CHAC: a weather pattern classification system for regional climate downscaling of daily precipitation

A weather pattern clustering method is applied and calibrated to Argentinean daily weather stations in order to predict daily precipitation data. The clustering technique is based on k-means and is applied to a set of 17 atmospheric variables from the ERA-40 reanalysis covering the period 1979–1999. The set of atmospheric variables represent the different components of the atmosphere (dynamical, thermal and moisture). Different sensitivity tests are applied to optimize (1) the number of observations (weather patterns) per cluster, (2) the spatial domain size of the weather pattern around the station and (3) the number of members of the ensembles. All the sensitivity tests are compared using the ROC (Relative Operating Characteristic) Skill Score (RSS) derived from the ROC curve used to assess the performance of a predictive system. First, we found the number of observations per cluster to be optimum for values larger than 39. Second, the spatial domain size (~4° × 4°) was found to be closer to a local scale than to a synoptic scale, certainly due to a dominant role of the moisture components in the optimization of the transfer function. Indeed, when reducing the set of variables to the subset of dynamical variables, the predictive skill of the method is significantly reduced, but at the same time the domain size must be increased. A potential improvement of the method may therefore be to consider different domains for dynamical and non-dynamical variables. Third, the number of members per ensembles of simulations was estimated to be always two to three times larger than the mean number of observations per cluster (meaning that at least all the observed weather patterns are selected by one member). The skill of the statistical method to predict daily precipitation is found to be relatively homogeneous all over the country for different thresholds of precipitation.     

Short‐term stream water temperature observations permit rapid assessment of potential climate change impacts

Assessment of potential climate change impacts on stream water temperature (T_s) across large scales remains challenging for resource managers because energy exchange processes between the atmosphere and the stream environment are complex and uncertain, and few long‐term datasets are available to evaluate changes over time. In this study, we demonstrate how simple monthly linear regression models based on short‐term historical T_s observations and readily available interpolated air temperature (T_a) estimates can be used for rapid assessment of historical and future changes in T_s. Models were developed for 61 sites in the southeastern USA using ≥18 months of observations and were validated at sites with longer periods of record. The T_s models were then used to estimate temporal changes in T_s at each site using both historical estimates and future T_a projections. Results suggested that the linear regression models adequately explained the variability in T_s across sites, and the relationships between T_s and T_a remained consistent over 37 years. We estimated that most sites had increases in historical annual mean T_s between 1961 and 2010 (mean of +0.11 °C decade^?1). All 61 sites were projected to experience increases in T_s from 2011 to 2060 under the three climate projections evaluated (mean of +0.41 °C decade^?1). Several of the sites with the largest historical and future T_s changes were located in ecoregions home to temperature‐sensitive fish species. This methodology can be used by resource managers for rapid assessment of potential climate change impacts on stream water temperature. Copyright © 2014 John Wiley & Sons, Ltd.     

Coupled HM analysis using zero‐thickness interface elements with double nodes. Part I: Theoretical model

In recent years, the authors have proposed a new double‐node zero‐thickness interface element for diffusion analysis via the finite element method (FEM) (Int. J. Numer. Anal. Meth. Geomech. 2004; 28 (9): 947–962). In the present paper, that formulation is combined with an existing mechanical formulation in order to obtain a fully coupled hydro‐mechanical (or HM) model applicable to fractured/fracturing geomaterials. Each element (continuum or interface) is formulated in terms of the displacements (u) and the fluid pressure (p) at the nodes. After assembly, a particular expression of the traditional ‘u–p’ system of coupled equations is obtained, which is highly non‐linear due to the strong dependence between the permeability and the aperture of discontinuities. The formulation is valid for both pre‐existing and developing discontinuities by using the appropriate constitutive model that relates effective stresses to relative displacements in the interface. The system of coupled equations is solved following two different numerical approaches: staggered and fully coupled. In the latter, the Newton–Raphson method is used, and it is shown that the Jacobian matrix becomes non‐symmetric due to the dependence of the discontinuity permeability on the aperture. In the part II companion paper (Int. J. Numer. Anal. Meth. Geomech. 2008; DOI: 10.1002/nag.730 ), the formulation proposed is verified and illustrated with some application examples. Copyright © 2008 John Wiley & Sons, Ltd.     

Ore and Alteration Types of the Gold and Copper Mineralization in the Lascogon Project, Surigao del Norte, Mindanao Island, Philippines

Two ore and three alteration types were identified in the Lascogon Project of Philex Gold Philippines, in Surigao del Norte, Mindanao Island, Philippines. The jasperoid ore is the host to the Carlin‐like gold mineralization in the Lascogon and Danao prospects. The ore occurs in a decalcified and silicified horizon, with minor chlorite and goethite, stibnite, pyrite and quartz crystals ranging from cryptocrystalline to botryoidal. The stringer–stockwork type Cu‐Au mineralization in the Suyoc prospect is hosted in argillized andesitic rocks of the Mabuhay Formation. The primary ore minerals are chalcopyrite with minor amounts of sphalerite. The alteration types identified are propylitic alteration, argillic alteration and silicification. The propylitized basaltic and andesitic flows of the Bacuag Formation bound the jasperoid mineralization in the Lascogon prospect. Stratigraphically, the relationship between propylitized basalts and stringer–stockwork Cu‐Au is not clear but a lateral change can be inferred from jasperoid in the center and stringer–stockwork towards the east.     

Projection of future climate change conditions using IPCC simulations, neural networks and Bayesian statistics. Part 2: Precipitation mean state and seasonal cycle in South America

Evaluating the response of climate to greenhouse gas forcing is a major objective of the climate community, and the use of large ensemble of simulations is considered as a significant step toward that goal. The present paper thus discusses a new methodology based on neural network to mix ensemble of climate model simulations. Our analysis consists of one simulation of seven Atmosphere–Ocean Global Climate Models, which participated in the IPCC Project and provided at least one simulation for the twentieth century (20c3m) and one simulation for each of three SRES scenarios: A2, A1B and B1. Our statistical method based on neural networks and Bayesian statistics computes a transfer function between models and observations. Such a transfer function was then used to project future conditions and to derive what we would call the optimal ensemble combination for twenty-first century climate change projections. Our approach is therefore based on one statement and one hypothesis. The statement is that an optimal ensemble projection should be built by giving larger weights to models, which have more skill in representing present climate conditions. The hypothesis is that our method based on neural network is actually weighting the models that way. While the statement is actually an open question, which answer may vary according to the region or climate signal under study, our results demonstrate that the neural network approach indeed allows to weighting models according to their skills. As such, our method is an improvement of existing Bayesian methods developed to mix ensembles of simulations. However, the general low skill of climate models in simulating precipitation mean climatology implies that the final projection maps (whatever the method used to compute them) may significantly change in the future as models improve. Therefore, the projection results for late twenty-first century conditions are presented as possible projections based on the “state-of-the-art” of present climate modeling. First, various criteria were computed making it possible to evaluate the models’ skills in simulating late twentieth century precipitation over continental areas as well as their divergence in projecting climate change conditions. Despite the relatively poor skill of most of the climate models in simulating present-day large scale precipitation patterns, we identified two types of models: the climate models with moderate-to-normal (i.e., close to observations) precipitation amplitudes over the Amazonian basin; and the climate models with a low precipitation in that region and too high a precipitation on the equatorial Pacific coast. Under SRES A2 greenhouse gas forcing, the neural network simulates an increase in precipitation over the La Plata basin coherent with the mean model ensemble projection. Over the Amazonian basin, a decrease in precipitation is projected. However, the models strongly diverge, and the neural network was found to give more weight to models, which better simulate present-day climate conditions. In the southern tip of the continent, the models poorly simulate present-day climate. However, they display a fairly good convergence when simulating climate change response with a weak increase south of 45°S and a decrease in Chile between 30 and 45°S. Other scenarios (A1B and B1) strongly resemble the SRES A2 trends but with weaker amplitudes.     

Modelling microseismicity of a producing reservoir from coupled fluid‐flow and geomechanical simulation

In this paper, we investigate production induced microseismicity based on modelling material failure from coupled fluid‐flow and geomechanical simulation. The model is a graben style reservoir characterized by two normal faults subdividing a sandstone reservoir into three compartments. The results are analysed in terms of spatial and temporal variations in distribution of material failure. We observe that material failure and hence potentially microseismicity is sensitive to not only fault movement but also fluid movement across faults. For sealing faults, failure is confined to the volume in and around the well compartment, with shear failure localized along the boundaries of the compartment and shear‐enhanced compaction failure widespread throughout the reservoir compartment. For non‐sealing faults, failure is observed within and surrounding all three reservoir compartments as well as a significant distribution located near the surface of the overburden. All shear‐enhanced compaction failures are localized within the reservoir compartments. Fault movement leads to an increase in shear‐enhanced compaction events within the reservoir as well as shear events located within the side‐burden adjacent to the fault. We also evaluate the associated moment tensor mechanisms to estimate the pseudo scalar seismic moment of failure based on the assumption that failure is not aseismic. The shear‐enhanced compaction events display a relatively normal and tight pseudo scalar seismic moment distribution centred about 10⁶ Pa, whereas the shear events have pseudo scalar seismic moments that vary over three orders of magnitude. Overall, the results from the study indicate that it may be possible to identify compartment boundaries based on the results of microseismic monitoring.     

The influence of lithology on channel geometry and bed sediment organization in mountainous hillslope-coupled streams

Sediment transport and channel morphology in mountainous hillslope-coupled streams reflect a mixture of hillslope and channel processes. However, the influence of lithology on channel form and adjustment and sediment transport remains poorly understood. Patterns of channel form, grain size, and transport capacity were investigated in two gravel-bed streams with contrasting lithology (basalt and sandstone) in the Oregon Coast Range, USA, in a region in which widespread landslides and debris flows occurred in 1996. This information was used to evaluate threshold channel conditions and channel bed adjustment since 1996. Channel geometry, slope, and valley width were measured or extracted from LiDAR and sediment textures were measured in the surface and subsurface. Similar coarsening patterns in the first few kilometres of both streams indicated strong hillslope influences, but subsequent downstream fining was lithology-dependent. Despite these differences, surface grain size was strongly related to shear stress, such that the ratio of available to critical shear stress for motion of the median surface grain size at bankfull stage was around one over most of the surveyed lengths. This indicated hydraulic sorting of supplied sediment, independent of lithology. We infer a cycle of adjustment to sediment delivered during the 1996 flooding, from threshold conditions, to non-alluvial characteristics, to threshold conditions in both basins. The sandstone basin can also experience complete depletion of the gravel-size alluvium to sand size, leading to bedrock exposure because of high diminution rates. Although debris flows being more frequent in a basalt basin, this system will likely display threshold-like characteristics over a longer period, indicating that the lithologic control on channel adjustment is driven by differences in rock competence that control grain size and available gravel for bed load transport. © 2020 John Wiley & Sons, Ltd.     

Thermal inertia and bolometric Bond albedo values for Mimas, Enceladus, Tethys, Dione, Rhea and Iapetus as derived from Cassini/CIRS measurements

Spectra taken by Cassini’s Composite Infrared Spectrometer (CIRS) between 10 and 600 cm⁻¹ (17-1000 μm) of surface thermal emission of Mimas, Enceladus, Tethys, Dione, Rhea and Iapetus have been used to derive the thermal inertia and bolometric Bond albedo values. Only an upper limit for the bolometric Bond albedo of Iapetus’ dark leading side could be determined due to the insensitivity of the thermal model to albedo when albedos are very low. The thermal inertia in this region however is better constrained. The CIRS coverage of Enceladus is extensive enough that the latitudinal variation in these values from 60°S to 70°N has been determined in 10° wide bins. The bolometric Bond albedos determined here are consistent with literature values which show the surface of the saturnian icy moons to be covered in ice contaminated to varying degrees. The thermal inertia of the moons is shown to be in the range 9-, approximately 2-6 times lower than that of the Galilean satellites, implying a less well consolidated and more porous surface. The thermal inertias of Iapetus and Phoebe are somewhat higher, suggesting that the very low thermal inertias of satellites from Rhea inwards may be related to their probable coating of E-ring material. Latitudinal variations on the surface of Enceladus show that the bolometric Bond albedo and thermal inertia increase towards the active plume source at the south pole.     

New and exceptional discovery in the Upper Cretaceous of the Iberian Peninsula: the palaeontological site of “Lo Hueco”, Cuenca,Spain

The palaeontological site of “Lo Hueco” was discovered in Cuenca, Spain, in 2007. It includes a stratigraphic interval in “Garumn” facies belonging to the upper part of the Villalba de la Sierra Formation. A succession of versicolor marly mudstone levels (V, G1, R1, G2, R2 and M) can be observed at the site studied. This succession is partially modified by a sandy channel structure (C) and by a sulphated interval (S). The C structure and the G1, G2 and R2 (lower part) levels have an extremely rich and varied fossil concentration and have provided to date more than 8500 macroremains. These are mainly from vertebrates, but also from plants and invertebrates. In general, vertebrates are represented by mineralized bones with an early infilling of gypsum, a ferruginous crust, and a secondary precipitation of gypsum; invertebrates by internal moulds; and plants by carbonized remains. Among the vertebrates, titanosaur dinosaurs (some of them with partially articulated skeletons) are by far the most common representatives, although lepisosteid fishes, bothremydid turtles, squamate lizards, eusuchian crocodiles, and ornithischian and theropod dinosaurs are also well represented. The relative stratigraphic position and the palaeontological content of this site allow to attribute it to the upper Campanian-lower Maastrichtian. Interpretation of its materials suggests a near coast muddy flood plain crossed by distributary sandy channels environment, exposed to brackish to fresh water aquatic influence.