Cloud Formation Research Articles

Underwater point cloud transmission framework: hybrid encoder implementation based on CNN and transformer

Abstract In underwater multi-robot systems, 3D point cloud data generated by sonar and depth sensors facilitates the execution of more complex collaborative tasks among robots, which partly rely on efficient data transmission. In this work, we propose a hybrid encoder framework based on convolutional neural network and Transformer for underwater point cloud transmission, aimed at dealing with large-scale point cloud data. Our encoder allows setting lower compression rate on regions or objects of interest for semantic point clouds, preserving crucial information in the point cloud. For underwater acoustic communication, we employ orthogonal frequency division multiplexing combined with deep joint source-channel coding for transmission to enhance the system’s error-resilience. Compared to state-of-the-art methods in the simulation experiments, our end-to-end framework achieves considerable compression performance while eliminating certain cliff and leveling effects, also demonstrating robustness even with changing channels.

Impact of mountain-wave-induced temperature fluctuations on the occurrence of polar stratospheric ice clouds: a statistical analysis based on MIPAS observations and ERA5 data

Abstract. Temperature fluctuations induced by mountain waves can play a crucial role in the formation of polar stratospheric clouds (PSCs). In particular, the cold phase of the waves can lower local temperatures sufficiently to trigger PSC formation, even when large-scale background temperatures are too high. To provide new quantitative constraints on the relevance of this effect, this study analyzes a decade (2002–2012) of ice PSC detections obtained from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) measurements and ERA5 data in the polar winter lower stratosphere. In the MIPAS observations, we find that approximately 52 % of the Arctic ice PSCs and 26 % of the Antarctic ice PSCs are detected at temperatures above the local Tice. Ice PSCs above Tice are concentrated around mountainous regions and their downwind directions. A backward-trajectory analysis is performed to investigate the temperature history of each ice PSC observation. The cumulative fraction of ice PSCs above Tice increases as the trajectory gets closer to the observation point. The most significant change in the fraction of ice PSCs above Tice occurs within the 6 h preceding the observations. At the observation point, the mean fractions of ice PSCs above Tice, taking into account temperature fluctuations along the backward trajectory, are 33 % in the Arctic and 9 % in the Antarctic. The results provide a quantitative assessment of the occurrence of ice PSCs above Tice in connection with orographic waves. Additionally, the observational statistics presented can be utilized for comparison with chemistry climate simulations.

Multiwavelength Raman lidar system for profiling the CCN number concentrations

Cloud condensation nuclei (CCN) play an important role in the research of cloud microphysical and aerosol–cloud interactions. This study employs a multiwavelength Raman lidar for measuring CCN concentration. First, the multiwavelength Raman lidar was used to measure the atmospheric relative humidity profile, and the combination of relative humidity and the aerosol backscattering coefficient was used to retrieve the hygroscopic growth factor. By fitting the hygroscopic growth factor using the κkappa parameter model, the hygroscopic parameter κkappa that characterizes the hygroscopicity of aerosols was obtained. Then, the critical activation radius of aerosols was derived using the κ–Köhler theory and hygroscopicity parameter κkappa. Finally, the CCN number concentration was obtained by combining with the aerosol particle size distribution. Experiments were conducted to verify the feasibility of the multiwavelength Raman lidar. Results showed that the effective detection range of the lidar is approximately 0–4 km. The error of the temperature measured by the lidar at the height of 0.3–3.8 km is approximately ±1K. When the relative humidity change is 0.77–0.87, the range of the hygroscopic growth factor change is 1.06–1.10, the hygroscopic parameter γ is 0.065, and the hygroscopic parameter κkappa is 0.009. The CCN numbers concentration decreases with height but increases closer to the cloud. The multiwavelength Raman lidar is an important tool for detection of cloud microphysical and aerosol–cloud interactions and could have scientific importance and research value, both for improved understanding of the formation of clouds and precipitation and for enhanced accuracy of weather modification.

Size-Dependent Nascent Sea Spray Aerosol Bounce Fractions and Estimated Viscosity: The Role of Divalent Cation Enrichment, Surface Tension, and the Kelvin Effect.

Viscosity, or the "thickness," of aerosols plays a key role in atmospheric processes like ice formation, water absorption, and heterogeneous kinetics. However, the viscosity of sea spray aerosols (SSA) has not been widely studied. This research explored the relationship between particle size and viscosity of authentic SSA particles through particle bounce, atomic force microscopy analysis, and predictive viscosity modeling from molecular composition. The study found that 40 nm SSA particles had estimated viscosities around 104 Pa·s and bounce fractions three times higher than 100 and 200 nm particles with less than 102 Pa·s at a relative humidity (RH) of 60%. Additional studies revealed the Kelvin effect and particle density, influenced by particle size, have a greater impact on size-dependent bounce fractions than changes in RH across impactor stages. While changes in the level of surfactants can impact particle bounce, the increased viscosity in smaller SSA is attributed to the formation of gel-like phase states caused by cation-organic cross-links between divalent calcium ions and organic anions enriched in the smaller particles. This work shows the smallest gel-like SSA particles observed in the field are highly viscous, which has implications for cloud formation, secondary aerosol growth, and pollutant transport in coastal environments.

ExoLyn: A golden mean approach to multispecies cloud modeling in atmospheric retrieval

Clouds are ubiquitous in exoplanets' atmospheres and play an important role in setting the opacity and chemical inventory of the atmosphere. Understanding clouds is a critical step in interpreting exoplanets' spectroscopic data. The aim is to model the multispecies nature of clouds in atmospheric retrieval studies. To this end, we developed -- a 1D cloud model that balances physical consistency with computational efficiency. solves the transport equation of cloud particles and vapor under cloud condensation rates that are self-consistently calculated from thermodynamics. is a standalone, open source package capable of being combined with optool to calculate solid opacities and with petitRADTRANS to generate transmission or emission spectra. With we find that the compositional structure of clouds in hot Jupiter planets' atmospheres is layered with a cloud dominated by magnesiumsilicates on top of an iron cloud. This finding is consistent with more complex cloud formation models but can be obtained with in only a few seconds. The composition of the cloud particles can be constrained from the spectrum, for example MgSiO3 and Mg2SiO4 components give rise to an absorption feature at $8-10\ m $. We investigate the dependence of the cloud structure on the bulk elemental composition of the planet and find that SiO2 -dominated clouds form on metal-rich planets and Fe clouds with a strong extinction effect form on C-rich planets. Designed toward maximum flexibility can also be used in retrieval analysis of sub-Neptunes and self-luminous planets. The efficiency of opens the possibility of joint retrieval of exoplanets' gas and cloud components.

A statistically significant increase in ice supersaturation in the atmosphere in the past 40 years

Ice saturation (and supersaturation) is a frequent phenomenon in cold regions of the upper troposphere. Its existence is essential for the formation of ice clouds and a necessary condition for the persistence of contrails. Its spatial and temporal evolution is important for weather and climate. The ice saturation and supersaturation values are found in the upper tail of the probability density function (pdf) of upper tropospheric humidity with respect to ice (UTHi). Here, we analyse the changes in the frequency of occurrence of ice saturation and supersaturation from 1979 to 2020 and compare them to changes in the mean UTHi. Our results show that while the mean UTHi increases near-globally with a rate of about 0.15% per decade, high UTHi values exceeding the 70%, 80%, 90% and 100% thresholds increase faster than the mean, at rates of about 0.7%, 0.6%, 0.4% and 0.3% per decade, respectively. The increasing rates of values found in the upper tail of the UTHi pdf suggest that the ambient conditions for cirrus and contrail formation and persistence will be more favourable in the future and this is expected to further enhance the impact of aviation on climate.

Water Uptake of Airborne Cells of P. syringae Measured with a Hygroscopicity Tandem Differential Mobility Analyzer.

Airborne microorganisms impact cloud formation and are involved in disease spreading. The ability of airborne cells to survive and express genes may be limited by reduced water availability in the atmosphere and depend on the ability of the cells to attract water vapor at subsaturated conditions, i.e., their hygroscopicity. We assessed hygroscopic properties of the plant pathogen Pseudomonas syringae, known to participate in cloud formation. We used a hygroscopicity tandem differential mobility analyzer to examine both hydration and dehydration behavior in the relative humidity (RH) range 5-90%. The cells were aerosolized either from Milli-Q water or from a 35 g L-1 NaCl solution, resulting in pure cells or cells associated with NaCl. Pure cells exhibited no deliquescence/efflorescence and a small gradual water uptake reaching a maximum growth factor (GF) of 1.09 ± 0.01 at 90% RH. For cells associated with NaCl, we observed deliquescence and a much larger maximum GF of 1.74 ± 0.03 at 90% RH. Deliquescence RH was comparable to that of pure NaCl, highlighting the major role of the salt associated with the cells. It remains to be investigated how the observed hygroscopic properties relate to survival, metabolic, and ice-nucleation activities of airborne P. syringae.

EIDU-Net: edge-preserved inception DenseGCN U-Net for LiDAR point cloud segmentation

With the development of laser scanners and machine learning, point cloud semantic segmentation plays a significant role in autonomous driving, scene reconstruction, human-computer interaction, and other fields. In recent years, point cloud semantic segmentation based on deep learning has become one of the key research directions in point cloud processing. Due to the limited ability to exploit geometric details and contextual information in point clouds, most methods that adopt encoder-decoder architecture lose local structural information easily, especially detailed features, and extract features insufficiently. To address this issue, the edge-preserving inception DenseGCN U-Net (entitled as EIDU-Net) is proposed. EIDU-Net makes full use of the complementation between geometric details in the original point cloud and high-level features. The edge-preserved graph pooling (EGP) layer, the key module of the EIDU-Net, is designed to retain additional edge feature information from the original point cloud during pooling operations. Accordingly, the edge-preserved graph unpooling (EGU) layer can restore the feature graph more efficiently based on the additionally retained edge features. Extensive experiments demonstrate that our proposed EIDU-Net has remarkable improvements on semantic segmentation tasks under whatever S3DIS or Terracotta Warrior fragments. Our code is publicly available at https://github.com/caoxin918/EIDU-Net.

Pulsar Nulling and Vacuum Radio Emission from Axion Clouds.

Nonrelativistic axions can be efficiently produced in the polar caps of pulsars, resulting in the formation of a dense cloud of gravitationally bound axions. Here, we investigate the interplay between such an axion cloud and the electrodynamics in the pulsar magnetosphere, focusing specifically on the dynamics in the polar caps, where the impact of the axion cloud is expected to be most pronounced. For sufficiently light axions m_{a}≲10^{-7} eV, we show that the axion cloud can occasionally screen the local electric field responsible for particle acceleration and pair production, inducing a periodic nulling of the pulsar's intrinsic radio emission. At larger axion masses, the small-scale fluctuations in the axion field tend to suppress the backreaction of the axion on the electrodynamics; however, we point out that the incoherent oscillations of the axion in short-lived regions of vacuum near the neutron star surface can produce a narrow radio line, which provides a complementary source of radio emission to the plasma-resonant emission processes identified in previous work. While this Letter focuses on the leading order correction to pair production in the magnetosphere, we speculate that there can exist dramatic deviations in the electrodynamics of these systems when the axion backreaction becomes nonlinear.

Variations of Planetary Wave Activity in the Lower Stratosphere in February as a Predictor of Ozone Depletion in the Arctic in March

This study is dedicated to the investigation of the relationship between the wave activity in February and temperature variations in the Arctic lower stratosphere in March. To study this relationship, the correlation coefficients (CCs) between the minimum temperature of the Arctic lower stratosphere in March (Tmin) and the amplitude of the planetary wave with zonal number 1 (PW1) in February were calculated. Tmin determines the conditions for the formation of polar stratospheric clouds (PSCs) following the chemical destruction of the ozone layer. The NCEP and ERA5 reanalysis data and the modern and future climate simulations of the Earth system models INM CM5 and SOCOLv4 were employed. It is shown that the maximum significant CC value between Tmin at 70 hPa in the polar region in March and the amplitude of the PW1 in February in the reanalysis data in the lower stratosphere is 0.67 at the pressure level of 200 hPa. The CCs calculated using the model data are characterized by maximum values of ~0.5, also near the same pressure level. Thus, it is demonstrated that the change in the planetary wave activity in the lower extratropical stratosphere in February can be one of the predictors of the Tmin. For further analysis of the dynamic structure in the lower stratosphere, composites of 10 seasons with the lowest and highest Tmin of the Arctic lower stratosphere in March were assembled. For these composites, differences in the vertical distribution and total ozone content, surface temperature, and residual meridional circulation (RMC) were considered, and features of the spatial distribution of wave activity fluxes were investigated. The obtained results may be useful for the development of forecasting of the Arctic winter stratosphere circulation, especially for the late winter season, when substantial ozone depletion occurs in some years.

Role of midtropospheric heating and surface forcing on monsoon intraseasonal transitions

AbstractMonsoon intraseasonal transitions are intrinsically chaotic; hence, their predictability is limited. In the past the majority of studies were conducted solely keeping in account of dynamic prospective like boreal summer intraseasonal oscillation or Madden–Julian oscillation; however its thermodynamic aspect got limited attention. The current study looks at the internal thermodynamic mechanisms pertaining to monsoon intraseasonal transition using two independent sets of reanalysis data (European Centre for Medium‐range Weather Forecasts Reanalysis version 5 and Indian Monsoon Data Assimilation and Analysis), along with the observed cloud type from Met Office Integrated Data Archive System Land and Marine surface station data. A lead–lag composite analysis shows that the midtropospheric warming by diabatic heating is a thermal control to restrict the deepening of convective cloud (cumulonimbus) as the wet spell progresses. This midtroposhperic heating cuts off the formation of deep convective clouds and results in the formation of relatively shallow clouds, such as stratocumulus and stratus. On the other hand, surface forcing during dry spells humidifies the troposphere by detrainment from the shallow convection with the formation of cumulus and cumulus congestus clouds. This facilitates the preconditioning of the atmosphere for deep convection and results in the onset of wet spells by the formation of cumulonimbus clouds. The comprehensive approach used in this work may further help in identifying the limitation of the predictability in monsoon transition period from the numerical weather prediction models.

Impact of Asian Dust on Cirrus Formation Over the Central Pacific: CALIOP‐ and CloudSat‐Observation‐Based Case Studies

AbstractCirrus clouds are of great importance to the global climate, with their net radiative forcing strongly dependent on the microphysical properties that are related to the ice‐nucleating regime. However, the influence of long‐range transport of dust on primary ice formation in cirrus clouds is limitedly understood, specifically over the clean remote ocean regions. Here, two case studies show that transpacific Asian dust can impact the ice formation of cirrus clouds over the central Pacific based on Cloud‐Aerosol Lidar with Orthogonal Polarization and Cloud Profiling Radar (CPR, CloudSat) observations. One case shows a well‐developed horizontally extended cirrus embedded in a pure dust layer, with an average dust‐related ice‐nucleating particle concentration (INPC) of 7 L−1 and 96 L−1 for an ice saturation ratio Si of 1.15 and 1.25, respectively; ice crystal number concentration (ICNC) with diameters >25 and 100 μm (denoted as nice,25 μm and nice,100 μm) are 64 L−1 and 7 L−1, respectively. Another case shows that cirrus clouds with a much smaller horizontal extent appeared in the vicinity of polluted dust, with an average INPC of 42–310 L−1 for the typical higher Si of 1.25–1.35 by considering a tenfold reduction of the ice nucleation efficiency of ice crystals; nice,25 μm and nice,100 μm are 168 L−1 and 20 L−1, respectively. The estimated INPC and ICNC values suggest the dominance of ice formation by dust‐induced heterogeneous nucleation, proving that the long‐range transport of dust toward the upper troposphere and the potential influence on cirrus formation over the central Pacific should be well considered in atmospheric models.

TAG-fusion: Two-stage attention guided multi-modal fusion network for semantic segmentation

In the current research, leveraging auxiliary modalities, such as depth information or point cloud information, to improve RGB semantic segmentation has shown significant potential. However, existing methods mainly use convolutional modules for aggregating features from auxiliary modalities, thereby lacking sufficient exploitation of long-range dependencies. Moreover, fusion strategies are typically limited to singular approaches. In this paper, we propose a transformer-based multimodal fusion framework to better utilize auxiliary modalities for enhancing semantic segmentation results. Specifically, we employ a dual-stream architecture for extracting features from RGB and auxiliary modalities, respectively. We incorporate both early fusion and deep feature fusion techniques. At each layer, we introduce mixed attention mechanisms to leverage features from other modalities, guiding and enhancing the current modality's features before propagating them to the subsequent stage of feature extraction. After the extraction of features from different modalities, we employ an enhanced cross-attention mechanism for feature interaction, followed by channel fusion to obtain the final semantic features. Subsequently, we provide separate supervision to the network on the RGB stream, auxiliary stream, and fusion stream to facilitate the learning of representations for different modalities. The experimental results demonstrate that our framework exhibits superior performance across diverse modalities. Specifically, our approach achieves state-of-the-art results on the NYU Depth V2, SUN-RGBD, DELIVER and MFNet datasets.

Compact and high excitation molecular clumps in the extended ultraviolet disk of M83

The extended ultraviolet (XUV) disks of nearby galaxies show ongoing massive-star formation, but their parental molecular clouds remain mostly undetected despite searches in CO(1-0) and CO(2-1). The recent detection of 23 clouds in the higher excitation transition CO(3-2) within the XUV disk of M83 thus requires an explanation. We test the hypothesis introduced to explain the non-detections and recent detection simultaneously: The clouds in XUV disks have a clump-envelope structure similar to those in Galactic star-forming clouds, having dense star-forming clumps (or concentrations of multiple clumps) at their centers, which predominantly contribute to the CO(3-2) emission and are surrounded by less dense envelopes, where CO molecules are photo-dissociated due to the low-metallicity environment there. We utilized new high-resolution ALMA CO(3-2) observations of a subset (11) of the 23 clouds in the XUV disk of M83. We confirm the compactness of the CO(3-2)-emitting dense clumps (or their concentrations), finding clump diameters below the spatial resolution of 6-9 pc. This is similar to the size of the dense gas region in the Orion A molecular cloud, a local star-forming cloud with massive-star formation. The dense star-forming clumps are common between normal and XUV disks. This may also indicate that once the cloud structure is set, the process of star formation is governed by the cloud's internal physics rather than by external triggers. This simple model explains the current observations of clouds with ongoing massive-star formation, although it may require some adjustment, for example including the effect of cloud evolution, to describe star formation in molecular clouds more generally.

The impact of the QBO vertical structure on June extreme high temperatures in South Asia

Using observation data and numerical simulations, we have demonstrated that the stratospheric Quasi-Biennial Oscillation (QBO) can predict extreme high temperatures (EHTs) in South Asia in June. The vertical structure of the QBO plays a crucial role in this prediction. When the QBO in June shows easterlies (westerlies) at 50 hPa and westerlies (easterlies) at 70 hPa, more (fewer) EHT events occur. This likely results from the QBO’s vertical structure causing positive (negative) temperature anomalies in the lower stratosphere and negative (positive) static stability anomalies near the tropical tropopause. These anomalies enhance (weaken) convective activity over the equatorial Indian Ocean, leading to anomalous circulation with ascending (descending) air over the equatorial Indian Ocean and descending (ascending) air over northern and central South Asia. This suppresses (promotes) convection over northern and central South Asia, affecting cloud formation and precipitation. Consequently, more (less) solar radiation reaches the region, along with weaker (stronger) evaporative cooling effects, warming (cooling) the surface and creating a background state conducive to (against) EHT events. Additionally, the opposite zonal winds at 30 hPa and 50 hPa in April may serve as a reference factor for predicting the probability of EHT events in northern and central South Asia. This study provides a potential approach for forecasting tropospheric extreme weather events based on stratospheric signals.

Microplastics stress alters microorganism community structure and reduces the production of biogenic dimethylated sulfur compounds

AbstractDimethylsulfoniopropionate (DMSP) is a plentiful organic sulfur metabolite and the primary precursor for dimethyl sulfide (DMS), which plays a crucial role in global sulfur cycling, the formation of clouds, and cooling the warming earth. The origin and fate of DMSP are intricately linked to marine microorganisms, making the variation of the microorganism community crucial for DMSP dynamics. Nonetheless, the impact of pervasive marine microplastics on microorganisms and processes related to DMSP synthesis and degradation remains insufficiently investigated. To bridge this gap, a 14‐d deck‐based microcosm experiment was conducted, revealing that microplastics significantly altered the composition of microorganism communities and dramatically inhibited the release of DMS and DMSP. Furthermore, multivariate analysis demonstrated that the variations both in environmental variables and microorganism communities caused by microplastics were forcing factors in reducing DMS and DMSP release. In addition, the predicted function of the bacterial community showed a significant reduction in the presence of dddP and dmdA genes when exposed to microplastics, which directly disrupted both the demethylation and cleavage pathways of DMSP. These results indicate that the release of DMS and DMSP in marine ecosystems can be significantly affected by microplastics through influencing microorganisms. Thus, it is imperative to conduct research on controlling the synthesis and degradation of DMSP in the ocean, particularly in response to these environmental pollution issues. Such research can help discern new patterns from specific phenomena and identify crucial processes.

Atmospheric Fungal Spore Injection: A Promising Breakthrough for Challenging the Impacts of Climate Change Through Cloud Seeding and Weather Modification

Cloud seeding is a technique used to enhance precipitation in drought-prone areas, support agricultural productivity, ensure water supply for human consumption, improve hydropower generation from dams, lessen hurricanes, cool urban heat, and disperse fog in airports. Growing global population size and climate change are the biggest impetus for weather modification and cloud seeding operations. Currently, salt powders like silver iodide, potassium iodide, sodium chloride, calcium chloride, dry ice (solid carbon dioxide), and liquid propane are widely used as ice nucleating particles for cloud seeding purposes while in natural cloud formation, and precipitation particles from dust storms, mineral dust and biological aerosols (like spores, pollen, bacteria) are the dominant ice nucleators. Having this knowledge on hand and the ubiquitous nature of fungi on the other hand; it is feasible to exploit the ice nucleating ability of fungal spores and use it as potential candidates for cloud seeding and weather modification operations.

Enhancing Data Security and Accountability in Cloud Computing: A Decentralized Cloud Information Accountability Framework

Enhancing Data Security and Accountability in Cloud Computing: A Decentralized Cloud Information Accountability Framework

Impact of biomass burning on air quality: A case study of the agricultural region in South Korea

Various combustion processes occur concurrently during biomass burning events, emitting a complex mixture of particulate and gaseous pollutants into the atmosphere. These emissions undergo chemical transformations facilitated by factors such as solar radiation and cloud formation, thereby altering the composition of aerosols. Additionally, these pollutants can affect the region of origin and neighboring countries, presenting regional and global environmental challenges. Therefore, precise evaluation of the particulate and gaseous pollutants emitted during biomass burning is essential to formulate effective management strategies. This study aimed to assess the concentration and chemical characteristics of particulate matter emitted during biomass burning in South Korea. On June 7, 2021, a research flight was conducted utilizing a High Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and a Single Particle Soot Photometer (SP2) for airborne measurements over South Korea inland areas. For data analysis based on administrative regions, the flight path was divided into four major areas (Areas A, B, C, and D). During the research flight, evidence of biomass burning events was observed primarily in Area C. A positive matrix factorization (PMF) analysis categorized the organic aerosols (OA) into five factors: biomass burning OA (BBOA), hydrocarbon-like OA (HOA1, HOA2), low-oxidized oxygenated OA (LO-OOA), and more-oxidized OOA (MO-OOA). Across all areas, MO-OOA accounted for the highest proportion of aerosols, whereas BBOA dominated in Area C at 23.8%, indicating the significant influence of biomass burning in this region. Instead of running a PMF analysis with all measurement data, a BBOA formula was derived from the previous study and this one. This allows us to estimate BBOA concentration without running PMF.

Nightside Clouds on Tidally Locked Terrestrial Planets Mimic Atmosphere-free Scenarios

We investigate the impact of nightside cloud formation on the observable day/night contrast of tidally locked terrestrial planet atmospheres. We demonstrate that, in the case where the planetary dayside is only 10 s of Kelvin hotter than the planetary nightside, the presence of optically thick nightside clouds can lead to observations that mimic a planet without an atmosphere, despite the planet actually hosting a significant (10 bar) atmosphere. The scenario presented in this work requires a level of intrinsic atmospheric day/night temperature contrast such that the nightside can form clouds while the dayside is too hot for cloud formation to occur. This scenario is most likely for hotter terrestrials and terrestrials with low volatile inventories. We thus note that a substantial dayside/nightside temperature difference alone does not robustly indicate that a planet does not host an atmosphere, and additional observations and modeling are essential for characterization. We further discuss several avenues for future study to improve our understanding of the terrestrial planets and how best to characterize them with JWST.