Atmospheric Physical Parameters Research Articles

Parameter estimation of LAMOST Medium-Resolution Stellar Spectra

ABSTRACT This paper investigates the problem of estimating three stellar atmospheric physical parameters and 13 elemental abundances for medium-resolution spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). Typical characteristics of these spectra are their huge scale, wide range of spectral signal-to-noise ratio (S/N), and uneven distribution in parameter space. These characteristics lead to unsatisfactory results on the spectra with low temperature, high temperature, or low metallicity. To this end, this paper proposes a stellar parameter estimation method based on multiple regions (SPEMR) that effectively improves parameter estimation accuracy. On the spectra with S/N ≥ 10, the precisions are 47 K, 0.08 dex, 0.03 dex, respectively, for the estimations of (Teff, $\log \, g$, and $\rm [Fe/H]$), 0.03–0.06 dex for elements C, Mg, Al, Si, Ca, Mn, and Ni, 0.07–0.13 dex for N, O, S, K, and Ti, while that of Cr is 0.16 dex. For the reference of astronomical science researchers and algorithm researchers, we released a catalogue for 4.19 million medium-resolution spectra from the LAMOST DR8, experimental code, trained model, training data, and test data.

Estimating stellar parameters from LAMOST low-resolution spectra

ABSTRACTThe Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) has acquired tens of millions of low-resolution spectra of stars. This paper investigates the parameter estimation problem for these spectra. To this end, we propose the deep learning model StarGRU network (StarGRUNet). This network is applied to estimate the stellar atmospheric physical parameters and 13 elemental abundances from LAMOST low-resolution spectra. On the spectra with signal-to-noise ratios greater than or equal to 5, the estimation precisions are 94 K and 0.16 dex on $T_\texttt {eff}$ and log g respectively, 0.07 to 0.10 dex on [C/H], [Mg/H], [Al/H], [Si/H], [Ca/H], [Ni/H] and [Fe/H], 0.10 to 0.16 dex on [O/H], [S/H], [K/H], [Ti/H] and [Mn/H], and 0.18 and 0.22 dex on [N/H] and [Cr/H]. The model shows advantages over other available models and high consistency with high-resolution surveys. We released the estimated catalogue computed from about 8.21 million low-resolution spectra in LAMOST DR8, code, trained model, and experimental data for astronomical science exploration and data processing algorithm research.

Regression Prediction of Effective Temperature of Stellar Spectrum Based on Kernel Method

There are many factors that lead to the huge difference in stellar spectra, the most important of which are atmospheric physical parameters, namely, effective temperature, surface gravity and chemical abundance. This study is based on the classified star data in LAMOST DR6 with a temperature value of 7500-9000K and a signal-to-noise ratio of S/N greater than 50. The results of the two methods are compared through the regression verification of nuclear least squares regression (KLSR) and nuclear PCA regression (KPCR), The scope of application of the two methods is discussed, and the two most important lick parameters affecting the effective temperature are regressed. By regressing the effective temperature of such stars, a method for predicting the effective temperature of measured spectral data under large samples is given, which provides a certain reference for predicting the trend of star evolution and studying the evolution law of such stars.

Cost effective meter of moisture integral parameters of the atmospheric column

Continuous remote monitoring of the atmospheric physical parameters is an urgent task for solving the issues related to meteorology, climatology, artificial influence on clouds, studying the physical parameters of cloud cover etc. In the developed countries such issues are solved using science-driven technologies of millimeter wave range radiometry. They allow, in particular, quick restoration of the values of total content and effective temperature of droplet and vaporous moisture in the atmospheric column, and distinguishing the areas with crystalline, droplet or vaporous water phases.
 This work aims at substantiating, by calculation and experiment, the possibility of large-scale solving the problems of continuous remote monitoring of the studied atmospheric moisture parameters using the method of centimetre wavelength range radiometry. To determine the best pair of frequencies for restoring the atmospheric moisture parameters based on radiometric data of remote sensing the linear absorption coefficients were calculated for clear atmosphere, for cloudy atmosphere depending on the temperature of drops and for rainfalls of various intensities for 4, 12, 20, 40 and 94 GHz frequencies. In order to calculate these data, we used a well-known MPM model (Atmospheric Millimeter-Wave Propagation Model). At the same time, calculation of the altitude profiles of the atmospheric meteorological parameters was carried out based on the ERA-15 model.
 Comparison of the data obtained by calculation, taking into account the progress of the technical parameters of the serial element base, indicated a possibility of solving the above problems in the centimetre wavelength as well. The research presents a description of the diagram and technical solutions, as well as the appearance of a two-frequency radiometric system with 1.5 cm and 2.5 cm ranges created at the National Aerospace University (KhAI) on the basis of an easily accessible modern element base and full-scale tests' results. The budget-friendly focus of the described product allows for radiophysical measurement with a sensitivity of radiometers exceeding 0.01 K while ensuring the cost of small-scale production of the radio technical part of the system, comparable to the cost of TV converters commonly used in everyday life.

Reconstructing Global Chlorophyll-a Variations Using a Non-linear Statistical Approach

Monitoring the spatio-temporal variations of surface chlorophyll-a concentration (Chl, a proxy of phytoplankton biomass) greatly benefited from the availability of continuous and global ocean color satellite measurements from 1997 onward. These two decades of satellite observations are however still too short to provide a comprehensive description of Chl variations at decadal to multi-decadal timescales. This paper investigates the ability of a machine learning approach (a non-linear statistical approach based on Support Vector Regression, hereafter SVR) to reconstruct global spatio-temporal Chl variations from selected surface oceanic and atmospheric physical parameters. With a limited training period (13 years), we first demonstrate that Chl variability from a 32-years global physical-biogeochemical simulation can generally be skillfully reproduced with a SVR using the model surface variables as input parameters. We then apply the SVR to reconstruct satellite Chl observations using the physical predictors from the above numerical model and show that the Chl reconstructed by this SVR more accurately reproduces some aspects of observed Chl variability and trends compared to the model simulation. This SVR is able to reproduce the main modes of interannual Chl variations depicted by satellite observations in most regions, including El Niño signature in the tropical Pacific and Indian Oceans. In stark contrast with the trends simulated by the biogeochemical model, it also accurately captures spatial patterns of Chl trends estimated by satellite data, with a Chl increase in most extratropical regions and a Chl decrease in the center of the subtropical gyres, although the amplitude of these trends are underestimated by half. Results from our SVR reconstruction over the entire period (1979–2010) also suggest that the Interdecadal Pacific Oscillation drives a significant part of decadal Chl variations in both the tropical Pacific and Indian Oceans. Overall, this study demonstrates that non-linear statistical reconstructions can be complementary tools to in situ and satellite observations as well as conventional physical-biogeochemical numerical simulations to reconstruct and investigate Chl decadal variability.

RESEARCH ON INVERSION OF LIDAR EQUATION BASED ON NEURAL NETWORK

Abstract. Lidar is an advanced atmospheric and meteorological monitoring instrument. The atmospheric aerosol physical parameters can be acquired through inversion of lidar signals. However, traditional methods of solving lidar equations require many assumptions and cannot get accurate analytical solutions. In order to solve this problem, a method of inverting lidar equation using artificial neural network is proposed. This method is based on BP (Back Propagation) artificial neural network, the weights and thresholds of BP artificial neural network is optimized by Genetic Algorithm. The lidar equation inversion prediction model is established. The actual lidar detection signals are inversed using this method, and the results are compared with the traditional method. The result shows that the extinction coefficient and backscattering coefficient inverted by the GA-based BP neural network model are accurate than that inverted by traditional method, the relative error is below 4%. This method can solve the problem of complicated calculation process, as while as providing a new method for the inversion of lidar equations.

Discontinuities in numerical radiative transfer

Observations and magnetohydrodynamic simulations of solar and stellar atmospheres reveal an intermittent behavior or steep gradients in physical parameters, such as magnetic field, temperature, and bulk velocities. The numerical solution of the stationary radiative transfer equation is particularly challenging in such situations, because standard numerical methods may perform very inefficiently in the absence of local smoothness. However, a rigorous investigation of the numerical treatment of the radiative transfer equation in discontinuous media is still lacking. The aim of this work is to expose the limitations of standard convergence analyses for this problem and to identify the relevant issues. Moreover, specific numerical tests are performed. These show that discontinuities in the atmospheric physical parameters effectively induce first-order discontinuities in the radiative transfer equation, reducing the accuracy of the solution and thwarting high-order convergence. In addition, a survey of the existing numerical schemes for discontinuous ordinary differential systems and interpolation techniques for discontinuous discrete data is given, evaluating their applicability to the radiative transfer problem.

Refraction in exoplanet atmospheres

Context.Refraction deflects photons that pass through atmospheres, which affects transit light curves. Refraction thus provides an avenue to probe physical properties of exoplanet atmospheres and to constrain the presence of clouds and hazes. In addition, an effective surface can be imposed by refraction, thereby limiting the pressure levels probed by transmission spectroscopy.Aims.The main objective of the paper is to model the effects of refraction on photometric light curves for realistic planets and to explore the dependencies on atmospheric physical parameters. We also explore under which circumstances transmission spectra are significantly affected by refraction. Finally, we search for refraction signatures in photometric residuals inKeplerdata.Methods.We use the model of Hui & Seager (2002, ApJ, 572, 540) to compute deflection angles and refraction transit light curves, allowing us to explore the parameter space of atmospheric properties. The observational search is performed by stacking large samples of transit light curves fromKepler.Results.We find that out-of-transit refraction shoulders are the most easily observable features, which can reach peak amplitudes of ~10 parts per million (ppm) for planets around Sun-like stars. More typical amplitudes are a few ppm or less for Jovians and at the sub-ppm level for super-Earths. In-transit, ingress, and egress refraction features are challenging to detect because of the short timescales and degeneracies with other transit model parameters. Interestingly, the signal-to-noise ratio of any refraction residuals for planets orbiting Sun-like hosts are expected to be similar for planets orbiting red dwarfs and ultra-cool stars. We also find that the maximum depth probed by transmission spectroscopy is not limited by refraction for weakly lensing planets, but that the incidence of refraction can vary significantly for strongly lensing planets. We find no signs of refraction features in the stackedKeplerlight curves, which is in agreement with our model predictions.

Application of Multi-task Sparse Lasso Feature Extraction and Support Vector Machine Regression in the Stellar Atmospheric Parameterization

The multi-task learning takes the multiple tasks together to make analysis and calculation, so as to dig out the correlations among them, and therefore to improve the accuracy of the analyzed results. This kind of methods have been widely applied to the machine learning, pattern recognition, computer vision, and other related fields. This paper investigates the application of multi-task learning in estimating the stellar atmospheric parameters, including the surface temperature (Teff), surface gravitational acceleration (lg g), and chemical abundance ([Fe/H]). Firstly, the spectral features of the three stellar atmospheric parameters are extracted by using the multi-task sparse group Lasso algorithm, then the support vector machine is used to estimate the atmospheric physical parameters. The proposed scheme is evaluated on both the Sloan stellar spectra and the theoretical spectra computed from the Kurucz's New Opacity Distribution Function (NEWODF) model. The mean absolute errors (MAEs) on the Sloan spectra are: 0.0064 for lg (Teff /K), 0.1622 for lg (g/(cm · s−2)), and 0.1221 dex for [Fe/H]; the MAEs on the synthetic spectra are 0.0006 for lg (Teff /K), 0.0098 for lg (g/(cm · s−2)), and 0.0082 dex for [Fe/H]. Experimental results show that the proposed scheme has a rather high accuracy for the estimation of stellar atmospheric parameters.

Analysis of a spatially deconvolved solar pore

Solar pores are active regions with large magnetic field strengths and apparent simple magnetic configurations. Their properties resemble the ones found for the sunspot umbra although pores do not show penumbra. Therefore, solar pores present themselves as an intriguing phenomenon that is not completely understood. We examine in this work a solar pore observed with Hinode/SP using two state of the art techniques. The first one is the spatial deconvolution of the spectropolarimetric data that allows removing the stray light contamination induced by the spatial point spread function of the telescope. The second one is the inversion of the Stokes profiles assuming local thermodynamic equilibrium that let us to infer the atmospheric physical parameters. After applying these techniques, we found that the spatial deconvolution method does not introduce artefacts, even at the edges of the magnetic structure, where large horizontal gradients are detected on the atmospheric parameters. Moreover, we also describe the physical properties of the magnetic structure at different heights finding that, in the inner part of the solar pore, the temperature is lower than outside, the magnetic field strength is larger than 2 kG and unipolar, and the LOS velocity is almost null. At neighbouring pixels, we found low magnetic field strengths of same polarity and strong downward motions that only occur at the low photosphere, below the continuum optical depth $\log \tau=-1$. Finally, we studied the spatial relation between different atmospheric parameters at different heights corroborating the physical properties described before.

Analysis of horizontal flows in the solar granulation

Solar limb observations sometimes reveal the presence of a satellite lobe in the blue wing of the Stokes I profile from pixels belonging to granules. The presence of this satellite lobe has been associated in the past to strong line of sight gradients and, as the line of sight component is almost parallel to the solar surface, to horizontal granular flows. We aim to increase the knowledge about these horizontal flows studying a spectropolarimetric observation of the north solar pole. We will make use of two state of the art techniques, the spatial deconvolution procedure that increases the quality of the data removing the stray light contamination, and spectropolarimetric inversions that will provide the vertical stratification of the atmospheric physical parameters where the observed spectral lines form. We inverted the Stokes profiles using a two component configuration, obtaining that one component is strongly blueshifted and displays a temperature enhancement at upper photospheric layers while the second component has low redshifted velocities and it is cool at upper layers. In addition, we examined a large number of cases located at different heliocentric angles, finding smaller velocities as we move from the centre to the edge of the granule. Moreover, the height location of the enhancement on the temperature stratification of the blueshifted component also evolves with the spatial location on the granule being positioned on lower heights as we move to the periphery of the granular structure.

Automatic Measurement of the Stellar Atmospheric Parameters Based Mass Estimation

We have collected massive stellar spectral data in recent years, which leads to the research on the automatic measurement of stellar atmospheric physical parameters (effective temperature Teff, surface gravity log g and metallic abundance [Fe/ H]) become an important issue. To study the automatic measurement of these three parameters has important significance for some scientific problems, such as the evolution of the universe and so on. But the research of this problem is not very widely, some of the current methods are not able to estimate the values of the stellar atmospheric physical parameters completely and accurately. So in this paper, an automatic method to predict stellar atmospheric parameters based on mass estimation was presented, which can achieve the prediction of stellar effective temperature Teff, surface gravity log g and metallic abundance [Fe/H]. This method has small amount of computation and fast training speed. The main idea of this method is that firstly it need us to build some mass distributions, secondly the original spectral data was mapped into the mass space and then to predict the stellar parameter with the support vector regression (SVR) in the mass space. we choose the stellar spectral data from the United States SDSS-DR8 for the training and testing. We also compared the predicted results of this method with the SSPP and achieve higher accuracy. The predicted results are more stable and the experimental results show that the method is feasible and can predict the stellar atmospheric physical parameters effectively.

Statistical Characteristics and Variations of Thunderstorm Frequency in South China from 1980 to 2010

By using the observed data from 20 weather stations in South China,the characteristics of diurnal,seasonal,multi-year variations and relative atmospheric physical parameters and circulation fields were demonstrated. The results show ed that the thunderstorm frequency peak from afternoon to the evening(9% at 12: 00(UTC,hereafter the same)),and least in the morning(2% at 03: 00). The higher thunderstorm frequency occurred in July and August( 35%),and the low er thunderstorm frequency in December and January( 1%).The annual and summer thunderstorm frequency decreased with a rate of-1% ·(10a)-1and-3. 5% ·(10a)-1from 1980 s to 21 thcentury,yet after 21 thcentury,it has a weak increasing trend. On the whole year,the ratio of thunderstorm precipitation and total precipitation was 48%,but in summer,the value was 64%. The variation of annual(summer) thunderstorm precipitation were relatively similar with annual(summer) thunderstorm frequency,their correlation coefficient was 0. 46(0. 71). In summer,accompany with the variation of thunderstorm frequency,the atmospheric circulation exhibits large-scale abnormally in east Asia. During higher thunderstorm frequency month,the western Pacific subtropical high was abnormally weaker. Meanw hile,there was abnormally ascending flow s in the upper-middle troposphere over the South China. In addition,from the view of thermal instability,the abnormally high total tolals index and abnormally high convective available potential energy index has significant relationship with thunderstorm frequency,their correlation coefficients were 0. 58 and 0. 76. The thunderstorm frequency has statistical relevance with the surface temperature,how ever,it requires substantial investigation to make sure that whether it is a response of thunderstorms thermal and dynamical factor to the global climate change.

Corrigendum to "Speciated mercury at marine, coastal, and inland sites in New England – Part 2: Relationships with atmospheric physical parameters" published in Atmos. Chem. Phys., 12, 4181–4206, 2012

H. Mao1, R. Talbot2, J. Hegarty3, and J. Koermer4 1Department of Chemistry, State University of New York, College of Environmental Science and Forestry, Syracuse, NY 13210, USA 2Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX 77204, USA 3AER, Inc., 131 Hartwell Avenue, Lexington, MA, 02421, USA 4Department of Atmospheric Science & Chemistry, Plymouth State University, Plymouth, New Hampshire 03264, USA

Speciated mercury at marine, coastal, and inland sites in New England – Part 2: Relationships with atmospheric physical parameters

Abstract. Long-term continuous measurements of gaseous elemental mercury (Hg0), reactive gaseous mercury (RGM), and particulate phase mercury (HgP) were conducted at coastal (Thompson Farm, denoted as TF), marine (Appledore Island, denoted as AI), and elevated inland rural (Pac Monadnock, denoted as PM) monitoring sites of the AIRMAP Observing Network. Diurnal, seasonal, annual, and interannual variability in Hg0, RGM, and HgP from the three distinctly different environments were characterized and compared in Part 1. Here in Part 2 relationships between speciated mercury (i.e., Hg0, RGM, and HgP) and climate variables (e.g., temperature, wind speed, humidity, solar radiation, and precipitation) were examined. The best point-to-point correlations were found between Hg0 and temperature in summer at TF and spring at PM, but there was no similar correlation at AI. Subsets of data demonstrated regional impacts of episodic dynamic processes such as strong cyclonic systems on ambient levels of Hg0 at all three sites, possibly through enhanced oceanic evasion of Hg0. A tendency of higher levels of RGM and HgP was identified in spring and summer under sunny conditions in all environments. Specifically, the 10th, 25th, median, 75th, and 90th percentile mixing ratios of RGM and HgP increased with stronger solar radiation at both the coastal and marine sites. These metrics decreased with increasing wind speed at AI indicating enhanced loss of RGM and HgP through deposition. RGM and HgP levels correlated with temperature positively in spring, summer and fall at the coastal and marine locations. At the coastal site relationships between RGM and relative humidity suggested a clear decreasing tendency in all metrics from <40% to 100% relative humidity in all seasons especially in spring, compared to less variability in the marine environment. The effect of precipitation on RGM at coastal and marine locations was similar. At the coastal site, RGM levels were a factor of 3–4 to two orders of magnitude higher under dry conditions than rainy conditions in all seasons. In winter RGM mixing ratios appeared to be mostly above the limit of detection (LOD) during snowfalls suggesting less scavenging efficiency of snow. Mixing ratios of HgP at the coastal and marine sites remained above the LOD under rainy conditions. Precipitation had negligible impact on the magnitude and pattern of diurnal variation of HgP in all seasons in the marine environment.

Physical atmospheric structure and tropospheric mixing information in vertical profiles of atmospheric CO2 mixing ratios

Vertical distribution of atmospheric CO2 mixing ratios, as well as CO2 vertical variance and gradient are related to the vertical stability at the time of measurement, to the transport of coherent upstream plumes studied through changes in the upstream surface influence or to the historic mixing processes and dispersive behavior. Three vertical profiles of CO2 mixing ratios measured from 900 to 4200 m above sea level (masl) in 2006 at La Muela, Spain (LMU, 41.60°N 1.10°W, 570 masl) are examined. Changes in CO2 mixing ratio are associated with changes of the atmospheric physical parameters on the day of the survey; and with the transport of coherent air masses. Its consistency is examined through changes of the historical horizontal dispersion and chaotic mixing dynamics of air masses during the four days prior to measurements. A climatology of Lagrangian backward simulations run once a week at four altitudes (600, 1200, 2500 and 4000 masl) at LMU for 2006 shows that dispersion in these altitudes is superdiffusive (exponent coefficient γ > 1/2) and mixing follows a chaotic dynamics (power law exponent λ > 0) at all altitudes and in all seasons. Furthermore, a Horizontal Mixing Discontinuity (HMD) at ∼2500 masl separates two layers with different constraints on vertical mixing. Above the HMD, more coherent air masses and laminar transport characterizes the dynamics of atmospheric horizontal mixing whereas below it, filamentation and chaotic mixing dominate horizontal mixing. In the lower part of the vertical profile, within the ABL, mixing takes place by convection. Chaotic mixing below the HMD induces the boundary layer entrainment. Results highlight that there are two main discontinuities in the air column which separates different atmospheric dynamics. The ABL is driven by local meteorological conditions of the site at the sampling time; the HMD is driven by the synoptic‐scale historical mixing conditions of air masses. The effect of horizontal transport in the free troposphere should be considered equally as important as the local vertical mixing processes in the atmospheric boundary layer when interpreting CO2 vertical gradients. The dispersive exponents can be used to identify the transport of coherent plumes from anthropogenic emissions with different carbon composition that the one‐single backtrajectories models do not detect.

Field Sensor Virtual Organization Integrated with Satellite Data on a Geo Grid

Remotely sensed satellite data can provide spatial and temporal coverage for global environmental monitoring. Calibration and validation are very important for more accurate satellite products and can contribute to the detection of climate changes on earth. Calibration and validation of satellite products normally use both ground-based and satellite-based data, which have geospatial metainformation and various data policies. Our proposal adopts both the Open Geospatial Consortium (OGC) standards and the virtual organization (VO) concept to develop a calibration and validation system for satellite products. In this research, we construct the Field Observation Network (FON) VO, which provides an interoperable system for various ground-based and satellite-based data by using the OGC standards Sensor Observation Service (SOS). FON VO also makes it possible to protect data policies. Ground-based and satellite-based atmospheric and ground physical parameters are the focus of this study.

A spectroscopic search for non-radial pulsations in the Scuti star Bootis

High-resolution spectroscopic observations of the rapidly rotating δ Scuti star γ Bootis have been carried out in 2005, over six consecutive nights, in order to search for line-profile variability. Time-series, consisting of flux measurements at each wavelength bin across the Ti II 4571.917 A line profile as a function of time, have been Fourier analysed. The results confirm the early detection reported by Kennelly et al. of a dominant periodic component at frequency 21.28 cycles d −1 in the observer’s frame, probably due to a high-azimuthal-order sectorial mode. Moreover, we found other periodicities at 5.06, 12.02 cycles d −1 , probably present but not secure, and at 11.70 and 18.09 cycles d −1 , uncertain. The latter frequency, if present, should be identifiable as another high-azimuthal-order sectorial mode and the three additional terms as low-l modes as proved by the analysis of the first three moments of the line. Owing to the short time baseline and the one-site temporal sampling we consider our results only preliminary but encouraging for a more extensive multisite campaign. A refinement of the atmospheric physical parameters of the star has been obtained from our spectroscopic data and adopted for preliminary computations of evolutionary models of

The Lack of Blue Supergiants in NGC 7419, a Red Supergiant-rich Galactic Open Cluster with Rapidly Rotating Stars

According to previous studies based on photometry alone, NGC 7419 reveals a surprisingly low ratio of blue to red supergiants: only one blue supergiant (BSG) along with a record number of five red supergiants (RSGs). However, for a cluster like NGC 7419 with solar metallicity, one expects twice as many BSGs as RSGs. To verify the small ratio of BSGs to RSGs, we have obtained spectroscopic observations of the seven most luminous blue member stars using the 1.6 m telescope of the Mount Megantic Observatory. (The RSGs have already been studied spectroscopically.) To classify the stars, we have developed a system especially adapted for these heavily reddened stars in a spectral region from 8400 to 8920 A, near the hydrogen Paschen series limit. This classification system is based on standard stars of known MK spectral type extending over O9–B5 and all luminosity classes and is linked through a grid of synthetic spectra to the atmospheric physical parameters Teff and log g. We also include Be stars. Among the seven blue stars observed in NGC 7419, four have red spectra that are dominated by absorption lines and three by emission lines. The spectral types for the former are B2.5 II–III, B2.5 III, B0 III, and B4 III (e), while those for the latter are Be, B1 III–Ve, and Be, respectively. The average heliocentric radial velocity of these stars is -66 ± 6 km s-1, compatible with the value of -74 ± 9 km s-1 measured for the five RSG members. A distance of 1.7 ± 0.4 kpc for this cluster was estimated using the blue-star spectral types, in agreement with the value of 2.3 ± 0.3 kpc found by Beauchamp and coworkers, based on isochrone fitting in the color-magnitude diagram. With no BSG stars detected spectroscopically, we confirm the low number, in this case absence, of BSGs in this cluster. The high fraction of Be stars detected by us and others among the bright blue member stars could be explained by an average rotational velocity for the stars in NGC 7419, which is significantly higher than in other clusters of similar age and metallicity. Since higher stellar rotation rates shorten the BSG phase, we suggest that this explains why the evolved stars in NGC 7419 have become RSGs. Thus, NGC 7419 is an exceptional case, since high stellar rotation normally tends to occur at lower metallicity.

Space‐Earth absorption in the absence of rain: Radiometric inversion coefficients for Italy

AbstractSpace‐earth atmospheric attenuation in absence of rain can be estimated from atmospheric physical parameters, which are, in turn, obtainable from radiometric measurements of the sky brightness temperature. In this paper the radiometric inversion coefficients needed to retrieve the total vapour and liquid water content of the atmosphere from radiometric measurements are computed making use of a statistically significant data‐ base of radiosonde vertical profiles. Linear regression is applied to data collected over ten years at five Italian sites to derive the inversion coefficients under various operational hypotheses. Site‐to‐site and seasonal variabilities are analysed as well as the influence of both the instrumental characteristics and the criterium for detecting cloud liquid. A first set of values valid for the Italian territory is presented for system design purpose.