pinecone/core-2020-05-10-deduplication huggingface dataset:
Tuning of length-scale and observation-error for radar data assimilation using four dimensional variational (4D-Var) method

The effects of tuning of length-scale and observation-error on heavy rainfall forecasts are investigated. Length scale and observation error are tuned based on observation minus background (O - B) covariances and theoretically expected cost function values, respectively. Tuned length scale and observation error are applied to radar data assimilation using the Four Dimensional Variational (4D-Var) method. Length-scale tuning leads to improved Quantitative Precipitation Forecast (QPF) skill for heavy precipitation, better analyses, and reduced errors of wind, temperature, humidity, and hydrometeor forecasts. The effects of observation-error tuning are not as significant as those of length-scale tuning, and they are limited to improvements in QPF skill. This is because tuned observation errors are close to pre-assumed values. Proper tuning of length-scale and observation-error is essential for radar data assimilation using the 4D-Var method
Intraseasonal variation of the East Asian summer monsoon associated with the MJO

We investigate the daily variability of the East Asian summer monsoon (EASM) by projecting daily wind anomaly data onto the two major modes of an interannual multivariate Empirical Orthogonal Functions analysis. Mode 1, closely resembling the Pacific-Japan (PJ) pattern and referred to as PJ-mode, transits from positive to negative phase around mid-summer consistent with the Meiyu rains predominantly being an early summer phenomenon. Mode 2, which is influenced by the Indian summer monsoon (ISM) and referred to as ISM-mode, peaks in late July and early August and is associated with rainfall farther north over China. We then analyze the relation between the intraseasonal variation of the EASM and the Madden-Julian Oscillation (MJO) by analyzing circulation anomalies following MJO events. In the lower troposphere, the circulation anomalies associated with the MJO most strongly project on the PJ-mode. MJO phases 1-4 (5-8) favor the positive (negative) phase of the PJ-mode by favoring the anticyclonic (cyclonic) anomalies over the subtropical western North Pacific. In the upper troposphere, the circulation anomalies associated with the MJO project mainly on the ISM-mode
Evidence of convective transport in tropical West Pacific region during SHIVA experiment

Air masses in the convective outflows of four large convective systems near Borneo Island in Malaysia were sampled in the height range 11–13 km within the frame of the SHIVA (Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere) FP7 European project in November and December 2011. Correlated enhancements of CO, CH4 and the short-lived halogen species (CH3I and CHBr3) were detected when the aircraft crossed the anvils of the four systems. These enhancements were interpreted as the fingerprint of vertical transport from the boundary layer by the convective updraft and then horizontal advection in the outflow. For the four observations, the fraction f of air from the boundary layer ranged between 15 and 67%, showing the variability in transport efficiency depending on the dynamics of the convective system
Seasonal prediction of equatorial Atlantic sea surface temperature using simple initialization and bias correction techniques

Due to strong mean state‐biases most coupled models are unable to simulate equatorial Atlantic variability. Here, we use the Kiel Climate Model to assess the impact of bias reduction on the seasonal prediction of equatorial Atlantic sea surface temperature (SST). We compare a standard experiment (STD) with an experiment that employs surface heat flux correction to reduce the SST bias (FLX) and, in addition, apply a correction for initial errors in SST. Initial conditions for both experiments are generated in partially coupled mode, and seasonal hindcasts are initialized at the beginning of February, May, August and November for 1981–2012. Surface heat flux correction generally improves hindcast skill. Hindcasts initialized in February have the least skill, even though the model bias is not particularly strong at that time of year. In contrast, hindcasts initialized in May achieve the highest skill. We argue this is because of the emergence of a closed Bjerknes feedback loop in boreal summer in FLX that is a feature of observations but is missing in STD
Tropical precipitation influencing boreal winter midlatitude blocking

Recent studies using reanalysis data and complex models suggest that the Tropics influence midlatitude blocking. Here, the influence of tropical precipitation anomalies is investigated further using a dry dynamical model driven by specified diabatic heating anomalies. The model uses a quasi‐realistic setup based on idealized orography and an idealized representation of the land‐ocean thermal contrast. Results concerning the El Niño Southern Oscillation and the Madden‐Julian Oscillation are mostly consistent with previous studies and emphasize the importance of tropical dynamics for driving the variability of blocking at midlatitudes. It is also shown that a common bias in models of the Coupled Model Intercomparison Project Phase 5 (CMIP5), namely, excessive tropical precipitation, leads to an underestimation of midlatitude blocking in our model, also a common bias in the CMIP5 models. The strongest blocking anomalies associated with the tropical precipitation bias are found over Europe, where the underestimation of blocking in CMIP5 models is also particularly strong
Decadal-scale variability in hazardous winds in northern Switzerland since end of the 19th century

The decadal-scale variability in winter hazardous winds in northern Switzerland from 1871 to present is investigated in the Twentieth Century Reanalysis (20CR). Independent wind speed measurements taken at Zurich climate station show that the interannual and decadal variability in hazardous winds in northern Switzerland is realistically represented in the 20CR. Both time series exhibit pronounced decadal-scale variability with periods between approximately 36 and 47 years. At these periodicities, the hazardous wind variability in northern Switzerland is positively correlated with the variability in the North Atlantic Oscillation, however the strength and statistical significance of their co-variability varies over time
The impact of volcanic eruptions in the period 2000-2013 on global mean temperature trends evaluated in the HadGEM2-ES climate model

This is the final version of the article. Available from Wiley via the DOI in this record.The slow-down in global warming over the last decade has lead to significant debate about whether the causes are of natural or anthropogenic origin. Using an ensemble of HadGEM2-ES coupled climate model simulations we investigate the impact of overlooked modest volcanic eruptions. We deduce a global mean cooling of around -0.02 to -0.03K over the period 2008-2012. Thus while these eruptions do cause a cooling of the Earth and may therefore contribute to the slow-down in global warming, they do not appear to be the sole or primary cause. © 2014 Royal Meteorological Society.JMH, AJ, and GSJ were supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output
The influence of synoptic weather regimes on UK air quality: analysis of satellite column NO2

Groupings of Lamb weather types (LWTs) are used to assess the influence of synoptic meteorology on UK tropospheric column NO2. Composite satellite maps using daily 2005–2011 data show significant NO2 anomalies for each group. Hence, despite large day-to-day variability and significant uncertainty in individual retrievals, the satellite data can be used to determine national-scale column NO2 variations under different meteorological conditions. Under cyclonic conditions, NO2 is reduced, while anticyclonic conditions aid its accumulation, especially during winter, consistent with trapping of surface emissions and slower photochemical processing. This composite dataset can be used to test seasonal simulations of air quality models
Understanding and representing atmospheric convection across scales: Recommendations from the meeting held at Dartington Hall, Devon, UK, 28-30 January 2013

As weather and climate models move towards higher resolution, there is growing excitement about potential future improvements in the understanding and prediction of atmospheric convection and its interaction with larger-scale phenomena. A meeting in January 2013 in Dartington, Devon was convened to address the best way to maximise these improvements, specifically in a UK context but with international relevance. Specific recommendations included increased convective-scale observations, high-resolution virtual laboratories, and a system of parameterization test beds with a range of complexities. The main recommendation was to facilitate the development of physically based convective parameterizations that are scale-aware, non-local, non-equilibrium, and stochastic.Joint Weather and Climate Research Programme (JWCRP)Met Office Academic Partnership (MOAP)Natural Environment Research Council (NERC
The modulation of tropical storm activity in the Western North Pacific by the Madden-Julian Oscillation in GEOS-5 AGCM experiments

This study examines the influence of the Madden-Julian Oscillation (MJO) on tropical storm (TS) activity in the western North Pacific, using observations and GEOS-5 simulations at 50-km horizontal resolution. While GEOS-5 produces an MJO of faster propagation and weaker amplitude, it nevertheless reproduces the observed modulation of TS activity by the MJO with the highest TS genesis and increased track density in the active phases of MJO. The study suggests that the simulation of the sub-seasonal variability of TS activity could be improved by improving the simulations of the MJO in climate models.close0
Orographic disturbances of surface winds over the shelf waters adjacent to South Georgia

This study seeks to quantify the influence of South Georgia's orography on regional surface winds. A typical case study characterized by large-scale westerly winds is analysed using a high-resolution setup (3.3 km) of the Weather Research and Forecasting (WRF) regional model. The simulation produces significant fine-scale spatial variability which is in agreement with satellite-derived winds. The model simulation indicates that these orography-driven wind disturbances are responsible for strong wind stress curl and enhanced heat flux over the shelf waters surrounding South Georgia. Such surface forcing is entirely absent from the reanalysis, highlighting the need to use high-resolution forcing in regional ocean model simulation
An evaluation of CORDEX regional climate models in simulating precipitation over Southern Africa

This article evaluates the ability of the Coordinated Regional Downscaling Experiment
(CORDEX) regional climate models (RCMs) in simulating monthly rainfall variation during
the austral summer half year (October to March) over southern Africa, the timing of the
rainy season and the relative frequencies of rainfall events of varying intensities. The phasing
and amplitude of monthly rainfall evolution and the spatial progression of the wet season
onset are well simulated by the models. Notwithstanding some systematic biases in a few
models, the simulated onset and end of the rainy season and their interannual variability
are highly correlated with those computed from the reference data. The strongest agreements
between the reference and modelled precipitation patterns are found north of about 20∘S in the
vicinity of the Inter Tropical Convergence Zone. A majority of the RCMs adequately capture
the reference precipitation probability density functions, with a few showing a bias towards
excessive light rainfall events.The CORDEX-Africa programme was supported
by the Global Change System for Analysis, Research, and
Training (START) through the Climate Systems Analysis Group
of the University of Cape Town. Support from the World Climate Research Program (WCRP), the Climate and Development
Knowledge Network (CDKN), the International Centre
for Theoretical Physics (ICTP), the Swedish Meteorological
and Hydrological Institute (SMHI) and the European Union
Seventh Framework Programme.http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1530-261Xhb2016Geography, Geoinformatics and Meteorolog
On Identifying the role of Sun and the El Nino Southern Oscillation on Indian Summer Monsoon Rainfall

Open accessA solar influence on Indian Summer Monsoon (ISM) rainfall, identified in previous studies using the method of solar peak year compositing, may not be robust and can be influenced by other factors such as the El Nino Southern Oscillation (ENSO) and trends. Regression analysis, which takes into account variations across the whole solar cycle rather than just the minimum /maximum solar years, fails to detect any direct solar influence on the ISM during June–August. Regression suggests that the spatial pattern of ENSO, as imprinted in the sea level pressure in the Indian Ocean region, covering parts of Australia, has changed during the second half of last century. Thus ENSO impacts via variations in the local Hadley circulation may have played a role in modulating the ISM during that period. Finally, we discuss a possible indirect connection between the solar cycle and monsoon rainfall, which are different since the 1950s.Natural Environment Research Council (NERC
Pathways between soil moisture and precipitation in southeastern South America

Southeastern South America (SESA) is found to be the main hot spot of soil moisture?evapotranspiration coupling of South America during a dry summer. However, only its eastern part is a soil moisture?precipitation hot spot. Pathways between soil moisture and precipitation are evaluated through studying the coupling of soil moisture with surface and boundary layer variables. The outcome suggests that both the moist static energy and its vertical gradient are important for the development of precipitation, as a result of the total surface heat fluxes that are affected by soil moisture only in the eastern part of SESA.Fil: Ruscica, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinacion Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Sörensson, Anna A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinacion Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Menendez, Claudio Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinacion Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentin
KRIGING PREDICTION FROM A CIRCULAR GRID: APPLICATION TO WAFER DIFFUSION

In the production process of silicon wafers, which are crystalline slices used as substrate of electronic micro-circuits, the thickness of the SiO2 deposition on their top is a main characteristic to be controlled during the process. The experimental design that is commonly used to monitor the thickness to the target value consists of a regular array of points lying on concentric circles, the silicon wafer itself being a disk. To speed up the control process, the engineers aim to use just only a limited subset of such points. To reconstruct the values on untried locations of the silicon wafer, the Kriging interpolation has been proposed because of its recog- nized ability in providing fairly good predictions. In this paper, we consider two methodological issues related to universal Kriging models. First, we discuss the modeling of the covariance structure among the measured points; in fact, spatial data usually show a strong correlation when they come from spatially near observed points. Second, we put forward an algebraic method to assess the identifiability of trend models, based both on the full experimental design and on special fractions of it. Our findings are illustrated by a data set from an industrial applicatio
The impact of price skimming on supply and exit decisions

Cataloged from PDF version of article.Stochastic inventory control theory has focused on the order and/or pricing policy when the length of the selling period is known. In contrast to this focus, we examine the optimal length of the selling period—which we refer to as market exit time—in the context of a novel inventory replenishment problem faced by a supplier of a new, trendy, and relatively expensive product with a short life cycle. An important characteristic of the problem is that the supplier applies a price skimming strategy over time and the demand is modeled as a nonhomogeneous Poisson process with an intensity that is dependent on time. The supplier's problems of finding the optimal order quantity and market exit time, with the objective of maximizing expected profit, is studied. Procedures are proposed for joint optimization of the objective function with respect to the order quantity and the market exit time. Then, the effects of the order quantity and market exit time on the supplier's profitability are explored on the basis of a quantitative investigation. Copyright © 2014 John Wiley & Sons, Ltd
Some properties and applications of cumulative Kullback-Leibler information

The cumulative Kullback–Leibler information has been proposed recently as a suitable extension of Kullback–Leibler information to the cumulative distribution function. In this paper, we obtain various results on such a measure, with reference to its relation with other information measures and notions of reliability theory. We also provide some lower and upper bounds. A dynamic version of the cumulative Kullback–Leibler information is then proposed for past lifetimes. Furthermore, we investigate its monotonicity property, which is related to some new concepts of relative aging. Moreover, we propose an application to the failure of nanocomponents. Finally, in order to provide an application in image analysis, we introduce the empirical cumulative Kullback–Leibler information and prove an asymptotic result
On a new multivariate IFR ageing notion based on the standard construction

Many criteria of ageing for random variables or vectors have been proposed in the literature over many years. For instance, a random variable is increasing in failure rate (IFR) if, and only if, it can be ordered with an exponentially distributed random variable in the classical univariate convex transform order. A new multivariate generalization of the convex transform order has recently been proposed in the literature. In this work, we propose a new multivariate IFR notion for multivariate distributions based on comparisons in this new order with a properly defined exponentially distributed random vector. Properties, applications, and illustrations of this new notion are given as well.Félix Belzunce and Julio Mulero acknowledge the support received from the Ministerio de Economía y Competitividad (Spain) under grant MTM2012-34023-FEDER. Alfonso Suárez-Llorens and Antonio Arriaza acknowledge the support received from the Ministerio de Economía y Competitividad (Spain) under grant MTM2014-57559-P
Dynamic dependence networks: Financial time series forecasting and
  portfolio decisions (with discussion)

We discuss Bayesian forecasting of increasingly high-dimensional time series,
a key area of application of stochastic dynamic models in the financial
industry and allied areas of business. Novel state-space models characterizing
sparse patterns of dependence among multiple time series extend existing
multivariate volatility models to enable scaling to higher numbers of
individual time series. The theory of these "dynamic dependence network" models
shows how the individual series can be "decoupled" for sequential analysis, and
then "recoupled" for applied forecasting and decision analysis. Decoupling
allows fast, efficient analysis of each of the series in individual univariate
models that are linked-- for later recoupling-- through a theoretical
multivariate volatility structure defined by a sparse underlying graphical
model. Computational advances are especially significant in connection with
model uncertainty about the sparsity patterns among series that define this
graphical model; Bayesian model averaging using discounting of historical
information builds substantially on this computational advance. An extensive,
detailed case study showcases the use of these models, and the improvements in
forecasting and financial portfolio investment decisions that are achievable.
Using a long series of daily international currency, stock indices and
commodity prices, the case study includes evaluations of multi-day forecasts
and Bayesian portfolio analysis with a variety of practical utility functions,
as well as comparisons against commodity trading advisor benchmarks.Comment: 31 pages, 9 figures, 3 table
The Pathmox approach for PLS path modeling segmentation

This is the peer reviewed version of the following article: Giuseppe Lamberti, Aluja, T., Sanchez, G. The Pathmox approach for PLS path modeling segmentation. "Applied stochastic models in business and industry", Agost 2016, vol. 32, núm. 4, p. 453-468, which has been published in final form at DOI: 10.1002/asmb.2168. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Modeling has often failed to meet expectations, mostly because of the difficulty of comprehending relationships within phenomena and expressing them in mathematical models. Reality is frequently too complex to be reflected in a single model. This is often the case of marketing research, where variables relating to socioeconomics or psychographics constitute potential sources of heterogeneity. In such cases, the assumption of ‘one model fits all’ is unrealistic and may lead to inaccurate decisions. Thus, heterogeneity is a major issue in modeling. Once a model has been fitted to a complete data set that fulfills all validation criteria, it is difficult to establish whether it is valid for the whole population or it is merely an average artifact from several sub-populations. The purpose of this paper is to present the Pathmox approach to deal with heterogeneity in partial least squares path modeling. The idea behind Pathmox is to build a tree of path models that have look-alike structure as a binary decision tree, with different models for each of its nodes. The split criterion consists of an F statistic comparing two structural models. In order to ensure the suitability of the split criterion, a simulation study was conducted. Finally, we have applied Pathmox to a survey that measured Satisfaction among Spanish mobile phone operators. Results suggest that the Pathmox approach performs adequately in detecting partial least squares path modeling heterogeneity. Copyright © 2016 John Wiley & Sons, Ltd.Peer ReviewedPostprint (author's final draft