Evaluating model simulations of twentieth-century sea-level rise. Part II: regional sea-level changes

Twentieth-century regional sea level changes are estimated from 12 climate models from phase 5 of the Climate Model Intercomparison Project (CMIP5). The output of the CMIP5 climate model simulations was used to calculate the global and regional sea level changes associated with dynamic sea level, atmospheric loading, glacier mass changes, and ice sheet surface mass balance contributions. The contribution from groundwater depletion, reservoir storage, and dynamic ice sheet mass changes are estimated from observations as they are not simulated by climate models. All contributions are summed, including the glacial isostatic adjustment (GIA) contribution, and compared to observational estimates from 27 tide gauge records over the twentieth century (1900–2015). A general agreement is found between the simulated sea level and tide gauge records in terms of interannual to multidecadal variability over 1900–2015. But climate models tend to systematically underestimate the observed sea level trends, particularly in the first half of the twentieth century. The corrections based on attributable biases between observations and models that have been identified in Part I of this two-part paper result in an improved explanation of the spatial variability in observed sea level trends by climate models. Climate models show that the spatial variability in sea level trends observed by tide gauge records is dominated by the GIA contribution and the steric contribution over 1900–2015. Climate models also show that it is important to include all contributions to sea level changes as they cause significant local deviations; note, for example, the groundwater depletion around India, which is responsible for the low twentieth-century sea level rise in the region

Intestinal fungi contribute to development of alcoholic liver disease

This study was supported in part by NIH grants R01 AA020703, U01 AA021856 and by Award Number I01BX002213 from the Biomedical Laboratory Research & Development Service of the VA Office of Research and Development (to B.S.). K.H. was supported by a DFG (Deutsche Forschungsgemeinschaft) fellowship (HO/ 5690/1-1). S.B. was supported by a grant from the Swiss National Science Foundation (P2SKP3_158649). G.G. received funding from the Yale Liver Center NIH P30 DK34989 and R.B. from NIAAA grant U01 AA021908. A.K. received support from NIH grants RC2 AA019405, R01 AA020216 and R01 AA023417. G.D.B. is supported by funds from the Wellcome Trust. We acknowledge the Human Tissue and Cell Research (HTCR) Foundation for making human tissue available for research and Hepacult GmbH (Munich, Germany) for providing primary human hepatocytes for in vitro analyses. We thank Dr. Chien-Yu Lin Department of Medicine, Fu-Jen Catholic University, Taiwan for statistical analysis.Peer reviewedPublisher PD

The Vaginal Microbiome: Disease, Genetics and the Environment

The vagina is an interactive interface between the host and the environment. Its surface is covered by a protective epithelium colonized by bacteria and other microorganisms. The ectocervix is nonsterile, whereas the endocervix and the upper genital tract are assumed to be sterile in healthy women. Therefore, the cervix serves a pivotal role as a gatekeeper to protect the upper genital tract from microbial invasion and subsequent reproductive pathology. Microorganisms that cross this barrier can cause preterm labor, pelvic inflammatory disease, and other gynecologic and reproductive disorders. Homeostasis of the microbiome in the vagina and ectocervix plays a paramount role in reproductive health. Depending on its composition, the microbiome may protect the vagina from infectious or non-infectious diseases, or it may enhance its susceptibility to them. Because of the nature of this organ, and the fact that it is continuously colonized by bacteria from birth to death, it is virtually certain that this rich environment evolved in concert with its microbial flora. Specific interactions dictated by the genetics of both the host and microbes are likely responsible for maintaining both the environment and the microbiome. However, the genetic basis of these interactions in both the host and the bacterial colonizers is currently unknown. _Lactobacillus_ species are associated with vaginal health, but the role of these species in the maintenance of health is not yet well defined. Similarly, other species, including those representing minor components of the overall flora, undoubtedly influence the ability of potential pathogens to thrive and cause disease. Gross alterations in the vaginal microbiome are frequently observed in women with bacterial vaginosis, but the exact etiology of this disorder is still unknown. There are also implications for vaginal flora in non-infectious conditions such as pregnancy, pre-term labor and birth, and possibly fertility and other aspects of women’s health. Conversely, the role of environmental factors in the maintenance of a healthy vaginal microbiome is largely unknown. To explore these issues, we have proposed to address the following questions:

*1.	Do the genes of the host contribute to the composition of the vaginal microbiome?* We hypothesize that genes of both host and bacteria have important impacts on the vaginal microbiome. We are addressing this question by examining the vaginal microbiomes of mono- and dizygotic twin pairs selected from the over 170,000 twin pairs in the Mid-Atlantic Twin Registry (MATR). Subsequent studies, beyond the scope of the current project, may investigate which host genes impact the microbial flora and how they do so.
*2.	What changes in the microbiome are associated with common non-infectious pathological states of the host?* We hypothesize that altered physiological (e.g., pregnancy) and pathologic (e.g., immune suppression) conditions, or environmental exposures (e.g., antibiotics) predictably alter the vaginal microbiome. Conversely, certain vaginal microbiome characteristics are thought to contribute to a woman’s risk for outcomes such as preterm delivery. We are addressing this question by recruiting study participants from the ~40,000 annual clinical visits to women’s clinics of the VCU Health System.
*3.	What changes in the vaginal microbiome are associated with relevant infectious diseases and conditions?* We hypothesize that susceptibility to infectious disease (e.g. HPV, _Chlamydia_ infection, vaginitis, vaginosis, etc.) is impacted by the vaginal microbiome. In turn, these infectious conditions clearly can affect the ability of other bacteria to colonize and cause pathology. Again, we are exploring these issues by recruiting participants from visitors to women’s clinics in the VCU Health System.

Three kinds of sequence data are generated in this project: i) rDNA sequences from vaginal microbes; ii) whole metagenome shotgun sequences from vaginal samples; and iii) whole genome shotgun sequences of bacterial clones selected from vaginal samples. The study includes samples from three vaginal sites: mid-vaginal, cervical, and introital. The data sets also include buccal and perianal samples from all twin participants. Samples from these additional sites are used to test the hypothesis of a per continuum spread of bacteria in relation to vaginal health. An extended set of clinical metadata associated with these sequences are deposited with dbGAP. We have currently collected over 4,400 samples from ~100 twins and over 450 clinical participants. We have analyzed and deposited data for 480 rDNA samples, eight whole metagenome shotgun samples, and over 50 complete bacterial genomes. These data are available to accredited investigators according to NIH and Human Microbiome Project (HMP) guidelines. The bacterial clones are deposited in the Biodefense and Emerging Infections Research Resources Repository ("http://www.beiresources.org/":http://www.beiresources.org/). 

In addition to the extensive sequence data obtained in this study, we are collecting metadata associated with each of the study participants. Thus, participants are asked to complete an extensive health history questionnaire at the time samples are collected. Selected clinical data associated with the visit are also obtained, and relevant information is collected from the medical records when available. This data is maintained securely in a HIPAA-compliant data system as required by VCU’s Institutional Review Board (IRB). The preponderance of these data (i.e., that judged appropriate by NIH staff and VCU’s IRB are deposited at dbGAP ("http://www.ncbi.nlm.nih.gov/gap":http://www.ncbi.nlm.nih.gov/gap). Selected fields of this data have been identified by NIH staff as ‘too sensitive’ and are not available in dbGAP. Individuals requiring access to these data fields are asked to contact the PI of this project or NIH Program Staff. 
&#xa

A High-End Estimate of Sea Level Rise for Practitioners

Sea level rise (SLR) is a long-lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process-based models. However, risk-averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high-end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high-end scenarios. High-end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1-2.6) relative to pre-industrial values our high-end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5-8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long-term benefits of mitigation. However, even a modest 2°C warming may cause multi-meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high-end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high-end SLR

Application of a two-step approach for mapping ice thickness to various glacier types on Svalbard

The basal topography is largely unknown beneath most glaciers and ice caps, and many attempts have been made to estimate a thickness field from other more accessible information at the surface. Here, we present a two-step reconstruction approach for ice thickness that solves mass conservation over single or several connected drainage basins. The approach is applied to a variety of test geometries with abundant thickness measurements including marine- and land-terminating glaciers as well as a 2400-km2 ice cap on Svalbard. The input requirements are kept to a minimum for the first step. In this step, a geometrically controlled, non-local flux solution is converted into thickness values relying on the shallow ice approximation (SIA). In a second step, the thickness field is updated along fast-flowing glacier trunks on the basis of velocity observations. Both steps account for available thickness measurements. Each thickness field is presented together with an error-estimate map based on a formal propagation of input uncertainties. These error estimates point out that the thickness field is least constrained near ice divides or in other stagnant areas. Withholding a share of the thickness measurements, error estimates tend to overestimate mismatch values in a median sense. We also have to accept an aggregate uncertainty of at least 25-% in the reconstructed thickness field for glaciers with very sparse or no observations. For Vestfonna ice cap (VIC), a previous ice volume estimate based on the same measurement record as used here has to be corrected upward by 22-%. We also find that a 13-% area fraction of the ice cap is in fact grounded below sea level. The former 5-% estimate from a direct measurement interpolation exceeds an aggregate maximum range of 6-23-% as inferred from the error estimates here.This study received primary funding from the German Research Foundation (DFG) under grant number FU1032/1-1. Results presented in this publication are based on numerical simulations conducted at the high-performance computing centre of the Regionales Rechenzentrum Erlangen (RRZE) of the University of Erlangen-Nuremberg. The reconstruction approach also benefits from co-development work of the Elmer/Ice team at the CSC-IT Center for Science Ltd. (Finland). The velocity analysis on Svalbard was funded by DFG within the priority programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas under contract number BR2105/9-1 and received financial support from the Helmholtz Association of the German Research Centres (HGF) Alliance on Remote Sensing and Earth System Dynamics. Thickness data collection in Wedel Jarlsberg Land was funded by the Spanish R&D projects C11093001 and C150954001, NCBiR/PolarCLIMATE-2009/2-2/2010 from the Polish National Centre for R&D, by IPY/269/2006 from the Polish Ministry of Science and Higher Education, by Polish-Norwegian funding through the AWAKE (PNRF-22-AI-1/07) project, by the EU FP7 ice2sea programme (grant number 226375) and by funds of the Leading National Research Centre (KNOW) received by the Centre for Polar Studies of the University of Silesia, Poland. The DEM generation inWedel Jarlsberg Land received financial support from the European Research Council (grant 320816) and from ESA (project Glaciers CCI, 4000109873/14/I-NB). TanDEM-X data were provided under AO XTIGLAC6770. The WRF-SMB field was produced within the PERMANOR project funded by the Norwegian Research Council (255331)

Greenland ice sheet surface mass loss: recent developments in observation and modeling

Surface processes currently dominate Greenland ice sheet (GrIS) mass loss. We review recent developments in the observation and modelling of GrIS surface mass balance (SMB), published after the July 2012 deadline for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Since IPCC AR5 our understanding of GrIS SMB has further improved, but new observational and model studies have also revealed that temporal and spatial variability of many processes are still poorly quantified and understood, e.g. bio-albedo, the formation of ice lenses and their impact on lateral meltwater transport, heterogeneous vertical meltwater transport (‘piping’), the impact of atmospheric circulation changes and mixed-phase clouds on the surface energy balance and the magnitude of turbulent heat exchange over rough ice surfaces. As a result, these processes are only schematically or not at all included in models that are currently used to assess and predict future GrIS surface mass loss

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes