Tartu Observatory

Naturally occurring events are generally characterized by dynamic states that are mostly unpredictable and undergo temporal changes. Mapping such events is essential to pursuing studies of their temporal states and eventually being able to understand and map the event occurrence. This is especially required when studying celestial events like high-velocity flybys to small bodies or performing planetary defense activities. In this work, we propose a methodology for ascertaining the optimal positions of agents to capture the most certain event occurrence fulfilled by functional agreements. To validate our methodology, we perform evaluations and comparisons with other samplers, as well as simultaneous experiments within a simulation environment and a physical analog environment at the Tartu Observatory to observe proxy cometary flyby instantaneously. The work has the potential to augment relative spacecraft positioning for intercepting pristine targets as proposed by the Comet Interceptor mission, towards optimal positioning for observing the aftermath of the DART mission or towards endeavors for sighting Apophis.

<strong class="journal-contentHeaderColor">Abstract.</strong> Teleconnections between the North Atlantic and the Baltic Sea region are shaped by the polar jet stream and are critical drivers of weather and climate in the region, thereby impacting the physical and biogeochemical properties of the Baltic Sea ecosystem. This review synthesizes how key circulation features and modes of climate variability, including the North Atlantic Oscillation, atmospheric blocking and the Atlantic Multidecadal Variability, influence the Baltic Sea region. By examining existing literature data and observational and climate model data, we summarize links to temperature, precipitation, storms and other key indicators from synoptic to multidecadal time scales. We then assess how these climate controls cascade into ecosystem relevant processes, namely oxygen dynamics, primary productivity and ocean acidification. Although physical links are already established, the pathways connecting large-scale atmospheric patterns to biogeochemistry are still poorly constrained, partly because dedicated field studies and targeted model experiments are limited. We outline priority research needs to enhance near-term predictability and reduce uncertainty in future projections for the Baltic Sea.

Abstract. Teleconnections between the North Atlantic and the Baltic Sea region are shaped by the polar jet stream and are critical drivers of weather and climate in the region, thereby impacting the physical and biogeochemical properties of the Baltic Sea ecosystem. This review synthesizes how key circulation features and modes of climate variability, including the North Atlantic Oscillation, atmospheric blocking and the Atlantic Multidecadal Variability, influence the Baltic Sea region. By examining existing literature data and observational and climate model data, we summarize links to temperature, precipitation, storms and other key indicators from synoptic to multidecadal time scales. We then assess how these climate controls cascade into ecosystem relevant processes, namely oxygen dynamics, primary productivity and ocean acidification. Although physical links are already established, the pathways connecting large-scale atmospheric patterns to biogeochemistry are still poorly constrained, partly because dedicated field studies and targeted model experiments are limited. We outline priority research needs to enhance near-term predictability and reduce uncertainty in future projections for the Baltic Sea.

Leaf inclination angle (LIA) is a critical parameter influencing photosynthesis, light interception, and hydrological processes. Traditional methods for measuring LIA, such as clinometers and digital leveled photography (DLP), are often time-consuming and require specialized equipment. To address this, we developed EST-LEAF, a mobile application that uses internal phone sensors to measure leaf inclination angles rapidly and accurately. EST-LEAF also instantly provides parameters for statistical distributions, records GPS locations, and stores images for future analysis.EST-LEAF was validated against clinometer and DLP methods across four plant species: Rhododendron ‘P. M. A. Tigerstedt’, Rhododendron catawbiense, Rhododendron degronianum, and Euphorbia leuconeura L.The results highlight EST-LEAF’s potential as a practical, accessible tool for field measurements of LIA, and ultimate validation of retrievals from remote sensing platforms. Freely available under a Creative Commons license, EST-LEAF simplifies ecological data collection, supporting canopy modelling, research, and education.

The accretion and processing of neutral and ionized gas play substantial roles in the evolution of the Milky Way. From the position of the Sun, circumgalactic gas flows in the Milky Way halo are known to span a large range of radial velocities, but the complex kinematics of the circumgalactic medium (CGM) cannot be fully reconstructed from observations because of the blending with foreground interstellar gas in the Milky Way disk. For this paper we used three zoom-in magnetohydrodynamic simulations of the Milky Way and the Local Group from the HESTIA project to systematically investigate the radial velocity distribution of neutral hydrogen (H I) clouds in the CGM in the (simulated) Local Standard of Rest (LSR) velocity frame. Our three simulations, which exhibit substantial differences in their global CGM properties, reveal that 48–65 percent of the extraplanar H I at z &gt; 2 kpc above the plane is confined to a velocity range |vLSR| ≤ 100 km s−1, implying that the gas is (at least partly) corotating with the underlying disk. In the two most realistic Milky Way realizations, the CGM velocity distribution is skewed toward negative velocities (in particular for H I clouds at vertical distances z &gt; 10 kpc), indicating a net accretion of neutral gas. These results are in line with the statistics from UV absorption-line measurements of the Milky Way CGM, and we also find broad agreement with the Illustris TNG50 simulation. Our study supports a scenario in which a substantial fraction of the Milky Way’s CGM resides close to the disk at |vLSR| ≤ 100 km s−1, where it is hiding from observations as its spectral signatures are covered by foreground interstellar gas features. We furthermore find that 97 percent of the clumps live in the Milky Way halo and are not associated with satellite galaxies. The clumps are magnetized with a magnetic pressure often dominating over the thermal pressure.

Spectropolarimetry, the observation of polarization and intensity as a function of wavelength, is a powerful tool in stellar astrophysics. It is particularly useful for characterizing stars and circumstellar material, and for tracing the influence of magnetic fields on a host star and its environment. Maintaining modern, flexible, and accessible computational tools that enable spectropolarimetric studies is thus essential. The SpecpolFlow package is a new, completely Pythonic workflow for analyzing stellar spectropolarimetric observations. Its suite of tools provides a user-friendly interface for working with data from an assortment of instruments and telescopes. SpecpolFlow contains tools for spectral normalization and visualization, the extraction of Least-Squares Deconvolution (LSD) profiles, the generation and optimization of line masks for LSD analyses, and the calculation of longitudinal magnetic field measurements from the LSD profiles. It also provides Python classes for the manipulation of spectropolarimetric products. The SpecpolFlow website includes an array of tutorials that guide users through common analysis cases using the software. SpecpolFlow is distributed as a free, open-source package, with fully documented tools (via an API and command line interface) which are actively maintained by a team of contributors.

SummaryLeaf inclination angle distribution (LIAD) is a fundamental parameter of models that illustrate the energy and mass exchanges for vegetation at all scales. Terrestrial laser scanning (TLS) instruments have emerged as valuable tools for acquiring detailed measurements of canopy structure. Here, we present the first intercomparison of the available LIAD estimation techniques using TLS data.The available LIAD estimation techniques were evaluated using TLS point clouds of both real and synthetic trees covering the full range of the existing LIAD types. The performance of the proposed TLS‐based methods was also compared with the established, non‐TLS‐based leveled digital photography approach.The study highlighted that the algorithms that used merged point clouds performed better than their single‐scan counterparts. TLS offered a more comprehensive representation of the canopy structure and overcame the limitations of the traditional leveled digital photography approach for both real and simulated trees.This study may serve as a template for establishing benchmark datasets, evaluation protocols, and accessibility of algorithms that could facilitate systematic comparisons of LIAD estimation algorithms. This collaborative effort promotes fairness, reproducibility, and the advancement of LIAD estimation techniques by enabling researchers to identify strengths, weaknesses, and areas for improvement in their algorithms.

Aims. We model the atmosphere of the ultra-hot Jupiter (UHJ) WASP-178b while accounting for non-local thermodynamical equilibrium (NLTE) effects and compare synthetic transmission spectra with near-ultraviolet (NUV) and optical observations. Methods. We used the HELIOS code (LTE) in the lower atmosphere and the ClOUDY code (LTE or NLTE) in the middle and upper atmosphere to compute the temperature-pressure (TP) and abundance profiles. We further used CLOUDY to compute the theoretical planetary transmission spectrum both in LTE and NLTE for comparison with observations. Results. We find an isothermal TP profile at pressures higher than 10 mbar and lower than 10−8 bar, with an almost linear increase from ∼2200 K to ∼8100 K in between. The temperature structure is driven by NLTE effects, particularly in the form of increased heating resulting from the overpopulation of long-lived FeII levels with strong transitions in the NUV band, where the stellar emission is strong, and of decreased cooling due to the underpopulation of MgI and MgII levels that dominate the cooling. The planetary atmosphere is hydrostatic up to pressures of ∼1 nbar, and thus accurately modelling spectral lines forming at pressures lower than ∼1 nbar requires accounting for both hydrodynamics and NLTE effects. The NLTE synthetic transmission spectrum overestimates the observed Hα and Hβ absorption, while the LTE model is in good agreement, which is surprising because the opposite has been found for the other UHJs for which NLTE modelling has been performed. In the NUV, we find an excellent match between the NLTE transmission spectrum and the HST/UVIS data, contrary to the LTE model. This contrasts with previous LTE results requiring SiO absorption to fit the observations. Conclusions. The accurate characterisation of the atmosphere of UHJs is possible only when accounting for NLTE effects and particularly for the level population of Fe and Mg, which respectively dominate heating and cooling.

Abstract Effective management of forest ecosystems requires accurate predictions of damage by ungulates, a challenge particularly acute in the Kyiv Polissya. This study aims to identify key drivers of ungulate browsing intensity and compare the effectiveness of the random forest model (RFM) and generalized linear model (GLM) in forecasting damage to young forests. We analysed field data from three experimental enterprises in the Kyiv region, covering a combined area of 71.4 thousand hectares and involving 275 experimental plots. The study identified ungulate population density as the most influential factor affecting browsing intensity, surpassing variables such as tree age, tree species ratio and forest type. In comparing models, RFM demonstrated superior predictive accuracy over GLM, highlighting its effectiveness in forecasting damage to young forests. The study highlights how machine learning enhances the accuracy of ecological predictions and underscores the significance of selecting variables thoughtfully during model development. The findings point to the need for flexible forest management strategies focused on regulating wild ungulate populations and protecting young forests.

Abstract. A dilute plasma is continuously maintained in the troposphere by ionising particle radiation from galactic cosmic rays and radon decay. Small ions in the 1–2 nm size range play an important role in atmospheric processes such as ion-induced nucleation of aerosol particles. Consequently there is a need for precise and robust instruments to measure small ions both for atmospheric observations and for laboratory experiments that simulate the atmosphere. Here we describe the design and performance of the Cluster Ion Counter (CIC, Airel OÜ), which simultaneously measures the number concentrations of positively- and negatively-charged ions and particles below 5 nm mobility diameter, with low noise and fast time response. The detection efficiency is above 80 % for ions and charged particles between 1.2 and 2.0 nm, and above 90 % between 2.0 and 3.0 nm. The ion concentrations measured by the CIC agree well with reference instruments. The noise level (1 σ of background measurements) is typically between 20 and 30 ions cm-3 at 1 Hz sampling rate and an air flow rate of 7 l min-1 per analyzer. The noise level improves when higher flow rates and longer sampling periods are used. The CIC responds rapidly with 1 s time resolution to pulses of ionisation produced in the CLOUD chamber by a CERN particle beam.