Basic and other measurements of radiation at station Ny-Ålesund (2015-03)

On 20 March 2015, a total solar eclipse occurred over Ny-Ålesund (78.9° N, 11.9° E), Svalbard, in the high Arctic. It was the first time that the surface radiation components during the totality of a solar eclipse were measured by a Baseline Surface Radiation Network (BSRN) station. With the Ny-Ålesund long-term radiation data set as background (available at doi:10.1594/PANGAEA.150000), we present here the peculiarities of the radiation components and basic meteorology observed during the eclipse event. The supplementary data set contains the basic BSRN radiation and surface meteorological data in 1 min resolution for March 2015, and is available at doi:10.1594/PANGAEA.854326. The eclipse radiation data will be a useful auxiliary data set for further studies on micrometeorological surface-atmosphere exchange processes in the Svalbard environment, and may serve as a test case for radiative transfer studies.

EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study

Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.

Stable carbon and oxygen isotope ratios for different test sizes of live benthic foraminifera from the Arabian Sea

We determined the stable oxygen and carbon isotopic composition of live (Rose Bengal stained) tests belonging to different size classes of two benthic foraminiferal species from the Pakistan continental margin. Samples were taken at 2 sites, with water depth of about 135 and 275 m, corresponding to the upper boundary and upper part of the core region of the oxygen minimum zone (OMZ). For Uvigerina ex gr. U. semiornata and Bolivina aff. B. dilatata, delta13C and delta18O values increased significantly with increasing test size. In the case of U. ex gr. U. semiornata, delta13C increased linearly by about 0.105 per mil for each 100-µm increment in test size, whereas delta18O increased by 0.02 to 0.06 per mil per 100 µm increment. For B. aff. B. dilatata the relationship between test size and stable isotopic composition is better described by logarithmic equations. A strong positive linear correlation is observed between delta18O and delta13C values of both taxa, with a constant ratio of delta18O and delta13C values close to 2:1. This suggests that the strong ontogenetic effect is mainly caused by kinetic isotope fractionation during CO2 uptake. Our data underline the necessity to base longer delta18O and delta13C isotope records derived from benthic foraminifera on size windows of 100 µm or less. This is already common practice in down-core isotopic studies of planktonic foraminifera.

A probabilistic model estimating oil spill clean-up costs - a case study for the Gulf of Finland

Existing models estimating oil spill costs at sea are based on data from the past, and they usually lack a systematic approach. This make them passive, and limits their ability to forecast the effect of the changes in the oil combating fleet or location of a spill on the oil spill costs. In this paper we make an attempt towards the development of a probabilistic and systematic model estimating the costs of clean-up operations for the Gulf of Finland. For this purpose we utilize expert knowledge along with the available data and information from literature. Then, the obtained information is combined into a framework with the use of a Bayesian Belief Networks. Due to lack of data, we validate the model by comparing its results with existing models, with which we found good agreement. We anticipate that the presented model can contribute to the cost-effective oil-combating fleet optimization for the Gulf of Finland. It can also facilitate the accident consequences estimation in the framework of formal safety assessment (FSA).