Ground-based Observations Research Articles

Looking for timing variations in the transits of 16 exoplanets

ABSTRACT We update the ephemerides of 16 transiting exoplanets using our ground-based observations, new Transiting Exoplanet Survey Satellite data, and previously published observations including those of amateur astronomers. All these light curves were modelled by making use of a set of quantitative criteria with the exofast code to obtain mid-transit times. We searched for statistically significant secular and/or periodic trends in the mid-transit times. We found that the timing data are well modelled by a linear ephemeris for all systems except for XO-2 b, for which we detect an orbital decay with the rate of −12.95 ± 1.85 ms yr−1 that can be confirmed with future observations. We also detect a hint of potential periodic variations in the transit timing variation data of HAT-P-13 b, which also requires confirmation with further precise observations.

Revisiting the warm sub-Saturn TOI-1710b

The Transiting Exoplanet Survey Satellite (TESS) provides a continuous suite of new planet candidates that need confirmation and precise mass determination from ground-based observatories. This is the case for the G-type star TOI-1710, which is known to host a transiting sub-Saturn planet (Mp = 28.3 ± 4.7 M⊕) in a long-period orbit (P = 24.28 days). Here we combine archival SOPHIE and new and archival HARPS-N radial velocity data with newly available TESS data to refine the planetary parameters of the system and derive a new mass measurement for the transiting planet, taking into account the impact of the stellar activity on the mass measurement. We report for TOI-1710b a radius of Rp = 5.15 ± 0.12 R⊕, a mass of Mp = 18.4 ± 4.5 M⊕, and a mean bulk density of ρp = 0.73 ± 0.18 g cm−3, which are consistent at 1.2σ, 1.5σ, and 0.7σ, respectively, with previous measurements. Although there is not a significant difference in the final mass measurement, we needed to add a Gaussian process component to successfully fit the radial velocity dataset. This work illustrates that adding more measurements does not necessarily imply a better mass determination in terms of precision, even though they contribute to increasing our full understanding of the system. Furthermore, TOI-1710b joins an intriguing class of planets with radii in the range 4–8 R⊕ that have no counterparts in the Solar System. A large gaseous envelope and a bright host star make TOI-1710b a very suitable candidate for follow-up atmospheric characterization.

Double Power-law Formation by Sequential Particle Acceleration

Spectral double power laws are common in solar high-energy phenomena such as flares and interplanetary energetic-electron events. However, the physical mechanism that produces the changes in power-law index within a single spectrum is unclear. We developed a fully analytical method of forming single power-law spectra from sequential acceleration of particles orbiting inside and hopping between simulated large-scale magnetic islands formed by flare reconnection. Here, we extend the analytical method to the formation of double power-law spectra by assuming sequential acceleration in two successive regions with different acceleration and particle-transport rates. The resulting spectral distribution is continuous and smooth, with a flattening at low energies, two power-law regions at mid-energies, and a steep rollover at high energies. The model provides analytical expressions for the spectral indices, all energy breaks, and normalization constants as functions of just three physical parameters of each acceleration region: (1) the energy gain in each accelerator, (2) the percentage of particles transferred between accelerators, and (3) the number of accelerators visited. One of the most salient predictions of our work is that the spectral index at high (low) energies is determined by the parameters of the first “seed” (second) acceleration region. By constructing the spectral distribution through an iterative analytical process, the evolution toward a double power law is easily characterized and explained. Our analytical model provides tools to interpret space- and ground-based observations from RHESSI, FOXSI, NuSTAR, Solar Orbiter/STIX, EOVSA, and future high-energy missions.

Rotational Study of 5:3 and 7:4 Resonant Objects within the Main Classical Trans-Neptunian Belt

The 5:3 and 7:4 mean motion resonances of Neptune are at 42.3 and 43.7 au, respectively, and overlap with objects in the classical trans-Neptunian belt (Kuiper Belt). We report the complete/partial lightcurves of 13 and 14 trans-Neptunian objects (TNOs) in the 5:3 and 7:4 resonances, respectively. We report a most likely contact binary in the 7:4 resonance, 2013 FR28, with a periodicity of 13.97 ± 0.04 hr and a lightcurve amplitude of 0.94 ± 0.02 mag. With a V-/U-shaped lightcurve, 2013 FR28 has one of the largest well-sampled TNO amplitudes observed with ground-based observations, comparable to the well-determined contact binary 2001 QG298. 2013 FR28 has a mass ratio q ∼ 1 with a density ρ ∼ 1 g cm−3. We find several objects with large amplitudes and classify 2004 SC60, 2006 CJ69, and 2013 BN82 as likely contact binaries and 2001 QF331, 2003 YW179, and 2015 FP345 as likely elongated objects. We observe the 17:9 resonant or classical object 2003 SP317 that we classify as a likely contact binary. A lower estimate of 10%–50% and 20%–55% for the fraction of (nearly) equal-sized contact binaries is calculated in the 5:3 and 7:4 resonances, respectively. Surface colors of 2004 SC60, 2013 BN82, 2014 OL394, and 2015 FP345 have been obtained. Including these colors with ones from the literature reveals that elongated objects and contact binaries share the same ultrared surface color, except Manwë–Thorondor and 2004 SC60. Not only are the colors of the 7:4 and 5:3 TNOs similar to the cold classicals, but we demonstrate that the rotational properties of the 5:3 and 7:4 resonants are similar to those of the cold classicals, inferring a clear link between these subpopulations.

Evaluating and locating a suitable bedrock drilling site near zhongshan station with airborne and ground-based observations

Understanding the interaction between the Antarctic biogeochemical cycle and global environmental change requires a comprehensive investigation of the ice sheet and underlying bedrock. An effective approach to investigating subglacial characteristics is through bedrock drilling, making the identification of a suitable drilling site a crucial prerequisite. In this study, data from airborne ice-penetrating radar and an Uncrewed Aerial Vehicle (UAV) remote sensing were used in combination to obtain real-time and high-resolution information about the surface, ice thickness, and subglacial conditions in a local area near Zhongshan Station, and further to identify a drilling site that is both safe and optimal for the successful acquisition of bedrock samples beneath the East Antarctic Ice Sheet. By analyzing the airborne ice-penetrating radar data from the 35th Chinese National Antarctic Research Expedition (CHINARE) (2018–2019), a potential drilling site was selected based on ice thickness (≤200 m) and a dry basal condition with no channels or basal crevasses, to avoid drilling fluid leakage. UAV data confirmed stable surface topography, ice flow, and the absence of surface crevasses. The optimal site was identified as located close to the western flank of the upstream part of the Dålk Glacier. In 2019, CHINARE successfully retrieved a valuable bedrock core sample from the borehole at this location. This study provides a feasible and effective methodology for locating a bedrock drilling site by using data from airborne ice-penetrating radar and UAV remote sensing.

ПРИМЕНЕНИЕ ГЛУБИННЫХ НЕЙРОННЫХ СЕТЕЙ ДЛЯ ОБНАРУЖЕНИЯ ВЕРОЯТНЫХ ЗОН АТМОСФЕРНЫХ ОСАДКОВ И ГРОЗ

A method for the probabilistic identification of the precipitation and thunderstorm zones using artificial neural networks (ANNs), in particular, deep neural networks is described. The vertical profiles of temperature and humidity retrieved from satellite data are used as initial data. The ANN calculations have been validated using the ground-based observations in the Siberian region.

Ground-based MAX-DOAS observations of formaldehyde and glyoxal in Xishuangbanna, China

Multi-axial differential optical absorption spectroscopy (MAX-DOAS) measurements were conducted in Xishuangbanna, Yunnan, China, between November 1, 2021 and June 30, 2022 to obtain vertical distributions of formaldehyde (HCHO) and glyoxal (CHOCHO). The observations show an increase in vertical column densities (VCDs) and volume mixing ratios (VMRs) for both HCHO and CHOCHO concentrations during periods of biomass combustion. The VCDs of HCHO and CHOCHO from TROPOMI are in good agreement with the MAX-DOAS observations. (R2HCHO = 0.71; R2CHOCHO = 0.70). Regarding seasonal variations, HCHO predominantly occupies the upper layer (400-800 m) during the biomass burning, possibly attributed to the formation of secondary HCHO as the plume ascends during combustion. CHOCHO is primarily found in the lower layer (0-200 m), suggesting a longer lifespan for HCHO compared to CHOCHO, preventing the latter from diffusing to higher altitudes. Concerning the daily variation patterns, both HCHO and CHOCHO VMRs exhibited peaks at 9:00 and 13:00, which were attributed to the nighttime accumulation and midday oxidation. Furthermore, we also investigated the sources of volatile organic compounds (VOCs) using the CHOCHO to HCHO ratio (RGF). During the period of biomass burning, there are minimal differences in the daily RGF across layers, indicating that biomass burning is the predominant source. During the non-biomass burning period, the daily RGF shows significant differences among layers, indicating that emissions from biological and anthropogenic sources primarily contribute during the period.

BSN: Photometric Light Curve Analysis of Two Contact Binary Systems LS Del and V997 Cyg

The light curve analyses and orbital period variations for two contact binary stars, LS Del and V997 Cyg, are presented in this work which was conducted in the frame of the Binary Systems of South and North project. Ground-based photometric observations were performed at two observatories in France. We used the Transiting Exoplanet Survey Satellite (TESS) data for extracting times of minima and light curve analysis of the target systems. The O − C diagram for both systems displays a parabolic trend. LS Del and V997 Cyg’s orbital periods are increasing at rates of dP/dt = 7.20 × 10−08 days yr−1 and dP/dt = 2.54 × 10−08 days yr−1, respectively. Therefore, it can be concluded that mass is being transferred from the less massive star to the more massive component with a rate of dM/dt = –1.96 × 10−7 M ⊙ yr−1 for the LS Del system, and dM/dt =–3.83 × 10−7 M ⊙ yr−1 for V997 Cyg. The parameters of a third possible object in the system are also considered. The PHysics Of Eclipsing BinariEs Python code was used to analyze the light curves. The light curve solutions needed a cold starspot due to the asymmetry in the LS Del system’s light curve maxima. The mass ratio, fill-out factor, and star temperature all indicate that both systems are contact binary types in this investigation. Two methods were applied to estimate the absolute parameters of the systems: one method relied on the parallax of Gaia DR3, and the other used a P − M relationship. The positions of the systems are also depicted on the M − L, M − R, q − L ratio, and logMtot−logJ0 diagrams. We recommend that further observations and investigations be done on the existence of a fourth body in this system.

The Unusual Brightness Phase Curve of (65803) Didymos

On 2022 September 26, NASA's Double Asteroid Redirection Test (DART) successfully hit Dimorphos, the smaller companion of the binary system formed with the asteroid (65803) Didymos. Both the binary system and the impact event were imaged by the Light Italian Cubesat for Imaging of Asteroids, detached from DART 15 days before the impact. Images from the onboard LUKE red, green, and blue camera together with ground-based observations enabled the reconstruction of Didymos's brightness phase curve, with phase angles ranging from 2.35° to 107.7°. The opposition effect regime was studied using the exponential-linear equation, the “Shevchenko” function and the linear-by-parts model while the IAU-official HG1G2 magnitude system was applied to the full phase curve. The opposition effect indicates an unusual asteroid surface for an S type, with characteristics similar to M-type asteroids. While the HG1G2 parameters from the full phase curve place Didymos well among asteroids of the taxonomic C complex. Didymos’s phase curve parameters when compared to near-Earth asteroids are very close to the Q type (1862) Apollo, indicating possible depletion of fine submicrometric grains through resurfacing. Didymos's geometric albedo (0.15 ± 0.01) is reported to be 30%–45% smaller than the average geometric albedo for near-Earth S types (0.26 ± 0.04). We propose that Didymos might be an LL ordinary chondrite analog containing albedo-suppressing, shock-darkened/impact melt minerals that have undergone resurfacing processes in the past. A comparison with meteorites indicates that, less likely, Didymos could also contain materials analog to carbon-bearing brecciated L3 ordinary chondrites.

Rotation of ZZ Ceti stars as seen by TESS

Context. Knowing the rotation rates and masses of white dwarf stars is an important step towards characterising the angular momentum transport mechanism in their progenitors, and coupling the cores of red giants to their envelopes. However, deriving these rotation rates is not an easy task. One can use the rotational broadening of spectral lines, but there is another way to gather reliable information on the stellar rotation periods of pulsators: through studying the splitting effect of rotation on oscillation frequencies. Aims. We aim to derive stellar rotation periods in the TESS sample for as many white dwarf pulsators as possible. Methods. We rely on light-curve analysis of the TESS observations, and search for closely spaced frequency multiplets that could be rotationally split pulsation modes. We work with triplet frequencies, even if one or two triplet components are only marginally detectable. We also utilise ground-based observations available from the literature in an attempt to confirm the presence of several triplets. Results. We successfully identified rotationally split multiplets and derived rotation rates for 14 stars. The fastest rotators we identified have rotation periods of 6.6–10.0 h. The majority of the pulsators rotate with periods of 11.9–47.5 h, while we derived 85.5 and 93.2 h periods for the slowest rotators. In addition to providing stellar mass estimations, our results confirm previous findings that larger-mass WDs rotate faster than their lower-mass counterparts. We determine the rotation periods of four stars for the first time.

A Novel Abiotic Pathway for Phosphine Synthesis over Acidic Dust in Venus' Atmosphere.

Recent ground-based observations of Venus have detected a single spectral feature consistent with phosphine (PH3) in the middle atmosphere, a gas which has been suggested as a biosignature on rocky planets. The presence of PH3 in the oxidized atmosphere of Venus has not yet been explained by any abiotic process. However, state-of-the-art experimental and theoretical research published in previous works demonstrated a photochemical origin of another potential biosignature-the hydride methane-from carbon dioxide over acidic mineral surfaces on Mars. The production of methane includes formation of the HC · O radical. Our density functional theory (DFT) calculations predict an energetically plausible reaction network leading to PH3, involving either HC · O or H· radicals. We suggest that, similarly to the photochemical formation of methane over acidic minerals already discussed for Mars, the origin of PH3 in Venus' atmosphere could be explained by radical chemistry starting with the reaction of ·PO with HC·O, the latter being produced by reduction of CO2 over acidic dust in upper atmospheric layers of Venus by ultraviolet radiation. HPO, H2P·O, and H3P·OH have been identified as key intermediate species in our model pathway for phosphine synthesis.

СПОСОБ ОБЪЕКТНО-ОРИЕНТИРОВАННОГО РАСПОЗНАВАНИЯ ОБЛАЧНОСТИ ГЛУБОКОЙ КОНВЕКЦИИ НА ОСНОВЕ ДАННЫХ ГЕОСТАЦИОНАРНОГО МЕТЕОРОЛОГИЧЕСКОГО ИСКУССТВЕННОГО CПУТНИКА ЗЕМЛИ С ПРИМЕНЕНИЕМ МАШИННОГО ОБУЧЕНИЯ

Due to high spatial and temporal resolution, geostationary meteorological satellite imagery is a valuable source of information on the development of deep convective clouds and related severe weather events. Some methods for automatic deep convection detection from satellite data provide a satisfactory probability of detection for independent datasets, but are characterized by a high false alarm rate. The paper gives a description of an algorithm for automatic detection of deep convective clouds with satellite imagery using gradient boosting, logistic regression, and artificial neural network models. The results of validation of the proposed method using dependent and independent data of ground-based observations for the period 2013-2020 are presented. A low false alarm rate and high probability of detection suggest that the algorithm can be used in the operational mode.

COSMOS-Web: Intrinsically Luminous z ≳ 10 Galaxy Candidates Test Early Stellar Mass Assembly

We report the discovery of 15 exceptionally luminous 10 ≲ z ≲ 14 candidate galaxies discovered in the first 0.28 deg2 of JWST/NIRCam imaging from the COSMOS-Web survey. These sources span rest-frame UV magnitudes of −20.5 > M UV > −22, and thus constitute the most intrinsically luminous z ≳ 10 candidates identified by JWST to date. Selected via NIRCam imaging, deep ground-based observations corroborate their detection and help significantly constrain their photometric redshifts. We analyze their spectral energy distributions using multiple open-source codes and evaluate the probability of low-redshift solutions; we conclude that 12/15 (80%) are likely genuine z ≳ 10 sources and 3/15 (20%) likely low-redshift contaminants. Three of our z ∼ 12 candidates push the limits of early stellar mass assembly: they have estimated stellar masses ∼ 5 × 109 M ⊙, implying an effective stellar baryon fraction of ϵ ⋆ ∼ 0.2−0.5, where ϵ ⋆ ≡ M ⋆/(f b M halo). The assembly of such stellar reservoirs is made possible due to rapid, burst-driven star formation on timescales < 100 Myr where the star formation rate may far outpace the growth of the underlying dark matter halos. This is supported by the similar volume densities inferred for M ⋆ ∼ 1010 M ⊙ galaxies relative to M ⋆ ∼ 109 M ⊙—both about 10−6 Mpc−3—implying they live in halos of comparable mass. At such high redshifts, the duty cycle for starbursts would be of order unity, which could cause the observed change in the shape of the UV luminosity function from a double power law to a Schechter function at z ≈ 8. Spectroscopic redshift confirmation and ensuing constraints of their masses will be critical to understand how, and if, such early massive galaxies push the limits of galaxy formation in the Lambda cold dark matter paradigm.

Trans-Boundary Dust Transport of Dust Storms in Northern China: A Study Utilizing Ground-Based Lidar Network and CALIPSO Satellite

During 14–16 March 2021, a large-scale dust storm event occurred in the northern region of China, and it was considered the most intense event in the past decade. This study employs observation data for PM2.5 and PM10 from the air quality monitoring station, the HYSPLIT model, ground-based polarized Lidar networks, AGRI payload data from Fengyun satellites and CALIPSO satellite Lidar data to jointly explore and scrutinize the three-dimensional spatial and temporal characteristics of aerosol transport. Firstly, by integrating meteorological data for PM2.5 and PM10, the air quality is assessed across six stations within the Lidar network during the dust storm. Secondly, employing a backward trajectory tracking model, the study elucidates sources of dust at the Lidar network sites. Thirdly, deploying a newly devised portable infrared 1064 nm Lidar and a pulsed 532 nm Lidar, a ground-based Lidar observation network is established for vertical probing of transboundary dust transport within the observed region. Finally, by incorporating cloud imagery from Fengyun satellites and CALIPSO satellite Lidar data, this study revealed the classification of dust and the height distribution of dust layers at pertinent sites within the Lidar observation network. The findings affirm that the eastward movement and southward compression of the intensifying Mongolian cyclone led to severe dust storm weather in western and southern Mongolia, as well as Inner Mongolia, further transporting dust into northern, northwestern, and northeastern parts of China. This dust event wielded a substantial impact on a broad expanse in northern China, manifesting in localized dust storms in Inner Mongolia, Beijing, Gansu, and surrounding areas. In essence, the dust emanated from the deserts in Mongolia and northwest China, encompassing both deserts and the Gobi region. The amalgamation of ground-based and spaceborne Lidar observations conclusively establishes that the distribution height of dust in the source region ranged from 3 to 5 km. Influenced by high-pressure systems, the protracted transport of dust over extensive distances prompted a gradual reduction in its distribution height owing to sedimentation. The comprehensive analysis of pertinent research data and information collectively affirms the precision and efficacy of the three-dimensional aerosol monitoring conducted by the ground-based Lidar network within the region.

Contribution of γ-Ray Burst Afterglow Emissions to the Isotropic Diffuse γ-Ray Background

The isotropic diffuse γ-ray background (IGRB) serves as a fundamental probe of the evolution of the extreme Universe. Although various astrophysical sources have been proposed as potential contributors to the IGRB, the dominant population is still under debate. γ-ray bursts (GRBs) are among candidate contributors of IGRB, although they are not as frequently discussed as blazars or starburst galaxies. Recent observations of TeV emission from GRB afterglows have provided fresh insights into this subject. This work aims to investigate the potential contribution of GRB afterglows to the IGRB under the standard afterglow model. We carefully examine the influence of each microphysical parameter of the afterglow model on this contribution, with a particular emphasis on the significant role played by the initial kinematic energy. To determine the energy and quantify the contribution of GRB afterglow to IGRBs, we utilize the observed GRB afterglow energy emissions from the Swift X-ray Telescope and Fermi Large Area Telescope instruments. Our calculations, considering the synchrotron self-Compton emission, suggest that GRB afterglows make up less than 10% of the IGRBs. To enhance the precision of our findings, it is crucial to further constrain these parameters by conducting additional ground-based observations of GRB afterglows.

Evaluating the spatial representativeness of ground-based observations for satellite total ozone products

External verification based on ground-based data is commonly used to assess the accuracy of satellite products for total ozone. However, the spatial representativeness of ground-based observations at the pixel scale and the effects of the spatial mismatch between ground observations and satellite pixels are often overlooked. Therefore, this study focused on an Ozone Monitoring Instrument (OMI) and proposed a novel method to evaluate spatial representativeness using the total ozone product itself without relying on higher spatial resolution imagery from other sensors. A Pixel-level Spatial Mismatch Index (PSMI) was developed to quantify the peaks and stable intervals of the spatial response to the relative deviation of total ozone observations. The analysis revealed that increased uncertainty at the pixel edges can cause significant relative deviation, with the peak deviation occurring within a range of 4–7 km near the pixel boundary. The position of the high precision interval in PSMI was found to be <–22.38 km or >10 km, with mean values of 3.70 % and standard deviations of 3.45 % for the relative deviation. This interval is spatially distance-independent and can be observed on both sides of the pixel boundary. These findings highlight the importance of considering spatial patterns between satellite pixels and ground stations for external validation. Furthermore, avoiding a spatial response peak of the relative deviation at the pixel edge is crucial. Overall, this research provides new perspectives and insights for the verification of total ozone products. By considering these factors mentioned above, future verification of total ozone products can be improved, leading to enhanced their evaluation systems.

Mapping nationwide concentrations of sulfate and nitrate in ambient PM2.5 in South Korea using machine learning with ground observation data

Particulate matter (PM) is a major air pollutant in Northeast Asia, with frequent high PM episodes. To investigate the nationwide spatial distribution maps of PM2.5 and secondary inorganic aerosols in South Korea, prediction models for mapping SO42− and NO3− concentrations in PM2.5 were developed using machine learning with ground-based observation data. Specifically, the random forest algorithm was used in this study to predict the SO42− and NO3− concentrations at 548 air quality monitoring stations located within the representative radii of eight intensive air quality monitoring stations. The average concentrations of PM2.5, SO42−, and NO3− across the entire nation were 17.2 ± 2.8, 3.0 ± 0.6, and 3.4 ± 1.2 μg/m3, respectively. The spatial distributions of SO42− and NO3− concentrations in 2021 revealed elevated concentrations in both the western and central regions of South Korea. This result suggests that SO42− concentrations were primarily influenced by industrial activities rather than vehicle emissions, whereas NO3− concentrations were more associated with vehicle emissions. During a high PM2.5 event (November 19–21, 2021), the concentration of SO42− was primarily influenced by SOX emissions from China, while the concentration of NO3− was affected by NOX emissions from both China and Korea. The methodology developed in this study can be used to explore the chemical characteristics of PM2.5 with high spatiotemporal resolution. It can also provide valuable insights for the nationwide mitigation of secondary PM2.5 pollution.

A novel machine learning-based approach for improving global correction of AIRS-derived water vapor satellite product

Precise precipitable water vapor (PWV) observations play a crucially important role in weather and climate research. The Atmospheric Infrared Sounder (AIRS) on-board the Aqua spacecraft is a hyperspectral instrument that offers operational PWV products using infrared (IR) channels. However, the observational accuracy of AIRS-sensed cloudy-sky PWV products is much poorer than that of PWV retrievals under clear sky conditions. We present a new machine learning-based calibration model to improve the observational performance of operational AIRS-derived IR PWV satellite products under all sky conditions, which considers using several dependence elements correlated with remotely sensed IR PWV observations. The first-guess PWV estimates, obtained from the ERA5 reanalysis, are also utilized in the newly developed calibration approach. The ground-based GNSS-sensed PWV observations, collected in 2017 across the world, are used as the expected PWV output for the training of the newly proposed calibration model. The newly calibrated PWV data records considerably outperform operational AIRS-sensed PWV products, compared with independent PWV estimates from radiosonde observations during 2017–2020. The root-mean-square error of operational PWV satellite products decreases 19.05 % from 2.31 mm to 1.87 mm under cloud fraction (CF) = 0 condition (clear sky), 30.71 % from 3.68 mm to 2.55 mm under CF = (0,1] condition (cloudy sky), and 30.14 % from 3.55 mm to 2.48 mm under CF = [0,1] condition (all sky). The calibration method exhibits much higher RMSE reductions than previous approaches that do not utilize the first-guess PWV estimates, illustrating the effectiveness of our calibration approach. This research provides insights into calibrating satellite-sensed PWV estimates based on machine learning by jointly using ground-based and reanalysis-based PWV observations. The newly proposed calibration method has significant potential to calibrate operational PWV products from other satellite-borne sensors, in addition to the AIRS instrument.

LIME: Lunar Irradiance Model of ESA, a new tool for absolute radiometric calibration using the Moon

Abstract. Absolute calibration of Earth observation (EO) sensors is key to ensuring long-term stability and interoperability, and it is essential for long-term global climate records and forecasts. The Moon provides a photometrically stable calibration source within the range of the Earth's radiometric levels and is free from atmospheric interference. However, to use this ideal calibration source, one must model the variation in its disc-integrated irradiance resulting from changes in Sun–Earth–Moon geometries. The Lunar Irradiance Model of the European Space Agency (LIME) is a new lunar irradiance model developed from ground-based observations acquired using a lunar radiometer operating from the Izaña Atmospheric Observatory near Mount Teide, located in Tenerife, Spain. Nightly top-of-atmosphere (TOA) irradiance is determined using the Langley plot method, and each observation is traceable to the international system of units (SI) through the radiometer calibration performed at the National Physical Laboratory (NPL). Approximately 590 lunar observations acquired between March 2018 and December 2022 currently contribute to the model parameter derivation, which builds on the widely used ROLO (Robotic Lunar Observatory) model analytical formulation. This paper presents the strategy used to derive LIME parameters: the characterisation of the lunar radiometer, the derivation of nightly top-of-atmosphere lunar irradiance and a description of the model parameter derivation, along with the associated metrologically rigorous uncertainty. The model output has been compared to PROBA-V, Pléiades and Sentinel-3B, as well as to the VITO implementation of the ROLO model. Initial results indicate that LIME predicts 3 %–5 % higher lunar-disc-integrated irradiance than the ROLO model for the visible and near-infrared channels. The model output has an expanded (k=2) radiometric uncertainty of ∼ 2 % at the lunar radiometer wavelengths, and it is expected that planned observations until at least 2024 further constrain the model parameters in subsequent updates.

Uncertainties from biomass burning aerosols in air quality models obscure public health impacts in Southeast Asia

Abstract. Models suggest that biomass burning causes thousands of premature deaths annually in Southeast Asia due to excessive exposure to particulate matter (PM) in smoke. However, measurements of surface air quality are sparse across the region, and consequently estimates for the public health impacts of seasonal biomass burning, are not well constrained. We use the nested GEOS-Chem model of chemistry and transport (horizontal resolution of 0.25°×0.3125°) to simulate atmospheric composition over Southeast Asia during the peak burning months of March and September in the moderate burning year of 2014. Model simulations with GEOS-Chem indicate that regional surface levels of PM2.5 (fine particulate matter with a diameter ≤2.5 µm) greatly exceed World Health Organization guidelines during the burning seasons, resulting in up to 10 000 premature deaths in a single month. However, the model substantially underestimates the regional aerosol burden compared to satellite observations of aerosol optical depth (AOD) (20 %–52 %) and ground-based observations of PM (up to 54 %), especially during the early burning season in March. We investigate potential uncertainties limiting the model representation of biomass burning aerosols and develop sensitivity simulations that improve model–measurement agreement in March (to within 31 %) and increase the estimated number of PM2.5-related premature deaths that month by almost half. Our modifications have a much smaller impact on the same metrics for September, but we find that this is due to canceling errors in the model. Compared to PM2.5 simulated directly with GEOS-Chem, PM2.5 derived from satellite AOD is less sensitive to model uncertainties and may provide a more accurate foundation for public health calculations in the short term, but continued investigation of uncertainties is still needed so that model analysis can be applied to support mitigation efforts. Further reduction of uncertainties can be achieved with the deployment of more aerosol measurements across Southeast Asia.