic behavior at high pressure and temperature. Here, we use plate-impact experiments combined with velocity interferometry to determine the stress, density, and longitudinal sound speed in stishovite formed during shock compression of fused silica at 44 GPa and above. The measured sound speeds range from 12.3(8) km/s at 43.8(8) GPa to 9.8(4) km/s at 72.7(11) GPa. The decrease observed at 64 GPa reacts a decrease in the shear modulus of stishovite, likely due to the onset of melting. By 72 GPa, the measured sound speed agrees with the theoretical bulk sound speed indicating loss of all shear stiffness due to complete melting. Our sound velocity results provide direct evidence for shock-induced melting, in agreement with previous pyrometry data.
- Type:
- Dataset
- Issue Date:
- 2019
4. An extended MHD study of the 16 October 2015 MMS diffusion region crossing
- Abstract:
- The Magnetospheric Multiscale (MMS) mission has given us unprecedented access to high cadence particle and field data of magnetic reconnection at Earth's magnetopause. MMS first passed very near an X-line on 16 October 2015, the Burch event, and has since observed multiple X-line crossings. Subsequent 3D particle-in-cell (PIC) modeling efforts of and comparison with the Burch event have revealed a host of novel physical insights concerning magnetic reconnection, turbulence induced particle mixing, and secondary instabilities. In this study, we employ the Gkeyll simulation framework to study the Burch event with different classes of extended, multi-fluid magnetohydrodynamics (MHD), including models that incorporate important kinetic effects, such as the electron pressure tensor, with physics-based closure relations designed to capture linear Landau damping. Such fluid modeling approaches are able to capture different levels of kinetic physics in global simulations and are generally less costly than fully kinetic PIC. We focus on the additional physics one can capture with increasing levels of fluid closure refinement via comparison with MMS data and existing PIC simulations. In particular, we find that the ten-moment model well captures the agyrotropic structure of the pressure tensor in the vicinity of the X-line and the magnitude of anisotropic electron heating observed in MMS and PIC simulations. However, the ten-moment model has difficulty resolving the lower hybrid drift instability, which has been observed to plays a fundamental role in heating and mixing electrons in the current layer.
- Type:
- Dataset
5. Dust and Starlight Maps for Galaxies in the KINGFISH Sample
- Author(s):
- Aniano, G.; Draine, B.T.; Hunt, L.K.; Sandstrom, K.; Calzetti, D.; Kennicutt, R.C.; Dale, D.A.; Galametz, M.; Gordon, K.D.; Leroy, A.K.; Smith, J.-D.T.; Roussel, H.; Sauvage, M.; Walter, F.; Armus, L.; Bolatto, A.D.; Boquien, M.; Crocker, A.; De Looze, I.; Donovan Meyer, J.; Helou, G.; Hinz, J.; Johnson, B.D.; Koda, J.; Miller, A.; Montiel, E.; Murphy, E.J.; Relano, M.; Rix, H.-W.; Schinnerer, E.; Skibba, R.; Wolfire, M.G.; Engelbracht, C.W.
- Abstract:
- Dust and starlight have been modeled for the KINGFISH project galaxies. For each pixel in each galaxy, we estimate: (1) dust surface density; (2) q_PAH, the dust mass fraction in PAHs; (3) distribution of starlight intensities heating the dust; (4) luminosity emitted by the dust; and (5) dust luminosity from regions with high starlight intensity. The modeling is as described in the paper "Modeling Dust and Starlight in Galaxies Observed by Spitzer and Herschel: The KINGFISH Sample", by G. Aniano, B.T. Draine, L.K. Hunt, K. Sandstrom, D. Calzetti, R.C. Kennicutt, D.A, Dale, and 26 other authors, accepted for publication in The Astrophysical Journal.
- Type:
- Dataset and Image
6. Light Curves from a Search for Variable Stars in the Globular Cluster M4 with K2
- Abstract:
- The data are 4554 light curves derived from images taken of the globular cluster M4 by the Kepler space telescope during the K2 portion of its mission, specifically during Campaign 2 of that mission, which occurred in 2014. A total of 3856 images were taken over approximately three months at a cadence of approximately half an hour. The purpose of these observations was to find stars and other objects that vary in brightness over time --- variable stars. Also included is a table with associated information for each of the 4554 objects and their light curves.
- Type:
- collection and Dataset
