Estimating the uncertainty of areal precipitation using data assimilation

We present a method to estimate spatially and temporally variable uncertainty of areal precipitation data. The aim of the method is to merge measurements from different sources, remote sensing and in situ, into a combined precipitation product and to provide an associated dynamic uncertainty estimate. This estimate should provide an accurate representation of uncertainty both in time and space, an adjustment to additional observations merged into the product through data assimilation, and flow dependency. Such a detailed uncertainty description is important for example to generate precipitation ensembles for probabilistic hydrological modelling or to specify accurate error covariances when using precipitation observations for data assimilation into numerical weather prediction models. The presented method uses the Local Ensemble Transform Kalman Filter and an ensemble nowcasting model. The model provides information about the precipitation displacement over time and is continuously updated by assimilation of observations. In this way, the precipitation product and its uncertainty estimate provided by the nowcasting ensemble evolve consistently in time and become flow-dependent. The method is evaluated in a proof of concept study focusing on weather radar data of four precipitation events. The study demonstrates that the dynamic areal uncertainty estimate outperforms a constant benchmark uncertainty value in all cases for one of the evaluated scores, and in half the number of cases for the other score. Thus, the flow dependency introduced by the coupling of data assimilation and nowcasting enables a more accurate spatial and temporal distribution of uncertainty. The mixed results achieved in the second score point out the importance of a good probabilistic nowcasting scheme for the performance of the method

Numerical renormalization group calculation of impurity internal energy and specific heat of quantum impurity models

We introduce a method to obtain the specific heat of quantum impurity models via a direct calculation of the impurity internal energy requiring only the evaluation of local quantities within a single numerical renormalization group (NRG) calculation for the total system. For the Anderson impurity model, we show that the impurity internal energy can be expressed as a sum of purely local static correlation functions and a term that involves also the impurity Green function. The temperature dependence of the latter can be neglected in many cases, thereby allowing the impurity specific heat, $C_{\rm imp}$, to be calculated accurately from local static correlation functions; specifically via $C_{\rm imp}=\frac{\partial E_{\rm ionic}}{\partial T} + 1/2\frac{\partial E_{\rm hyb}}{\partial T}$, where $E_{\rm ionic}$ and $E_{\rm hyb}$ are the energies of the (embedded) impurity and the hybridization energy, respectively. The term involving the Green function can also be evaluated in cases where its temperature dependence is non-negligible, adding an extra term to $C_{\rm imp}$. For the non-degenerate Anderson impurity model, we show by comparison with exact Bethe ansatz calculations that the results recover accurately both the Kondo induced peak in the specific heat at low temperatures as well as the high temperature peak due to the resonant level. The approach applies to multiorbital and multichannel Anderson impurity models with arbitrary local Coulomb interactions. An application to the Ohmic two state system and the anisotropic Kondo model is also given, with comparisons to Bethe ansatz calculations. The new approach could also be of interest within other impurity solvers, e.g., within quantum Monte Carlo techniques.Comment: 16 pages, 15 figures, published versio

The Hamburg Tornado (7 June 2016) from the perspective of low-cost high-resolution radar data and weather forecast model

A tornado hit the northeastern suburbs of Hamburg, Germany, on 7 June 2016. It had an estimated strength of upper end F1 on the Fujita scale and was short-lived with an approximate duration of only 13 min and a path length of just about 1.3 km. We demonstrate that such a small-scale, extreme event can be observed and forecasted accurately by a low-cost radar and by an atmospheric model with low computational costs, respectively. Observations from a low-cost single polarized X-band radar covering the urban area of Hamburg with 60 m spatial and 30 s temporal resolution are analyzed with respect to their ability to capture the development as well as the track of the tornado. In contrast to the national C-band radar network, the X-band radar is capable of capturing the hook echo of the tornado as well as the circular pattern in rain rates, because of its higher resolution in space and time. High-resolution forecasts of the tornado event are conducted with the computational efficient Conformal Cubic Atmosphere Model (CCAM) in order to test the capability of predicting the tornado with a lead time of a few hours. A three step downscaling method is used to obtain a spatial resolution of 1 km with initial conditions taken from the NCEP analysis. Calculated severe weather indices clearly indicate a potential for a tornado. CCAM cannot explicitly resolve small scale tornadic features but the model simulates a strong convective cell only a few kilometers apart from the tornadic thunderstorm observed by the radar

Effective algebraic degeneracy

We prove that any nonconstant entire holomorphic curve from the complex line C into a projective algebraic hypersurface X = X^n in P^{n+1}(C) of arbitrary dimension n (at least 2) must be algebraically degenerate provided X is generic if its degree d = deg(X) satisfies the effective lower bound: d larger than or equal to n^{{(n+1)}^{n+5}}

Reaction wavefront theory of notochord segment patterning

The vertebrate axis is segmented into repetitive structures, the vertebrae. In fish, these segmented structures are thought to form from the paraxial mesoderm and the adjacent notochord. Recent work revealed an autonomous patterning mechanism in the zebrafish notochord, with inputs from the segmented paraxial mesoderm. The notochord pattern is established in a sequential manner, progressing from anterior to posterior. Building on this previous work, here, we propose a reaction wavefront theory describing notochord patterning in zebrafish. The pattern is generated by an activator–inhibitor reaction–diffusion mechanism. Cues from the paraxial mesoderm are introduced as a profile of inhibitor sinks. Reactions are turned on by a wavefront that advances from anterior to posterior. We show that this reaction wavefront ensures that a pattern is formed sequentially, in register with the cues, despite the presence of fluctuations. We find that the velocity and shape of the reaction wavefront can modulate the prevalence of defective patterns. Normal patterning is supported in a wide range of sink profile wavelengths, while a minimum sink strength is required for the pattern to follow the cues. The theory predicts that distinct defect types occur for small or large wavelengths. Thus, the reaction wavefront theory provides a possible scenario for notochord patterning, with testable predictions that prompt future experiments.Fil: Fernández Arancibia, Sol Maria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; ArgentinaFil: Oates, Andrew C.. Ecole Polytechnique Fédérale de Lausanne; SuizaFil: Schulte Merker, Stefan. Westfälische Wilhelms Universität; AlemaniaFil: Morelli, Luis Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Institut Max Planck fur Molekulare Physiologie; Alemani

Living IoT: A Flying Wireless Platform on Live Insects

Sensor networks with devices capable of moving could enable applications ranging from precision irrigation to environmental sensing. Using mechanical drones to move sensors, however, severely limits operation time since flight time is limited by the energy density of current battery technology. We explore an alternative, biology-based solution: integrate sensing, computing and communication functionalities onto live flying insects to create a mobile IoT platform. Such an approach takes advantage of these tiny, highly efficient biological insects which are ubiquitous in many outdoor ecosystems, to essentially provide mobility for free. Doing so however requires addressing key technical challenges of power, size, weight and self-localization in order for the insects to perform location-dependent sensing operations as they carry our IoT payload through the environment. We develop and deploy our platform on bumblebees which includes backscatter communication, low-power self-localization hardware, sensors, and a power source. We show that our platform is capable of sensing, backscattering data at 1 kbps when the insects are back at the hive, and localizing itself up to distances of 80 m from the access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang, In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201

Efficiencies and armature reactions of 500 volt shunt motors

Thesis (BS)--University of Illinois, 1898M

MicroRNA-24 regulates vascularity after myocardial infarction

BACKGROUND: Myocardial infarction leads to cardiac remodeling and development of heart failure. Insufficient myocardial capillary density after myocardial infarction has been identified as a critical event in this process, although the underlying mechanisms of cardiac angiogenesis are mechanistically not well understood. METHODS AND RESULTS: Here, we show that the small noncoding RNA microRNA-24 (miR-24) is enriched in cardiac endothelial cells and considerably upregulated after cardiac ischemia. MiR-24 induces endothelial cell apoptosis, abolishes endothelial capillary network formation on Matrigel, and inhibits cell sprouting from endothelial spheroids. These effects are mediated through targeting of the endothelium-enriched transcription factor GATA2 and the p21-activated kinase PAK4, which were identified by bioinformatic predictions and validated by luciferase gene reporter assays. Respective downstream signaling cascades involving phosphorylated BAD (Bcl-XL/Bcl-2-associated death promoter) and Sirtuin1 were identified by transcriptome, protein arrays, and chromatin immunoprecipitation analyses. Overexpression of miR-24 or silencing of its targets significantly impaired angiogenesis in zebrafish embryos. Blocking of endothelial miR-24 limited myocardial infarct size of mice via prevention of endothelial apoptosis and enhancement of vascularity, which led to preserved cardiac function and survival. CONCLUSIONS: Our findings indicate that miR-24 acts as a critical regulator of endothelial cell apoptosis and angiogenesis and is suitable for therapeutic intervention in the setting of ischemic heart disease. [KEYWORDS: Animals, Apoptosis/drug effects, Arterioles/pathology, Capillaries/pathology, Cell Hypoxia, Cells, Cultured/drug effects/metabolism, Collagen, Drug Combinations, Drug Evaluation, Preclinical, Endothelial Cells/ metabolism/pathology, GATA2 Transcription Factor/biosynthesis/genetics, Gene Expression Profiling, Heart Failure/etiology, Heme Oxygenase-1/biosynthesis/genetics, Laminin, Male, Mice, Mice, Inbred C57BL, MicroRNAs/antagonists & inhibitors/genetics/ physiology, Myocardial Infarc

Origin of symbol-using systems: speech, but not sign, without the semantic urge

Natural language—spoken and signed—is a multichannel phenomenon, involving facial and body expression, and voice and visual intonation that is often used in the service of a social urge to communicate meaning. Given that iconicity seems easier and less abstract than making arbitrary connections between sound and meaning, iconicity and gesture have often been invoked in the origin of language alongside the urge to convey meaning. To get a fresh perspective, we critically distinguish the origin of a system capable of evolution from the subsequent evolution that system becomes capable of. Human language arose on a substrate of a system already capable of Darwinian evolution; the genetically supported uniquely human ability to learn a language reflects a key contact point between Darwinian evolution and language. Though implemented in brains generated by DNA symbols coding for protein meaning, the second higher-level symbol-using system of language now operates in a world mostly decoupled from Darwinian evolutionary constraints. Examination of Darwinian evolution of vocal learning in other animals suggests that the initial fixation of a key prerequisite to language into the human genome may actually have required initially side-stepping not only iconicity, but the urge to mean itself. If sign languages came later, they would not have faced this constraint