Craters,smooth terrains,flows, and layering on the comet nuclei

The paper considers morphology of craters, smooth surfaces, and flows as well as signatures of layering observed on nuclei of Borrelly, Wild 2, and Tempel 1. In our analysis, we emphasize the role of the so-called planation process, which involves avalanche-type flows and can be responsible for the formation of flow-like features, smooth terrains, terraces, and flat floors of some craters observed on cometary nuclei. In agreement with some other researchers (e.g., Belton, 2006), we suggest that in the thicker layers on Tempel 1 and in some features on Borrelly and Wild 2, we may see elements of the comet primordial structure. We also see more and less degraded impact craters formed early in the comet history in distant parts of the Solar System and landforms formed very recently during comet visits to the inner part of the Solar System. The recent resurfacing processes certainly changed the nucleus surface materials, possibly enhancing the sublimation of volatile species, so it should be taken into account in interpretations of the Deep Impact results and in selecting study areas when the Rosetta spacecraft will approach its target comet.     

Foraminifera from the early Danian intertrappean beds in Rajahmundry quarries,Andhra Pradesh

Intertrappean beds exposed between upper and lower traps of the Government and Sunnamrayalu quarries of Rajahmundry were analyzed based on benthic and planktic foraminifera, ostracodes and algae observed in thin sections. Planktic foraminifera indicate deposition occurred in the early Danian Parvularugoglobigerina eugubina (P1a) zone shortly after deposition of the lower trap flows. The most diverse planktic assemblages were deposited in limestones of the middle intertrappean interval and indicate an upper P1a age, or subzone P1a(2), as marked by the co-occurrence of P. eugubina, Globoconusa daubjergensis, Parasubbotina pseudobulloides and Subbotina triloculinoides. Reworked late Maastrichtian planktic foraminifera are common in a limestone interval and suggest erosion of uplifted Cretaceous sediments. Benthic foraminiferal assemblages indicate deposition occurred predominantly in shallow inner shelf to brackish environments. Similarly, ostracodes indicate variable environments ranging from inner neritic to brackish with fresh water influx, as also indicated by the presence of fresh water algae. These data confirm an overall deepening from restricted shallow marine to estuarine, lagoonal and finally open marine conditions followed by abrupt emersion and paleosoil deposition prior to the arrival of the upper trap flows at or near the base of C29n.     

Special Contribution: ALP 2002 Seismic Experiment

Studia Geophysica et Geodaetica -     

Epistemic and ethical trade-offs in decision analytical modelling

Designing decision analytical models requires making choices that can involve a range of trade-offs and interactions between epistemic and ethical considerations. Such choices include determining the complexity of a model and deciding what types of risk will be assessed. Here, we demonstrate how model design choices can involve trade-offs between the epistemic benefits of representational completeness and simplicity, which interact with ethical considerations about fairness and human life. We illustrate this point by focusing on modeling studies that assess flood risks in New Orleans, Louisiana. Addressing the ethical and epistemic implications of model design choices can help clarify the scope of factors necessary to inform ethically sound and economically efficient decision-making.     

基于ALOS-PALSAR卫星数据对青藏高原东缘龙日坝断裂带地表构造伸展的研究及其大地构造指示意义

龙日坝断裂带位于青藏高原最东缘,呈北东-南西向延伸,平行于其东侧的龙门山断裂带,二者大约相距150 km。与龙门山断裂带不同的是,龙日坝断裂带在青藏高原东缘相关GPS测量中表现为一明显的速度梯度带,说明龙日坝断裂带可能具有很重要的构造属性。然而有关龙日坝断裂带的地表结构构造延伸问题一直悬而未决,目前还存在许多的争议,这在一定程度上也阻碍了我们对青藏高原东缘相对于印度-欧亚板块碰撞地球动力学响应的了解。在本次研究中,我们将首次采用ALOS-PALSAR卫星数据,并结合地表地质和前人的地球物理学研究成果,来监测与龙日坝断裂带的构造活动相关的细微地表形变,并由此控制龙日坝断裂带的延伸范围。研究结果表明,龙日坝断裂带与其西南侧的抚边河断裂带相交且近乎垂直,而非前人研究所认为的龙日坝断裂带延伸至其西缘的鲜水河断裂带。综合研究结果也为了解龙日坝断裂带的大地构造属性提供了数据支持。     

Learning and climate change

Abstract

Learning—i.e. the acquisition of new information that leads to changes in our assessment of uncertainty—plays a prominent role in the international climate policy debate. For example, the view that we should postpone actions until we know more continues to be influential. The latest work on learning and climate change includes new theoretical models, better informed simulations of how learning affects the optimal timing of emissions reductions, analyses of how new information could affect the prospects for reaching and maintaining political agreements and for adapting to climate change, and explorations of how learning could lead us astray rather than closer to the truth. Despite the diversity of this new work, a clear consensus on a central point is that the prospect of learning does not support the postponement of emissions reductions today.     

Classification of marine bioregions on the east coast of South Africa

Marine bioregional planning requires a meaningful classification and spatial delineation of the ocean environment using biological and physical characteristics. The relative inaccessibility of much of the ocean and the paucity of directly measured data spanning entire planning regions mean that surrogate data, such as satellite imagery, are frequently used to develop spatial classifications. However, due to a lack of appropriate biological data, these classifications often rely on abiotic variables, which act as surrogates for biodiversity. The aim of this study was to produce a fine-scale bioregional classification, using multivariate clustering, for the inshore and offshore marine environment off the east coast of South Africa, adjacent to the province of KwaZulu-Natal and out to the boundary of the exclusive economic zone (EEZ), 200 nautical miles offshore. We used remotely sensed data of sea surface temperature, chlorophyll a and turbidity, together with interpolated bathymetry and continental-slope data, as well as additional inshore data on sediments, seabed oxygen and bottom temperature. A multivariate k-means analysis was used to produce a fine-scale marine bioregionalisation, with three bioregions subdivided into 12 biozones. The offshore classification was primarily a pelagic bioregionalisation, whereas the inshore classification (on the continental shelf) was a coupled benthopelagic bioregionalisation, owing to the availability of benthic data for this area. The resulting classification was used as a base layer for a systematic conservation plan developed for the province, and provided the methods for subsequent planning conducted for the entire South African EEZ. Validation of the classification is currently being conducted in marine research programmes that are sampling benthic biota and habitats in a sampling design stratified according to the biozones delineated in this study.     

Adaptation of the torus and Rosborough approach to radial base functions

The most common approach for the processing of data of gravity field satellite missions is the so-called time-wise approach. In this approach satellite data are considered as a time series and processed by a standard least-squares approach. This approach has a very strong flexibility but it is computationally very demanding. To improve the computational efficiency and numerical stability, the so-called torus and Rosborough approaches have been developed. So far, these approaches have been applied only for global gravity field determinations, based on spherical harmonics as basis functions. For regional applications basis functions with a local support are superior to spherical harmonics, because they provide the same approximation quality with much less parameters. So far, torus and Rosborough approach have been developed for spherical harmonics only. Therefore, the paper aims at the development and testing of the torus and Rosborough approach for regional gravity field improvements, based on radial basis functions as basis functions. The developed regional Rosborough approach is tested against a changing gravity field produced by simulated ice-mass changes over Greenland. With only 350 parameters a recovery of the simulated mass changes with a relative accuracy of 5% is possible.     

Observations of Comet 9P/Tempel 1 around the Deep Impact event by the OSIRIS cameras onboard Rosetta

The OSIRIS cameras on the Rosetta spacecraft observed Comet 9P/Tempel 1 from 5 days before to 10 days after it was hit by the Deep Impact projectile. The Narrow Angle Camera (NAC) monitored the cometary dust in 5 different filters. The Wide Angle Camera (WAC) observed through filters sensitive to emissions from OH, CN, Na, and OI together with the associated continuum. Before and after the impact the comet showed regular variations in intensity. The period of the brightness changes is consistent with the rotation period of Tempel 1. The overall brightness of Tempel 1 decreased by about 10% during the OSIRIS observations. The analysis of the impact ejecta shows that no new permanent coma structures were created by the impact. Most of the material moved with . Much of it left the comet in the form of icy grains which sublimated and fragmented within the first hour after the impact. The light curve of the comet after the impact and the amount of material leaving the comet ( of water ice and a presumably larger amount of dust) suggest that the impact ejecta were quickly accelerated by collisions with gas molecules. Therefore, the motion of the bulk of the ejecta cannot be described by ballistic trajectories, and the validity of determinations of the density and tensile strength of the nucleus of Tempel 1 with models using ballistic ejection of particles is uncertain.     

A study on combining global and regional climate model results for generating climate scenarios of temperature and precipitation for the Netherlands

Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate. In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty, while high resolution regional climate models (RCMs) are more suitable to quantify the third level. Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined statistical–dynamical downscaling approach, with the statistical relations based on regional model output.