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Using the 8.5‐year Venus Express measurements, we demonstrate the asymmetric plasma distributions in the Venusian magnetosheath. An escaping plume is formed by pickup oxygen ions in the hemisphere where the motional electric field points outward from Venus, while the velocity of solar wind protons is faster in the opposite hemisphere. The pickup O+ escape rate is estimated to be (3.6 ± 1.4) × 1024 s−1 at solar maximum, which is comparable to the ion loss rate through the magnetotail, and (1.3 ± 0.4) × 1024 s−1 at solar minimum. The increase of O+ fluxes with extreme ultraviolet (EUV) intensity is significant upstream of the bow shock, partially attributed to the increase of exospheric neutral oxygen density. However, the solar wind velocity just has a slight effect on the pickup O+ escape rate in the magnetosheath, while the effect of solar wind density is not observed. Our results suggest the pickup O+ escape rate is mainly controlled by EUV radiation. Plain Language Summary The atmospheric evolution and water escape of Venus might be influenced by the solar wind‐Venus interaction. The atoms outside the induced magnetosphere are ionized by the solar radiation and accelerated to the escape velocity by solar wind electric field. In this way, the oxygen ions are picked up by solar wind and lost from the atmosphere to space. We use the data from Venus Express spacecraft to analyze the distribution of pickup oxygen ions in the vicinity of the planet. The planetary oxygen ions form a strong escaping plume, indicating the pickup process is an efficient escape channel removing the atmospheric particles. With an enhanced solar extreme ultraviolet radiation, the escape rate through this channel would be higher because more ions are produced and then picked up. This indicates an enhanced ion loss billions of years ago since the young Sun is more active, which might be a reason for the disappearance of a presumably‐existed ocean. Key Points The pickup O+ escape rate at Venus increases with solar activity, and it is comparable to the ion loss rate through the magnetotail The solar wind velocity has a slight effect on the pickup O+ escape rate in the magnetosheath The neutral oxygen density upstream of the bow shock might increase by a factor of two from solar minimum to maximum

The interaction between planets and stellar winds can lead to atmospheric loss and is, thus, important for the evolution of planetary atmospheres 1 . The planets in our Solar System typically interact with the solar wind, whose velocity is at a large angle to the embedded stellar magnetic field. For planets without an intrinsic magnetic field, this interaction creates an induced magnetosphere and a bow shock in front of the planet 2 . However, when the angle between the solar wind velocity and the solar wind magnetic field (cone angle) is small, the interaction is very different 3 . Here we show that when the cone angle is small at Mars, the induced magnetosphere degenerates. There is no shock on the dayside, only weak flank shocks. A cross-flow plume appears and the ambipolar field drives planetary ions upstream. Hybrid simulations with a 4° cone angle show agreement with observations by the Mars Atmosphere and Volatile Evolution mission 4 and Mars Express 5 . Degenerate, induced magnetospheres are complex and not yet explored objects. It remains to be studied what the secondary effects are on processes like atmospheric loss through ion escape. When the cone angle between the solar wind velocity and the solar wind magnetic field is small at Mars, the induced magnetosphere degenerates.

Geomagnetic storms represent a critical yet sometimes overlooked factor affecting the reliability of modern power systems. This study examines the relationship between geomagnetic storm activity—characterized by the Dst index and categorized into weak, moderate, strong, severe, and extreme intensities—and reported power outages of unknown or unusual origin in the United States from 2006 to 2023. Outage data come from the DOE OE-417 Annual Summaries, while heliospheric and solar wind parameters (including proton density, plasma speed, and the interplanetary magnetic field) were obtained from NASA’s OMNIWeb database. Results indicate that years with a higher total count of geomagnetic storms, especially those featuring multiple strong or severe events, exhibit elevated incidences of unexplained power interruptions. Correlation analyses further reveal that increasingly negative Dst values, enhanced solar wind velocity, and higher alpha/proton ratios align with greater numbers of outages attributed to unknown causes, underscoring the pivotal role of solar wind–magnetosphere coupling. A simple regression model confirms that storm intensity and average magnetic field strength are statistically significant predictors of unexplained outages, more so than broad indicators such as sunspot number alone. These findings highlight the importance of monitoring high-intensity geomagnetic storms and associated heliospheric variables to mitigate potential risks. Greater attention to space weather impacts and improved reporting of outage causes could bolster grid resilience, helping operators anticipate and manage disruptions linked to geomagnetic disturbances.

As the interplanetary magnetic field (IMF) carried by the solar wind encounters the martian atmosphere, it tends to pile up and drape around the planet, forming looping magnetic fields and inducing marsward ion flows on the nightside. Previous statistical observations revealed asymmetrical distribution features within this morphology; however, the underlying physical mechanism remains unclear. In this study, utilizing a three‐dimensional multi‐fluid magnetohydrodynamic simulation model, we successfully reproduce the asymmetrical distributions of the looping magnetic fields and corresponding marsward flows on the martian nightside. Analyzing the magnetic forces resulting from the bending of the IMF over the polar area, we find that the asymmetry is guided by the orientation of the solar wind motional electric field (ESW). A higher solar wind velocity leads to enhanced magnetic forces, resulting in more tightly wrapped magnetic fields with an increased efficiency in accelerating flows as they approach closer to Mars. Plain Language Summary As incident solar wind interacts with Mars, the entrained interplanetary magnetic field drapes and stretches around the planet. The draped fields are orientated in opposite directions on the east and west sides of Mars, resulting in magnetic reconnection, the formation of looping magnetic fields and induced marsward plasma flows on the nightside. Statistical observations suggest an asymmetric distribution of these structures, however, the underlying physical mechanisms for this asymmetry have not been determined due to limited spatial coverage offered by the single spacecraft investigations. In this study, by taking advantage of a Hall‐MHD model, we have successfully reproduced the asymmetrical distributions and elucidated the underlying mechanisms governing these morphologies. Simulation results demonstrate that magnetic forces tend to emerge around the polar region, which are determined by the orientation of the ESW, shifting the plasma flows and magnetic fields in the direction opposite to the motional electric field. A higher solar wind velocity condition will induce amplified magnetic forces, resulting in more tightly wrapped magnetic fields and an increase in the velocity of marsward flows closer to the martian nightside. These findings provide valuable insights into the influence of the ESW and solar wind velocity on the martian induced magnetosphere. Key Points The asymmetrical distributions of looping magnetic fields and associated marsward flows can be well reproduced by a multi‐fluid magnetohydrodynamic (MHD) model The impacts of the motional electric field direction and the solar wind velocity on the asymmetries are investigated, respectively Magnetic forces shift the magnetic fields and marsward flows toward the direction opposite to the motional electric field

The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed “Arctic amplification”. The response of low-level clouds to changing aerosol characteristics throughout the year is therefore an important driver of Arctic change that currently lacks sufficient constraints. As such, during the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT) extending over a full year from October 2019 to October 2020, microphysical properties of aerosols and clouds were studied at the Zeppelin station (475 m a.s.l.), Ny-Ålesund, Svalbard, Norway. Particle number size distributions obtained from differential mobility particle sizers as well as chemical composition derived from filter samples and an aerosol chemical speciation monitor were analyzed together with meteorological data, in particular vertical wind velocity. The results were used as input to a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation that can develop, the droplet susceptibility to aerosol and the role of vertical velocity. We evaluate the parameterization and the droplet numbers calculated through a droplet closure with in-cloud in situ measurements taken during nine flights over 4 d. A remarkable finding is that, for the clouds sampled in situ, closure is successful in mixed-phase cloud conditions regardless of the cloud glaciation fraction. This suggests that ice production through ice–ice collisions or droplet shattering may have explained the high ice fraction, as opposed to rime splintering that would have significantly reduced the cloud droplet number below levels predicted by warm-cloud activation theory. We also show that pristine-like conditions during fall led to clouds that formed over an aerosol-limited regime, with high levels of supersaturation (generally around 1 %, although highly variable) that activate particles smaller than 20 nm in diameter. Clouds formed in the same regime in late spring and summer, but aerosol activation diameters were much larger due to lower cloud supersaturations (ca. 0.5 %) that develop because of higher aerosol concentrations and lower vertical velocities. The contribution of new particle formation to cloud formation was therefore strongly limited, at least until these newly formed particles started growing. However, clouds forming during the Arctic haze period (winter and early spring) can be limited by updraft velocity, although rarely, with supersaturation levels dropping below 0.1 % and generally activating larger particles (20 to 200 nm), including pollution transported over a long range. The relationship between updraft velocity and the limiting cloud droplet number agrees with previous observations of various types of clouds worldwide, which supports the universality of this relationship.

Lake surface fluxes provide important information about the lake's thermal environment. To capture their spatial variations, a ship serves as an excellent platform for applying the eddy correlation (EC) method. Although ship‐based EC measurements have been conducted over the ocean, this has not been the case over lake surfaces. Ship‐based measurements in a lake differ from those over the ocean in terms of the freedom to select the ship, route, and operation, as well as the wave regime, creating measurement conditions that have not been addressed in ocean studies. Thus, 10‐day EC flux measurements on the highly maneuverable yet stable research ship NIES'94 were conducted in Lake Kasumigaura (surface area of 172 km2), which facilitated extensive data analysis on the ship's motion and fluxes under various conditions. The results indicated that the ship's motion differs greatly depending on the ship's shape and dimensions, and that a larger fluctuation in roll and pitch angles propagates into a larger error of the vertical wind velocity measurements. The motion correction was found necessary for momentum fluxes, while it is preferable but may not be essential under favorable conditions for scalar fluxes. Comparisons between the fluxes obtained from the EC method and those from the bulk method showed that the ship's speed and direction and wave height have minimal impact on the agreement, reflecting the use of a stable ship and lower wave height in our study, leading to small ship motion in Lake Kasumigaura compared to the ocean.

The total electron content (TEC) is an important parameter for characterizing the morphology of the ionosphere. Modeling the ionospheric TEC accurately during the storm time could contribute to the operation of global navigation satellite systems (GNSS), satellite communications, and other applications. This study uses an image-based convolutional long short-term memory (ConvLSTM) network with multichannel features to forecast ionospheric TEC during the quiet periods and storm periods. The sunspot number (SSN), solar wind velocity ( V sw ), Dst, and Kp geomagnetic indices are firstly fed into the model as the channel features to improve generalization performance. Based on the variation of the Dst index, we have collected gridded TEC maps from 2011 to 2018 with a 1-h interval from the global ionospheric maps (GIM) as the data set including quiet periods and storm periods of ionospheric TEC. The performance of the ConvLSTM model in forecasting TEC is also compared with other deep learning models such as LSTM, gated recurrent unit (GRU), and LSTM-CNN. Furthermore, the accuracy consistency of the ConvLSTM model during the different phases of the storm period is also evaluated for the different output steps of predicted TEC maps. The optimal combination of input features for the model is also investigated during the storm period. Testing results show that the ConvLSTM network with multichannel features has good prediction performance for quiet periods and storm periods by incorporating both solar and geomagnetic activity indices. The statistical indicators show that the ConvLSTM model performs well with lower mean absolute error (MAE), root mean square error (RMSE), and larger correlation coefficient (R) compared with other methods. We have demonstrated that the model with a larger prediction step has worse prediction performance at the low-latitude area, especially during the storm period. In our future work, the larger TEC data set and more solar and geomagnetic indices will be investigated. Highlights An image-based convolutional long short-term memory (ConvLSTM) network with multichannel features for forecasting ionospheric TEC. Solar and geomagnetic indices as the input features for improving the performance of the model. The ConvLSTM model has good prediction performance for quiet and storm periods by incorporating both solar and geomagnetic activity indices.

We studied the influence of the Planetary Boundary Layer (PBL) on the air masses sampled at the mountaintop Hellenic Atmospheric Aerosol and Climate Change station ((HAC)2) at Mount Helmos (Greece) during the Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISTHO) Campaign from September 2021 to March 2022. The PBL Height (PBLH) was determined from the standard deviation of the vertical wind velocity (σw) measured by a wind Doppler lidar (over a 30-min time window with 30 m spatial resolution); the height for which σw drops below a characteristic threshold of 0.1 m s–1 corresponds to the PBLH. The air mass characterization is independently carried out using in situ measurements sampled at (HAC)2 (equivalent black carbon, eBC; fluorescent particle number, aerosol size distributions, absolute humidity).We found that a distinct diurnal cycle of aerosol properties is seen when the station is inside the PBL (i.e., PBLH exceeds the (HAC)2 altitude); and a complete lack thereof when it is in the Free Tropospheric Layer (FTL). Additionally, we identified transition periods where the (HAC)2 site location alternates between the FTL (usually during the early morning hours) and the PBL (usually during the midday and late afternoon hours), during which the concentration and characteristics of the aerosols vary the most. Transition periods are also when orographic clouds are formed. The highest PBLH values occur in September [400 m above (HAC)2] followed by a transition period in November, while the lowest ones occur in January [200 m below (HAC)2]. We found also that the PBLH increases by 16 m per 1°C increase of the ground temperature.

Micropulse differential absorption lidars (MPD) for water vapor, temperature, and aerosol profiling have been developed, demonstrated, and are addressing the needs of the atmospheric science community for low-cost ground-based networkable instruments capable of long-term monitoring of the lower troposphere. The MPD instruments use a diode-laser-based (DLB) architecture that can easily be adapted for a wide range of applications. In this study, a DLB direct-detection Doppler lidar based on the current MPD architecture is modeled to better understand the efficacy of the instrument for vertical wind velocity measurements, with the long-term goal of incorporating these measurements into the current network of MPD instruments. The direct-detection Doppler lidar is based on a double-edge receiver that utilizes two Fabry–Pérot interferometers and a vertical velocity retrieval that requires the ancillary measurement of the backscatter ratio, which is the ratio of the total backscatter coefficient to the molecular backscatter coefficient. The modeling in this paper accounts for the major sources of error. It indicates that the vertical velocity can be retrieved with an error of less than 0.56 m s −1 below 4 km with a 150-m range resolution and an averaging time of 5 min.

Vertical wind velocity and its fluctuations are essential parameters in the atmospheric boundary layer (ABL) to determine turbulent fluxes and scaling parameters for ABL processes. The typical instrument to measure fluxes of momentum and heat in the surface layer are sonic anemometers. Without the infrastructure of meteorological masts and above the typical heights of these masts, in situ point measurements of the three-dimensional wind vector are hardly available. We present a method to obtain the three-dimensional wind vector from avionic data of small multicopter uncrewed aircraft systems (UAS). To achieve a good accuracy in both average and fluctuating parts of the wind components, calibrated motor thrusts and measured accelerations by the UAS are used. In a validation campaign, in comparison to sonic anemometers on a 99 m mast, accuracies below 0.2 m s−1 are achieved for the mean wind components and below 0.2 m2 s−2 for their variances. The spectra of variances and covariances show good agreement with the sonic anemometer up to 1 Hz temporal resolution. A case study of continuous measurements in a morning transition of a convective boundary layer with five UAS illustrates the potential of such measurements for ABL research.