183 research outputs found
Structure of ll- VI Lattice Mismatched Epilayers used for Blue-Green Lasers for Underwater Communication
Critical thickness (hc) is calculated for capped and uncapped lattice mismatched II-VIsemiconductor epilayers. Both the old equilibrium theory and the improved theory have been used.The calculated values are compared with the experimental data on epilayers of several II-VIsemiconductors and alloys. The observed values of hc are larger than the calculated values. Howeverthe discrepancy is much smaller than that found in InGaAs/GaAs and GeSilSi layers. Moreover ascompared to InGaAs/GaA.s:a nd GeSilSi layers, the experimental data show a much smaller scatter andcan be fitted with one curve. Strain relaxation in layers with thickness h > hc is also calculated. Strainrelaxation in ZnSe layers grown on (100) GaAs shows good agreement with the equilibrium theory. Inother cases the observed relaxation is sluggish, the residual strain is larger than its calculated value.Thick highly mismatched layers behave differently. The residual strain agrees with theory anddislocations are distributed periodically, A model to interpret these observations is suggested.Implications of this study on the stability of 11V- I strained layers are discussed
A New Global Ocean Climatology
A new global ocean temperature and salinity climatology is proposed for two time periods: a long time mean using multiple sensor data for the 1900–2017 period and a shorter time mean using only profiling float data for the 2003–2017 period. We use the historical database of World Ocean Database 2018. The estimation approach is novel as an additional quality control procedure is implemented, along with a new mapping algorithm based on Data Interpolating Variational Analysis. The new procedure, in addition to the traditional quality control approach, resulted in low sensitivity in terms of the first guess field choice. The roughness index and the root mean square of residuals are new indices applied to the selection of the free mapping parameters along with sensitivity experiments. Overall, the new estimates were consistent with previous climatologies, but several differences were found. The cause of these discrepancies is difficult to identify due to several differences in the procedures. To minimise these uncertainties, a multi-model ensemble mean is proposed as the least uncertain estimate of the global ocean temperature and salinity climatology
Ocean ensemble forecasting. Part I: Ensemble Mediterranean winds from a Bayesian hierarchical model
A Bayesian hierarchical model (BHM) is developed to estimate surface vector
wind (SVW) fields and associated uncertainties over the Mediterranean Sea. The
BHM–SVW incorporates data-stage inputs from analyses and forecasts of the
European Centre for Medium-Range Weather Forecasts (ECMWF) and SVW
retrievals from the QuikSCAT data record. The process-model stage of the
BHM–SVW is based on a Rayleigh friction equation model for surface winds.
Dynamical interpretations of posterior distributions of the BHM–SVW parameters
are discussed. Ten realizations from the posterior distribution of the BHM–SVW
are used to force the data-assimilation step of an experimental ensemble ocean
forecast system for the Mediterranean Sea in order to create a set of ensemble
initial conditions. The sequential data-assimilation method of the Mediterranean
forecast system (MFS) is adapted to the ensemble implementation. Analyses
of sample ensemble initial conditions for a single data-assimilation period in
MFS are presented to demonstrate the multivariate impact of the BHM–SVW
ensemble generation methodology. Ensemble initial-condition spread is quantified
by computing standard deviations of ocean state variable fields over the ten ensemble
members. The methodological findings in this article are of two kinds. From the
perspective of statistical modelling, the process-model development is more closely
related tophysicalbalances than inpreviousworkwithmodels for the SVW.Fromthe
ocean forecast perspective, the generation of ocean ensemble initial conditions via
BHM is shown to be practical for operational implementation in an ensemble ocean
forecast system. Phenomenologically, ensemble spread generated via BHM–SVW
occurs on ocean mesoscale time- and space-scales, in close association with strong
synoptic-scale wind-forcing events. A companion article describes the impacts of
the BHM–SVW ensemble method on the ocean forecast in comparisons with more
traditional ensemble methods
Ocean ensemble forecasting. Part II: Mediterranean Forecast System response
This article analyzes the ocean forecast response to surface vector wind (SVW)
distributions generated by a Bayesian hierarchical model (BHM) developed in Part
I of this series. A new method for ocean ensemble forecasting (OEF), the socalled
BHM-SVW-OEF, is described. BHM-SVW realizations are used to produce
and force perturbations in the ocean state during 14 day analysis and 10 day
forecast cycles of the Mediterranean Forecast System (MFS). The BHM-SVW-OEF
ocean response spread is amplified at the mesoscales and in the pycnocline of
the eddy field. The new method is compared with an ensemble response forced
by European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble
prediction system (EEPS) surface winds, and with an ensemble forecast started from
perturbed initial conditions derived froman ad hoc thermocline intensified random
perturbation (TIRP) method. The EEPS-OEF shows spread on basin scales while the
TIRP-OEF response is mesoscale-intensified as in the BHM-SVW-OEF response.
TIRP-OEF perturbations fill more of the MFS domain, while the BHM-SVW-OEF
perturbations are more location-specific, concentrating ensemble spread at the sites
where the ocean-model response to uncertainty in the surface wind forcing is largest
Mediterranean Forecasting System: forecast and analysis assessment through skill scores
Abstract. This paper describes the first evaluation of the quality of the forecast and analyses produced at the basin scale by the Mediterranean ocean Forecasting System (MFS) (http://gnoo.bo.ingv.it/mfs). The system produces short-term ocean forecasts for the following ten days. Analyses are produced weekly using a daily assimilation cycle. The analyses are compared with independent data from buoys, where available, and with the assimilated data before the data are inserted. In this work we have considered 53 ten days forecasts produced from 16 August 2005 to 15 August 2006. The forecast skill is evaluated by means of root mean square error (rmse) differences, bias and anomaly correlations at different depths for temperature and salinity, computing differences between forecast and analysis, analysis and persistence and forecast and persistence. The Skill Score (SS) is defined as the ratio of the rmse of the difference between analysis and forecast and the rmse of the difference between analysis and persistence. The SS shows that at 5 and 30 m the forecast is always better than the persistence, but at 300 m it can be worse than persistence for the first days of the forecast. This result may be related to flow adjustments introduced by the data assimilation scheme. The monthly variability of SS shows that when the system variability is high, the values of SS are higher, therefore the forecast has higher skill than persistence. We give evidence that the error growth in the surface layers is controlled by the atmospheric forcing inaccuracies, while at depth the forecast error can be interpreted as due to the data insertion procedure. The data, both in situ and satellite, are not homogeneously distributed in the basin; therefore, the quality of the analyses may be different in different areas of the basin
Ocean Ensemble Forecasting, Part II: Mediterranean Forecast System Response
This paper analyzes the ocean forecast response to surface vector wind (SVW) distributions
generated by a Bayesian Hierarchical Model (BHM) developed in Part I (Milliff et al., 2009).
A new method for Ocean Ensemble Forecasting (OEF), so-called BHM-SVW-OEF, is described.
BHM-SVW realizations are used to produce and force perturbations in the ocean
state during 14-day analysis and 10-day forecast cycles of the Mediterranean Forecast System
(MFS). The BHM-SVW-OEF ocean response spread is amplified at the mesoscales and
pycnocline of the eddy field. The new method is compared to an ensemble response forced by
ECMWF Ensemble Prediction System (EEPS) surface winds, and to an ensemble forecast
started from perturbed initial conditions derived from an ad hoc Thermocline Intensified
Random Perturbation (TIRP) method. The EEPS-OEF shows spread at the basin scales
while the TIRP-OEF response is mesoscale intensified as in the BHM-SVW-OEF response.
TIRP-OEF perturbations fill more of the MFS domain while the BHM-SVW-OEF perturbations
are more location-specific, concentrating ensemble spread at the sites where the ocean
model response to uncertainty in the surface wind forcing is largest. The BHM-SVW-OEF
method offers a practical and objective means for producing short-term forecast spread by
modeling surface atmospheric forcing uncertainties that have maximum impact at the ocean
mesoscales
Mediterranean Forecasting System: forecast and analysis assessment through skill scores
This paper describes the first evaluation of the
quality of the forecast and analyses produced at the basin
scale by the Mediterranean ocean Forecasting System (MFS)
(http://gnoo.bo.ingv.it/mfs). The system produces short-term
ocean forecasts for the following ten days. Analyses are produced
weekly using a daily assimilation cycle. The analyses
are compared with independent data from buoys, where
available, and with the assimilated data before the data are
inserted. In this work we have considered 53 ten days forecasts
produced from 16 August 2005 to 15 August 2006.
The forecast skill is evaluated by means of root mean
square error (rmse) differences, bias and anomaly correlations
at different depths for temperature and salinity, computing
differences between forecast and analysis, analysis
and persistence and forecast and persistence. The Skill Score
(SS) is defined as the ratio of the rmse of the difference between
analysis and forecast and the rmse of the difference
between analysis and persistence. The SS shows that at 5 and
30m the forecast is always better than the persistence, but at
300m it can be worse than persistence for the first days of
the forecast. This result may be related to flow adjustments
introduced by the data assimilation scheme. The monthly
variability of SS shows that when the system variability is
high, the values of SS are higher, therefore the forecast has
higher skill than persistence.
We give evidence that the error growth in the surface layers
is controlled by the atmospheric forcing inaccuracies, while at depth the forecast error can be interpreted as due to the
data insertion procedure. The data, both in situ and satellite,
are not homogeneously distributed in the basin; therefore, the
quality of the analyses may be different in different areas of
the basin
Ordered vacancy network induced by the growth of epitaxial graphene on Pt(111)
We have studied large areas of (v3×v3)R30° graphene commensurate with a Pt(111) substrate. A combination of experimental techniques with ab initio density functional theory indicates that this structure is related to a reconstruction at the Pt surface, consisting of an ordered vacancy network formed in the outermost Pt layer and a graphene layer covalently bound to the Pt substrate. The formation of this reconstruction is enhanced if low temperatures and polycyclic aromatic hydrocarbons are used as molecular precursors for epitaxial growth of the graphene layers
Essential Constants for Spatially Homogeneous Ricci-flat manifolds of dimension 4+1
The present work considers (4+1)-dimensional spatially homogeneous vacuum
cosmological models. Exact solutions -- some already existing in the
literature, and others believed to be new -- are exhibited. Some of them are
the most general for the corresponding Lie group with which each homogeneous
slice is endowed, and some others are quite general. The characterization
``general'' is given based on the counting of the essential constants, the
line-element of each model must contain; indeed, this is the basic contribution
of the work. We give two different ways of calculating the number of essential
constants for the simply transitive spatially homogeneous (4+1)-dimensional
models. The first uses the initial value theorem; the second uses, through
Peano's theorem, the so-called time-dependent automorphism inducing
diffeomorphismsComment: 26 Pages, 2 Tables, latex2
A relocatable ocean model in support of environmental emergencies
During the Costa Concordia emergency case, regional, subregional, and relocatable ocean models have been used together with the oil spill model, MEDSLIK-II, to provide ocean currents forecasts, possible oil spill scenarios, and drifters trajectories simulations. The models results together with the evaluation of their performances are presented in this paper. In particular, we focused this work on the implementation of the Interactive Relocatable Nested Ocean Model (IRENOM), based on the Harvard Ocean Prediction System (HOPS), for the Costa Concordia emergency and on its validation using drifters released in the area of the accident. It is shown that thanks to the capability of improving easily and quickly its configuration, the IRENOM results are of greater accuracy than the results achieved using regional or subregional model products. The model topography, and to the initialization procedures, and the horizontal resolution are the key model settings to be configured. Furthermore, the IRENOM currents and the MEDSLIK-II simulated trajectories showed to be sensitive to the spatial resolution of the meteorological fields used, providing higher prediction skills with higher resolution wind forcing.MEDESS4MS Project; TESSA Project; MyOcean2 Projectinfo:eu-repo/semantics/publishedVersio
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