Planetary Science Institute

The all sky surveys done by the Palomar Observatory Schmidt, the European Southern Observatory Schmidt, and
\nthe United Kingdom Schmidt, the InfraRed Astronomical Satellite, and the Two Micron All Sky Survey have
\nproven to be extremely useful tools for astronomy with value that lasts for decades. The Wide-field Infrared
\nSurvey Explorer (WISE) is mapping the whole sky following its launch on 2009 December 14. WISE began
\nsurveying the sky on 2010 January 14 and completed its first full coverage of the sky on July 17. The survey
\nwill continue to cover the sky a second time until the cryogen is exhausted (anticipated in 2010 November).
\nWISE is achieving 5σ point source sensitivities better than 0.08, 0.11, 1, and 6 mJy in unconfused regions on
\nthe ecliptic in bands centered at wavelengths of 3.4, 4.6, 12, and 22μm. Sensitivity improves toward the ecliptic
\npoles due to denser coverage and lower zodiacal background. The angular resolution is 6".1, 6".4, 6".5, and 12".0 at 3.4, 4.6, 12, and 22μm, and the astrometric precision for high signal-to-noise sources is better than 0".15.
\n

A primary component of the observed recent climate change is the radiative forcing from increased concentrations of long‐lived greenhouse gases (LLGHGs). Effective simulation of anthropogenic climate change by general circulation models (GCMs) is strongly dependent on the accurate representation of radiative processes associated with water vapor, ozone, and LLGHGs. In the context of the increasing application of the Atmospheric and Environmental Research, Inc. (AER), radiation models within the GCM community, their capability to calculate longwave and shortwave radiative forcing for clear sky scenarios previously examined by the radiative transfer model intercomparison project (RTMIP) is presented. Forcing calculations with the AER line‐by‐line (LBL) models are very consistent with the RTMIP line‐by‐line results in the longwave and shortwave. The AER broadband models, in all but one case, calculate longwave forcings within a range of −0.20 to 0.23 W m −2 of LBL calculations and shortwave forcings within a range of −0.16 to 0.38 W m −2 of LBL results. These models also perform well at the surface, which RTMIP identified as a level at which GCM radiation models have particular difficulty reproducing LBL fluxes. Heating profile perturbations calculated by the broadband models generally reproduce high‐resolution calculations within a few hundredths K d −1 in the troposphere and within 0.15 K d −1 in the peak stratospheric heating near 1 hPa. In most cases, the AER broadband models provide radiative forcing results that are in closer agreement with high‐resolution calculations than the GCM radiation codes examined by RTMIP, which supports the application of the AER models to climate change research.

A review of the geologic history of the Himalayan-Tibetan orogen suggests that at least 1400 km of north-south shortening has been absorbed by the orogen since the onset of the Indo-Asian collision at about 70 Ma. Significant crustal shortening, which leads to eventual construction of the Cenozoic Tibetan plateau, began more or less synchronously in the Eocene (50–40 Ma) in the Tethyan Himalaya in the south, and in the Kunlun Shan and the Qilian Shan some 1000–1400 km in the north. The Paleozoic and Mesozoic tectonic histories in the Himalayan-Tibetan orogen exerted a strong control over the Cenozoic strain history and strain distribution. The presence of widespread Triassic flysch complex in the Songpan-Ganzi-Hoh Xil and the Qiangtang terranes can be spatially correlated with Cenozoic volcanism and thrusting in central Tibet. The marked difference in seismic properties of the crust and the upper mantle between southern and central Tibet is a manifestation of both Mesozoic and Cenozoic tectonics. The former, however, has played a decisive role in localizing Tertiary contractional deformation, which in turn leads to the release of free water into the upper mantle and the lower crust of central Tibet, causing partial melting in the mantle lithosphere and the crust.

Solar photospheric and meteoritic CI chondrite abundance determinations for all elements are summarized and the best currently available photospheric abundances are selected. The meteoritic and solar abundances of a few elements (e.g., noble gases, beryllium, boron, phosphorous, sulfur) are discussed in detail. The photospheric abundances give mass fractions of hydrogen (X 0:7491), helium (Y 0:2377), and heavy elements (Z 0:0133), leading to Z=X 0:0177, which is lower than the widely used Z=X 0:0245 from previous compilations. Recent results from standard solar models considering helium and heavy-element settling imply that photospheric abundances and mass fractions are not equal to proto-solar abundances (representative of solar system abundances). Protosolar elemental and isotopic abundances are derived from photospheric abundances by considering settling effects. Derived protosolar mass fractions are X0 0:7110, Y0 0:2741, and Z0 0:0149. The solar system and photospheric abundance tables are used to compute self-consistent sets of condensation temperatures for all elements. Subject headings: astrochemistry — meteors, meteoroids — solar system: formation — Sun: abundances — Sun: photosphere 1.

Research Article| May 01, 1989 Tectonic discrimination of granitoids PAPU D. MANIAR; PAPU D. MANIAR 1Department of Geology and Planetary Science, University of Pittsburgh, Pittsburgh, Pennsylvania 15260 Search for other works by this author on: GSW Google Scholar PHILIP M. PICCOLI PHILIP M. PICCOLI 1Department of Geology and Planetary Science, University of Pittsburgh, Pittsburgh, Pennsylvania 15260 Search for other works by this author on: GSW Google Scholar Author and Article Information PAPU D. MANIAR 1Department of Geology and Planetary Science, University of Pittsburgh, Pittsburgh, Pennsylvania 15260 PHILIP M. PICCOLI 1Department of Geology and Planetary Science, University of Pittsburgh, Pittsburgh, Pennsylvania 15260 Publisher: Geological Society of America First Online: 01 Jun 2017 Online ISSN: 1943-2674 Print ISSN: 0016-7606 Geological Society of America GSA Bulletin (1989) 101 (5): 635–643. https://doi.org/10.1130/0016-7606(1989)101<0635:TDOG>2.3.CO;2 Article history First Online: 01 Jun 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn Email Permissions Search Site Citation PAPU D. MANIAR, PHILIP M. PICCOLI; Tectonic discrimination of granitoids. GSA Bulletin 1989;; 101 (5): 635–643. doi: https://doi.org/10.1130/0016-7606(1989)101<0635:TDOG>2.3.CO;2 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyGSA Bulletin Search Advanced Search Abstract Granitoids as categorized by tectonic environment are (1) island arc granitoids (IAG), (2) continental arc granitoids (CAG), (3) continental collision granitoids (CCG), (4) postorogenic granitoids (POG), (5) rift-related granitoids (RRG), (6) continental epeirogenic uplift granitoids (CEUG), and (7) oceanic plagiogranites (OP). Of these, the IAG, CAG, CCG, and POG are considered orogenic granitoids, and the RRG, CEUG, and OP are considered anorogenic granitoids.The discrimination of granitoids is based on the major-element chemistry. Various discrimination plots are presented which sequentially discriminate the different tectonic environments. OP are separated from all other granitoids on the K2O versus SiO2 plot. Discrimination between group I (IAG + CAG + CCG), group II (RRG + CEUG), and group III (POG) granitoids can be achieved by using plots of Al2O3 versus SiO2, FeO(T)/ [FeO(T) + MgO] versus SiO2, and AFM and ACF ternary diagrams. In the figures, group I and group II plot in individual fields. Identification of group III is different, in that group III does not have a unique field in which it plots. Group III is identified because it consistently displays characteristics of both group I and group II. Further discrimination within group I can be accomplished on the basis of Shand's index. Only CCG have A/CNK [AL2O3/(CaO + Na2O + K2O)] values greater than 1.15. It is not possible to discriminate between IAG and CAG. Further discrimination within group II is done using the TiO2 versus SiO2 plot.The proposed discrimination scheme is applied to the Proterozoic granitoids of the midcontinent of the United States. It is shown that the Arbuckle granitoids are not anorogenic as previously thought. This content is PDF only. Please click on the PDF icon to access. First Page Preview Close Modal You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

The focus of this paper is the conversion of radiocarbon ages to calibrated (cal) ages for the interval 24,000–0 cal BP (Before Present, 0 cal BP = AD 1950), based upon a sample set of dendrochronologically dated tree rings, uranium-thorium dated corals, and varve-counted marine sediment. The 14 C age–cal age information, produced by many laboratories, is converted to Δ 14 C profiles and calibration curves, for the atmosphere as well as the oceans. We discuss offsets in measured l4 C ages and the errors therein, regional 14 C age differences, tree–coral 14 C age comparisons and the time dependence of marine reservoir ages, and evaluate decadal vs . single-year 14 C results. Changes in oceanic deepwater circulation, especially for the 16,000–11,000 cal BP interval, are reflected in the Δ 14 C values of INTCAL98.

Full list of authors: Price-Whelan, Adrian M.; Lim, Pey Lian; Earl, Nicholas; Starkman, Nathaniel; Bradley, Larry; Shupe, David L.; Patil, Aarya A.; Corrales, Lia; Brasseur, C. E.; Noethe, Maximilian; Donath, Axel; Tollerud, Erik; Morris, Brett M.; Ginsburg, Adam; Vaher, Eero; Weaver, Benjamin A.; Tocknell, James; Jamieson, William; van Kerkwijk, Marten H.; Robitaille, Thomas P.; Merry, Bruce; Bachetti, Matteo; Gunther, H. Moritz; Aldcroft, Thomas L.; Alvarado-Montes, Jaime A.; Archibald, Anne M.; Bodi, Attila; Bapat, Shreyas; Barentsen, Geert; Bazan, Juanjo; Biswas, Manish; Boquien, Mederic; Burke, D. J.; Cara, Daria; Cara, Mihai; Conroy, Kyle E.; Conseil, Simon; Craig, Matthew W.; Cross, Robert M.; Cruz, Kelle L.; D'Eugenio, Francesco; Dencheva, Nadia; Devillepoix, Hadrien A. R.; Dietrich, Jorg P.; Eigenbrot, Arthur Davis; Erben, Thomas; Ferreira, Leonardo; Foreman-Mackey, Daniel; Fox, Ryan; Freij, Nabil; Garg, Suyog; Geda, Robel; Glattly, Lauren; Gondhalekar, Yash; Gordon, Karl D.; Grant, David; Greenfield, Perry; Groener, Austen M.; Guest, Steve; Gurovich, Sebastian; Handberg, Rasmus; Hart, Akeem; Hatfield-Dodds, Zac; Homeier, Derek; Hosseinzadeh, Griffin; Jenness, Tim; Jones, Craig K.; Joseph, Prajwel; Kalmbach, J. Bryce; Karamehmetoglu, Emir; Kaluszynski, Mikolaj; Kelley, Michael S. P.; Kern, Nicholas; Kerzendorf, Wolfgang E.; Koch, Eric W.; Kulumani, Shankar; Lee, Antony; Ly, Chun; Ma, Zhiyuan; MacBride, Conor; Maljaars, Jakob M.; Muna, Demitri; Murphy, N. A.; Norman, Henrik; O'Steen, Richard; Oman, Kyle A.; Pacifici, Camilla; Pascual, Sergio; Pascual-Granado, J.; Patil, Rohit R.; Perren, Gabriel, I; Pickering, Timothy E.; Rastogi, Tanuj; Roulston, Benjamin R.; Ryan, Daniel F.; Rykoff, Eli S.; Sabater, Jose; Sakurikar, Parikshit; Salgado, Jesus; Sanghi, Aniket; Saunders, Nicholas; Savchenko, Volodymyr; Schwardt, Ludwig; Seifert-Eckert, Michael; Shih, Albert Y.; Jain, Anany Shrey; Shukla, Gyanendra; Sick, Jonathan; Simpson, Chris; Singanamalla, Sudheesh; Singer, Leo P.; Singhal, Jaladh; Sinha, Manodeep; Sipocz, Brigitta M.; Spitler, Lee R.; Stansby, David; Streicher, Ole; Sumak, Jani; Swinbank, John D.; Taranu, Dan S.; Tewary, Nikita; Tremblay, Grant R.; De Val-Borro, Miguel; Vasovic, Zlatan; Van Kooten, Samuel J.; Verma, Shresth; Cardoso, Jose Vinicius de Miranda; Williams, Peter K. G.; Wilson, Tom J.; Winkel, Benjamin; Wood-Vasey, W. M.; Xue, Rui; Yoachim, Peter; Zhang, Chen; Zonca, Andrea; Astropy Project Contributors; TARDIS Collaboration; Astropy Coordination Comm.--This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

The Kepler mission was designed to determine the frequency of Earth-sized planets in and near the habitable zone of Sun-like stars. The habitable zone is the region where planetary temperatures are suitable for water to exist on a planet's surface. During the first 6 weeks of observations, Kepler monitored 156,000 stars, and five new exoplanets with sizes between 0.37 and 1.6 Jupiter radii and orbital periods from 3.2 to 4.9 days were discovered. The density of the Neptune-sized Kepler-4b is similar to that of Neptune and GJ 436b, even though the irradiation level is 800,000 times higher. Kepler-7b is one of the lowest-density planets (approximately 0.17 gram per cubic centimeter) yet detected. Kepler-5b, -6b, and -8b confirm the existence of planets with densities lower than those predicted for gas giant planets.

We used 5704 14C, 10Be, and 3He ages that span the interval from 10,000 to 50,000 years ago (10 to 50 ka) to constrain the timing of the Last Glacial Maximum (LGM) in terms of global ice-sheet and mountain-glacier extent. Growth of the ice sheets to their maximum positions occurred between 33.0 and 26.5 ka in response to climate forcing from decreases in northern summer insolation, tropical Pacific sea surface temperatures, and atmospheric CO2. Nearly all ice sheets were at their LGM positions from 26.5 ka to 19 to 20 ka, corresponding to minima in these forcings. The onset of Northern Hemisphere deglaciation 19 to 20 ka was induced by an increase in northern summer insolation, providing the source for an abrupt rise in sea level. The onset of deglaciation of the West Antarctic Ice Sheet occurred between 14 and 15 ka, consistent with evidence that this was the primary source for an abrupt rise in sea level approximately 14.5 ka.

Recent revisions to the geomagnetic time scale indicate that global plate motion model NUVEL‐1 should be modified for comparison with other rates of motion including those estimated from space geodetic measurements. The optimal recalibration, which is a compromise among slightly different calibrations appropriate for slow, medium, and fast rates of seafloor spreading, is to multiply NUVEL‐1 angular velocities by a constant, α, of 0.9562. We refer to this simply recalibrated plate motion model as NUVEL‐1A, and give correspondingly revised tables of angular velocities and uncertainties. Published work indicates that space geodetic rates are slower on average than those calculated from NUVEL‐1 by 6±1%. This average discrepancy is reduced to less than 2% when space geodetic rates are instead compared with NUVEL‐1A.

The number of microbial genomes sequenced each year is expanding rapidly, in part due to genome-resolved metagenomic studies that routinely recover hundreds of draft-quality genomes. Rapid algorithms have been developed to comprehensively compare large genome sets, but they are not accurate with draft-quality genomes. Here we present dRep, a program that reduces the computational time for pairwise genome comparisons by sequentially applying a fast, inaccurate estimation of genome distance, and a slow, accurate measure of average nucleotide identity. dRep achieves a 28 × increase in speed with perfect recall and precision when benchmarked against previously developed algorithms. We demonstrate the use of dRep for genome recovery from time-series datasets. Each metagenome was assembled separately, and dRep was used to identify groups of essentially identical genomes and select the best genome from each replicate set. This resulted in recovery of significantly more and higher-quality genomes compared to the set recovered using co-assembly.

We present a first description and evaluation of GEOS‐CHEM, a global threedimensional (3‐D) model of tropospheric chemistry driven by assimilated meteorological observations from the Goddard Earth Observing System (GEOS) of the NASA Data Assimilation Office (DAO). The model is applied to a 1‐year simulation of tropospheric ozone‐NO x ‐hydrocarbon chemistry for 1994, and is evaluated with observations both for 1994 and for other years. It reproduces usually to within 10 ppb the concentrations of ozone observed from the worldwide ozonesonde data network. It simulates correctly the seasonal phases and amplitudes of ozone concentrations for different regions and altitudes, but tends to underestimate the seasonal amplitude at northern midlatitudes. Observed concentrations of NO and peroxyacetylnitrate (PAN) observed in aircraft campaigns are generally reproduced to within a factor of 2 and often much better. Concentrations of HNO 3 in the remote troposphere are overestimated typically by a factor of 2–3, a common problem in global models that may reflect a combination of insufficient precipitation scavenging and gas‐aerosol partitioning not resolved by the model. The model yields an atmospheric lifetime of methylchloroform (proxy for global OH) of 5.1 years, as compared to a best estimate from observations of 5.5 +/− 0.8 years, and simulates H 2 O 2 concentrations observed from aircraft with significant regional disagreements but no global bias. The OH concentrations are ∼20% higher than in our previous global 3‐D model which included an UV‐absorbing aerosol. Concentrations of CO tend to be underestimated by the model, often by 10–30 ppb, which could reflect a combination of excessive OH (a 20% decrease in model OH could be accommodated by the methylchloroform constraint) and an underestimate of CO sources (particularly biogenic). The model underestimates observed acetone concentrations over the South Pacific in fall by a factor of 3; a missing source from the ocean may be implicated.

We present two standards developed by the Genomic Standards Consortium (GSC) for reporting bacterial and archaeal genome sequences. Both are extensions of the Minimum Information about Any (x) Sequence (MIxS). The standards are the Minimum Information about a Single Amplified Genome (MISAG) and the Minimum Information about a Metagenome-Assembled Genome (MIMAG), including, but not limited to, assembly quality, and estimates of genome completeness and contamination. These standards can be used in combination with other GSC checklists, including the Minimum Information about a Genome Sequence (MIGS), Minimum Information about a Metagenomic Sequence (MIMS), and Minimum Information about a Marker Gene Sequence (MIMARKS). Community-wide adoption of MISAG and MIMAG will facilitate more robust comparative genomic analyses of bacterial and archaeal diversity.

Atmospheric reactions and slow geological processes controlled Earth's earliest nitrogen cycle, and by ~2.7 billion years ago, a linked suite of microbial processes evolved to form the modern nitrogen cycle with robust natural feedbacks and controls. Over the past century, however, the development of new agricultural practices to satisfy a growing global demand for food has drastically disrupted the nitrogen cycle. This has led to extensive eutrophication of fresh waters and coastal zones as well as increased inventories of the potent greenhouse gas nitrous oxide (N(2)O). Microbial processes will ultimately restore balance to the nitrogen cycle, but the damage done by humans to the nitrogen economy of the planet will persist for decades, possibly centuries, if active intervention and careful management strategies are not initiated.

Negative carbon isotope anomalies in carbonate rocks bracketing Neoproterozoic glacial deposits in Namibia, combined with estimates of thermal subsidence history, suggest that biological productivity in the surface ocean collapsed for millions of years. This collapse can be explained by a global glaciation (that is, a snowball Earth), which ended abruptly when subaerial volcanic outgassing raised atmospheric carbon dioxide to about 350 times the modern level. The rapid termination would have resulted in a warming of the snowball Earth to extreme greenhouse conditions. The transfer of atmospheric carbon dioxide to the ocean would result in the rapid precipitation of calcium carbonate in warm surface waters, producing the cap carbonate rocks observed globally.

Mercury (Hg) is a global pollutant that affects human and ecosystem health. We synthesize understanding of sources, atmosphere-land-ocean Hg dynamics and health effects, and consider the implications of Hg-control policies. Primary anthropogenic Hg emissions greatly exceed natural geogenic sources, resulting in increases in Hg reservoirs and subsequent secondary Hg emissions that facilitate its global distribution. The ultimate fate of emitted Hg is primarily recalcitrant soil pools and deep ocean waters and sediments. Transfers of Hg emissions to largely unavailable reservoirs occur over the time scale of centuries, and are primarily mediated through atmospheric exchanges of wet/dry deposition and evasion from vegetation, soil organic matter and ocean surfaces. A key link between inorganic Hg inputs and exposure of humans and wildlife is the net production of methylmercury, which occurs mainly in reducing zones in freshwater, terrestrial, and coastal environments, and the subsurface ocean. Elevated human exposure to methylmercury primarily results from consumption of estuarine and marine fish. Developing fetuses are most at risk from this neurotoxin but health effects of highly exposed populations and wildlife are also a concern. Integration of Hg science with national and international policy efforts is needed to target efforts and evaluate efficacy.

Motivated by the rapid increase in atmospheric CO2 due to human activities since the Industrial Revolution, several international scientific research programs have analyzed the role of individual components of the Earth system in the global carbon cycle. Our knowledge of the carbon cycle within the oceans, terrestrial ecosystems, and the atmosphere is sufficiently extensive to permit us to conclude that although natural processes can potentially slow the rate of increase in atmospheric CO2, there is no natural "savior" waiting to assimilate all the anthropogenically produced CO2 in the coming century. Our knowledge is insufficient to describe the interactions between the components of the Earth system and the relationship between the carbon cycle and other biogeochemical and climatological processes. Overcoming this limitation requires a systems approach.

The tree of life is one of the most important organizing principles in biology(1). Gene surveys suggest the existence of an enormous number of branches(2), but even an approximation of the full scale of the tree has remained elusive. Recent depictions of the tree of life have focused either on the nature of deep evolutionary relationships(3-5) or on the known, well-classified diversity of life with an emphasis on eukaryotes(6). These approaches overlook the dramatic change in our understanding of life's diversity resulting from genomic sampling of previously unexamined environments. New methods to generate genome sequences illuminate the identity of organisms and their metabolic capacities, placing them in community and ecosystem contexts(7,8). Here, we use new genomic data from over 1,000 uncultivated and little known organisms, together with published sequences, to infer a dramatically expanded version of the tree of life, with Bacteria, Archaea and Eukarya included. The depiction is both a global overview and a snapshot of the diversity within each major lineage. The results reveal the dominance of bacterial diversification and underline the importance of organisms lacking isolated representatives, with substantial evolution concentrated in a major radiation of such organisms. This tree highlights major lineages currently underrepresented in biogeochemical models and identifies radiations that are probably important for future evolutionary analyses.

Field and laboratory observations show that crystals commonly form by the addition and attachment of particles that range from multi-ion complexes to fully formed nanoparticles. The particles involved in these nonclassical pathways to crystallization are diverse, in contrast to classical models that consider only the addition of monomeric chemical species. We review progress toward understanding crystal growth by particle-attachment processes and show that multiple pathways result from the interplay of free-energy landscapes and reaction dynamics. Much remains unknown about the fundamental aspects, particularly the relationships between solution structure, interfacial forces, and particle motion. Developing a predictive description that connects molecular details to ensemble behavior will require revisiting long-standing interpretations of crystal formation in synthetic systems, biominerals, and patterns of mineralization in natural environments.

Surface temperature reconstructions of the past 1500 years suggest that recent warming is unprecedented in that time. Here we provide a broader perspective by reconstructing regional and global temperature anomalies for the past 11,300 years from 73 globally distributed records. Early Holocene (10,000 to 5000 years ago) warmth is followed by ~0.7°C cooling through the middle to late Holocene (<5000 years ago), culminating in the coolest temperatures of the Holocene during the Little Ice Age, about 200 years ago. This cooling is largely associated with ~2°C change in the North Atlantic. Current global temperatures of the past decade have not yet exceeded peak interglacial values but are warmer than during ~75% of the Holocene temperature history. Intergovernmental Panel on Climate Change model projections for 2100 exceed the full distribution of Holocene temperature under all plausible greenhouse gas emission scenarios.