Photometric analysis of the eclipsing binary 2MASS 19090585+4911585

We report on observations of the eclipsing binary 2MASS 19090585+4911585 with the 25 cm auxiliary telescope of the University Observatory Jena. We show that a nearby brighter star (2MASS 19090783+4912085) was previously misclassified as the eclipsing binary and find 2MASS 19090585+4911585 to be the true source of variation. We present photometric analysis of VRI light curves. The system is an overcontact binary of W UMa type with an orbital period of (0.288374 ± 0.000010) d (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The Askervein Hill Project: Vertical profiles of wind and turbulence

This is one of a series of papers on the Askervein Hill Project. It presents results from the Askervein 1982 and 1983 experiments in the form of vertical profiles of mean wind and turbulence integral statistics at upwind reference locations and at two hilltop sites. The data were obtained from a variety of sensors including sonic, Gill UVW and cup anemometers mounted on 50, 30, 17 and 10 m towers and TALA kite systems. Comparisons with numerical-model predictions are discussed.     

Stationarity Scores on Training Images for Multipoint Geostatistics

This research introduces a novel method to assess the validity of training images used as an input for Multipoint Geostatistics, alternatively called Multiple Point Simulation (MPS). MPS are a family of spatial statistical interpolation algorithms that are used to generate conditional simulations of property fields such as geological facies. They are able to honor absolute “hard” constraints (e.g., borehole data) as well as “soft” constraints (e.g., probability fields derived from seismic data, and rotation and scale). These algorithms require 2D or 3D training images or analogs whose textures represent a spatial arrangement of geological properties that is presumed to be similar to that of a target volume to be modeled. To use the current generation of MPS algorithms, statistically valid training image are required as input. In this context, “statistical validity” includes a requirement of stationarity, so that one can derive from the training image an average template pattern. This research focuses on a practical method to assess stationarity requirements for MPS algorithms, i.e., that statistical density or probability distribution of the quantity shown on the image does not change spatially, and that the image shows repetitive shapes whose orientation and scale are spatially constant. This method employs image-processing techniques based on measures of stationarity of the category distribution, the directional (or orientation) property field and the scale property field of those images. It was successfully tested on a set of two-dimensional images representing geological features and its predictions were compared to actual realizations of MPS algorithms. An extension of the algorithms to 3D images is also proposed. As MPS algorithms are being used increasingly in hydrocarbon reservoir modeling, the methods described should facilitate screening and selection of the input training images.     

Using high resolution tracer data to constrain water storage,flux and age estimates in a spatially distributed rainfall‐runoff model

Models simulating stream flow and conservative tracers can provide a representation of flow paths, storage distributions and mixing processes that is advantageous for many predictive purposes. Compared with models that only simulate stream flow, tracer data can be used to investigate the internal consistency of model behaviour and to gain insight into model performance. Here, we examine the strengths and weaknesses of a data‐driven, spatially distributed tracer‐aided rainfall‐runoff model. The model structure allowed us to assess the influence of landscape characteristics on the routing and mixing of water and tracers. The model was applied to a site in the Scottish Highlands with a unique tracer data set; ~4 years of daily isotope ratios in stream water and precipitation were available, as well as 2 years of weekly soil and ground water isotopes. The model structure was based on an empirically based, lumped tracer‐aided model previously developed for the catchment. The best model runs were selected from Monte Carlo simulations based on dual calibration criteria using objective functions for both stream isotopes and discharge at the outlet. Model performance for these criteria was reasonable (Nash–Sutcliffe efficiencies for discharge and isotope ratios were ~0.4–0.6). The model could generally reproduce the variable isotope signals in the soils of the steeper hill slopes where storage was low, and damped isotope responses in valley bottom cells with high storage. The model also allowed us to estimate the age distributions of internal stores, water fluxes and stream flow. Average stream water age was ~1.6 years, integrating older groundwater in the valley bottom and dynamic younger soil waters. By tracking water ages and simulating isotopes, the model captured the changes in connectivity driven by distributed storage dynamics. This has substantially improved the representation of spatio‐temporal process dynamics and gives a more robust framework for projecting environmental change impacts. Copyright © 2016 The Authors Hydrological Processes Published by John Wiley & Sons Ltd.     

Thermal characteristics of coal fires 2: Results of measurements on simulated coal fires

In this paper we present thermal characteristics of coal fires as measured during simulated fires under an experimental setting in Germany in July 2002. It is thus a continuation of the previously published paper “Thermal surface characteristics of coal fire 1: Results of in-situ measurement”, in which we presented temperature measurements of real subsurface coal fires in China [Zhang, J., Kuenzer, C., accepted for publication. Thermal Surface Characteristics of Coal Fires 1: Results of in-situ measurements. Accepted for publication at Journal of Applied Geophysics.]. The focus is on simulated coal fires, which are less complex in nature than fires under natural conditions. In the present study we simulated all the influences usually occurring under natural conditions in a controllable manner (uniform background material of known thermal properties, known ventilation pathways, homogeneous coal substrate), creating two artificial outdoor coal fires under simplified settings. One surface coal fire and one subsurface coal fire were observed over the course of 2 days. The set up of the fires allowed for measurements not always feasible under “real” in-situ conditions: thus compared to the in-situ investigations presented in paper one we could retrieve numerous temperature measurements inside of the fires. Single temperature measurements, diurnal profiles and airborne thermal surveying present the typical temperature patterns of a small surface-and a subsurface fire under undisturbed conditions (easily accessible terrain, 24 hour measurements period, homogeneous materials). We found that the outside air temperature does not influence the fire's surface temperature (up to 900 °C), while fire centre temperatures of up to 1200 °C strongly correlate with surface temperatures of the fire. The fires could heat their surrounding up to a distance of 4.5 m. However, thermal anomalies on the background surface only persist as long as the fire is burning and disappear very fast if the heat source is removed. Furthermore, heat outside of the fires is transported mainly by convection and not by radiation. In spatial thermal line scanner data the diurnal thermal patterns of the coal fire are clearly represented. Our experiments during that data collection also visualize the thermal anomaly differences between covered (underground) and uncovered (surface) coal fires. The latter could not be observed in-situ in a real coal fire area. Sub-surface coal fires express a much weaker signal than open surface fires and contrast only by few degrees against the background. In airborne thermal imaging scanner data the fires are also well represented. Here we could show that the mid-infrared domain (3.8 μm) is more suitable to pick up very hot anomalies, compared to the common thermal (8.8 μm) domain. Our results help to understand coal fires and their thermal patterns as well as the limitations occurring during their analysis. We believe that the results presented here can practicably help for the planning of coal fire thermal mapping campaigns — including remote sensing methods and the thermal data can be included into numerical coal fire modelling as initial or boundary conditions.     

On Modeling Dry Deposition of Long-Lived and Chemically Reactive Species over Heterogeneous Terrain

An explicit multi-layer subgrid-scheme was developed for ameso-/-scale model to consider subgrid-scale surface heterogeneity, dry deposition, biogenic and anthropogenic emission of trace gases. Since dry deposition measurements of highly reactive trace species are scarce we try to evaluate this scheme by heuristic principles. The results of simulations conducted for a 5×5 km² resolution with and without thisscheme are evaluated by using results of a model run with 1×1 km²resolution, which is taken as a `grand thruth' and which has the same resolution as the subgrid. The explict multi-layer subgrid scheme provides a similar distribution of dry deposition fluxes as the much more computationally expensive simulation with the 1×1 km² resolution.Dry deposition fluxes determined from observations give evidence that the explicit multi-layer subgrid scheme which does not require a constant flux approximation for a layer of several decameters leads to an improvement in determining the exchange between the atmosphere and the ground.Results of simulations with a microscale model show that the inhomogeneity at forest edges leads to an increase of the turbulent transports of up to a factor 4 compared to horizontally homogeneous terrain, which is assumed to be the conditions of the subgrid cells (and which is usually the assumption for the entire grid cell in mesoscale models). Inhomogeneity inside an extended stand of trees causes an overall increase of 5–10% withhigh local extremes, i.e. such an inhomogeneity results to an underestimation of dry deposition in meso-/-scale models. The effects are most pronounced for a wind direction perpendicular to the forest edge.