Underestimating Internal Variability Leads to Narrow Estimates of Climate System Properties

Probabilistic estimates of climate system properties often rely on the comparison of model simulations to observed temperature records and an estimate of the internal climate variability. In this study, we investigate the sensitivity of probability distributions for climate system properties in the Massachusetts Institute of Technology Earth System Model to the internal variability estimate. In particular, we derive probability distributions using the internal variability extracted from 25 different Coupled Model Intercomparison Project Phase 5 models. We further test the sensitivity by pooling variability estimates from models with similar characteristics. We find the distributions to be highly sensitive when estimating the internal variability from a single model. When merging the variability estimates across multiple models, the distributions tend to converge to a wider distribution for all properties. This suggests that using a single model to approximate the internal climate variability produces distributions that are too narrow and do not fully represent the uncertainty in the climate system property estimates

A framework for modeling uncertainty in regional climate change

In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States (US) associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework are the emissions projections, global climate system parameters, natural variability and model structural uncertainty. The modeling framework revolves around the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model with an Earth System Model of Intermediate Complexity (EMIC) (with a two-dimensional zonal-mean atmosphere). Regional climate change over the US is obtained through a two-pronged approach. First, we use the IGSM-CAM framework, which links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Second, we use a pattern-scaling method that extends the IGSM zonal mean based on climate change patterns from various climate models. Results show that the range of annual mean temperature changes are mainly driven by policy choices and the range of climate sensitivity considered. Meanwhile, the four sources of uncertainty contribute more equally to end-of-century precipitation changes, with natural variability dominating until 2050. For the set of scenarios used in this study, the choice of policy is the largest driver of uncertainty, defined as the range of warming and changes in precipitation, in future projections of climate change over the US

Oscillatory surface rheotaxis of swimming E. coli bacteria

Bacterial contamination of biological conducts, catheters or water resources is a major threat to public health and can be amplified by the ability of bacteria to swim upstream. The mechanisms of this rheotaxis, the reorientation with respect to flow gradients, often in complex and confined environments, are still poorly understood. Here, we follow individual E. coli bacteria swimming at surfaces under shear flow with two complementary experimental assays, based on 3D Lagrangian tracking and fluorescent flagellar labelling and we develop a theoretical model for their rheotactic motion. Three transitions are identified with increasing shear rate: Above a first critical shear rate, bacteria shift to swimming upstream. After a second threshold, we report the discovery of an oscillatory rheotaxis. Beyond a third transition, we further observe coexistence of rheotaxis along the positive and negative vorticity directions. A full theoretical analysis explains these regimes and predicts the corresponding critical shear rates. The predicted transitions as well as the oscillation dynamics are in good agreement with experimental observations. Our results shed new light on bacterial transport and reveal new strategies for contamination prevention.Comment: 12 pages, 5 figure

The Spin Structure of the Nucleon

We present an overview of recent experimental and theoretical advances in our understanding of the spin structure of protons and neutrons.Comment: 84 pages, 29 figure

Alignment of the ALICE Inner Tracking System with cosmic-ray tracks

37 pages, 15 figures, revised version, accepted by JINSTALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 micron in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10^5 charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.Peer reviewe

Genotyping of Capreolus pygargus Fossil DNA from Denisova Cave Reveals Phylogenetic Relationships between Ancient and Modern Populations

BACKGROUND: The extant roe deer (Capreolus Gray, 1821) includes two species: the European roe deer (C. capreolus) and the Siberian roe deer (C. pygargus) that are distinguished by morphological and karyotypical differences. The Siberian roe deer occupies a vast area of Asia and is considerably less studied than the European roe deer. Modern systematics of the Siberian roe deer remain controversial with 4 morphological subspecies. Roe deer fossilized bones are quite abundant in Denisova cave (Altai Mountains, South Siberia), where dozens of both extant and extinct mammalian species from modern Holocene to Middle Pleistocene have been retrieved. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed a 629 bp fragment of the mitochondrial control region from ancient bones of 10 Holocene and four Pleistocene Siberian roe deer from Denisova cave as well as 37 modern specimen belonging to populations from Altai, Tian Shan (Kyrgyzstan), Yakutia, Novosibirsk region and the Russian Far East. Genealogical reconstructions indicated that most Holocene haplotypes were probably ancestral for modern roe deer populations of Western Siberia and Tian Shan. One of the Pleistocene haplotypes was possibly ancestral for modern Yakutian populations, and two extinct Pleistocene haplotypes were close to modern roe deer from Tian Shan and Yakutia. Most modern geographical populations (except for West Siberian Plains) are heterogeneous and there is some tentative evidence for structure. However, we did not find any distinct phylogenetic signal characterizing particular subspecies in either modern or ancient samples. CONCLUSION/SIGNIFICANCE: Analysis of mitochondrial DNA from both ancient and modern samples of Siberian roe deer shed new light on understanding the evolutionary history of roe deer. Our data indicate that during the last 50,000 years multiple replacements of populations of the Siberian roe deer took place in the Altai Mountains correlating with climatic changes. The Siberian roe deer represent a complex and heterogeneous species with high migration rates and without evident subspecies structure. Low genetic diversity of the West Siberian Plain population indicates a recent bottleneck or founder effect

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the 21st century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include: warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land-use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia's role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large scale water withdrawals, land use and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that Integrated Assessment Models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

Whole-Community Facilitation Regulates Biodiversity on Patagonian Rocky Shores

Understanding the factors that generate and maintain biodiversity is a central goal in ecology. While positive species interactions (i.e., facilitation) have historically been underemphasized in ecological research, they are increasingly recognized as playing important roles in the evolution and maintenance of biodiversity. Dominant habitat-forming species (foundation species) buffer environmental conditions and can therefore facilitate myriad associated species. Theory predicts that facilitation will be the dominant community-structuring force under harsh environmental conditions, where organisms depend on shelter for survival and predation is diminished. Wind-swept, arid Patagonian rocky shores are one of the most desiccating intertidal rocky shores ever studied, providing an opportunity to test this theory and elucidate the context-dependency of facilitation.Surveys across 2100 km of southern Argentinean coastline and experimental manipulations both supported theoretical predictions, with 43 out of 46 species in the animal assemblage obligated to living within the matrices of mussels for protection from potentially lethal desiccation stress and predators having no detectable impact on diversity.These results provide the first experimental support of long-standing theoretical predictions and reveal that in extreme climates, maintenance of whole-community diversity can be maintained by positive interactions that ameliorate physical stress. These findings have important conservation implications and emphasize that preserving foundation species should be a priority in remediating the biodiversity consequences of global climate change