Database of Ice-Rich Yedoma Permafrost (IRYP)

Vast portions of Arctic and sub-Arctic Siberia, Alaska and the Yukon Territory are covered by ice-rich silty to sandy deposits that are containing large ice wedges, resulting from syngenetic sedimentation and freezing. Accompanied by wedge-ice growth in polygonal landscapes, the sedimentation process was driven by cold continental climatic and environmental conditions in unglaciated regions during the late Pleistocene, inducing the accumulation of the unique Yedoma deposits up to >50 meters thick. Because of fast incorporation of organic material into syngenetic permafrost during its formation, Yedoma deposits include well-preserved organic matter. Ice-rich deposits like Yedoma are especially prone to degradation triggered by climate changes or human activity. When Yedoma deposits degrade, large amounts of sequestered organic carbon as well as other nutrients are released and become part of active biogeochemical cycling. This could be of global significance for future climate warming as increased permafrost thaw is likely to lead to a positive feedback through enhanced greenhouse gas fluxes. Therefore, a detailed assessment of the current Yedoma deposit coverage and its volume is of importance to estimate its potential response to future climate changes. We synthesized the map of the coverage and thickness estimation, which will provide critical data needed for further research. In particular, this preliminary Yedoma map is a great step forward to understand the spatial heterogeneity of Yedoma deposits and its regional coverage. There will be further applications in the context of reconstructing paleo-environmental dynamics and past ecosystems like the mammoth-steppe-tundra, or ground ice distribution including future thermokarst vulnerability. Moreover, the map will be a crucial improvement of the data basis needed to refine the present-day Yedoma permafrost organic carbon inventory, which is assumed to be between 83±12 (Strauss et al., 2013, doi:10.1002/2013GL058088) and 129±30 (Walter Anthony et al., 2014, doi:10.1038/nature13560) gigatonnes (Gt) of organic carbon in perennially-frozen archives. Hence, here we synthesize data on the circum-Arctic and sub-Arctic distribution and thickness of Yedoma for compiling a preliminary circum-polar Yedoma map. For compiling this map, we used (1) maps of the previous Yedoma coverage estimates, (2) included the digitized areas from Grosse et al. (2013) as well as extracted areas of potential Yedoma distribution from additional surface geological and Quaternary geological maps (1.: 1:500,000: Q-51-V,G; P-51-A,B; P-52-A,B; Q-52-V,G; P-52-V,G; Q-51-A,B; R-51-V,G; R-52-V,G; R-52-A,B; 2.: 1:1,000,000: P-50-51; P-52-53; P-58-59; Q-42-43; Q-44-45; Q-50-51; Q-52-53; Q-54-55; Q-56-57; Q-58-59; Q-60-1; R-(40)-42; R-43-(45); R-(45)-47; R-48-(50); R-51; R-53-(55); R-(55)-57; R-58-(60); S-44-46; S-47-49; S-50-52; S-53-55; 3.: 1:2,500,000: Quaternary map of the territory of Russian Federation, 4.: Alaska Permafrost Map). The digitalization was done using GIS techniques (ArcGIS) and vectorization of raster Images (Adobe Photoshop and Illustrator). Data on Yedoma thickness are obtained from boreholes and exposures reported in the scientific literature. The map and database are still preliminary and will have to undergo a technical and scientific vetting and review process. In their current form, we included a range of attributes for Yedoma area polygons based on lithological and stratigraphical information from the original source maps as well as a confidence level for our classification of an area as Yedoma (3 stages: confirmed, likely, or uncertain). In its current version, our database includes more than 365 boreholes and exposures and more than 2000 digitized Yedoma areas. We expect that the database will continue to grow. In this preliminary stage, we estimate the Northern Hemisphere Yedoma deposit area to cover approximately 625,000 km². We estimate that 53% of the total Yedoma area today is located in the tundra zone, 47% in the taiga zone. Separated from west to east, 29% of the Yedoma area is found in North America and 71 % in North Asia. The latter include 9% in West Siberia, 11% in Central Siberia, 44% in East Siberia and 7% in Far East Russia. Adding the recent maximum Yedoma region (including all Yedoma uplands, thermokarst lakes and basins, and river valleys) of 1.4 million km² (Strauss et al., 2013, doi:10.1002/2013GL058088) and postulating that Yedoma occupied up to 80% of the adjacent formerly exposed and now flooded Beringia shelves (1.9 million km², down to 125 m below modern sea level, between 105°E - 128°W and >68°N), we assume that the Last Glacial Maximum Yedoma region likely covered more than 3 million km² of Beringia. Acknowledgements: This project is part of the Action Group "The Yedoma Region: A Synthesis of Circum-Arctic Distribution and Thickness" (funded by the International Permafrost Association (IPA) to J. Strauss) and is embedded into the Permafrost Carbon Network (working group Yedoma Carbon Stocks). We acknowledge the support by the European Research Council (Starting Grant #338335), the German Federal Ministry of Education and Research (Grant 01DM12011 and "CarboPerm" (03G0836A)), the Initiative and Networking Fund of the Helmholtz Association (#ERC-0013) and the German Federal Environment Agency (UBA, project UFOPLAN FKZ 3712 41 106).

Air photography Samoylov Island

For the qualitative description of surface properties like vegetation cover or land-water-ratio of Samoylov Island as well as for the evaluation of fetch homogeneity considerations of the eddy covariance measurements and for the up-scaling of chamber flux measurements, a detailed surface classification of the island at the sub-polygonal scale is necessary. However, up to know only grey-scale Corona satellite images from the 1960s with a resolution of 2 x 2 m and recent multi-spectral LandSat images with a resolution of 30 x 30 m were available for this region. Both are not useable for the desired classification because of missing spectral information and inadequate resolution, respectively. During the Lena 2003 expedition, a survey of the island by air photography was carried out in order to obtain images for surface classification. The photographs were taken from a helicopter on 10.07.2002, using a Canon EOS100 reflex camera, a Soligor 19-23 mm lens and colour slide film. The height from which the photographs were taken was approximately 600 meters. Due to limited flight time, not all the area of the island could be photographed and some regions could only be photographed with a slanted view. As a result, the images are of a varying quality and resolution. In Potsdam, after processing the films were scanned using a Nikon LS-2000 scanner at maximal resolution setting. This resulted in a ground resolution of the scanned images of approximately 0.3x0.3 m. The images were subsequently geo-referenced using the ENVI software and a referenced Corona image dating from 18.07.1964 (Spott, 2003). Geo-referencing was only possible for the Holocene river terrace areas; the floodplain regions in the western part of the island could not be referenced due to the lack of ground reference points. In Figure 3.7-1, the aerial view of Samoylov Island composed of the geo-referenced images is shown. Further work is necessary for the classification and interpretation of the images. If possible, air photography surveys will be carried out during future expeditions in order to determine changes in surface pattern and composition.

An Efficient Hybrid GO-PWS Algorithm to Analyze Conformal Serrated-Edge Reflectors for Millimeter-Wave Compact Range

A method to analyze parabolic reflectors with arbitrary piecewise rim is presented in this communication. This kind of reflectors, when operating as collimators in compact range facilities, needs to be large in terms of wavelength. Their analysis is very inefficient, when it is carried out with fullwave/MoM techniques, and it is not very appropriate for designing with PO techniques. Also, fast GO formulations do not offer enough accuracy to reach performance results. The proposed algorithm is based on a GO-PWS hybrid scheme, using analytical as well as non-analytical formulations. On one side, an analytical treatment of the polygonal rim reflectors is carried out. On the other side, non-analytical calculi are based on efficient operations, such as M2 order 2-dimensional FFT. A combination of these two techniques in the algorithm ensures real ad-hoc design capabilities, reached through analysis speedup. The purpose of the algorithm is to obtain an optimal conformal serrated-edge reflector design through the analysis of the field quality within the quiet zone that it is able to generate in its forward half space.

Probabilistic mapping with mobile robots in structured environments

La mayor parte de los entornos diseñados por el hombre presentan características geométricas específicas. En ellos es frecuente encontrar formas poligonales, rectangulares, circulares . . . con una serie de relaciones típicas entre distintos elementos del entorno. Introducir este tipo de conocimiento en el proceso de construcción de mapas de un robot móvil puede mejorar notablemente la calidad y la precisión de los mapas resultantes. También puede hacerlos más útiles de cara a un razonamiento de más alto nivel. Cuando la construcción de mapas se formula en un marco probabilístico Bayesiano, una especificación completa del problema requiere considerar cierta información a priori sobre el tipo de entorno. El conocimiento previo puede aplicarse de varias maneras, en esta tesis se presentan dos marcos diferentes: uno basado en el uso de primitivas geométricas y otro que emplea un método de representación cercano al espacio de las medidas brutas. Un enfoque basado en características geométricas supone implícitamente imponer un cierto modelo a priori para el entorno. En este sentido, el desarrollo de una solución al problema SLAM mediante la optimización de un grafo de características geométricas constituye un primer paso hacia nuevos métodos de construcción de mapas en entornos estructurados. En el primero de los dos marcos propuestos, el sistema deduce la información a priori a aplicar en cada caso en base a una extensa colección de posibles modelos geométricos genéricos, siguiendo un método de Maximización de la Esperanza para hallar la estructura y el mapa más probables. La representación de la estructura del entorno se basa en un enfoque jerárquico, con diferentes niveles de abstracción para los distintos elementos geométricos que puedan describirlo. Se llevaron a cabo diversos experimentos para mostrar la versatilidad y el buen funcionamiento del método propuesto. En el segundo marco, el usuario puede definir diferentes modelos de estructura para el entorno mediante grupos de restricciones y energías locales entre puntos vecinos de un conjunto de datos del mismo. El grupo de restricciones que se aplica a cada grupo de puntos depende de la topología, que es inferida por el propio sistema. De este modo, se pueden incorporar nuevos modelos genéricos de estructura para el entorno con gran flexibilidad y facilidad. Se realizaron distintos experimentos para demostrar la flexibilidad y los buenos resultados del enfoque propuesto. Abstract Most human designed environments present specific geometrical characteristics. In them, it is easy to find polygonal, rectangular and circular shapes, with a series of typical relations between different elements of the environment. Introducing this kind of knowledge in the mapping process of mobile robots can notably improve the quality and accuracy of the resulting maps. It can also make them more suitable for higher level reasoning applications. When mapping is formulated in a Bayesian probabilistic framework, a complete specification of the problem requires considering a prior for the environment. The prior over the structure of the environment can be applied in several ways; this dissertation presents two different frameworks, one using a feature based approach and another one employing a dense representation close to the measurements space. A feature based approach implicitly imposes a prior for the environment. In this sense, feature based graph SLAM was a first step towards a new mapping solution for structured scenarios. In the first framework, the prior is inferred by the system from a wide collection of feature based priors, following an Expectation-Maximization approach to obtain the most probable structure and the most probable map. The representation of the structure of the environment is based on a hierarchical model with different levels of abstraction for the geometrical elements describing it. Various experiments were conducted to show the versatility and the good performance of the proposed method. In the second framework, different priors can be defined by the user as sets of local constraints and energies for consecutive points in a range scan from a given environment. The set of constraints applied to each group of points depends on the topology, which is inferred by the system. This way, flexible and generic priors can be incorporated very easily. Several tests were carried out to demonstrate the flexibility and the good results of the proposed approach.

Methodology for kinematic cycle characterization of vehicles with fixed routes in urban areas

This paper analyses the driving cycles of a fleet of vehicles with predetermined urban itineraries. Most driving cycles developed for such type of vehicles do not properly address variability among itineraries. Here we develop a polygonal driving cycle that assesses each group of related routes, based on microscopic parameters. It measures the kinematic cycles of the routes traveled by the vehicle fleet, segments cycles into micro-cycles, and characterizes their properties, groups them into clusters with homogeneous kinematic characteristics within their specific micro-cycles, and constructs a standard cycle for each cluster. The process is used to study public bus operations in Madrid.

Supramolecular organization of immature and mature murine leukemia virus revealed by electron cryo-microscopy: Implications for retroviral assembly mechanisms

We have used electron cryo-microscopy and image analysis to examine the native structure of immature, protease-deficient (PR−) and mature, wild-type (WT) Moloney murine leukemia virus (MuLV). Maturational cleavage of the Gag polyprotein by the viral protease is associated with striking morphological changes. The PR− MuLV particles exhibit a rounded central core, which has a characteristic track-like shell on its surface, whereas the WT MuLV cores display a polygonal surface with loss of the track-like feature. The pleomorphic shape and inability to refine unique orientation angles suggest that neither the PR− nor the WT MuLV adheres to strict icosahedral symmetry. Nevertheless, the PR− MuLV particles do exhibit paracrystalline order with a spacing between Gag molecules of ≈45 Å and a length of ≈200 Å. Because of the pleomorphic shape and paracrystalline packing of the Gag–RNA complexes, we raise the possibility that assembly of MuLV is driven by protein–RNA, as well as protein–protein, interactions. The maturation process involves a dramatic reorganization of the packing arrangements within the ribonucleoprotein core with disordering and loosening of the individual protein components.