Analysis of trends in annual streamflow to the Arctic Ocean

There is increasing interest in the magnitude of the flow of freshwater to the Arctic Ocean due to its impacts on the biogeophysical and socio‐economic systems in the north and its influence on global climate. This study examines freshwater flow based on a dataset of 72 rivers that either directly or indirectly contribute flow to the Arctic Ocean or reflect the hydrologic regime of areas contributing flow to the Arctic Ocean. Annual streamflow for the 72 rivers is categorized as to the nature and location of the contribution to the Arctic Ocean, and composite series of annual flows are determined for each category for the period 1975 to 2015. A trend analysis is then conducted for the annual discharge series assembled for each category. The results reveal a general increase in freshwater flow to the Arctic Ocean with this increase being more prominent from the Eurasian rivers than from the North American rivers. A comparison with trends obtained from an earlier study ending in 2000 indicates similar trend response from the Eurasian rivers, but dramatic differences from some of the North American rivers. A total annual discharge increase of 8.7 km³/y/y is found, with an annual discharge increase of 5.8 km³/y/y observed for the rivers directly flowing to the Arctic Ocean. The influence of annual or seasonal climate oscillation indices on annual discharge series is also assessed. Several river categories are found to have significant correlations with the Arctic Oscillation, the North Atlantic Oscillation, or the Pacific Decadal Oscillation. However, no significant association with climate indices is found for the river categories leading to the largest freshwater contribution to the Arctic Ocean.     

Multi-temporal assessment of vulnerability to climate change: insights from the agricultural sector in Mexico

Vulnerability to climate change was evaluated for three different time periods: 1990, 2000, and 2010. Our objective was to discuss the scope of a multi-temporal assessment of vulnerability. The method used 55 indicators—with emphasis on the agricultural sector in Mexico—of which 27 were updated for the year 2010 and 33 were retrospectively estimated for the year 1990. The results show that in the 20-year study period, the exposure of the municipalities (and inhabitants) has increased, and sensitivity and adaptive capacity have decreased. The number of municipalities vulnerable to climate change declined over the 20-year period. We found that calculating vulnerability by adding exposure and sensitivity and subtracting adaptive capacity (E?+?S???AC) can lead to unintentional underestimation of total vulnerability. When rating vulnerability, care must be taken in what is reported: the results differ for the number of inhabitants versus the number of municipalities. Our previous published vulnerability evaluation was for the year 2000, so we wanted to evaluate the sensitivity of some variables and the vulnerability formula itself we used in that moment. It is possible to evaluate the vulnerability multi-temporally, which allows to evaluate the sensibility and calibration of the variables and indicators used and the reconsideration of their application.     

Dolomite in caves: Recent dolomite formation in oxic, non-sulfate environments. Castañar Cave, Spain

Dolomite is a common mineral in the rock record but rare in recent superficial environments. Where it does occur, it is related to anoxic, sulfate-rich environments and microbial activity. The occurrence of some dolomite deposits in caves, however, indicates that dolomite formation is also possible in oxic, non-sulfate settings. Dolomite is forming at 17 °C and in oxic-vadose conditions on the host rocks and aragonite speleothems of the Castañar Cave, Cáceres, Spain. It appears as spheroids and dumbbells 50–300 μm in diameter that internally consist of micron-sized rhombic to rounded crystals. Initially this dolomite is Ca-rich, non-stoichiometric and poorly ordered. Mg-rich solutions allow the precipitation of metastable Mg-rich carbonates, such as huntite. This soon transforms into this Ca-rich dolomite, which later “ages” to form a more stoichiometric dolomite. These dolomites show similarities to those grown under anoxic, sulfate-rich conditions and their presence in caves provides a different setting that may contribute to the understanding of the “dolomite problem”, including their initial formation and later recrystallization processes.     

Galileo Constellation Design

A significant effort has been carried out in Europe to define the European Global Navigation Satellite System (GNSS), named Galileo Satellites flying in Medium Earth Orbits (MEO) will compose the system (according to the most recent architecture definition baseline); a regional complement of geosynchronous satellites may be required to increase performances over Europe and maybe also to provide some specific communication services. Nominal medium performances are envisaged, but they will be increased by means of augmentation systems (local or wide area), or even by using simultaneously other GNSSs such as GPS. All the involved requirements make the design process quite complex. A powerful software tool, Elcano, has been developed for this purpose; its capabilities will be outlined, and the results of the design process will be presented. ? 2001 John Wiley & Sons, Inc.     

Real-time genetic spatial optimization to improve forest fire spread forecasting in high-performance computing environments

Abstract

Forest fires are a kind of natural hazard with a high number of occurrences in southern European countries. To avoid major damages and to improve forest fire management, one can use forest fire spread simulators to predict fire behavior. When providing forest fire predictions, there are two main considerations: accuracy and computation time. In the context of natural hazards simulation, it is well known that part of the final forecast error comes from uncertainty in the input data. These data typically consist of a set of GIS files, which should be appropriately conflated. For this reason, several input data calibration methods have been developed by the scientific community. In this work, the Two-Stage calibration methodology, which has been shown to provide good results, is used. This calibration strategy is computationally intensive and time-consuming because it uses a Genetic Algorithm as a solution. Taking into account the aspect of urgency in forest fire spread prediction, it is necessary to maintain a balance between accuracy and the time needed to calibrate the input parameters. In order to take advantage of this technique, one must deal with the problem that some of the obtained solutions are impractical, since they involve simulation times that are too long, preventing the prediction system from being deployed at an operational level. A new method which finds the minimum resolution reduction for such long simulations, keeping accuracy loss to a known interval, is proposed. The proposed improvement is based on a time-aware core allocation policy that enables real-time forest fire spread forecasting. The final prediction system is a cyberinfrastructure, which enables forest fire spread prediction at real time.