A comparison of three methods for downscaling daily precipitation in the Punjab region

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.

Determinant: Old algorithms, new insights (Extended Abstract)

In this paper we approach the problem of computing the characteristic polynomial of a matrix from the combinatorial viewpoint. We present several combinatorial characterizations of the coefficients of the characteristic polynomial, in terms of walks and closed walks of different kinds in the underlying graph. We develop algorithms based on these characterizations, and show that they tally with well-known algorithms arrived at independently from considerations in linear algebra.

The inhomogeneous extended Bose-Hubbard model: A mean-field theory

We develop an inhomogeneous mean-field theory for the extended Bose-Hubbard model with a quadratic, confining potential. In the absence of this potential, our mean-field theory yields the phase diagram of the homogeneous extended Bose-Hubbard model. This phase diagram shows a superfluid (SF) phase and lobes of Mott-insulator (MI), density-wave (DW), and supersolid (SS) phases in the plane of the chemical potential mu and on-site repulsion U; we present phase diagrams for representative values of V, the repulsive energy for bosons on nearest-neighbor sites. We demonstrate that, when the confining potential is present, superfluid and density-wave order parameters are nonuniform; in particular, we obtain, for a few representative values of parameters, spherical shells of SF, MI, DW, and SS phases. We explore the implications of our study for experiments on cold-atom dipolar condensates in optical lattices in a confining potential.

Daily relative humidity projections in an Indian river basin for IPCC SRES scenarios

A two-stage methodology is developed to obtain future projections of daily relative humidity in a river basin for climate change scenarios. In the first stage, Support Vector Machine (SVM) models are developed to downscale nine sets of predictor variables (large-scale atmospheric variables) for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) (A1B, A2, B1, and COMMIT) to R (H) in a river basin at monthly scale. Uncertainty in the future projections of R (H) is studied for combinations of SRES scenarios, and predictors selected. Subsequently, in the second stage, the monthly sequences of R (H) are disaggregated to daily scale using k-nearest neighbor method. The effectiveness of the developed methodology is demonstrated through application to the catchment of Malaprabha reservoir in India. For downscaling, the probable predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis data set for the period 1978-2000 and (2) simulations of the third-generation Canadian Coupled Global Climate Model for the period 1978-2100. The performance of the downscaling and disaggregation models is evaluated by split sample validation. Results show that among the SVM models, the model developed using predictors pertaining to only land location performed better. The R (H) is projected to increase in the future for A1B and A2 scenarios, while no trend is discerned for B1 and COMMIT.

Simulating the daily discharge of the Mandovi River, west coast of India

A hydrological modelling framework was assembled to simulate the daily discharge of the Mandovi River on the Indian west coast. Approximately 90% of the west-coast rainfall, and therefore discharge, occurs during the summer monsoon (June-September), with a peak during July-August. The modelling framework consisted of a digital elevation model (DEM) called GLOBE, a hydrological routing algorithm, the Terrestrial Hydrological Model with Biogeochemistry (THMB), an algorithm to map the rainfall recorded by sparse rain-gauges to the model grid, and a modified Soil Conservation Service Curve Number (SCS-CN) method. A series of discharge simulations (with and without the SCS method) was carried out. The best simulation was obtained after incorporating spatio-temporal variability in the SCS parameters, which was achieved by an objective division of the season into five regimes: the lean season, monsoon onset, peak monsoon, end-monsoon, and post-monsoon. A novel attempt was made to incorporate objectively the different regimes encountered before, during and after the Indian monsoon, into a hydrological modelling framework. The strength of our method lies in the low demand it makes on hydrological data. Apart from information on the average soil type in a region, the entire parameterization is built on the basis of the rainfall that is used to force the model. That the model does not need to be calibrated separately for each river is important, because most of the Indian west-coast basins are ungauged. Hence, even though the model has been validated only for the Mandovi basin, its potential region of application is considerable. In the context of the Prediction in Ungauged Basins (PUB) framework, the potential of the proposed approach is significant, because the discharge of these (ungauged) rivers into the eastern Arabian Sea is not small, making them an important element of the local climate system.

Stabilization of O-Mn-O clusters (Mn-5) in three dimensionally extended MOF structures: synthesis, structure and properties

Four new three-dimensional Mn2+ ion-containing compounds have been prepared by employing a hydrothermal reaction between Mn(CH3COO)(2)center dot 4H(2)O, sulfodibenzoic acid (H(2)SDBA), imidazole, alkali hydroxide and water at 220 degrees C for 1 day. The compounds have Mn-5 (1-4) clusters connected by SDBA, forming the three-dimensional structure. A time and temperature dependent study on the synthesis mixture revealed the formation of a one-dimensional compound, Mn(SDBA)(H2O)(2), at lower temperatures (T <= 180 degrees C). The stabilization of the fcu related topology in the compounds is noteworthy. Magnetic studies indicate strong anti-ferromagnetic interactions between the Mn2+ ions within the clusters in the temperature range 75-300 K. The rare participation of a sulfonyl group in the bonding is important and can pave way for the design of new structures.

Effect of high gold salt concentrations on the size and polydispersity of gold nanoparticles prepared by an extended Turkevich-Frens method

The Turkevich-Frens synthesis starting conditions are expanded, ranging the gold salt concentrations up to 2 mM and citrate/gold(III) molar ratios up to 18:1. For each concentration of the initial gold salt solution, the citrate/gold(III) molar ratios are systematically varied from 2:1 to 18:1 and both the size and size distribution of the resulting gold nanoparticles are compared. This study reveals a different nanoparticle size evolution for gold salt solutions ranging below 0.8 mM compared to the case of gold salt solutions above 0.8 mM. In the case of Au3+]<0.8 mM, both the size and size distribution vary substantially with the citrate/gold(III) ratio, both displaying plateaux that evolve inversely to Au3+] at larger ratios. Conversely, for Au3+]>= 0.8 mM, the size and size distribution of the synthesized gold nanoparticles continuously rise as the citrate/gold(III) ratio is increased. A starting gold salt concentration of 0.6 mM leads to the formation of the most monodisperse gold nanoparticles (polydispersity index<0.1) for a wide range of citrate/gold(III) molar ratios (from 4:1 to 18:1). Via a model for the formation of gold nanoparticles by the citrate method, the experimental trends in size could be qualitatively predicted:the simulations showed that the destabilizing effect of increased electrolyte concentration at high initial Au3+] is compensated by a slight increase in zeta potential of gold nanoparticles to produce concentrated dispersion of gold nanoparticles of small sizes.

Extended histories: improving regularity and performance in correlation prefetchers

Data Prefetchers identify and make use of any regularity present in the history/training stream to predict future references and prefetch them into the cache. The training information used is typically the primary misses seen at a particular cache level, which is a filtered version of the accesses seen by the cache. In this work we demonstrate that extending the training information to include secondary misses and hits along with primary misses helps improve the performance of prefetchers. In addition to empirical evaluation, we use the information theoretic metric entropy, to quantify the regularity present in extended histories. Entropy measurements indicate that extended histories are more regular than the default primary miss only training stream. Entropy measurements also help corroborate our empirical findings. With extended histories, further benefits can be achieved by triggering prefetches during secondary misses also. In this paper we explore the design space of extended prefetch histories and alternative prefetch trigger points for delta correlation prefetchers. We observe that different prefetch schemes benefit to a different extent with extended histories and alternative trigger points. Also the best performing design point varies on a per-benchmark basis. To meet these requirements, we propose a simple adaptive scheme that identifies the best performing design point for a benchmark-prefetcher combination at runtime. In SPEC2000 benchmarks, using all the L2 accesses as history for prefetcher improves the performance in terms of both IPC and misses reduced over techniques that use only primary misses as history. The adaptive scheme improves the performance of CZone prefetcher over Baseline by 4.6% on an average. These performance gains are accompanied by a moderate reduction in the memory traffic requirements.

Tuning of the extended concentric tube resonators

It has been shown recently that the acoustic performance of the extended tube expansion chambers can be improved substantially by making the extended inlet and outlet equal to half and quarter chamber lengths, duly incorporating the end corrections due to the evanescent higher order modes that would be generated at the discontinuities. Such chambers however suffer from the disadvantages of high back pressure and generation of aerodynamic noise at the area discontinuities. These two disadvantages can be overcome by means of a perforated bridge between the extended inlet and extended outlet. This paper deals with design or tuning of these extended concentric tube resonators.

Predictability and chaotic nature of daily streamflow

The predictability of a chaotic series is limited to a few future time steps due to its sensitivity to initial conditions and the exponential divergence of the trajectories. Over the years, streamflow has been considered as a stochastic system in many approaches. In this study, the chaotic nature of daily streamflow is investigated using autocorrelation function, Fourier spectrum, correlation dimension method (Grassberger-Procaccia algorithm) and false nearest neighbor method. Embedding dimensions of 6-7 obtained indicates the possible presence of low-dimensional chaotic behavior. The predictability of the system is estimated by calculating the system’s Lyapunov exponent. A positive maximum Lyapunov exponent of 0.167 indicates that the system is chaotic and unstable with a maximum predictability of only 6 days. These results give a positive indication towards considering streamflow as a low dimensional chaotic system than as a stochastic system.

A fully discrete C-0 interior penalty Galerkin approximation of the extended Fisher-Kolmogorov equation

A fully discrete C-0 interior penalty finite element method is proposed and analyzed for the Extended Fisher-Kolmogorov (EFK) equation u(t) + gamma Delta(2)u - Delta u + u(3) - u = 0 with appropriate initial and boundary conditions, where gamma is a positive constant. We derive a regularity estimate for the solution u of the EFK equation that is explicit in gamma and as a consequence we derive a priori error estimates that are robust in gamma. (C) 2013 Elsevier B.V. All rights reserved.

Generation of extended light-sheets for single and multi-photon fluorescence microscopy

We theoretically propose and computationally demonstrate the generation of extended light-sheet for fluorescence microscopy. This is made possible by the introduction of a specially designed double-window spatial filter that allows the light to pass through the periphery and center of a cylindrical lens. When illuminated with a plane wave, the proposed filter results in an extended depth-of-focus along with side-lobes which are due to other interferences in the transverse focal plane. Computational studies show a maximum extension of light-sheet by 3.38 times for single photon excitation and 3.68 times for multiphoton excitation as compared to state-of-art single plane illumination microscopy system. This technique may facilitate the study of large biological specimens (such as Zebrafish embryo and tissue) with high spatial resolution and reduced photobleaching. (C) 2013 AIP Publishing LLC.

Polymorphic phase boundaries and enhanced piezoelectric response in extended composition range in the lead free ferroelectric BaTi1-xZrxO3

Neutron powder diffraction study of Ba(Ti1-xZrx)O-3 at close composition intervals has revealed coexistence of ferroelectric phases: orthorhombic (Amm2) + tetragonal (P4mm) for 0.02 <= x <= 0.05 and rhombohedral (R3m) + orthorhombic (Amm2) for 0.07 <= x < 0.09. These compositions exhibit relatively enhanced piezoelectric properties as compared to their single phase counterparts outside this composition region, confirming the polymorphic phase boundary nature of the phase coexistence regions. (C) 2013 AIP Publishing LLC.