bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparisons of Time Series of Annual Mean Surface Air Temperature for China since the 1900s: Observations, Model Simulations, and Extended Reanalysis
Authors: Li Qingxiang , Zhang Lei , Xu Wenhui , Zhou Tianjun , Wang Jinfeng , Zhai Panmao , Jones Phil 
Published: August 2016

Abstract
Time series of global or regional average surface air temperature (SAT) are fundamental to climate change studies. A number of studies have developed several national and regional SAT series for China, but because of the diversity of the meteorological observational sites, the different quality control routines for processing the data, and the inconsistency of the statistical methods used, they differ in their long-term trends. This paper assesses the similarities and differences of the existing time series of the annual average SAT for China that are based upon historical meteorological observations since the 1900s. The results indicate that the China average is similar to the series for the Northern Hemisphere (NH) landmass, except that the initial warming of the NH series derived from the CRUTEM3/4 datasets, which represent global historical land surface air temperatures and near-surface air temperature anomalies over land, respectively, ends earlier (before the early 1940s) than in China’s series. A major difference among the existing China average time series is the 1940s warmth, a period when there were very few observations across the country because of World War II. The SAT anomalies for China during the 1930s to 1940s have been reduced by improved homogeneity assessment compared to previous estimates. The new improved time series is in better agreement with both the historical twentieth-century reanalysis data and the historical climate simulation of phase 5 of the Coupled Model Intercomparison Project (CMIP5) models. The new time series also shows the slowdown of the warming trend during the past 18 yr (1998–2015). The best estimate of a linear trend for increases in temperature with a 95% uncertainty range is 0.121° ± 0.009°C decade–1 for 1900–2015, indicating that the improved homogeneity assessment for China leads to a slightly greater trend than that based on raw data (0.107° ± 0.009°C decade–1).
The Interaction between Atmospheric Gravity Waves and Large-Scale Flows: An Efficient Description beyond the Nonacceleration Paradigm
Authors: Bölöni Gergely , Ribstein Bruno , Muraschko Jewgenija , Sgoff Christine , Wei Junhong , Achatz Ulrich 
Published: August 2016

Abstract
With the aim of contributing to the improvement of subgrid-scale gravity wave (GW) parameterizations in numerical weather prediction and climate models, the comparative relevance in GW drag of direct GW–mean flow interactions and turbulent wave breakdown are investigated. Of equal interest is how well Wentzel–Kramer–Brillouin (WKB) theory can capture direct wave–mean flow interactions that are excluded by applying the steady-state approximation. WKB is implemented in a very efficient Lagrangian ray-tracing approach that considers wave-action density in phase space, thereby avoiding numerical instabilities due to caustics. It is supplemented by a simple wave-breaking scheme based on a static-instability saturation criterion. Idealized test cases of horizontally homogeneous GW packets are considered where wave-resolving large-eddy simulations (LESs) provide the reference. In all of these cases, the WKB simulations including direct GW–mean flow interactions already reproduce the LES data to a good accuracy without a wave-breaking scheme. The latter scheme provides a next-order correction that is useful for fully capturing the total energy balance between wave and mean flow. Moreover, a steady-state WKB implementation as used in present GW parameterizations where turbulence provides by the noninteraction paradigm, the only possibility to affect the mean flow, is much less able to yield reliable results. The GW energy is damped too strongly and induces an oversimplified mean flow. This argues for WKB approaches to GW parameterization that take wave transience into account.
Increased Drought and Pluvial Risk over California due to Changing Oceanic Conditions
Authors: Kam Jonghun , Sheffield Justin 
Published: August 2016

Abstract
This study evaluates wintertime drought and pluvial risk over California through a Bayesian analysis of the upper and lower quartile of PRISM-based precipitation from 1901 to 2015. Risk is evaluated for different time windows to estimate the impact of interannual and decadal-to-multidecadal Pacific and Atlantic variability [positive and negative phases of ENSO, Pacific decadal oscillation (PDO), and Atlantic multidecadal oscillation (AMO)]. The impact of increasing trends in global sea surface temperature (SST) on drought and pluvial risk is also examined with idealized experimental runs from three climate models [GFDL Atmospheric Model version 2.1 (AM2.1), CCM3, and GFS]. The results show that the influence of oceanic conditions on drought risk in California is significant but has changed with higher risk in the last half century, especially in Southern California. The influence of oceanic conditions on pluvial risk has also been significant, especially during the warm phase of the Pacific Ocean, but increases over the last century are small compared to drought. Results from the idealized climate model experiments show that natural variability likely played a major role in the observed changes in risk, with the global SST increasing trend possibly tempering the increases regionally but not significantly over California. Despite evolving preferential oceanic conditions for a pluvial event during the 2015/16 winter (positive phase of ENSO and PDO), California received an 11% winter precipitation surplus, which was not sufficient for drought recovery. The seasonal and longer-term outlook for negative phases of ENSO and PDO implies that drought risk will be elevated in Southern California for the next decade.
How Does Interhemispheric Coupling Contribute to Cool Down the Summer Polar Mesosphere?
Authors: Karlsson Bodil , Becker Erich 
Published: August 2016

Abstract
Interhemispheric coupling is commonly associated with events of high planetary wave activity in the winter stratosphere triggering a heating of the polar mesopause region in the opposite hemisphere. Here, a more fundamental role that this mechanism plays in the absence of planetary wave variability is highlighted. This study focuses directly on the mesospheric part of the coupling chain, which is induced by the gravity wave drag in the winter mesosphere. To investigate the effect that the winter residual flow has on the summertime high-latitude upwelling, the Kühlungsborn Mechanistic General Circulation Model (KMCM) is used to compare a control simulation to runs where the parameterized gravity waves are removed from the winter hemisphere. The model response in the summer mesosphere reveals that the winter mesospheric residual circulation fosters a net (and substantial) cooling of the summer polar mesopause. These results offer an extension of the current view of interhemispheric coupling: from a mode of internal variability to a constant, gravity wave–driven phenomenon that is modulated by planetary wave activity.
Forecasting Hail Using a One-Dimensional Hail Growth Model within WRF
Authors: Adams-Selin Rebecca D. , Ziegler Conrad L. 
Published: August 2016

AbstractThe HAILCAST hail growth model has been integrated into the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model to predict hail size at the ground. Significant updates to the physics of the hail growth model are added, including variable hail density for both wet and dry growth regimes, an updraft multiplier that parameterizes advection of the hail embryo across an updraft, temperature-dependent ice collection efficiency, mass growth by vapor deposition or condensation, and an improved liquid water shedding threshold. Sample hail trajectories from three different updrafts are presented showing the effects of these physical updates. The updraft multiplier in particular improves the representation of the hail growth by not requiring a hail embryo to be locked in the center of an updraft until it grows large enough to fall. Five weeks of hail diameter forecasts are verified using a maximum expected size of hail (MESH) product. At points where WRF successfully forecasts convection, the forecasted hail size is within 0.5 in. 66% of the time.
The Baroclinic Moisture Flux
Authors: McTaggart-Cowan Ron , Gyakum John R. , Moore Richard W. 
Published: August 2016

Abstract
As subsaturated air ascends sloping isentropic surfaces, adiabatic expansion results in cooling and relative moistening. This process is an effective way to precondition the atmosphere for efficient moist processes while bringing parcels to saturation, and thereafter acts to maintain saturation during condensation. The goal of this study is to develop a diagnostic quantity that highlights circulations and regions in which the process of parcel moistening by isentropic ascent is active. Among the many features that rely on this process for the generation of an important fraction of their energy are oceanic cyclones, transitioning tropical cyclones, warm conveyor belts, diabatic Rossby vortices, and predecessor rain events. The baroclinic moisture flux (BMF) is defined as moisture transport by the component of vertical motion associated with isentropic upgliding. In warm conveyor belt and diabatic Rossby vortex case studies, the BMF appears to be successful in identifying the portion of the circulation in which this process is actively bringing parcels to saturation to promote the formation of clouds and precipitation. On a broader scale, the climatological maxima of the BMF highlight regions in which parcel moistening by isentropic ascent is anticipated to have a nonnegligible impact on the atmospheric state either through the action of the mean flow or via the repeated occurrence of isolated large-BMF events. The process-centric foundation of the BMF makes it useful as a filtering or exploratory variable, with the potential for extension into predictive applications.
On the Efficiency of Ban Estimates of the Parameter of an Exponential Population Based on Singly and Doubly Truncated or Censored Samples
Authors: Doss S. A. D. C. 
Published: August 2016

Summary A study is made regarding the precision of various types of samples in estimating the parameter of an exponential population. The following cases are considered : (i) a singly or doubly truncated sample of size N relative to a complete sample of the same size ; (ii) a singly or doubly censored sample of size N relative to a complete sample of size n, where n is the number of measured observations in the censored sample, It is observed that order case (i) right truncated and doubly truncated samples are inferior to the complete sample, whereas the left truncated sample is as good as the complete sample. Under case (ii) left censored and doubly censored samples are observed to be superior to the complete sample, while the right censored sample is as good as the complete sample.
Estimating the Mean by Two-Stage Sampling with Replacement
Authors: Ghosh Sakti P. 
Published: August 2016

Summary In two-stage sampling when sampling is done with replacement at each stage, a better estimate of the population mean can be obtained by considering the distinct units only at each stage. The mean of the distinct uniss is chosen as the desired estimate and an exact expression for the variance is obtained. A sufficient condition for the variance of the estimate based on distinct units to be smaller than the variance of the usual estimate of a two-stage sample based on all units is given.
On the Efficiency of Ban Estimates of the Parameters of Normal Populations Based on Truncated Samples
Authors: Doss S. A. D. C. 
Published: August 2016

Summary It is shown that when estimating tbe mean μ of a normal population, the standard deviation σ being known. the BAN estimate of μ based on a truncated sample of size n is less efficient than that based on a complete sample of the same size whatever be the point of truncation xa. On the contrary, when estimating σ alone μ being known, the BAN estimate of σ based on the truncated sample is substantially more efficient than that based on the complete sample whenever xa> μ in the case of left truncation, and xa< μ in the case of right truncation.
Non-Parametric Tests for the Bivariate Two-Sample Location Problem
Authors: Chatterjee Shoutir Kishore , Sen Pranab Kumar 
Published: August 2016

Summary In this paper, the Wilcoxon-Mann-Whitney rank-sum test and Mood's median test for the univariate two-sample location problem have been extended to the case of two variables, following a conditional approach. Various properties of the proposed tests have been studied and their asymptotic powers compared.
Operating Characteristic and Expected Sample Size of a Sequential Probability Ratio Test for the Simple Exponential Distribution
Authors: Raghavachari M. 
Published: August 2016

Summary For the problem of testing the simple hypothesis H : θ = θ1 against the simple alternative K : θ = θ2 with θ2 > θ1 , where θ is the unknown parameter of the simple exponential distribution, the familar Wald's Sequential Probability ratio test may be adopted. It is shown in the present paper that for a class of sequential probability ratio tests, exact expressions for the operating characteristic and the expected sample size can be given. The nature of the expected sample size function and the effect of Walo's approximations to the stopping bounds of the sequential probability ratio test are also studied.
Robust Sequential Confidence Intervals for the Behrens–Fisher Problem*
Authors: Ghosh Malay 
Published: August 2016

Summary The problem of providing a bounded length (sequential) confidence interval for the median of a symmetric (but otherwise unknown) distribution based on a general class of one-sample rank-order statistics was investigated in (Sen & Ghosh, 1971). The purpose of the present note is to indicate how the techniques developed there can be extended to the two-sample problem. It has been shown that in particular for the Behrens- Fisher situation (see e.g., Høyland, 1965 or Ramchandramurty, 1966), when the proposed procedure is based on the “normal-scores” statistic, under very general conditions on the unknown distribution function (d.f.), it is asymptotically at least as efficient as an analogous procedure suggested in (Robbins, Simons & Starr, 1967) and (Srivastava, 1970).
Optimum Nonparametric Inference of the Partial Regression Coefficients
Authors: Samanta M. 
Published: August 2016

Summary IN this paper the problem of nonparametric inference about the regression vector in a linear regression in a ( k + 1) variate population has been considered. It is assumed that the conditional density function of Y given ( X1 X2, ..., Xk) = ( x1 , x2, ..., xk) is f( y— β0 — β1 x1—...— βkxk)where the form of f is unknown and ( β1, β2, ..., βk) is the regression vector (in the linear regression of Yon X1, X2, ..., Xk) which is to be estimated. Without loss of generality we assume β0 to be zero. It is also assumed that X1, X2, ..., Xk are bounded random variables. In the present study nonparametric estimates of the density function are obtained by the so-called kernel method. This gives rise to the concept of an empirical likelihood function. Motivated by the likelihood principle we then obtain an estimate of the regression vector, proceeding formally by maximizing the empirical likelihood function. For technical reasons, the tail observations have been treated in a different way from other observations. In fact, the observations in the tails have been pooled into two classes. The large sample properties of this estimate have been derived by using the convergence properties of kernel estimates of the density function and its derivatives in conjunction with the properties of U-statistic. It is found that the large sample properties of this estimate are very close to the large sample properties of the corresponding maximum likelihood estimate.
Asymptotic Distribution of Sample Quantiles for Exchangeable Random Variables
Authors: Chanda K. C. 
Published: August 2016

Summary The purpose of this article is to investigate the ‘large sample’ properties of sample quantiles when we assume that the basic random variables are exchangeable (ref. Loève (1960) p. 365). It is shown that under different conditions (to be specified below) on the nature of these exchangeable random variables the distribution of the sample quantile Xr : n where Xr : n is the rth order statistic for the first n exchangeable random variables [Formula: see text] tends, as n → ∞, to different nondegenerate forms. As an example, the special case of random variables with equicor-related multivariate normal distribution is discussed.
Construction of BIBD'S from OA'S and Combinatorial Arrangements Analogous to OA'S
Authors: Mukhopadhyay A. C. 
Published: August 2016

Summary The paper considers a generalisation of the result by Ramanujacharyulu (1966). Orthogonal arrays of type II defined by Rao (1961) are utilised for the purpose. It also contains a generalisation of a theorem by Shrikhande and Bose (1960) on the construction of BIBD's with the help of OA's of strength 2.
Extended Generalized Right Angular Designs and their Applications as Confounded Asymmetrical Factorial Experiments
Authors: Raghavarao D. , Aggarwal K. R. 
Published: August 2016

Summary In this paper the authors introduce extended generalized right angular (EGRA) designs as generalizations of generalized right angular (GRA) designs of Tharthare (1965) to enlarge the scope of confounding asymmetrical factorial experiments. The applications of two series of these designs as confounded asymmetrical factorial experiments were also discussed.
Some Optimal Selection Procedures for Dependent Normal Populations
Authors: Hsu Tong—An 
Published: August 2016

We consider k dependent normal populations having known equal variance. The problem is to select the population associated with the largest mean. Let π1, ..., πk be k populations. We assume that the random variable Xi associated with πi ( i = 1, ..., k). Let X1, ..., Xk be k—variate normal distribution with unknown mean μ1, ... , μk and with equal variance σ2 and with correlation matrix { ρi j} For two case : (a) ρi j = aiaj for i ≠ j and (b) ρi j = ρ, for i ≠ j, we construct some optimal subset selection procedure to select a subset of the k dependent normal population containing the largest population mean. AMS ( 1980) subject classification : Primary 62F07 ; Secondary 62030
Detailed Statistical Inference—An Alternative Non-Bayesian Approach : Two-Decision Problem
Authors: Chatterjee Shoutir Kishore , Chattopadhyay Gaurangadeb 
Published: August 2016

In this paper we propose a new approach to detailed inference for any two-decision problem under the frequentist framework, based on a somewhat different interpretation of the confidence coefficients in terms of betting odds. We first elaborate this interpretation with reference to summary inference and enlarge the interpretation to the needs of detailed inference. The actual application of the proposed technique requires the choice of some suitable utility functions. We illustrate our ideas through some examples. AMS Subject Classification: 62 A 99.
Selection Procedures for Location Parameters Based on Two-Sample U-Statistics
Authors: Kumar Narinder , Gill Amar Nath , Mehta Gobind P . 
Published: August 2016

Let π1, ... , πk be k independent populations and let Fi ( x)= F( x - θi) be the absolutely continuous cumulative distribution function (cdf) of the i-th population indexed by the location parameter θi; i=1,,.... k. A class of subset selection procedures based on sub-sample extrema for unequal sample sizes is proposed for the problem of selecting a subset from ( π1, .... πk) which contains the population with largest location parameter. The proposed subset selection procedures are then compared with the subset selection procedures of Hsu (1981) in the sense of Pitman ARE (asymptotic relative efficiency). It is shown that these procedures can approximately be implemented with the help of existing tables and sample size sufficient for their implementation, based on simulation results, is discussed. AMS (1980) Subject Classification: Primary 62F07; Secondary 62H10
Construction of Generalized Cyclic Combinatorially Balanced Designs for First Order Residual Treatment Effects
Authors: Vartak M.N. , Mashouri G.H. , Aggarwal M.L. 
Published: August 2016

Designs combioatorially balanced for residual treatment effects of various orders, (especialJy first and second orders) with and without interactions were discussed in considerable details by williams (1949). Construction of combinatorially balanced designs for residual treatment effects was also considered by Patterson (1952); Hedayat and Afsarinejad (1975, 1978); Cheng and Wu (1980). An excellent account of such designs is given by Jones and Kenward (1989). In this paper, a method of construction of generalized cyclic designs combinatorially balanced for residual treatment effects of the first order without interactions, is presented. The method is based on an extension of theorems on symmetricaliy repeated difference sets developed by Bose (1939) and others. See Raghavarao (1971) for deiails, AMS (1980) Subject Classification: Primary 62k99; Secondary 05B10,05B30
Statistics : A Key Technology for Development—How well have We Used the Key ?*
Authors: Parikh Kirit S. 
Published: August 2016

I am deeply honoured to be invited to aive the First Soumitra Kumar Chakravarti Memorial Lecture. Calcutta has been the cradle of statistics in India where many distinguished great statisticians of India have grown. Many of them have been associated with tho Calcutta Statistical Association. I am therefore, particlarly honoured that you have asked me, who is not a statistician by training, to give this Pirst Memorial Lecture, I do hope, the viewpoints of a user of statistics will be found useful.
On Stochastic Ordering and a General Class of Poverty Indexes
Authors: Chatterjee Shoutir Kishore , Sen Pranab Kumar 
Published: August 2016

Although measures of diversity and inequality have been extensively proposed in socio-economic and health perspectives, violation of a subtle monotonicity criterion (under stochastic ordering) diminishes their rationality and utility in the context of poverty and other ecomomic indexes. A modification is proposed here to develop certain stochastic ordering monotonicity preserving diversity measures that overcome this drawback. Such measures are shown to be invariant under increasing transformation, and thereby appropriate for (partially) ordered categorical response data models. AMS{2000) Subject Classification: 62H17, 62-07.
Bayesian Nonparametric Estimation of Intensity Functions Using Markov Chain Monte Carlo Method
Authors: Deshpande J.V. , Mukhopadhyay M. , Nimbalkar U.V. Naik 
Published: August 2016

Let N( t) be a counting process indicating the failures (and instantaneous repairs) of a repairable system up to time t. We model the probabilistic behaviour of the process by a nonhomogeneous Poisson process (NHHP) with intensity function λ( t). In the absence of any grounds in favour of a specific parametric form for λ( t) we assume that it is constant between failure epochs and at these epochs receives a jump (the damage-atfrulure- model). Again we don't know the heights of these jumps. Therefore we assume a heirarchical Bayes formulation. The heights of the jumps are assumed to have constrained conditional gamma distributions. The hyperparameters of the gamma distribution are assumed to have known uniform distributions. The exact Bayes solutions are analytically intractable. Hence we provide a scheme of simulation via the Metropolis-Hastings algorithm to estimate the features of the posterior distribution. The methodology is illustrated by applying it to a well known data set. AMS (2000) Subject Classification: Primary 62F15, 62G05; Secondary 65C05.