Optical Depth Research Articles

Local H i absorption towards the magellanic cloud foreground using ASKAP

ABSTRACT We present the largest Galactic neutral hydrogen H i absorption survey to date, utilizing the Australian SKA Pathfinder Telescope at an unprecedented spatial resolution of 30 arcsec. This survey, GASKAP-H i, unbiasedly targets 2714 continuum background sources over 250 square degrees in the direction of the Magellanic Clouds, a significant increase compared to a total of 373 sources observed by previous Galactic absorption surveys across the entire Milky Way. We aim to investigate the physical properties of cold (CNM) and warm (WNM) neutral atomic gas in the Milky Way foreground, characterized by two prominent filaments at high Galactic latitudes (between $-45^{\circ }$ and $-25^{\circ }$). We detected strong H i absorption along 462 lines of sight above the 3$\sigma$ threshold, achieving an absorption detection rate of 17 per cent. GASKAP-H i’s unprecedented angular resolution allows for simultaneous absorption and emission measurements to sample almost the same gas clouds along a line of sight. A joint Gaussian decomposition is then applied to absorption-emission spectra to provide direct estimates of H i optical depths, temperatures, and column densities for the CNM and WNM components. The thermal properties of CNM components are consistent with those previously observed along a wide range of Solar neighbourhood environments, indicating that cold H i properties are widely prevalent throughout the local interstellar medium. Across our region of interest, CNM accounts for $\sim$30 per cent of the total H i gas, with the CNM fraction increasing with column density towards the two filaments. Our analysis reveals an anticorrelation between CNM temperature and its optical depth, which implies that CNM with lower optical depth leads to a higher temperature.

Interdecadal Springtime Aerosol Increase in the North Indian Ocean Observed From the Satellite AVHRR Instrument

AbstractA 38‐year aerosol optical thickness (AOT) satellite product from the Advanced Very High‐Resolution Radiometer (AVHRR) is used to investigate the aerosol variabilities in the North Indian Ocean (NIO). A dipolar mode with a notable meridional contrast between the equatorial and northern NIO is revealed by the second mode of Empirical Orthogonal Function (EOF) analysis with a sharp rise over the Arabian Sea (AS) and Bay of Bengal (BoB) since 2002. Our results show that the aerosol dipolar variation is primarily modulated by an El Niño–Southern Oscillation (ENSO) during 1983–2001 (ID1) and by a warm phase of Atlantic Multi‐decadal Oscillation (AMO) during 2002–2020 (ID2), leading to a dry‐and‐warming condition spanning the coasts of East Africa, the Arabian Peninsula (AP), and South Asia (SA) that favors increasing aerosol emission and a longer life cycle in the upstream regions. A warm phase of the AMO tends to excite an anomalous cyclone in western Siberia and reinforces anticyclonic circulation in the Tibetan Plateau. Correlation analyses between the second EOF mode time series and other parameters in ID1 and ID2 show that an interannual dry‐and‐warming condition over the AP–SA is associated with a noticeable north‐south contrast of convection between the equatorial NIO and AP–SA in ID1. But in ID2, a zonal contrast of anomalous convective activities between the AP–SA and the BoB‐South China Sea is dominant, partially due to the warming AMO, which aids the development of anticyclonic cells over the TP and the strengthened subtropical westerly jet streams.

Aerosol optical depth retrieval using scaled digital number (DN) values of multi-spectral satellite and a generating adversarial model based on deep learning application

ABSTRACT The current quantitative retrieval of Aerosol Optical Depth (AOD) typically uses Top-of-atmosphere (TOA) reflectance data obtained by the scale and offset terms of radiometric calibration. Errors can be introduced during the conversion of Digital Number (DN) values to TOA reflectance, restraining the accurate retrieval of AOD. Particularly when surface reflectance is high, conversion errors can significantly distort the retrieval of Aerosol Optical Depth (AOD), given the minimal impact of aerosols on the radiation detected by satellite sensors. To counteract this, we introduce an innovative retrieval algorithm that harnesses a Generative Adversarial Network (GANN), a deep learning (DL) model, to accurately derive AOD from the scaled digital number (DN) values of multi-spectral satellite imagery. The DL technology enables the use of scaled DN values for AOD retrieval, bypassing the conversion errors associated with TOA reflectance since it relies on a sample learning approach instead of radiative transfer calculations. To ensure the number and representativeness of training samples, a total of 37,103 samples from different underlying surfaces from 2014 to 2018 were obtained using a space-time matching strategy. Our K-cross validation demonstrates that employing DN values for AOD retrieval promises to yield higher accuracy compared to using TOA reflectance. Independent 2019 data were used to estimate GANN, MCD19A2 and MOD04_3K aerosol products. Our model showed superior performance compared to the other products in terms of a higher correlation (R = 0.8184) with AERONET AOD and obtaining more reliable retrievals (7601). The sensitivity experiment suggests that GANN exhibits limitations in areas characterized by high aerosol loads and heterogeneity. Our study can give a novel insight into AOD retrieval based on multi-spectral satellite and DL models.

Satellite-observed relationships between land cover, burned area, and atmospheric composition over the southern Amazon

Abstract. Land surface changes can have substantial impacts on biosphere–atmosphere interactions. In South America, rainforests abundantly emit biogenic volatile organic compounds (BVOCs), which, when coupled with pyrogenic emissions from deforestation fires, can have substantial impacts on regional air quality. We use novel and long-term satellite records of five trace gases, namely isoprene (C5H8), formaldehyde (HCHO), methanol (CH3OH), carbon monoxide (CO), and nitrogen dioxide (NO2), in addition to aerosol optical depth (AOD), vegetation (land cover and leaf area index), and burned area. We characterise the impacts of biogenic and pyrogenic emissions on atmospheric composition for the period 2001 to 2019 in the southern Amazon, a region of substantial deforestation. The seasonal cycle for all of the atmospheric constituents peaks in the dry season (August–October), and the year-to-year variability in CO, HCHO, NO2, and AOD is strongly linked to the burned area. We find a robust relationship between the broadleaf forest cover and total column C5H8 (R2 = 0.59), while the burned area exhibits an approximate fifth root power law relationship with tropospheric column NO2 (R2 = 0.32) in the dry season. Vegetation and burned area together show a relationship with HCHO (R2 = 0.23). Wet-season AOD and CO follow the forest cover distribution. The land surface variables are very weakly correlated with CH3OH, suggesting that other factors drive its spatial distribution. Overall, we provide a detailed observational quantification of biospheric process influences on southern Amazon regional atmospheric composition, which in future studies can be used to help constrain the underpinning processes in Earth system models.

Exploring the use of ground-based remote sensing to identify new particle formation events: A case study in the Beijing area

New Particle Formation (NPF) is an important process of secondary aerosol production in the atmosphere, which has significant impacts on the Earth's radiation balance, air quality, and climate change. In this study, we develop a method to identify NPF events based on ground-based remote sensing. We propose a proxy to characterize NPF events utilizing ground-based remote sensing of gaseous precursors and aerosol optical depth (AOD). This proxy is applied to identify the NPF events in Beijing in the winter of 2022 and tested by comparison with in-situ observations of aerosol particle number size distributions (PNSD) from SMPS. The comparison shows that the NPF events for regional nucleation can be identified effectively when the threshold for sulfur dioxide and organic gases (i.e. formaldehyde) are determined as 0.44 × 10−4 and 1.07 × 10−4. Based on these thresholds, the NPF events can be identified at a high percentage (84 %) compared with in-situ observations. The relationship between identification of NPF events and meteorological conditions shows that NPF events in Beijing winter occurred more frequently under weather conditions with north-west wind direction, high wind speed and low relative humidity.

Spaceborne lidar measurement of global cloud properties through machine learning

With a large footprint size, multiple scattering measurements of clouds from spaceborne lidar provide useful information about cloud physical properties, such as cloud optical depths and cloud droplet size, both during daytime and nighttime. A neural network algorithm, with a subset of cloud backscatter profiles of dual-polarization and dual-wavelength Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar measurements during daytime as input variables and cloud physical properties derived from collocated Moderate Resolution Imaging Spectroradiometer (MODIS) multi-spectral measurements as output, is developed and evaluated with an independent subset of the collocated CALIPSO and MODIS measurements. The study suggests that with a receiver footprint size of 110 m, CALIPSO lidar measurements are sensitive to liquid-phase cloud optical depth variations from 0 to 25. A larger footprint size, thus more multiple scattering, is required for lidar to have sensitivities to all liquid-phase clouds. The technique can be applied to all 17 years of CALIPSO daytime and nighttime measurements and, thus, provides useful information about global distributions of cloud physical properties both during day and night.

Retrieving hourly aerosol optical depth for geostationary satellite FY-4B/AGRI by surface-related dynamic spectral reflectance ratio method

The Advanced Geostationary Radiation Imager (AGRI) on board Fengyun-4B (FY-4B) has been found to have significant advantages in aerosol dynamic monitoring. This study proposed a surface-related dynamic spectral reflectance ratio (SDSRR) method for FY-4B AGRI to solve the problem of inaccurate surface reflectance estimation in Aerosol Optical Depth (AOD) retrieval. This method introduced Moderate-resolution Imaging Spectroradiometer (MODIS) aerosol product to assist in calculating the surface reflectance of the AGRI blue channel and the spectral reflectance ratio between the shortwave infrared (SWIR) channel and the blue channel, then constructed a surface-related dynamic spectral reflectance ratio series by combining the spectral reflectance ratio, Normalized Difference Vegetation Index (NDVI) and Scattering Angle (SCA) to obtain aerosol retrieval results. To verify the accuracy of the SDSRR method, the AOD dataset of the SDSRR method, the official aerosol products of AGRI (LDA) and Advanced Himawari Imager (AHI) AOD datasets were compared with the ground-based observations of Aerosol Robotic Network (AERONET) and Sun-shy radiometer Observation Network (SONET) in East Asia. The results indicate that the SDSRR method performs more consistently in East Asia compared to the official ARGI aerosol products. The root-mean-square-error (RMSE), mean error (ME), and correlation coefficient (R) between SDSRR AOD and ground-based measurements are 0.286, 0.180 and 0.70, which is better than that of LDA AOD (RMSE = 0.508, ME = 0.292, R = 0.69). Additionally, the RMSE, ME, and R of AHI AOD were 0.253, 0.168, and 0.74, respectively.

Survival of gas in subhalos and its impact on the 21 cm forest signals: insights from hydrodynamic simulations

Understanding the survival of gas within subhalos under various astrophysical processes is crucial for elucidating cosmic structure formation and evolution. We study the resilience of gas in subhalos, focusing on the impact of tidal and ram pressure stripping through hydrodynamic simulations. Our results uncover significant gas stripping primarily driven by ram pressure effects, which also profoundly influence the gas distribution within these subhalos. Notably, despite their vulnerability to ram pressure effects, the low-mass subhalos can play a pivotal role in influencing the observable characteristics of cosmic structures due to their large abundance. Specifically, we explore the application of our findings to the 21 cm forest, showing how the survival dynamics of gas in subhalos can modulate the 21 cm optical depth, a key probe for detecting minihalos in the pre-reionization era. Our previous study demonstrated that the 21 cm optical depth can be enhanced by the subhalos, but the effects of tidal and ram pressure stripping on the subhalo abundance have not been fully considered. In this work, we further investigate the contribution of subhalos to the 21 cm optical depth with hydrodynamic simulations, particularly highlighting the trajectories and fates of subhalos within mass ranges of 104-6 M ⊙ h -1 in a host halo of 107 M ⊙h-1, and subhalos within mass range of 104-5 M ⊙h-1 in a host halo of 106 M ⊙h-1. Despite their susceptibility to ram pressure stripping, the contribution of abundant low-mass subhalos to the 21 cm optical depth is more significant than that of their massive counterparts primarily due to their greater abundance. We find that the 21 cm optical depth can be increased by a factor of approximately two due to the abundant low-mass subhalos. However, this enhancement is about twice as low as previously estimated in our earlier study, a discrepancy attributed to the effects of ram pressure stripping. Our work provides critical insights into the gas dynamics within subhalos in the early universe, highlighting their resilience against environmental stripping effects, and their impact on observable 21 cm signals.

Dynamics of atmospheric emissions and meteorological variables in Bangladesh from pre-to post-COVID-19 lockdown

Following the COVID-19 restrictions, there was a sharp decline in global air quality and related environmental metrics. Due to the limited availability of in situ atmospheric data in Bangladesh, this study collected data on various air pollutants (NO2, SO2, CO, and PM2.5), greenhouse gases (CO2, CH4, and O3), as well as meteorological variables like Land Surface Temperature (LST), Relative Humidity (RH), Precipitation, surface albedo and Aerosol Optical Depth (AOD) from different datasets by Google Earth Engine (GEE), the International Energy Agency (IEA), NASA Giovanni, and NASA Power Access Viewer, covering periods before (2019), during (2020), and after (2021–2023) the COVID-19 lockdown in Bangladesh. GIS-based assessment alongside Principal Component Analysis (PCA) has been performed to explore the patterns, trends and correlations among the observed variables. Results showed in 2020 compared to 2019, NO2, SO2, CO, PM2.5, and CO2 concentrations decreases by 1.94, 16.67, 1.95, 2.08, and 6 %, respectively, while CH4 and O3 continued to rise. Meteorological variables exhibited a 0.16 °C decreases in LST, 6.4 % increases in RH, a 6 % reduction in AOD, and 6.36 % declines in surface albedo. Post-lockdown in 2021, air pollutants surged (NO2, SO2, CO, and PM2.5 increases by 17.3, 23.6, 0.6, and 8.3 %, respectively), with CO2, LST, and AOD rising by 8.5 %, 0.13 °C, and 8.3 %, and a slight 0.46 % decrease in RH compared to 2019 due to resuming more economic activities, transportation and industrial production works. The years 2022–2023 saw slight improvements in most variables except CH4, though concentrations did not revert to those of 2019. The findings of correlation coefficients revealed that pollutants and GHG are highly correlated with the meteorological variables specially with RH. This study underscores the substantial shifts in atmospheric variables from pre-to post-lockdown periods, offering valuable insights for more effective management of the greenhouse effect and air pollution control strategies.

Development of over 30-years of high spatiotemporal resolution air pollution models and surfaces for California

California’s diverse geography and meteorological conditions necessitate models capturing fine-grained patterns of air pollution distribution. This study presents the development of high-resolution (100 m) daily land use regression (LUR) models spanning 1989–2021 for nitrogen dioxide (NO2), fine particulate matter (PM2.5), and ozone (O3) across California. These machine learning LUR algorithms integrated comprehensive data sources, including traffic, land use, land cover, meteorological conditions, vegetation dynamics, and satellite data. The modeling process incorporated historical air quality observations utilizing continuous regulatory, fixed site saturation, and Google Streetcar mobile monitoring data. The model performance (adjusted R2) for NO2, PM2.5, and O3 was 84 %, 65 %, and 92 %, respectively.Over the years, NO2 concentrations showed a consistent decline, attributed to regulatory efforts and reduced human activities on weekends. Traffic density and weather conditions significantly influenced NO2 levels. PM2.5 concentrations also decreased over time, influenced by aerosol optical depth (AOD), traffic density, weather, and land use patterns, such as developed open spaces and vegetation. Industrial activities and residential areas contributed to higher PM2.5 concentrations. O3 concentrations exhibited no significant annual trend, with higher levels observed on weekends and lower levels associated with traffic density due to the scavenger effect. Weather conditions and land use, such as commercial areas and water bodies, influenced O3 concentrations.To extend the prediction of daily NO2, PM2.5, and O3 to 1989, models were developed for predictors such as daily road traffic, normalized difference vegetation index (NDVI), Ozone Monitoring Instrument (OMI)–NO2, monthly AOD, and OMI-O3. These models enabled effective estimation for any period with known daily weather conditions.Longitudinal analysis revealed a consistent NO2 decline, regulatory-driven PM2.5 decreases countered by wildfire impacts, and spatially variable O3 concentrations with no long-term trend. This study enhances understanding of air pollution trends, aiding in identifying lifetime exposure for statewide populations and supporting informed policy decisions and environmental justice advocacy.

Two‐Streams Revisited: General Equations, Exact Coefficients, and Optimized Closures

AbstractTwo‐Stream Equations are the most parsimonious general models for radiative flux transfer with one equation to model each of upward and downward fluxes; these are coupled due to the transfer of fluxes between hemispheres. Standard two‐stream approximation of the Radiative Transfer Equation assumes that the ratios of flux transferred (coupling coefficients) are both invariant with optical depth and symmetric with respect to upwelling and downwelling radiation. Two‐stream closures are derived by making additional assumptions about the angular distribution of the intensity field, but none currently works well for all parts of the optical parameter space. We determine the exact values of the two‐stream coupling coefficients from multi‐stream numerical solutions to the Radiative Transfer Equation for shortwave radiation. The resulting unique coefficients accurately reconstruct entire flux profiles but depend on optical depth. More importantly, they generally take on unphysical values when symmetry is assumed. We derive a general form of the Two‐Stream Equations for which the four coupling coefficients are guaranteed to be physically explicable. While non‐constant coupling coefficients are required to reconstruct entire flux profiles, numerically optimized constant coupling coefficients (which admit analytic solutions) reproduced shortwave reflectance and transmittance with relative errors no greater than over a large range of optical parameters. The optimized coefficients show a dependence on solar zenith angle and total optical depth that diminishes as the latter increases. This explains why existing coupling coefficients, which often omit the former and mostly neglect the latter, tend to work well for only thin or only thick atmospheres.

X-ray view of dissipative warm corona in active galactic nuclei

Context. Detections of the X-ray spectra of active galactic nuclei (AGNs) typically reveal a noticeable excess of soft X-rays beyond the extrapolation of the power-law trend observed between 2 and 10 keV. However, the cause of this surplus remains unclear. In the scenario of soft Comptonization, observations suggest a warm corona temperature, ranging from 0.1 to 1 keV, and an optical depth of approximately 10 to 30. Furthermore, according to radiative constraints derived from spectral analyses employing Comptonization models, it has been suggested that most of the accretion power is released within the warm corona. At the same time, the disk beneath it is largely non-dissipative, mainly emitting the reprocessed radiation from the corona. Aims. We tested the dissipative warm corona model using the radiative transfer code TITAN-NOAR on a sample of 82 XMM-Newton EPIC-pn observations of 21 AGNs. Based on a spectral modeling of the X-ray data, we aim to estimate the total amount of internal heating inside the warm corona on top of the accretion disk. Methods. By modeling the 0.3–10 keV EPIC-pn spectra with the TITAN-NOAR model component, we estimated the internal heating and optical depth of the warm corona and checked their correlations with such global parameters as the hot corona spectral index, black hole mass, and accretion rate. From the model normalization, we computed the radial extent of the warm corona on top of the cold accretion disk. Results. Our model infers the presence of dissipative warm corona, with optical depths distributed across the range of ∼6–30 and a total internal heating in the range of ∼1–29 × 10−23 erg s−1 cm3. We do not detect any variation between these properties and global properties, such as the black hole mass and accretion rate. The extent of the warm corona is spread across a broad range, from 7–408 gravitational radii, and we find that the warm corona is more extended for higher accretion rates. Conclusions. Soft excess emission is ubiquitous across a wide mass range and accretion rate in AGNs. We confirm that the warm corona responsible for producing the soft X-ray excess is highly dissipative with greater optical depths being associated with lower internal heating and vice versa. The cold standard accretion disk regulates the extent of the warm corona.

Optical penetration depth and periodic motion of a photomechanical strip

Liquid crystal elastomers (LCEs) containing light-sensitive molecules exhibit large, reversible deformations when subjected to illumination. Here, we investigate the role of optical penetration depth on this photomechanical response. We present a model of the photomechanical behavior of photoactive LCE strips under illumination that goes beyond the common assumption of shallow penetration. This model reveals how the optical penetration depth and the consequent photomechanically induced deformation can depend on the concentration of photoactive molecules, their absorption cross-sections, and the intensity of illumination. Through a series of examples, we show that the penetration depth can quantitatively and qualitatively affect the photomechanical response of a strip. Shallow illumination leads to monotone curvature change while deep penetration can lead to non-monotone response with illumination duration. Further, the flapping behavior (a cyclic wave-like motion) of doubly clamped and buckled strips that has been proposed for locomotion can reverse direction with sufficiently large penetration depth. This opens the possibility of creating wireless light-driven photomechanical actuators and swimmers whose direction of motion can be controlled by light intensity and frequency.

Evaluating and comparison of WRF-chem model configurations for wind field impact on the April 2022 dust episode in western Iran

Accurate estimation of wind direction and speed is essential for enhancing the simulation and prediction of dust storms. Being highly susceptible to dust storms, Western Iran necessitates a detailed evaluation of dust concentration and wind fields. This study employs the WRF-Chem model to simulate these parameters over the period from April 7 to 26, 2022. Four different model configurations were tested, involving the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) boundary layer schemes, as well as the Lin and WRF Single-Moment 6-Class (WSM6) microphysics schemes. The results indicate that during the selected period, different synoptic systems led to the release of dust from Iraq and Saudi Arabia and its transport to western Iran. The mid-level southerly and southwesterly wind directions have a significant impact on dust transport to the northwestern regions of Iran by high and complex mountainous terrain. The horizontal and vertical distribution of simulated dust demonstrates good agreement with TERRA satellite imagery, MERRA-2 dust surface concentration, and CALIPSO, respectively. The daily dust concentration of the WRF-Chem model has a correlation of −0.32 to −0.96 with visibility and 0.68 to 0.86 with MERRA-2 data in Western Iran. The simulated dust concentration relation with visibility and AERONET AOD (Aerosol Optical Depth at 500 nm) was calculated at −0.78 and 0.29, respectively in Zanjan station. The horizontal and vertical distribution, temporal series, and statistical indices of the wind field show that the WRF-Chem model performs well in the Iran West boundary, especially in the west and northwest, where the 10-m wind speed increased to 14 m s−1. The boundary layer scheme in the WRF-Chem model has a more significant impact than the microphysics scheme in simulated 10-m wind speed and dust concentration. The final result shows that the combination of the YSU boundary layer and WSM6 microphysics schemes performs very well in simulating wind fields and dust in western Iran under various weather conditions.

Aerosol Components Derived from Global AERONET Measurements by GRASP: A New Value-Added Aerosol Component Global Dataset and Its Application

Abstract Aerosols affect Earth’s climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, southern Africa, sub-Sahel, Gobi Desert, Middle East, Sahara Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60–0.85 for BC; R = 0.75–0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing.

Prospects of Detecting a Jet in Sagittarius A* with Very-long-baseline Interferometry

Event Horizon Telescope (EHT) images of the horizon-scale emission around the Galactic center supermassive black hole Sagittarius A* (Sgr A*) favor accretion flow models with a jet component. However, this jet has not been conclusively detected. Using the “best-bet” models of Sgr A* from the EHT Collaboration, we assess whether this nondetection is expected for current facilities and explore the prospects of detecting a jet with very-long-baseline interferometry (VLBI) at four frequencies: 86, 115, 230, and 345 GHz. We produce synthetic image reconstructions for current and next-generation VLBI arrays at these frequencies that include the effects of interstellar scattering, optical depth, and time variability. We find that no existing VLBI arrays are expected to detect the jet in these best-bet models, consistent with observations to date. We show that next-generation VLBI arrays at 86 and 115 GHz—in particular, the EHT after upgrades through the ngEHT program and the ngVLA—successfully capture the jet in our tests due to improvements in instrument sensitivity and (u, v) coverage at spatial scales critical to jet detection. These results highlight the potential of enhanced VLBI capabilities in the coming decade to reveal the crucial properties of Sgr A* and its interaction with the Galactic center environment.

Molecular Distribution in the Central Region of M87

The central region of M87 has been observed by the Atacama Large Millimeter/submillimeter Array (ALMA) several times to resolve its molecular cloud distribution. We present the ALMA CO(1–0), CO(2–1), and CO(3–2) observations of the M87 circumnuclear region. The CO(1–0) shows emission as well as molecular absorption features toward its nucleus, indicating the existence of cold molecular clouds/gas. ALMA imaging of the CO(1–0) observations show the distribution of molecular clouds toward the nucleus of M87 with a radius of ∼105 pc. The clouds seen in the CO(1–0) are moving with very high velocity and have an apparent motion in the range of −1000 to 3600 km s−1 relative to the central supermassive black hole, which has a systemic velocity of ∼1266 km s−1. The molecular gas mass was estimated to be about 1.08 ± 0.64 × 107 M ⊙ in the central 210 pc of M87. We calculated the optical depths using the absorption lines of the CO(1–0) and CO(2–1). The excitation temperature was estimated to be ∼7.133 ± 0.03 K using the optical depth ratio of the CO(2-1) to CO(1-0). We also found the line-of-sight column density to be ∼2.25 × 1015 cm−2, which corresponds to a hydrogen column density of ∼0.28 × 1020 cm−2.

The Feasibility of Asynchronous Rotation via Thermal Tides for Diverse Atmospheric Compositions

The equilibrium rotation rate of a planet is determined by the sum of torques acting on its solid body. For planets with atmospheres, the dominant torques are usually the gravitational tide, which acts to slow the planet’s rotation rate, and the atmospheric thermal tide, which acts to spin up the planet. Previous work demonstrated that rocky planets with thick atmospheres may produce strong enough thermal tides to avoid tidal locking, but a study of how the strength of the thermal tide depends on atmospheric properties has not been done. In this work, we use a combination of simulations from a global climate model and analytic theory to explore how the thermal tide depends on the shortwave and longwave optical depth of the atmosphere, the surface pressure, and the absorbed stellar radiation. We find that for planets in the habitable zones of M stars only high-pressure but low-opacity atmospheres permit asynchronous rotation owing to the weakening of the thermal tide at high longwave and shortwave optical depths. We conclude that asynchronous rotation may be very unlikely around low-mass stars, which may limit the potential habitability of planets around M stars.

A new measurement of the Galactic 12C/13C gradient from sensitive HCO+ absorption observations

We present a new constraint on the Galactic 12C/13C gradient with sensitive HCO+ absorption observations against strong continuum sources. The new measurements suffer less from beam dilution, optical depths, and chemical fractionation, allowing us to derive the isotopic ratios precisely. The measured 12C/13C ratio in the solar neighborhood (66±5) is consistent with those obtained from CH+. Two measurements toward the GC are 42.2±1.7 and 37.5±6.5. Though the values are a factor of two to three higher than those derived from dense gas tracers (e.g., H2CO, complex organic molecules) toward Sagittarius (Sgr) B2 regions, our results are consistent with the absorption measurements from c-C3H2 toward Sgr B2 (~40) and those from CH+ toward Sgr A* and Sgr B2(N) (>30). We have calculated a new Galactic 12C/13C gradient of (6.4±1.9)RGC/kpc+(25.9±10.5) and found an increasing trend of the 12C/13C gradient obtained from high-density to low-density gas tracers, suggesting that opacity effects and chemical fractionation may have a strong impact on the isotopic ratios observed in high-density regions.

Use of satellite data to determine the cloud optical depths present during overirradiance conditions

Abstract Overirradiance conditions can negatively impact the operation of photovoltaic systems if no protective measures have been implemented, leading to potential damages and economic losses in photovoltaic generation plants. Current simulation models attempt to understand the mechanism of overirradiance conditions. However, their observations still differ significantly from experimental ones, emphasizing the need to better understand the two main hypotheses that account for overirradiance events: reflection at the edges of thick clouds and Mie scattering in thin clouds. This paper studies the qualitative correlation between the global tilted irradiance measured by a spectroradiometer on the surface and the optical depth of the clouds measured by the GOES-16 satellite to shed more light on this phenomenon. Our results show a good qualitative correlation between the global tilted irradiance and the optical depth of the clouds present during overirradiance events. We also show that all overirradiance conditions occurred when thick clouds were present. These results indicate that the overirradiance events analyzed have been produced predominantly by reflections at the edges of thick clouds, supporting the hypothesis that the increase in global irradiance is mainly due to a substantial increase in direct irradiance.