On the night of 21/22 May 2018, clear-sky conditions enabled a 12-hour-long temperature measurement of the Advanced Mesospheric Temperature Mapper (AMTM) in the mesosphere-lower thermosphere (MLT) region over Río Grande, Argentina. Given a westerly forcing over Patagonia, we observe North-South-oriented phase lines in the AMTM temperature maps exclusively during the westerly phase of the semi-diurnal tide, indicating the deep propagation of mountain waves (MWs) with horizontal wavelengths between 20 km and 40 km. After a wind reversal in the MLT, we observe two large-scale gravity waves (GWs) propagating rapidly in a south-eastward direction. We use one- and two-dimensional wavelet analysis to characterize the observed GWs and find that their wavelengths and phase speeds are consistent with secondary GW theory. Ray tracing results suggest a possible source region for these 2GWs located north-westward, near the Chilean Torres del Paine region. In addition, co-located temperature and wind measurements from the Compact Rayleigh Autonomous Lidar (CORAL) and the Southern Argentine Agile Meteor Radar (SAAMER), in combination with a Monte Carlo approach, allow for the accurate determination of both the GW momentum flux and its uncertainty. Although we exclude a direct cause-and-effect relationship within our field of view, we find that, on average, the observed MWs carry momentum fluxes an order of magnitude larger than those of the 2GWs.
How to cite: Reichert, R., Pautet, D., Kaifler, B., Janches, D., Ungermann, J., Rhode, S., and Sato, K.: Observation of mountain waves and secondary gravity waves in the MLT over Patagonia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6678, https://doi.org/10.5194/egusphere-egu25-6678, 2025.
Atmospheric gravity waves (GWs) are a key area of research due to their significant impact on atmospheric dynamics and chemistry, as well as the ongoing challenges in resolving small-scale structures in weather prediction and climate models. Over the past four decades, lidars have proven to be invaluable observational instruments for providing detailed insights into vertically propagating GWs in the middle atmosphere.
To advance the characterization of GWs, various signal processing techniques have been developed to extract GW-induced perturbations and calculate their associated potential and kinetic energy densities. In this study, we introduce a multiresolution analysis (MRA) method that enhances the interpretation of lidar signals by decomposing GWs into successive vertical wavelength bands, enabling a more refined understanding of their structure and dynamics. The MRA method is compared to conventional approaches by extracting perturbations and computing energy density profiles from temperature (from 30 to 80 km) and wind (from 7 to 60 km) lidar profiles observed on the night of November 20, 2023, over La Réunion (21.0°S, 55.5°E).
The results highlight the MRA method's superior efficiency in analyzing GWs embedded within lidar vertical profiles of temperature and horizontal wind, offering a powerful tool for advancing the study of atmospheric wave processes in the middle atmosphere.
How to cite: Trémoulu, S., Chane-Ming, F., Khaykin, S., and Keckhut, P.: Enhanced Lidar Signal Interpretation of Gravity Waves Using Multiresolution Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-783, https://doi.org/10.5194/egusphere-egu25-783, 2025.
Precise knowledge of winds and temperatures in the middle atmosphere is critical for the localization and characterization of infrasound sources. We present the concept, design, and measurement capabilities of a compact, mobile Doppler lidar system developed at the Leibniz Institute of Atmospheric Physics (IAP). This system, is designed for Doppler-Mie, -Rayleigh, and -resonance measurements in the middle atmosphere.
The daylight-capable instrument features a compact volume of about 1 m³ and is engineered for easy deployment as part of an array of lidar units. We highlight recent results, emphasizing collocated, high-resolution measurements of wind and temperature. By employing three to five individual fields of view, the system can measure both horizontal and vertical wind components. Between altitudes of 3 and 25 km, the instrument utilizes the narrowband properties of Mie backscatter, relying solely on aerosol backscatter to achieve precise three-dimensional wind measurements. In this altitude range, a novel method enables the measurement of vertical winds with an accuracy better than 0.5 m/s and a time resolution of just 60 seconds.
Above 25 km, winds will be measured using Doppler-Rayleigh and -resonance techniques. Concurrent Rayleigh temperature measurements utilize advanced aerosol correction methods, taking advantage of the instrument's high sensitivity to aerosols.
The feasibility of integrating this lidar system into a European lidar array is being investigated within the EULIAA (European Lidar Array for Atmospheric Climate Monitoring) project. The transfer of this technology to industry is currently being developed through the LidarCUBE project.
How to cite: Mense, T., Höffner, J., Froh, J., Eixmann, R., Mauer, A., Baumgarten, G., Munk, A., Strotkamp, M., and Scheuer, S.: A mobile universal Doppler-lidar for collocated, high-resolution measurements of winds and temperatures in the middle atmosphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12989, https://doi.org/10.5194/egusphere-egu25-12989, 2025.
Jet stream winds play an important role in our daily weather. Accurate wind and temperature estimations in the upper troposphere can lead to better medium to long-term weather forecasts. However, continuous measurement in the upper troposphere poses challenges, resulting in relatively sparse data.
This study revisits research from the 1960s and 1970s, on the use of ground-based pressure measurements as a measure for jet stream winds. It has been established that the jet stream can generate atmospheric gravity waves that radiate to the ground. Since the previous work, a global network of microbarometers has been established for verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). This network provides continuous pressure data that holds valuable information about the jet stream.
We present results from a microbarometer array in Southern Germany (IS26). The pressure data has been processed for frequencies within a range of 0.1 - 2 mHz, where gravity waves are detected. Signal characteristics from the array analysis, such as direction-of-arrival and incidence angle, enable a detailed monitoring of the jet stream strength and direction. The characteristics of these gravity waves are compiled, and compared to hourly ECMWF ERA5 model data and other observations, such as radiosonde balloon measurements.
How to cite: Bentvelsen, F., Assink, J., and Evers, L.: Tracking jet stream winds through gravity waves arriving on surface based pressure sensors, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9300, https://doi.org/10.5194/egusphere-egu25-9300, 2025.
The Central and Eastern European Infrasound Network (CEEIN) consists of nine infrasound arrays managed by research institutes in the Czech Republic, Austria, Hungary, Ukraine, and Romania. A hybrid machine learning model was previously developed to differentiate between natural and anthropogenic sources of infrasound. This model categorizes signals from thunderstorms, activity from Mount Etna, and human-related sources, including quarry blasts, power plants, oil refineries, and the conflict in Ukraine. The dataset includes more than 100,000 labeled detections spanning from 2017 to 2024. The hybrid model combines a Convolutional Neural Network, trained on spectrograms, with a Random Forest classifier, trained on features derived from the Progressive Multi-Channel Correlation (PMCC) method, which is used for processing the raw data. The model performed well on the test data (F1 score > 0.9); however, to assess its capabilities for near-real-time monitoring, the model was retrained with randomly selected, unlabeled detections from outside the aforementioned classes. Here, we present findings from several months of automatic monitoring, assessing both single array and network processing performance.
How to cite: Pásztor, M., Šindelářová, T., Ghica, D., Mitterbauer, U., Liashchuk, A., Lacanna, G., Ripepe, M., and Bondár, I.: Automatic infrasound monitoring at the Central and Eastern European Infrasound Network via Machine Learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-33, https://doi.org/10.5194/egusphere-egu25-33, 2025.
A new 4-element infrasound array (AGIR) of 0.2 km aperture was deployed by National Institute for Earth Physics (NIEP) in August 2024 in Eastern Romania, on the Black Sea coast. Between August and October, during the strong thunderstorms that crossed this region, long-duration trains of frequent sharp spikes in the amplitude associated with lightning discharges were observed into AGIR infrasound recordings. Some of these storm episodes could be correlated to cyclones moving over the Black Sea and greatly affecting Romania's regional climate in 2024.
We examined data from NIEP's current infrasound network – BURARI, IPLOR and AGIR stations –, in order to study the possibilities of infrasound-based monitoring of extratropical cyclones over the Black Sea. Association between infrasound detections into 0.5 to 7 Hz frequency band and lightning flashes detected by MTG Lightning Imager within 50 km from the AGIR infrasound station was investigated, assuming direct wave propagation path. Acoustic signatures of lightning activity show short-lived disturbances with dominant frequency of approx. 3 Hz and amplitudes up to about 3.5 Pa.
In addition to the strong lightning discharges during the storms, the cyclones were also accompanied by strong winds that produced waves in the Black Sea. We can consider these waves to be the cause of the significant fluctuations observed into the microbarom detections in the Black Sea region at BURARI and IPLOR stations, into the 0.1 Hz to 1 Hz frequency band. Microbarom power spectral noise amplitudes peak was observed around 0.3 Hz. Microbaroms detections are strongly influenced both by seasonally dependent stratospheric winds and local turbulence-induced pressure fluctuations. Local wind was averaged for the BURARI and IPLOR locations using NRL-G2S wind fields.
Infrasound signatures linked with certain extratropical cyclonic episodes were well identified. To improve storm track estimates, these infrasound-based detections were subsequently combined with conventional meteorological data including surface observations, electric field measurements, and satellite data. This study shows the potential of Romania's current infrasound infrastructure to support extratropical cyclone surveillance and improve forecasting capability in the region, even when more calibration of detection thresholds and source characterisation is required.
How to cite: Ghica, D., Antonescu, B., and Ene, D.: Using Romanian infrasound observations to analyze thunderstorms generated by extratropical cyclones over the Black Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5592, https://doi.org/10.5194/egusphere-egu25-5592, 2025.
The Epos-France Permanent Broadband Network (RLBP), originally designed for earthquake monitoring, provides real-time seismic data from over 200 stations across mainland France, enabling the detection and localization of atmospheric events such as meteors. This is achieved through seismic-acoustic coupling, where shock waves generated by meteors can be recorded by the network's sensors. We apply the Reverse Time Migration (RTM) method to identify acoustic sources of interest with accuracy. The method uses a "grid search" approach to evaluate potential source points, ordering seismic traces by distance (hodochrone) and calculating the sum of the envelopes of interest according to the velocity model considered. The integration of atmospheric data from the ECMWF model and an attenuation law optimizes this process by selecting the most relevant seismic stations, increasing signal-to-noise ratios, and improving localization precision. We present case studies including the fragmentation of a meteor over Normandy, France (February 13, 2023) and the eruption of Stromboli Volcano, Italy (July 11, 2024) enabling precise dating of the paroxysm and localization to within a few kilometers of the Sciara del Fuoco (i.e. ground truth validation). This approach, which allows for the localization of a meteor without direct visual observation, regardless of weather conditions or time of day, aims to complement the optical observations of the FRIPON network. Ongoing work that we also present aims to further refine the method to detect other anthropic phenomena in the atmosphere, such as satellite debris and jet shock waves, thereby enhancing the seismic network's ability to monitor an increasingly wide range of events.
How to cite: Dupont, A., Mazet-Roux, G., Azzaz, S., and Le Pichon, A.: Using seismic data to detect and locate meteors with the Epos-France Permanent Broadband Network, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7111, https://doi.org/10.5194/egusphere-egu25-7111, 2025.
Temporal variations of the noise conditions constrain the ability to detect and identify signals of interest at infrasound stations. Station-dependent factors that contribute to the noise include incoherent wind and turbulence. A coherent source of ambient noise at the global infrasound station network of the International Monitoring System are microbaroms from the oceans, which vary seasonally such that most stations observe the maximum noise during local winter.
For a realistic estimate of the station noise statistics, we computed the power spectral density (PSD) at all 53 elements of the operational IMS stations on an hourly basis over a four-year period (2021-2024), resulting in more than 10 million computed PSDs. This systematic processing of the background noise allows an assessment of the sensitivity of each measurement system to geographic and environmental parameters that include both wind-generated noise and coherent signals from geophysical and anthropogenic events. Using this unique high-resolution PSD dataset, we analyse the spatiotemporal noise variation across the IMS network and also examine local effects at the array sites such as vegetation or snow cover that also contribute to the noise level. This work aims at updating earlier statistical ambient noise models and facilitating detection capability simulations with high temporal resolution.
How to cite: Hupe, P., Le Pichon, A., Vergoz, J., and Pilger, C.: High-resolution analysis of spatiotemporal ambient noise variations across the infrasound network of the International Monitoring System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19412, https://doi.org/10.5194/egusphere-egu25-19412, 2025.
The detection capability of the International Monitoring System (IMS) deployed to monitor compliance with the Comprehensive Nuclear-Test ban Treaty (CTBT) is highly variable in space and time. Previous studies estimated the source energy from remote observations using empirical yield-scaling relations. However, these relations simplified the complexities of infrasound propagation as the wind correction applied does not account for an accurate description of the middle atmosphere along the propagation path. In order to reduce the variance in the calculated transmission loss, massive frequency and range-dependent full-wave propagation simulations are carried out, exploring a wide range of realistic atmospheric scenarios. A cost-effective approach is proposed to estimate the transmission losses at distances up to 4,000 km along with uncertainties derived from multiple gravity wave realizations. Transmission loss statistics are combined with an explosive source model and noise statistics to quantify the 90% probability detection threshold of the IMS network. In the context of the future verification of the CTBT, this approach helps advance the development of network performance simulations in higher resolution and the evaluation of middle atmospheric models at a global scale with limited computational resources.
How to cite: Le Pichon, A., Vergoz, J., Hupe, P., Listowski, C., and Kristoffersen, S.: A revisited Bayesian framework to predict the performance of the IMS infrasound network, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7109, https://doi.org/10.5194/egusphere-egu25-7109, 2025.
Accurately modeling transmission loss is essential for a variety of applications, such as
improving atmospheric data assimilation for numerical weather prediction, assessing attenuation
maps of sources of interest, or estimating detection capabilities of the International Monitoring
System infrasound network. However, the high computational cost of numerical modeling solvers
makes them impractical for a near-real-time analysis. To address this, a previous study trained a
Convolutional Neural Network on regional wind fields, predicting transmission losses in less than 0,05
seconds with a mean-squared error of 5 dB. However, this approach uses interpolated atmospheric
specifications and focused only on winds, limiting its applicability for long-range modeling. In this
work, we develop a convolutional recurrent network to predict transmission losses leveraging
realistic, range-dependent atmospheric specifications combining horizontal winds and temperatures,
including small-scale perturbations. The resulting model reaches an error of 4 dB while extending
propagation range up to 4,000 km and providing epistemic and data uncertainty estimates. First
studies of such an algorithm on regional scaled events (Tonga-Hunga eruption, Hukkakero explosions,
etc.) were performed to further evaluate the model. Predicted attenuation are compared with
results from an alternative regionally fine-tuned neural network. The model also demonstrated its
ability to adapt to new frequencies.
How to cite: Janela Cameijo, A., Sklab, Y., Arib, S., Le-Pichon, A., Aknine, S., Brissaud, Q., and Näsholm, S. P.: Deep learning-based method for near-real time estimation of infrasound transmission losses in theatmosphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10204, https://doi.org/10.5194/egusphere-egu25-10204, 2025.
Infrasound of oceanic origin, known as microbaroms, are globally and continuously detected by the infrasound stations of the International Monitoring System. They propagate over thousands of kilometers thanks to acoustic waveguides in the middle and upper atmosphere (~30-120 km). At these altitudes, Numerical Weather Prediction (NWP) models are biased, partly due to the lack of operationally assimilated observations that constrain model predictions (especially for winds). We present a processing chain that simulates microbarom arrivals at infrasound stations by coupling a microbarom source model and infrasound propagation modelling. These arrivals are modelled using atmospheric specifications from different NWP models and compared to the microbarom observations using a multidirectional metric. The objective of this processing chain is twofold: evaluating the relative performances of NWP models in support of operational infrasound monitoring activities and demonstrating the benefit of assimilating unconventional observations such as microbaroms in NWP models. To this end, we apply the processing chain to several infrasound stations and highlight NWP performance assessments during a sudden stratospheric warming and other dynamical events of the middle and upper atmosphere.
How to cite: Letournel, P., Listowski, C., Bocquet, M., Le Pichon, A., and Farchi, A.: Using an oceanic acoustic noise model to evaluate simulated atmospheric states, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3753, https://doi.org/10.5194/egusphere-egu25-3753, 2025.
Infrasound signals are used to monitor various anthropogenic and natural sources. To determine accurate source locations and energy, an accurate model of wind and temperature from the surface up to the lower thermosphere is necessary, hence operational NWP products are of great importance for routine infrasound monitoring activities. However, many of these models focus on tropospheric conditions, and the middle and upper atmosphere, where the relevant infrasound waveguides for long-range propagation are found, is not well represented. UA-ICON is an upper atmosphere version of the ICOsahedral Non-hydrostatic weather and climate model (ICON) that provides modelled atmospheric parameters up to 150 km. From an infrasound perspective, small-scale perturbations - most notably gravity waves - can have a large impact on propagation due to the effects on both the background winds and temperatures, hence on the acoustic waveguides, but also due to the small perturbations they produce, which cause partial reflections of acoustic waves. Therefore, the transient-3D Multi-Scale Gravity Wave Model (MSGWaM) was used within UA-ICON to produce accurate background conditions, and predict the global gravity wave activity. We will present the methodology used to generate the wind and temperature gravity wave perturbation profiles, as well as analysis of infrasound propagation using these gravity wave realisations.
How to cite: Kristoffersen, S., Listowski, C., Voelker, G.-S., Achatz, U., Vergoz, J., and Le Pichon, A.: Studying infrasound propagation in the middle atmosphere with UA-ICON: parameterisation and characterisation of gravity waves with the Multi-Scale Gravity Wave Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7087, https://doi.org/10.5194/egusphere-egu25-7087, 2025.
Atmospheric variability at short time-scales (seconds to minutes) is challenging to detect, quantify, and include in numerical models of atmospheric circulation. Infrasound can be generated by natural and anthropogenic sources, and due to the low frequency of the signal, it can travel relatively long distances (hundreds to thousands of kilometers) and be detected by acoustic arrays. When detected, the observed wavefront properties quantities (travel time, backazimuth angle, apparent velocity) contain integrated effects of the atmospheric slab through which the wave traveled. We use data assimilation, in particular an ensemble Kalman filter, to invert these observations to atmospheric quantities. As observations, we use three days of daily infrasonic signals originating from 52 explosions. The signals propagated through the stratospheric waveguide and were recorded at a distance of 256 km. The assimilation background field is provided by the 10-member ERA ensemble reanalysis product, which is valid every 3 hours. The departures with respect to the background shed light to the atmospheric variability in very short time-scales (minutes).
How to cite: Amezcua, J., Averbuch, G., Nasholm, S. P., and Arrowsmith, S.: Using infrasound observations and data assimilation to detect atmospheric variability over short timescales, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14647, https://doi.org/10.5194/egusphere-egu25-14647, 2025.
Seismic waves can couple to the atmosphere and propagate as acoustic waves, including infrasound at frequency below 20 Hz. Seismically generated infrasound can be recorded by ground-based microbarometers, but also at higher-altitude by pressure sensors carried by balloons. Balloon-borne acoustic observations could be the key to exploring Venus' interior, as surface conditions do not allow for the deployment of seismometers. However, it remains unclear how much information about the subsurface is contained in seismically generated infrasound.
In this contribution we use the recent earthquake-induced acoustic observations from a balloon network on Earth belonging to the Strateole2 campaign, following the 2021 Mw 7.3 earthquake in the Flores Sea, to invert for subsurface velocities. Seismic infrasound signals show body wave arrivals and surface wave dispersion similar to pure seismic signals recorded on the ground. Thus, beyond their detection capability, balloon infrasound also enables the use of classical inversion techniques to retrieve source and subsurface properties. We develop an inversion framework to jointly retrieve earthquake source location and seismic velocities of the subsurface based on arrival time measurements for P, S and Rayleigh waves at multiple balloon stations. We apply this approach to the Flores earthquake using data from four Strateole2 balloons.
The inversion results are the probability density distribution of the seismic source location and of the subsurface velocities in a layered model. Both the resulting location and subsurface model are in good agreement with those obtained from traditional seismic data, confirming balloon seismology as a credible alternative for the seismic exploration of the Earth and other celestial bodies with atmospheres, such as Venus.
How to cite: Froment, M., Brissaud, Q., Näsholm, S. P., Schweitzer, J., and Kaschwich, T.: Source and subsurface inversion using earthquake-generated infrasound recorded at a balloon platform: application to the 2021 Mw 7.3 Flores earthquake, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18062, https://doi.org/10.5194/egusphere-egu25-18062, 2025.
Energetic volcanic eruptions can inject large amounts of ash into the atmosphere, posing a direct threat to commercial flights and potentially overwhelming populations down the ash plume path. These eruptions also produce infrasound –acoustic waves below 20 Hz– which can propagate over hundreds to thousands of kilometers in the atmosphere due to favorable ducting conditions and its intrinsic low attenuation.
Within the Atmospheric dynamics Research InfraStructure in Europe (ARISE) project (FP7, H2020), in collaboration with the Toulouse Volcanic Ash Advisory Centre (VAAC), the Volcanic Information System (VIS) was created as a prototype monitoring system that uses long-range (>250 km) infrasound recordings to remotely detect and notify of explosive eruptions.
The VIS was designed to primarily use data recorded by the global International Monitoring System (IMS) infrasound network (53 stations of 60 planned stations), but it can also include non-IMS arrays (e.g., AMT, Florence, Italy) to increase the coverage. At its core, the VIS relies on a data processing output denoted the Infrasound Parameter (IP) to establish when an eruption occurs. The IP value accounts for propagation effects, detection persistency, and infrasound signal amplitude.
Currently, we are thoroughly testing the capabilities of the VIS, and considering the future developments that can be implemented to improve its reliability, before it is made publicly available.
Our recent efforts have expanded the VIS capabilities to use open-access (OA) streamlined and standardized IMS-derived infrasound array signal processing data products. We found that the eruption notification results using OA data were comparable to the notifications calculated with regular IMS data (i.e., PMCC detections).
In this work, we look in detail into the eruptive periods of April 2010 Eyjafjallajökull (Iceland), May 2016 Etna (Italy), and April 2021 La Soufrière (Saint Vincent island, Saint Vincent and the Grenadines), and test how year-long back-azimuth deviation predictions (i.e., pre-calculated back-azimuth bias values) for the nearest IMS stations (<2500 km) can help decreasing the eruption notification false positives and improve the VIS overall reliability. We compare the VIS notification results with detections calculated using both OA and PMCC data, and incorporate the available HOTVOLC webGIS satellite notifications (2010-2022), plus other available eruption catalogues (e.g., Global Volcanism Program). We present a preliminary eruption catalogue for these cases, and show to what extent infrasound-only, and infrasound+satellite monitoring (ASH2/ASH5 products from HOTVOLC) can achieve reliable eruption notifications in the studied areas.
As part of the European Geo-INQUIRE project (HORIZON-INFRA-2021-SERV-01), the VIS will be integrated into the Thematic Core Service Volcano Observation (TCS-VO) of the European Plate Observing System (EPOS). Future developments will also include integration into web services such as the HOTVOLC web-GIS interface (OPGC, CNRS-INSU) or the EPOS Data Portal.
How to cite: De Negri, R., Hupe, P., Gheri, D., Le Pichon, A., Marchetti, E., Näsholm, P., Mialle, P., and Labazuy, P.: The Volcanic Information System: Long-Range Infrasound Monitoring of Volcanic Eruptions With Open-Access Datasets And Year-Long Back-Azimuth Deviation Bias Predictions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7290, https://doi.org/10.5194/egusphere-egu25-7290, 2025.
