Cloud Region Research Articles

Using Lightning Flashes to Image Thunderclouds.

The optical energy emitted by lightning flashes interacts with the surrounding cloud medium through scattering and absorption. The optical signals recorded by space-based lightning imagers describe a convolution of lightning flash energetics and radiative transfer effects in the intervening cloud layer. A thundercloud imaging technique is presented that characterizes cloud regions based on how they are illuminated by lightning. This technique models the spatial distribution of optical energy in radiant lightning pulses to determine whether and to what extent each illuminated cloud pixel behaves like a homogeneous planar cloud layer. A gridded product is constructed that differentiates flashes that illuminate convective cells from stratiform flashes with long horizontal channels and anvil flashes whose optical emissions reflect off of nearby cloud surfaces. Producing this imagery with a rolling 15-min window allows us to visualize changes in convection with a rapid (20 s) update cycle.

The intrinsic reddening of the Magellanic Clouds as traced by background galaxies – I. The bar and outskirts of the Small Magellanic Cloud

ABSTRACT We present a method to map the total intrinsic reddening of a foreground extinguishing medium via the analysis of spectral energy distributions (SEDs) of background galaxies. In this pilot study, we implement this technique in two distinct regions of the Small Magellanic Cloud (SMC) – the bar and the southern outskirts – using a combination of optical and near-infrared ugrizYJKs broad-band imaging. We adopt the lephare χ2-minimization SED-fitting routine and various samples of galaxies and/or quasi-stellar objects to investigate the intrinsic reddening. We find that only when we construct reddening maps using objects classified as galaxies with low levels of intrinsic reddening (i.e. ellipticals/lenticulars and early-type spirals), the resultant maps are consistent with previous literature determinations, i.e. the intrinsic reddening of the SMC bar is higher than that in the outer environs. We employ two sets of galaxy templates – one theoretical and one empirical – to test for template dependences in the resulting reddening maps and find that the theoretical templates imply systematically higher reddening values by up to 0.20 mag in E(B − V). A comparison with previous reddening maps, based on the stellar components of the SMC, typically shows reasonable agreement. There is, however, significant variation amongst the literature reddening maps as to the level of intrinsic reddening associated with the bar. Thus, it is difficult to unambiguously state that instances of significant discrepancies are the result of appreciable levels of dust not accounted for in some literature reddening maps or whether they reflect issues with our adopted methodology.

LassoNet: Deep Lasso-Selection of 3D Point Clouds.

Selection is a fundamental task in exploratory analysis and visualization of 3D point clouds. Prior researches on selection methods were developed mainly based on heuristics such as local point density, thus limiting their applicability in general data. Specific challenges root in the great variabilities implied by point clouds (e.g., dense vs. sparse), viewpoint (e.g., occluded vs. non-occluded), and lasso (e.g., small vs. large). In this work, we introduce LassoNet, a new deep neural network for lasso selection of 3D point clouds, attempting to learn a latent mapping from viewpoint and lasso to point cloud regions. To achieve this, we couple user-target points with viewpoint and lasso information through 3D coordinate transform and naive selection, and improve the method scalability via an intention filtering and farthest point sampling. A hierarchical network is trained using a dataset with over 30K lasso-selection records on two different point cloud data. We conduct a formal user study to compare LassoNet with two state-of-the-art lasso-selection methods. The evaluations confirm that our approach improves the selection effectiveness and efficiency across different combinations of 3D point clouds, viewpoints, and lasso selections. Project Website: https://LassoNet.github.io.

Thermal instability through the outer half of quasi-static spherically symmetric molecular clumps and cores

Thermal instability (TI) is a trigger mechanism, which can explain formation of condensations through some regions of the interstellar clouds. Our goal here is to investigate some conditions for occurrence of TI and formation of pre-condensations through the outer half a quasi-static spherical molecular clump or core. The inner half is nearly singular and ambiguous so out of scope of this research. We consider a spherically symmetric molecular cloud in quasi-static and thermally equilibrium state, and we use the linear perturbation method to investigate occurrence of TI through its outer half. The origin of perturbations are assumed to be as Inside-Rush-Perturbation (IRP) with outward perturbed velocity at inner region of the cloud, and Outside-Rush-Perturbation (ORP) with inward perturbed velocity originated at the outer parts of the cloud. The local thermal balance at the outer half of the molecular cloud leads to a local loosely constrained power-law relation between the pressure and density as $p \propto \rho^{1+\chi}$, where $-0.4\lesssim \chi\lesssim 0.05$ depends on the functional form of the net cooling function. Physically, the value of $\chi$ depends on the power of dependence of magnetic field to the density, $\eta$, and also on the value of magnetic field gradient, $\zeta$. For strong magnetic field (smaller $\eta$) and/or large field gradient (greater $\zeta$), the value of $\chi$ decreases, and vice versa. The results show that increasing of the value of $\chi$ leads to form a flatter density profiles at the thermally equilibrium outer half of the molecular clump or core, and to occur more thermally unstable IRP and ORP with smaller growth time-scales, and vice versa.

Performance of CAMS-CSM in Simulating the Shortwave Cloud Radiative Effect over Global Stratus Cloud Regions: Baseline Evaluation and Sensitivity Test

The ability of climate models to correctly reproduce clouds and the radiative effects of clouds is vitally important in climate simulations and projections. In this study, simulations of the shortwave cloud radiative effect (SWCRE) using the Chinese Academy of Meteorological Sciences Climate System Model (CAMS-CSM) are evaluated. The relationships between SWCRE and dynamic–thermodynamic regimes are examined to understand whether the model can simulate realistic processes that are responsible for the generation and maintenance of stratus clouds. Over eastern China, CAMS-CSM well simulates the SWCRE climatological state and stratus cloud distribution. The model captures the strong dependence of SWCRE on the dynamic conditions. Over the marine boundary layer regions, the simulated SWCRE magnitude is weaker than that in the observations due to the lack of low-level stratus clouds in the model. The model fails to simulate the close relationship between SWCRE and local stability over these regions. A sensitivity numerical experiment using a specifically designed parameterization scheme for the stratocumulus cloud cover confirms this assertion. Parameterization schemes that directly depict the relationship between the stratus cloud amount and stability are beneficial for improving the model performance.

Classification of Clouds by the Eagle Strategy

In this article a method of image processing used to extract the different regions of clouds, from infrared images, visible images and water vapour images of satellite METEOSAT Second Generation MSG is presented. This research addresses one of the main problems of vision by computer, image segmentation, using a new strategy called eagle strategy. The results obtained have showed the effectiveness of this strategy.

Cloud detection from visual band of satellite image based on variance of fractal dimension

Cover ratio of cloud is a very important factor which affects the quality of a satellite image, therefore cloud detection from satellite images is a necessary step in assessing the image quality. The study on cloud detection from the visual band of a satellite image is developed. Firstly, we consider the differences between the cloud and ground including high grey level, good continuity of grey level, area of cloud region, and the variance of local fractal dimension (VLFD) of the cloud region. A single cloud region detection method is proposed. Secondly, by introducing a reference satellite image and by comparing the variance in the dimensions corresponding to the reference and the tested images, a method that detects multiple cloud regions and determines whether or not the cloud exists in an image is described. By using several Ikonos images, the performance of the proposed method is demonstrated.

Probing ISM Structure in Trumpler 14 and Carina I Using the Stratospheric Terahertz Observatory 2

Abstract We present observations of the Trumpler 14/Carina I region carried out using the Stratospheric Terahertz Observatory 2. The Trumpler 14/Carina I region is in the western part of the Carina Nebula Complex (CNC), which is one of the most extreme star-forming regions in the Milky Way. We observed Trumpler 14/Carina I in the 158 μm transition of [C ii] with a spatial resolution of 48″ and a velocity resolution of 0.17 km s−1. The observations cover a 0.°25 by 0.°28 area with central position l = 297.°34, b = −0.°60. The kinematics show that bright [C ii] structures are spatially and spectrally correlated with the surfaces of CO clouds, tracing the photodissociation region (PDR) and ionization front of each molecular cloud. Along seven lines of sight (LOSs) that traverse Tr 14 into the dark ridge to the southwest, we find that the [C ii] luminosity from the H ii region is 3.7 times that from the PDR. In the same LOS, we find in the PDRs an average ratio of 1 : 4.1 : 5.6 for the mass in atomic gas : dark CO gas : molecular gas traced by CO. Comparing multiple gas tracers, including H i 21 cm, [C ii], CO, and radio recombination lines, we find that the H ii regions of the CNC are well described as H ii regions with one side freely expanding toward us, consistent with the Champagne model of ionized gas evolution. The dispersal of the GMC in this region is dominated by EUV photoevaporation; the dispersal timescale is 20–30 Myr.

Revisiting the Temperature of the Diffuse ISM with CHESS Sounding Rocket Observations

Measuring the temperature and abundance patterns of clouds in the interstellar medium (ISM) provides an observational basis for models of the physical conditions within the clouds, which play an important role in studies of star and planet formation. The Colorado High-resolution Echelle Stellar Spectrograph (CHESS) is a far ultraviolet rocket-borne instrument designed to study the atomic-to-molecular transitions within diffuse molecular and translucent cloud regions. The final two flights of the instrument observed $\beta^{1}$ Scorpii ($\beta$ Sco) and $\gamma$ Arae. We present flight results of interstellar molecular hydrogen (H$_{\rm 2}$) excitation on the sightlines, including measurements of the column densities and temperatures. These results are compared to previous values that were measured using the damping wings of low J$^{\prime \prime}$ H$_{\rm 2}$ absorption features (Savage et al. 1977). For $\beta$ Sco, we find that the derived column density of the J$^{\prime \prime}$ = 1 rotational level differs by a factor of 2-3 when compared to the previous observations. We discuss the discrepancies between the two measurements and show that the source of the difference is due to the opacity of higher rotational levels contributing to the J$^{\prime \prime}$ = 1 absorption wing, increasing the inferred column density in the previous work. We extend this analysis to 9 $Copernicus$ and 13 $FUSE$ spectra to explore the interdependence of the column densities of different rotational levels and how the H$_{\rm 2}$ kinetic temperature is influenced by these relationships. We find a revised average gas kinetic temperature of the diffuse molecular ISM of T$_{01}$ = 68 $\pm$ 13 K, 12% lower than the value found previously.

POINT CLOUDS TO DIRECT INDOOR PEDESTRIAN PATHFINDING

Abstract. Increase in building complexity can cause difficulties orienting people, especially people with reduced mobility. This work presents a methodology to enable the direct use of indoor point clouds as navigable models for pathfinding. Input point cloud is classified in horizontal and vertical elements according to inclination of each point respect to n neighbour points. Points belonging to the main floor are detected by histogram application. Other floors at different heights and stairs are detected by analysing the proximity to the detected main floor. Then, point cloud regions classified as floor are rasterized to delimit navigable surface and occlusions are corrected by applying morphological operations assuming planarity and taking into account the existence of obstacles. Finally, point cloud of navigable floor is downsampled and structured in a grid. Remaining points are nodes to create navigable indoor graph. The methodology has been tested in two real case studies provided by the ISPRS benchmark on indoor modelling. A pathfinding algorithm is applied to generate routes and to verify the usability of generated graphs. Generated models and routes are coherent with selected motor skills because routes avoid obstacles and can cross areas of non-acquired data. The proposed methodology allows to use point clouds directly as navigation graphs, without an intermediate phase of generating parametric model of surfaces.

Cloud Detection in Remote Sensing Images Based on Multiscale Features-Convolutional Neural Network

Cloud detection in remote sensing images is a challenging but significant task. Due to the variety and complexity of underlying surfaces, most of the current cloud detection methods have difficulty in detecting thin cloud regions. In fact, it is quite meaningful to distinguish thin clouds from thick clouds, especially in cloud removal and target detection tasks. Therefore, we propose a method based on multiscale features-convolutional neural network (MF-CNN) to detect thin cloud, thick cloud, and noncloud pixels of remote sensing images simultaneously. Landsat 8 satellite imagery with various levels of cloud coverage is used to demonstrate the effectiveness of our proposed MF-CNN model. We first stack visible, near-infrared, short-wave, cirrus, and thermal infrared bands of Landsat 8 imagery to obtain the combined spectral information. The MF-CNN model is then used to learn the multiscale global features of input images. The high-level semantic information obtained in the process of feature learning is integrated with low-level spatial information to classify the imagery into thick, thin and noncloud regions. The performance of our proposed model is compared to that of various commonly used cloud detection methods in both qualitative and quantitative aspects. Compared to other cloud detection methods, the experimental results show that our proposed method has a better performance not only in thick and thin clouds but also in the entire cloud regions.

ALMA Reveals Kinematics of Super Star Cluster Candidate H72.97-69.39 in LMC-N79

Abstract Conditions in super star clusters (SSCs) lead to the formation of dozens of massive stars in close proximity. However, SSCs are rare in the local universe. H72.97-69.39, located in the N79 region of the Large Magellanic Cloud (LMC), is an SSC candidate. In this paper we report the ALMA observations of the potential SSC. ALMA reveals colliding filaments, outflows, an H ii region, and a C ii region associated with this cluster. The timescale of the outflow is 65,000 yr, which is consistent with this being a young cluster. The molecular gas around this potential early-stage SSC candidate is complex in nature on small scales (as seen with ALMA) and large scales (as seen with Herschel).

Relationships between the Structure of Convective Clouds and Lightning Frequency Derived from Radiophysical Measurements

The results of simultaneous radar, radiometric, and lightning location measurements are analyzed to reveal interrelations between the characteristics of electric discharges and the parameters of a cumulonimbus cloud developing near Saint Petersburg. The dependences of the cloud electric activity on the radar characteristics as well as on the parameters derived from the Meteosat SEVIRI radiometer measurements are considered. It is found that lightning frequency highly correlates with the volume of supercooled cloud regions with high values of reflectivity. An increase in the lightning frequency occurs about 20 minutes after the moment when supercooled cloud volumes with reflectivity above 35–55 dBZ reach the maximum values. The maximum precipitation flux precedes the maximum lightning frequency.

TRAO Survey of Nearby Filamentary Molecular Clouds, the Universal Nursery of Stars (TRAO FUNS). I. Dynamics and Chemistry of L1478 in the California Molecular Cloud

Abstract “TRAO FUNS” is a project to survey the Gould Belt’s clouds in molecular lines. This paper presents its first results on the central region of the California molecular cloud, L1478. We performed on-the-fly mapping observations using the Taeduk Radio Astronomy Observatory 14 m single-dish telescope equipped with a 16 multibeam array covering a ∼1.0 square degree area of this region using C 18 O ( 1 – 0 ) , mainly tracing low-density clouds, and a ∼460 square arcminute area using N 2 H + ( 1 – 0 ) , mainly tracing dense cores. CS ( 2 – 1 ) and SO ( 3 2 – 2 1 ) were also used simultaneously to map a ∼440 square arcminute area of this region. We identified 10 filaments by applying the dendrogram technique to the C 18 O data cube and 8 dense N 2 H + cores using FellWalker. Basic physical properties of filaments such as mass, length, width, velocity field, and velocity dispersion are derived. It is found that L1478 consists of several filaments with slightly different velocities. Particularly, the filaments that are supercritical are found to contain dense cores detected in N 2 H + . A comparison of nonthermal velocity dispersions derived from C 18 O and N 2 H + for the filaments and dense cores indicates that some of the dense cores share kinematics similar to those of the surrounding filaments, while several dense cores have different kinematics from those of their filaments. This suggests that the formation mechanism of dense cores and filaments can be different in individual filaments depending on their morphologies and environments.

Connecting the Scales: Large Area High-resolution Ammonia Mapping of NGC 1333

Abstract We use NH3 inversion transitions to trace the dense gas in the NGC 1333 region of the Perseus molecular cloud. NH3 (1, 1) and NH3 (2, 2) maps covering an area of 102 square arcminutes at an angular resolution of ∼3.″7 are produced by combining Very Large Array interferometric observations with Green Bank Telescope single-dish maps. The combined maps have a spectral resolution of 0.14 km s−1 and a sensitivity of 4 mJy/beam. We produce integrated intensity maps, peak intensity maps, and dispersion maps of NH3 (1, 1) and NH3 (2, 2) and a line-of-sight velocity map of NH3 (1, 1). These are used to derive the optical depth for the NH3 (1, 1) main component, the excitation temperature of NH3 (1, 1), and the rotational temperature, kinetic temperature, and column density of NH3 over the mapped area. We compare these observations with the CARMA J = 1–0 observations of N2H+ and H13CO+ and conclude that they all trace the same material in these dense star-forming regions. From the NH3 (1, 1) velocity map, we find that a velocity gradient ridge extends in an arc across the entire southern part of NGC 1333. We propose that a large-scale turbulent cell is colliding with the cloud, which could result in the formation of a layer of compressed gas. This region along the velocity gradient ridge is dotted with Class 0/I young stellar objects, which could have formed from local overdensities in the compressed gas leading to gravitational instabilities. The NH3 (1, 1) velocity dispersion map also has relatively high values along this region, thereby substantiating the shock layer argument.

Determination of the Primordial Helium Abundance Based on NGC 346, an H ii Region of the Small Magellanic Cloud

Abstract To place meaningful constraints on Big Bang Nucleosynthesis models, the primordial helium abundance determination is crucial. Low-metallicity H ii regions have been used to estimate it because their statistical uncertainties are relatively small. We present a new determination of the primordial helium abundance, based on long-slit spectra of the H ii region NGC 346 in the small Magellanic cloud. We obtained spectra using three 409″ × 0.51″ slits divided into 97 subsets. They cover the range λλ3600–7400 of the electromagnetic spectrum. We used PyNeb and standard reduction procedures to determine the physical conditions and chemical composition. We found that for NGC 346 X = 0.7465, Y = 0.2505, and Z = 0.0030. By assuming ΔY/ΔO = 3.3 ± 0.7 we found that the primordial helium abundance is Y P = 0.2451 ± 0.0026 (1σ). Our Y P value is in agreement with the value of neutrino families, N ν , and with the neutron half-life time, τ n , obtained in the laboratory.

Rapid ice aggregation process revealed through triple-wavelength Doppler spectrum radar analysis

Abstract. We have identified a region of an ice cloud where a sharp transition of dual-wavelength ratio occurs at a fixed height for longer than 20 min. In this paper we provide evidence that rapid aggregation of ice particles occurred in this region, creating large particles. This evidence comes from triple-wavelength Doppler spectrum radar data that were fortuitously being collected. Through quantitative comparison of the Doppler spectra from the three radars we are able to estimate the ice particle size distribution (of particles larger than 0.75 mm) at different heights in the cloud. This allows us to investigate the evolution of the ice particle size distribution and determine whether the evolution is consistent with aggregation, riming or vapour deposition. The newly developed method allows us to isolate the signal from the larger (non-Rayleigh scattering) particles in the distribution. Therefore, a particle size distribution retrieval is possible in areas of the cloud where the dual-wavelength ratio method would fail because the bulk dual-wavelength ratio value is too close to zero. The ice particles grow rapidly from a maximum size of 0.75 to 5 mm while falling less than 500 m in under 10 min. This rapid growth is shown to agree well with theoretical estimates of aggregation, with aggregation efficiency being approximately 0.7, and is inconsistent with other growth processes, e.g. growth by vapour deposition or riming. The aggregation occurs in the middle of the cloud and is not present throughout the entire lifetime of the cloud. However, the layer of rapid aggregation is very well defined at a constant height, where the temperature is −15 ∘C and lasts for at least 20 min (approximate horizontal distance: 24 km). Immediately above this layer, the radar Doppler spectrum is bi-modal, which signals the formation of new small ice particles at that height. We suggest that these newly formed particles, at approximately −15 ∘C, grow dendritic arms, enabling them to easily interlock and accelerate the aggregation process. The large estimated aggregation efficiency in this cloud is consistent with recent laboratory studies for dendrites at this temperature.

Effective Cloud Detection and Segmentation Using a Gradient-Based Algorithm for Satellite Imagery: Application to Improve PERSIANN-CCS

Abstract The effective identification of clouds and monitoring of their evolution are important toward more accurate quantitative precipitation estimation and forecast. In this study, a new gradient-based cloud-image segmentation algorithm is developed using image processing techniques. This method integrates morphological image gradient magnitudes to separate cloud systems and patches boundaries. A varying scale kernel is implemented to reduce the sensitivity of image segmentation to noise and to capture objects with various finenesses of the edges in remote sensing images. The proposed method is flexible and extendable from single to multispectral imagery. Case studies were carried out to validate the algorithm by applying the proposed segmentation algorithm to synthetic radiances for channels of the Geostationary Operational Environmental Satellite (GOES-16) simulated by a high-resolution weather prediction model. The proposed method compares favorably with the existing cloud-patch-based segmentation technique implemented in the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS) rainfall retrieval algorithm. Evaluation of event-based images indicates that the proposed algorithm has potentials comparing to the conventional segmentation technique used in PERSIANN-CCS to improve rain detection and estimation skills with an accuracy rate of up to 98% in identifying cloud regions.

The VLT-FLAMES Tarantula Survey

Aims. The incidence of multiplicity in cool, luminous massive stars is relatively unknown compared to their hotter counterparts. In this work we present radial velocity (RV) measurements and investigate the multiplicity properties of red supergiants (RSGs) in the 30 Doradus region of the Large Magellanic Cloud using multi-epoch visible spectroscopy from the VLT-FLAMES Tarantula Survey. Methods. Exploiting the high density of absorption features in visible spectra of cool stars, we used a novel slicing technique to estimate RVs of 17 candidate RSGs in 30 Doradus from cross-correlation of the observations with model spectra. Results. We provide absolute RV measurements (precise to better than ±1 km s−1) for our sample and estimate line-of-sight velocities for the Hodge 301 and SL 639 clusters, which agree well with those of hot stars in the same clusters. By combining results for the RSGs with those for nearby B-type stars, we estimate systemic velocities and line-of-sight velocity dispersions for the two clusters, obtaining estimates for their dynamical masses of log(Mdyn/M⊙) = 3.8 ± 0.3 for Hodge 301, and an upper limit of log(Mdyn/M⊙) < 3.1 ± 0.8 for SL 639, assuming virial equilibrium. Analysis of the multi-epoch data reveals one RV variable, potential binary candidate (VFTS 744), which is likely a semi-regular variable asymptotic giant branch star. Calculations of semi-amplitude velocities for a range of RSGs in model binary systems and literature examples of binary RSGs were used to guide our RV variability criteria. We estimate an upper limit on the observed binary fraction for our sample of 0.3; for this sample we are sensitive to maximum periods for individual objects in the range 1–10 000 days and mass ratios above 0.3 depending on the data quality. From simulations of RV measurements from binary systems given the current data, we conclude that systems within the parameter range q > 0.3, log P [days] < 3.5 would be detected by our variability criteria at the 90% confidence level. The intrinsic binary fraction, accounting for observational biases, is estimated using simulations of binary systems with an empirically defined distribution of parameters in which orbital periods are uniformly distributed in the 3.3 < log P [days] < 4.3 range. A range of intrinsic binary fractions are considered; a binary fraction of 0.3 is found to best reproduce the observed data. Conclusions. We demonstrate that RSGs are effective extragalactic kinematic tracers by estimating the kinematic properties, including the dynamical masses of two LMC young massive clusters. In the context of binary evolution models, we conclude that the large majority of our sample consists of effectively single stars that are either currently single or in long-period systems. Further observations at greater spectral resolution or over a longer baseline, or both, are required to search for such systems.

The VLT-FLAMES Tarantula Survey

Aims. We estimate physical parameters for the late-type massive stars observed as part of the VLT-FLAMES Tarantula Survey (VFTS) in the 30 Doradus region of the Large Magellanic Cloud (LMC). Methods. The observational sample comprises 20 candidate red supergiants (RSGs) which are the reddest ((B − V) > 1 mag) and brightest (V < 16 mag) objects in the VFTS. We use optical and near-infrared (near-IR) photometry to estimate their temperatures and luminosities, and introduce the luminosity–age diagram to estimate their ages. Results. We derive physical parameters for our targets, including temperatures from a new calibration of (J − Ks)0 colour for luminous cool stars in the LMC, luminosities from their J-band magnitudes (thence radii), and ages from comparisons with current evolutionary models. We show that interstellar extinction is a significant factor for our targets, highlighting the need to take it into account in the analysis of the physical parameters of RSGs. We find that some of the candidate RSGs could be massive AGB stars. The apparent ages of the RSGs in the Hodge 301 and SL 639 clusters show a significant spread (12–24 Myr). We also apply our approach to the RSG population of the relatively nearby NGC 2100 cluster, finding a similarly large spread. Conclusions. We argue that the effects of mass transfer in binaries may lead to more massive and luminous RSGs (which we call “red stragglers”) than expected from single-star evolution, and that the true cluster ages correspond to the upper limit of the estimated RSG ages. In this way, the RSGs can serve as a new and potentially reliable age tracer in young star clusters. The corresponding analysis yields ages of 24−3+5 Myr for Hodge 301, 22−5+6 Myr for SL 639, and 23−2+4 Myr for NGC 2100.