228 research outputs found
Thermal Expansion and Magnetostriction Studies of a Kondo Lattice Compound: Ceagsb2
We have investigated a single crystal of CeAgSb2 using low field
ac-susceptibility, thermal expansion and magnetostriction measurements in the
temperature range 1.5K to 90K. The ac-susceptibility exhibits a sharp peak at
9.7K for both B//c and B perp c due to the magnetic ordering of the Ce moment.
The thermal expansion coefficient alpha, exhibits highly anisotropic behaviour
between 3K and 80K : alpha is positive for dL/L perp c, but negative for dL/L
// c. Furthermore, alpha (for dL/L) perp c (i.e. in ab-plane) exhibits a sharp
peak at TN followed by a broad maximum at 20K, while a sharp negative peak at
TN followed by a minimum at 20K has been observed for (dL/L //) the c
direction. The observed maximum and minimum in alpha(T) at 20K have been
attributed to the crystalline field effect on the J=5/2 state of the Ce3+ ion.
The magnetostriction also exhibits anisotropic behaviour with a large
magnetostriction along the c-axis. The ab-plane magnetostriction exhibits a
peak at B=3.3T at 3K, which is consistent with the observed peak in the
magnetoresistance measurements.Comment: 4 Pages (B5), 3 figures, submitted to SCES200
Wavelet transform modulus maxima based fractal correlation analysis
The wavelet transform modulus maxima (WTMM) used in the singularity analysis
of one fractal function is extended to study the fractal correlation of two
multifractal functions. The technique is developed in the framework of joint
partition function analysis (JPFA) proposed by Meneveau et al. [1] and is shown
to be equally effective. In addition, we show that another leading approach
developed for the same purpose, namely, relative multifractal analysis, can be
considered as a special case of JPFA at a particular parameter setting.Comment: 18 pgs, 5 fig
Description and validation of an AOT product over land at the 0.6 μm channel of the SEVIRI sensor onboard MSG
The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) launched in 2003 by EUMETSAT is dedicated to the Nowcasting applications and Numerical Weather Prediction and to the provision of observations for climate monitoring and research. We use the data in visible and near infrared (NIR) channels to derive the aerosol optical thickness (AOT) over land. The algorithm is based on the assumption that the top of the atmosphere (TOA) reflectance increases with the aerosol load. This is a reasonable assumption except in case of absorbing aerosols above bright surfaces. We assume that the minimum in a 14-days time series of the TOA reflectance is, once corrected from gaseous scattering and absorption, representative of the surface reflectance. The AOT and the aerosol model (a set of 5 models is used), are retrieved by matching the simulated TOA reflectance with the TOA reflectances measured by SEVIRI in its visible and NIR spectral bands. <br><br> The high temporal resolution of the data acquisition by SEVIRI allows to retrieve the AOT every 15 min with a spatial resolution of 3 km at sub-satellite point, over the entire SEVIRI disk covering Europe, Africa and part of South America. The resulting AOT, a level 2 product at the native temporal and spatial SEVIRI resolutions, is presented and evaluated in this paper. <br><br> The AOT has been validated using ground based measurements from AErosol RObotic NETwork (AERONET), a sun-photometer network, focusing over Europe for 3 months in 2006. The SEVIRI estimates correlate well with the AERONET measurements, <i>r</i> = 0.64, with a slight overestimate, bias = &minus;0.017. The sources of errors are mainly the cloud contamination and the bad estimation of the surface reflectance. The temporal evolutions exhibited by both datasets show very good agreement which allows to conclude that the AOT Level 2 product from SEVIRI can be used to quantify the aerosol content and to monitor its daily evolution with a high temporal frequency. The comparison with daily maps of Moderate Resolution Imaging Spectroradiometer (MODIS) AOT level 3 product shows qualitative good agreement in the retrieved geographic patterns of AOT. <br><br> Given the high spatial and temporal resolutions obtained with this approach, our results have clear potential for applications ranging from air quality monitoring to climate studies. This paper presents a first evaluation and validation of the derived AOT over Europe in order to document the overall quality of a product that will be made publicly available to the users of the aforementioned research communities
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Cloud information content analysis of multi-angular measurements in the oxygen A-band: application to 3MI and MSPI
The vertical distribution of cloud cover has a significant impact on a large number of meteorological and climatic processes. Cloud top altitude and cloud geometrical thickness are then essential. Previous studies established the possibility of retrieving those parameters from multi-angular oxygen A-band measurements. Here we perform a study and comparison of the performances of future instruments. The 3MI (Multi-angle, Multi-channel and Multi-polarization Imager) instrument developed by EUMETSAT, which is an extension of the POLDER/PARASOL instrument, and MSPI (Multi-angles Spectro-Polarimetric Imager) develoloped by NASA's Jet Propulsion Laboratory will measure total and polarized light reflected by the Earth's atmosphere–surface system in several spectral bands (from UV to SWIR) and several viewing geometries. Those instruments should provide opportunities to observe the links between the cloud structures and the anisotropy of the reflected solar radiation into space. Specific algorithms will need be developed in order to take advantage of the new capabilities of this instrument. However, prior to this effort, we need to understand, through a theoretical Shannon information content analysis, the limits and advantages of these new instruments for retrieving liquid and ice cloud properties, and especially, in this study, the amount of information coming from the A-Band channel on the cloud top altitude (CTOP) and geometrical thickness (CGT). We compare the information content of 3MI A-Band in two configurations and that of MSPI. Quantitative information content estimates show that the retrieval of CTOP with a high accuracy is possible in almost all cases investigated. The retrieval of CGT seems less easy but possible for optically thick clouds above a black surface, at least when CGT > 1–2 km
Cloud thermodynamic phase inferred from merged POLDER and MODIS data
International audienceThe global spatial and diurnal distribution of cloud properties is a key issue for understanding the hydrological cycle, and critical for advancing efforts to improve numerical weather models and general circulation models. Satellite data provides the best way of gaining insight into global cloud properties. In particular, the determination of cloud thermodynamic phase is a critical first step in the process of inferring cloud optical and microphysical properties from satellite measurements. It is important that cloud phase be derived together with an estimate of the confidence of this determination, so that this information can be included with subsequent retrievals (optical thickness, effective particle radius, and ice/liquid water content). In this study, we combine three different and well documented approaches for inferring cloud phase into a single algorithm. The algorithm is applied to data obtained by the MODIS (MODerate resolution Imaging Spectroradiometer) and POLDER3 (Polarization and Directionality of the Earth Reflectance) instruments. It is shown that this synergistic algorithm can be used routinely to derive cloud phase along with an index that helps to discriminate ambiguous phase from confident phase cases. The resulting product provides a semi-continuous confidence index ranging from confident liquid to confident ice instead of the usual discrete classification of liquid phase, ice phase, mixed phase (potential combination of ice and liquid particles), or simply unknown phase clouds. This approach is expected to be useful for cloud assimilation and modeling efforts while providing more insight into the global cloud properties derived from satellite data
Comparison of PARASOL Observations with Polarized Reflectances Simulated Using Different Ice Habit Mixtures
Insufficient knowledge of the habit distribution and the degree of surface roughness of ice crystals within ice clouds is a source of uncertainty in the forward light scattering and radiative transfer simulations required in downstream applications involving these clouds. The widely used MODerate Resolution Imaging Spectroradiometer (MODIS) Collection 5 ice microphysical model assumes a mixture of various ice crystal shapes with smooth-facets except aggregates of columns for which a moderately rough condition is assumed. When compared with PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) polarized reflection data, simulations of polarized reflectance using smooth particles show a poor fit to the measurements, whereas very rough-faceted particles provide an improved fit to the polarized reflectance. In this study a new microphysical model based on a mixture of 9 different ice crystal habits with severely roughened facets is developed. Simulated polarized reflectance using the new ice habit distribution is calculated using a vector adding-doubling radiative transfer model, and the simulations closely agree with the polarized reflectance observed by PARASOL. The new general habit mixture is also tested using a spherical albedo differences analysis, and surface roughening is found to improve the consistency of multi-angular observations. It is suggested that an ice model incorporating an ensemble of different habits with severely roughened surfaces would potentially be an adequate choice for global ice cloud retrievals
Calculating and visualizing the density of states for simple quantum mechanical systems
We present a graphical approach to understanding the degeneracy, density of states, and cumulative state number for some simple quantum systems. By taking advantage of basic computing operations, we define a straightforward procedure for determining the relationship between discrete quantum energy levels and the corresponding density of states and cumulative level number. The density of states for a particle in a rigid box of various shapes and dimensions is examined and graphed. It is seen that the dimension of the box, rather than its shape, is the most important feature. In addition, we look at the density of states for a multi-particle system of identical bosons built on the single-particle spectra of those boxes. A simple model is used to explain how the N-particle density of states arises from the single particle system it is based on
Ice particle habit and surface roughness derived from PARASOL polarization measurements
Ice clouds are an important element in the radiative balance of the
earth's climate system, but their microphysical and optical
properties still are not well constrained, especially ice particle
habit and the degree of particle surface roughness. In situ
observations have revealed common ice particle habits and evidence
for surface roughness, but these observations are limited. An
alternative is to infer the ice particle shape and surface roughness
from satellite observations of polarized reflectivity since
they are sensitive to both particle shape and degree of
surface roughness. In this study an adding–doubling radiative
transfer code is used to simulate polarized reflectivity for nine
different ice habits and one habit mixture, along with 17 distinct
levels of the surface roughness. A lookup table (LUT) is
constructed from the simulation results and used to infer shape and
surface roughness from PARASOL satellite polarized reflectivity
data over the ocean. Globally, the retrievals yield a compact aggregate of columns
as the most commonly retrieved ice habit. Analysis of PARASOL data
from the tropics results in slightly more aggregates than in
midlatitude or polar regions. Some level of surface roughness is
inferred in nearly 70% of PARASOL data, with mean and median
roughness near σ = 0.2 and 0.15, respectively. Tropical
region analyses have 20% more pixels retrieved with particle
surface roughness than in midlatitude or polar regions. The global
asymmetry parameter inferred at a wavelength of 0.865 μm
has a mean value of 0.77 and a median value of 0.75
Ice particle habit and surface roughness derived from PARASOL polarization measurements
Ice clouds are an important element in the radiative balance of the
earth's climate system, but their microphysical and optical
properties still are not well constrained, especially ice particle
habit and the degree of particle surface roughness. In situ
observations have revealed common ice particle habits and evidence
for surface roughness, but these observations are limited. An
alternative is to infer the ice particle shape and surface roughness
from satellite observations of polarized reflectivity since
they are sensitive to both particle shape and degree of
surface roughness. In this study an adding–doubling radiative
transfer code is used to simulate polarized reflectivity for nine
different ice habits and one habit mixture, along with 17 distinct
levels of the surface roughness. A lookup table (LUT) is
constructed from the simulation results and used to infer shape and
surface roughness from PARASOL satellite polarized reflectivity
data over the ocean. Globally, the retrievals yield a compact aggregate of columns
as the most commonly retrieved ice habit. Analysis of PARASOL data
from the tropics results in slightly more aggregates than in
midlatitude or polar regions. Some level of surface roughness is
inferred in nearly 70% of PARASOL data, with mean and median
roughness near σ = 0.2 and 0.15, respectively. Tropical
region analyses have 20% more pixels retrieved with particle
surface roughness than in midlatitude or polar regions. The global
asymmetry parameter inferred at a wavelength of 0.865 μm
has a mean value of 0.77 and a median value of 0.75
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